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<div>[[File:Hiringfunnel.png |250px|thumbnail|right| There are many stages to the hiring process, and algorithms are involved in almost all of them. <ref name=upturn>Bogen, M. & Rieke, A. (2018). <i>Help Wanted: An Examination of Hiring Algorithms, Equity, and Bias</i>. Upturn. https://www.upturn.org/static/reports/2018/hiring-algorithms/files/Upturn%20--%20Help%20Wanted%20-%20An%20Exploration%20of%20Hiring%20Algorithms,%20Equity%20and%20Bias.pdf</ref>]]<br />
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The advancement of [[Wikipedia: Technology|technology]] and [[Wikipedia: Algorithm|algorithms]] has led to companies recruiting and hiring potential employees through the use of [[Wikipedia: Big data|big data]] and [[Wikipedia: Artificial intelligence|artificial intelligence]], which can amplify gender [[Wikipedia: Bias|bias]] in the online job search <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>. Gender bias refers to the “unfair difference” in the way that both men and women are treated <ref name=biasDefinition>Cambridge Dictionary.(n.d.). Gender Bias. In <i>Cambridge English Dictionary</i>. https://dictionary.cambridge.org/us/dictionary/english/gender-bias</ref>. In the context of the online job search, gender bias is defined as the advantage male job seekers have versus female job seekers. The use of algorithms in the online job search process can perpetuate existing biases which result in ethical implications regarding blocked job opportunities for females, and the disadvantage for female job seekers due to systematic [[Wikipedia: Gender role|gender roles]].<br />
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==<big> Artificial Intelligence in the Recruitment Process </big>==<br />
Companies utilize AI technology in their recruiting algorithms to recruit new employees more effectively. <ref name=ai_guide> (2021, February 26). <i>Ai for recruiting: A definitive guide for hr professionals. </i> Ideal. https://ideal.com/ai-recruiting/#:~:text=AI%20for%20recruiting%20is%20the,repetitive%2C%20high%2Dvolume%20tasks. </ref>. The introduction of AI into the recruiting process makes candidates 14% more likely to pass interviews and receive offers, 18% more likely to accept the job, but they are 12% less likely to inform recruiters of competing job offer during the negotiation process <ref> Cowgill, B. (2018).<i> Bias and productivity in humans and algorithms: Theory and evidence from resume screening. </i> Columbia Business School, Columbia University, 29. http://conference.iza.org/conference_files/MacroEcon_2017/cowgill_b8981.pdf </ref>. This technology is mainly used within four general types of recruitment activities: outreach, screening, assessment, and coordination <ref name=ai_manage> Black, J., & Esch, P. (2019, December 31). <i> Ai-enabled recruiting: What is it and how should a manager use it? </i> https://www.sciencedirect.com/science/article/pii/S0007681319301612 </ref>. <br />
[[File:life_cycle.png |250px|thumbnail|right|The Steps of the Recruitment Life Cycle. Sourced from https://medium.com/@corprate.io/ultimate-6-steps-guide-in-recruitment-process-ae9a6bd70863]]<br />
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===Outreach===<br />
Artificial intelligence helps companies find applicants that are the best fit. These potential applicants consist of active candidates (those who are deliberately searching for a new job) and passive candidates (those who are not actively searching but would show interest in the right opportunity). The AI uses data from websites like LinkedIn, Facebook, Twitter, etc. to match candidates to jobs. After enough training, the AI will have learned the most efficient way to word and present jobs to potential candidates. <ref name=ai_manage> </ref><br />
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===Screening===<br />
AI is also used for the resume screening process. AI can help companies reduce the time-to-hire. [[Wikipedia: Hilton_Hotels_%26_Resorts Hilton Hotels & Resorts| Hilton Hotels & Resorts]] implemented a screening tool that used AI and found an 88% decline in time-to-hire, or 42 days to 5 days. These AI screening tools can be more effective than humans because they can infer key terms from natural language. For example, instead of searching for the keyword, ‘persistence’, the AI can infer this term from other phrases or wording. <ref name=ai_manage> </ref><br />
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===Assessing===<br />
AI assessments are used to narrow a candidate pool after the resume screening step. AI can be used in varying types of assessments. It can range from realistic [[Wikipedia: Chatbot|chatbot]] conversations in [[Wikipedia: Situational_judgement_test| situational judgement tests]] to making decisions based on an applicant’s responses to test questions <ref name=assess>(n.d.). <i> Artificial intelligence (ai) in assessment. </i> Aon. https://assessment.aon.com/en-us/online-assessment/ai-in-assessment </ref>. These assessments can be used as an initial interview or to informally test candidates for desired traits, such as an individual’s risk propensity. <ref name=ai_manage> </ref><br />
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===Coordination===<br />
It is beneficial for companies to make their hiring process as positive of an experience as possible because a candidate might not be the right fit today, but they could be perfect in a year. AI can facilitate this because it creates a more seamless, digital experience. Companies can use chatbots to update candidates on where they are in the process, fill in information gaps like the candidate’s potential start date, and answer candidate questions. <ref name=ai_manage> </ref> Also, a company’s openness with their usage of AI in the recruitment process increased the likelihood of a job application, as well as having a positive experience with the process <ref name=marketing> Esch, P., Black, J., & Ferolie, J. (2018, September 17). <i> Marketing ai recruitment: The next phase in job application and selection. </i> https://www.sciencedirect.com/science/article/pii/S0747563218304497#sec5 </ref>.<br />
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==<big>Evidence of Bias</big>==<br />
[[File:LookalikeAudience.png |300px|thumbnail|left| Process of Facebook's lookalike audience tool. <ref name='Facebook'>Facebook. (n.d.). https://www.facebook.com/</ref>]]<br />
===Job Recruitment Algorithms===<br />
Job recruitment algorithms have been found to reinforce and perpetuate unconscious human gender bias <ref name=abc>Hanrahan, C. (2020, December 2. <i>Job recruitment algorithms can amplify unconscious bias favoring men, new research finds.</i> The ABC News. https://www.abc.net.au/news/2020-12-02/job-recruitment-algorithms-can-have-bias-against-women/12938870</ref>. Because job recruitment algorithms are trained on real-world data – and the real world is biased – the algorithms amplify this bias on a larger scale. Decision-making algorithms are “designed to mimic how a human would…choose a potential employee” and without careful consideration, algorithms can intensify bias in recruiting <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. <br />
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Utilizing real-world data to shape algorithms leads to algorithms producing biased outcomes. Algorithms make predictions by analyzing past data <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>. If the past data includes biased judgments, then the algorithm’s predictions will also be biased. [[Wikipedia: Facebook|Facebook’s]] tool called “[[Wikipedia: Lookalike audience|lookalike audience]]” allows advertisers – in this case, employers – to input a “[[Wikipedia: Target audience|source audience]]” that will dictate who Facebook advertises jobs to, which is based on a person’s similarities with this “source audience” <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>. This tool is meant to help employers predict which users are most likely to apply for jobs. If an employer provides the lookalike tool with a dataset that does not include a lot of women, then Facebook will not advertise the job to women. Employers could use this tool to deliberately exclude certain groups, but employers could also be unaware of the bias of their “source audience” <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>.<br />
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===Job Recommendation Algorithms===<br />
Job recommendation algorithms within online platforms are built to find and reproduce patterns in user behavior, updating predictions or decisions as job seekers and employers interact <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. If the system within the platform recognizes that the employer interacts with mostly men, then the algorithm will look for those characteristics in potential job applicants and replicate the pattern <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. This pattern picked up by the algorithm can happen without specific instruction from the employer, which leads to biases going unnoticed.<br />
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Another problem that is encountered with job recommendation algorithms is the “lack of publicly available information.”<ref name = "mitigating_bias">Raghavan M., Barocas S., Kleinberg J., Levy K. (6 December 2019). [https://arxiv.org/abs/1906.09208 "Mitigating Bias in Algorithmic Hiring: Evaluating Claims and Practices"] Retrieved on 9 April 2021</ref> While companies can say that they are working to account for biases in the algorithm, the general public does not actually know how these problems are being tackled. However, the reason why this information is not public is due to the sensitivity of employee data that is used to train the algorithms. Because of this, the information that we can gather about practices in the industry is limited.<ref name = "mitigating_bias"></ref><br />
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===Algorithms Extending Human Bias===<br />
Personal, human bias extends into [[Wikipedia: Algorithmic bias| algorithmic bias]]. A study conducted at the [[Wikipedia: University of California, Santa Barbara|University of California, Santa Barbara]] found that people’s own underlying biases were bigger determinants of their likelihood to apply to jobs than any gendered job posting <ref name=longitudinal> Tang, S., et al. (2017). Gender Bias in the Job Market: A Longitudinal Analysis. <i> ACM on the Human-Computer Interaction. </i>. https://dl.acm.org/doi/epdf/10.1145/3134734</ref>. Underlying human biases need to be reduced to work towards gender neutrality in the job market <ref name=longitudinal> Tang, S., et al. (2017). Gender Bias in the Job Market: A Longitudinal Analysis. <i> ACM on the Human-Computer Interaction. </i>. https://dl.acm.org/doi/epdf/10.1145/3134734</ref>. Humans choose the data to train algorithms with, and the "choice to use certain data inputs over others can lead to discriminatory outcomes" <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. Hiring algorithms can be an extension of "our opinions embedded in code" and further research highlights that algorithms reproduce existing societal, human bias <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. The people constructing hiring algorithms are in the tech industry, which is not very diverse. This leads to algorithms that are trained on non-diverse data, which extends human gender bias into the online job market <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. While creating algorithms, "biases creep in because human bias [influences] the algorithm" <ref name=cnbc> Rosenbaum, E. (2018, May 30). <i>Silicon Valley is stumped: A.I. cannot always remove bias from hiring</i>. Consumer News and Business Channel. https://www.cnbc.com/2018/05/30/silicon-valley-is-stumped-even-a-i-cannot-remove-bias-from-hiring.html</ref>. Humans build biased algorithms, so it is up to humans to notice the biases and fix them <ref name=cnbc></ref>.<br />
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==<big>Ethical Implications</big>==<br />
===Algorithms Blocking Opportunities===<br />
[[File:Men in tech.png |300px|thumbnail|right| Amazon's hiring algorithm was modeled after real-world data, where there are more men in the tech field. The difference in gender of employees is shown in the figure above <ref name=amazon> Dastin, J. (2018, October 10). <i>Amazon scraps secret AI recruiting tool that showed bias against women.</i> Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G</ref>.]]<br />
Algorithms in the online job search do not outright reject job seekers. Instead, they block certain groups of job seekers from seeing opportunities they are qualified for; as [[Wikipedia: Pauline Kim|Pauline Kim]], a legal scholar, stated, “not informing people of a job opportunity is a highly effective barrier” to job seekers <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. Qualified candidates cannot apply for a job if they have not been shown the opportunity. <br />
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[[Wikipedia: Amazon (company)|Amazon’s]] algorithmic recruiting tool was trained with 10 years’ worth of [[Wikipedia: Résumé|resumes]] that were sent to Amazon; however, because technology is a male-dominated field, most of the resumes were from male applicants, leading the algorithm to downvote women <ref name=amazon> Dastin, J. (2018, October 10). <i>Amazon scraps secret AI recruiting tool that showed bias against women.</i> Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G </ref>. This method of training taught the algorithm that men were preferred, therefore penalizing candidates who included the word “women’s” in their resume. For example, if the candidate listed an activity as “women’s team captain, ” their resume would be downgraded in the system <ref name=amazon> Dastin, J. (2018, October 10). <i>Amazon scraps secret AI recruiting tool that showed bias against women. </i> Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G </ref>. Amazon has since scrapped this recruiting algorithm <ref name=amazonscandal2> <i>Amazon scrapped 'sexist AI' tool</i>. (2018, October 10). British Broadcasting Corporation. https://www.bbc.com/news/technology-45809919 </ref>.<br />
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A test was also conducted on an ad-serving algorithm that displayed ads for jobs related to STEM. The algorithm was supposedly designed to display these ads to men and women equally and was tested in 191 different countries. The results showed that the ads were shown to around 20% more men than women. One of the explanations to the algorithm choosing to show the ads to more men than women comes from an economic standpoint. Online advertisers are constantly competing for users’ attention. A study has shown that on average, it is more expensive to get the attention of females over males when advertising online.<ref>Lambrecht A., Tucker C. (2019). [https://pubsonline-informs-org.proxy.lib.umich.edu/doi/pdf/10.1287/mnsc.2018.3093 "Algorithmic Bias? An Empirical Study of Apparent GenderBased Discrimination in the Display of STEM Career Ads"] Retrieved on 9 April 2021.</ref><br />
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===Traditional Gender Roles Affect Outcomes===<br />
It has been studied that women can have a better keyword match on their resume, yet not be selected for a job if a man has more experience than them <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. These hiring algorithms that are built and trained by humans do not take into account the time women must take off of work to have children or to take care of children <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. The author of a study done by the [[Wikipedia: University of Melbourne|University of Melbourne]] recounts that “women have less experience because they take time [off work] for caregiving, and that algorithm is going to bump men up and women down based on experience” <ref name=abc>Hanrahan, C. (2020, December 2. <i>Job recruitment algorithms can amplify unconscious bias favoring men, new research finds.</i> The ABC News. https://www.abc.net.au/news/2020-12-02/job-recruitment-algorithms-can-have-bias-against-women/12938870</ref>. Because women are more likely to experience a disruption in their career due to children, they will be viewed as a lesser candidate by the algorithm, even if they have more relevant experience than a male candidate <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. Hiring algorithms do not take into account gender roles, which include women taking time off to give birth. This replicates and reinforces gender bias in the online hiring process <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>.<br />
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==<big>Reducing Bias</big>==<br />
[[File:WordEmbeddings.png |350px|thumbnail|left| Basic graphic of how researchers observed and evaluated gender bias of word embeddings in algorithms. <ref name=SunEtAl>Sun, T., et al. (2019, June 21). ''Mitigating Gender Bias in Natural Language Processing: Literature Review''. Cornell University. https://arxiv.org/pdf/1906.08976.pdf</ref>]]<br />
===Rethinking How Algorithms are Built===<br />
Vendors that build recruitment algorithms to target specific job seekers need to think beyond the minimum [[Wikipedia: Compliance requirements|compliance requirements]]; they have to consider whether or not the algorithm they are building is leading to more fair hiring outcomes <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. Additionally, the people stating that their algorithms will reduce bias in the hiring process have to build and test their algorithms while keeping that goal in mind, or else the technology will continue to undermine the online job search process <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. Re-thinking algorithms and how to build them will begin to reduce bias in the job search, as many factors need to be considered.<br />
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One specific aspect of gender bias can be found in [[Wikipedia: Word embedding|word embeddings]]. Word embeddings are [[Wikipedia: Binary|binary]], pre-trained models that assign words or phrases specific representations and meanings; these models have been found to reflect societal bias <ref name=WordEmbeddings>GeeksforGeeks. (2020, October 14). Word Embeddings in NLP. https://www.geeksforgeeks.org/word-embeddings-in-nlp/</ref>. For example, words like ''"[[Wikipedia: Receptionist|receptionist]]"'' and ''"[[Wikipedia: Nursing|nurse]]"'' are linked to ''"women"'' and ''"she"'' whereas words like ''"[[Wikipedia: Physician|doctor]]"'' and ''"[[Wikipedia: Computer scientist|computer scientist]]"'' are linked to ''"men"'' and ''"he"''. In addition, there has been a “prevailing idealized concept of femininity” in the past.<ref name = "gender_bias">Leavy S., Meaney G., Wade K., Greene D. (12 July 2020) [https://link-springer-com.proxy.lib.umich.edu/chapter/10.1007%2F978-3-030-52485-2_2 "Mitigating Gender Bias in Machine Learning Data Sets"] Retrieved on 9 April 2021</ref> The term “female” appears more than twice the amount of times the term “male” appears. This suggests that in most contexts, males are the default assumption over females when referring to someone.<ref name = "gender_bias"></ref> Researchers have explored potential solutions to de-bias word embeddings by using methods such as building a genderless framework as well as teaching the algorithm gender-neutral word embeddings <ref name=SunEtAl></ref>. Such methods aim to minimize the difference between gendered words (i.e. ''male'' versus ''female'') and maximize "the difference between the gender direction and other neutral dimensions” <ref name=SunEtAl></ref><ref name='Bolukbasi'>Bolukbasi, T., et al. (2016). Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. ''Advances in Neural Information Processing Systems 29 (NIPS 2016)''</ref>. This allows algorithms to use or neglect the gender dimensions.<br />
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===Balancing Humans and Algorithms===<br />
Implementing a balance between predictive algorithms and human insight is a promising solution for employers looking to use algorithms in their hiring process while reducing bias <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. Using artificial intelligence and algorithms to parse through large amounts of data or applicants works well for processing. Balancing the processing by algorithms with the "human ability to recognize more intangible realities of what that data might mean" is the second step in the process of limiting algorithmic bias <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. For a partnership between humans and algorithms to be successful within companies, they need to consciously and deliberately implement new practices <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. Both algorithms and humans still need to be held accountable for reducing bias, and working together would encourage a good short-term solution to the phenomenon of gender bias in the online job search <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>.<br />
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While aiming to strike a balance between humans and algorithms is a promising solution, there is an important question to answer. What is considered “fair” when trying to find qualified candidates for a job. Most conversations have been geared towards “treating similar individuals similarly.”<ref name = "tackling_bias">Silberg J., Manyika J. (6 June 2019). [https://www.mckinsey.com/featured-insights/artificial-intelligence/tackling-bias-in-artificial-intelligence-and-in-humans# "Tackling bias in artificial intelligence (and in humans)"] Retrieved on 9 April 2021</ref> However, a study has shown that a “model cannot conform to more than a few group fairness metrics at the same time.”<ref name = "tackling_bias"></ref><br />
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===Unintended Consequences of Bias Reduction===<br />
It has been suggested that algorithms de-biased in terms of gender could still produce the same biased outcome. Algorithms may still use online [[Wikipedia: Proxy|proxies]] in their scoring process to produce discriminatory results as these proxies serve as stand-ins for [[Wikipedia: Protected group|protected groups]], like gender <ref name='TechScience'>Larson, J., Mattu, S., & Angwin, J. (2015, August 31). Unintended Consequences of Geographic Targeting. ''Technology Science''. https://techscience.org/a/2015090103/</ref><ref name='Zarsky'>Zarsky, T. Z. (2014). Understanding Discrimination in the Scored Society. ''Washington Law Review'', 89(4), 1375-1412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2550248</ref>. For example, while algorithms may be de-biased on the terms of gender specifically, the algorithm may use stand-in factors such as height or weight as a proxy to determine a candidate's gender <ref name='TechScience'></ref>. This leaves room for the algorithm to produce bias results based on a candidate's gender.<br />
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Although there is a [[Wikipedia: Statistics|statistical]] process that is known to eliminate proxy discrimination, the process requires the algorithmic model to include "training data information on legally prohibited characteristics” <ref name='PrinceSchwarcz'>Prince, A. E.R. & Schwarcz, D. (2020). Proxy Discrimination in the Age of Artificial Intelligence and Big Data. ''Iowa Law Review'', 105(3). https://ilr.law.uiowa.edu/print/volume-105-issue-3/proxy-discrimination-in-the-age-of-artificial-intelligence-and-big-data/</ref>. Even if such legally prohibited information is obtained, characteristics would then be measured on their predictive power of the [[Wikipedia: Dependent and independent variables|target variable]]; this could result in unintended amplification of the initial proxy discrimination <ref name='PrinceSchwarcz'></ref>. For example, if height was measured as a highly predictive characteristic and height was used as a proxy for gender, then the algorithm would intentionally discriminate on the predictive basis of height thus unintentionally discriminating against gender.<br />
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== References ==<br />
<references/></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Gender_bias_in_the_Online_Job_Search&diff=101592Gender bias in the Online Job Search2021-04-09T19:26:35Z<p>Ptse: </p>
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<div>[[File:Hiringfunnel.png |250px|thumbnail|right| There are many stages to the hiring process, and algorithms are involved in almost all of them. <ref name=upturn>Bogen, M. & Rieke, A. (2018). <i>Help Wanted: An Examination of Hiring Algorithms, Equity, and Bias</i>. Upturn. https://www.upturn.org/static/reports/2018/hiring-algorithms/files/Upturn%20--%20Help%20Wanted%20-%20An%20Exploration%20of%20Hiring%20Algorithms,%20Equity%20and%20Bias.pdf</ref>]]<br />
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The advancement of [[Wikipedia: Technology|technology]] and [[Wikipedia: Algorithm|algorithms]] has led to companies recruiting and hiring potential employees through the use of [[Wikipedia: Big data|big data]] and [[Wikipedia: Artificial intelligence|artificial intelligence]], which can amplify gender [[Wikipedia: Bias|bias]] in the online job search <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>. Gender bias refers to the “unfair difference” in the way that both men and women are treated <ref name=biasDefinition>Cambridge Dictionary.(n.d.). Gender Bias. In <i>Cambridge English Dictionary</i>. https://dictionary.cambridge.org/us/dictionary/english/gender-bias</ref>. In the context of the online job search, gender bias is defined as the advantage male job seekers have versus female job seekers. The use of algorithms in the online job search process can perpetuate existing biases which result in ethical implications regarding blocked job opportunities for females, and the disadvantage for female job seekers due to systematic [[Wikipedia: Gender role|gender roles]].<br />
<br />
==<big> Artificial Intelligence in the Recruitment Process </big>==<br />
Artificial intelligence is being utilized in recruiting algorithms. The AI technology is learning how to recruit most effectively for the company using it <ref name=ai_guide> (2021, February 26). <i>Ai for recruiting: A definitive guide for hr professionals. </i> Ideal. https://ideal.com/ai-recruiting/#:~:text=AI%20for%20recruiting%20is%20the,repetitive%2C%20high%2Dvolume%20tasks. </ref>. The introduction of AI into the recruiting process makes candidates 14% more likely to pass interviews and receive offers, 18% more likely to accept the job, and they are 12% less likely to inform recruiters of competing job offer during the negotiation process <ref> Cowgill, B. (2018).<i> Bias and productivity in humans and algorithms: Theory and evidence from resume screening. </i> Columbia Business School, Columbia University, 29. http://conference.iza.org/conference_files/MacroEcon_2017/cowgill_b8981.pdf </ref>. This technology is mainly used with four general types of recruitment activities: outreach, screening, assessment, and coordination <ref name=ai_manage> Black, J., & Esch, P. (2019, December 31). <i> Ai-enabled recruiting: What is it and how should a manager use it? </i> https://www.sciencedirect.com/science/article/pii/S0007681319301612 </ref>. <br />
[[File:life_cycle.png |250px|thumbnail|right|The Steps of the Recruitment Life Cycle. Sourced from https://medium.com/@corprate.io/ultimate-6-steps-guide-in-recruitment-process-ae9a6bd70863]]<br />
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===Outreach===<br />
Artificial intelligence helps companies find the right applicants. These potential applicants consist of active candidates (those who are deliberately searching for a new job) and passive candidates (those who are not actively searching but would show interest for the right opportunity). The AI uses data from websites like LinkedIn, Facebook, Twitter, etc. to match candidates to jobs. After enough training, the AI will have learned the most efficient way to word and present jobs to potential candidates. <ref name=ai_manage> </ref><br />
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===Screening===<br />
AI is also used for the resume screening process of recruitment. AI can help companies reduce the time-to-hire. [[Wikipedia: Hilton_Hotels_%26_Resorts Hilton Hotels & Resorts| Hilton Hotels & Resorts]] implemented a screening tool that used AI and found an 88% decline in time-to-hire, or 42 days to 5 days. These AI screening tools can be more effective than humans because they can infer key terms from natural language. For example, instead of searching for the keyword, ‘persistence’, the AI can infer this term from other phrases or wording. <ref name=ai_manage> </ref><br />
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===Assessing===<br />
AI assessments are used to narrow a candidate pool after the resume screening step. AI can be used in varying types of assessments. It can range from realistic [[Wikipedia: Chatbot|chatbot]] conversations in [[Wikipedia: Situational_judgement_test| situational judgement tests]] to making decisions based on an applicant’s responses to test questions <ref name=assess>(n.d.). <i> Artificial intelligence (ai) in assessment. </i> Aon. https://assessment.aon.com/en-us/online-assessment/ai-in-assessment </ref>. These assessments can be used as an initial interview or to informally test candidates for desired traits like an individual’s risk propensity. <ref name=ai_manage> </ref><br />
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===Coordination===<br />
It is beneficial for companies to make their hiring process as positive of an experience as possible because a candidate might not be the right fit today, but they could be perfect in a year. AI can facilitate with this because it creates a more seamless, digital experience. Companies can use chatbots to update candidates on where they are in the process, fill in information gaps like the candidate’s potential start date, and answer candidate questions. <ref name=ai_manage> </ref> Also, a company’s openness with their usage of AI in the recruitment process increased the likelihood of a job application, as well as having a positive experience with the process <ref name=marketing> Esch, P., Black, J., & Ferolie, J. (2018, September 17). <i> Marketing ai recruitment: The next phase in job application and selection. </i> https://www.sciencedirect.com/science/article/pii/S0747563218304497#sec5 </ref>.<br />
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==<big>Evidence of Bias</big>==<br />
[[File:LookalikeAudience.png |300px|thumbnail|left| Process of Facebook's lookalike audience tool. <ref name='Facebook'>Facebook. (n.d.). https://www.facebook.com/</ref>]]<br />
===Job Recruitment Algorithms===<br />
Job recruitment algorithms have been found to reinforce and perpetuate unconscious human gender bias <ref name=abc>Hanrahan, C. (2020, December 2. <i>Job recruitment algorithms can amplify unconscious bias favouring men, new research finds.</i> The ABC News. https://www.abc.net.au/news/2020-12-02/job-recruitment-algorithms-can-have-bias-against-women/12938870</ref>. Because job recruitment algorithms are trained on real-world data – and the real world is biased – the algorithms amplify this bias on a larger scale. Decision-making algorithms are “designed to mimic how a human would…choose a potential employee” and without careful consideration, algorithms can intensify bias in recruiting <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. <br />
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Utilizing real-world data to shape algorithms leads to algorithms producing biased outcomes. Algorithms make predictions by analyzing past data <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>. If the past data includes biased judgments, then the algorithm’s predictions will also be biased. [[Wikipedia: Facebook|Facebook’s]] tool called “[[Wikipedia: Lookalike audience|lookalike audience]]” allows advertisers – in this case, employers – to input a “[[Wikipedia: Target audience|source audience]]” that will dictate who Facebook advertises jobs to, based on a person’s similarities with this “source audience” <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>. This tool is meant to help employers predict which users are most likely to apply for jobs. If an employer provides the lookalike tool with a dataset that does not include a lot of women, then Facebook will not advertise the job to women. Employers could use this tool to deliberately exclude certain groups, but employers could also be unaware of the bias of their “source audience” <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>.<br />
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===Job Recommendation Algorithms===<br />
Job recommendation algorithms within online platforms are built to find and reproduce patterns in user behavior, updating predictions or decisions as job seekers and employers interact <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. If the system within the platform recognizes that the employer interacts with mostly men, then the algorithm will look for those characteristics in potential job applicants and replicate the pattern <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. This pattern picked up by the algorithm can happen without specific instruction from the employer, which leads to biases going unnoticed.<br />
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Another problem that is encountered with job recommendation algorithms is the “lack of publicly available information.”<ref name = "mitigating_bias">Raghavan M., Barocas S., Kleinberg J., Levy K. (6 December 2019). [https://arxiv.org/abs/1906.09208 "Mitigating Bias in Algorithmic Hiring: Evaluating Claims and Practices"] Retrieved on 9 April 2021</ref> While companies can say that they are working to account for biases in the algorithm, the general public does not actually know how these problems are being tackled. However, the reason why this information is not public is due to the sensitivity of employee data that is used to train the algorithms. Because of this, the information that we can gather about practices in industry is limited.<ref name = "mitigating_bias"></ref><br />
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===Algorithms Extending Human Bias===<br />
Personal, human bias extends into [[Wikipedia: Algorithmic bias| algorithmic bias]]. A study conducted at the [[Wikipedia: University of California, Santa Barbara|University of California, Santa Barbara]] found that people’s own underlying biases were bigger determinants of their likelihood to apply to jobs than any gendered job posting <ref name=longitudinal> Tang, S., et al. (2017). Gender Bias in the Job Market: A Longitudinal Analysis. <i> ACM on the Human-Computer Interaction. </i>. https://dl.acm.org/doi/epdf/10.1145/3134734</ref>. Underlying human biases need to be reduced to work towards gender neutrality in the job market <ref name=longitudinal> Tang, S., et al. (2017). Gender Bias in the Job Market: A Longitudinal Analysis. <i> ACM on the Human-Computer Interaction. </i>. https://dl.acm.org/doi/epdf/10.1145/3134734</ref>. Humans choose the data to train algorithms with, and the "choice to use certain data inputs over others can lead to discriminatory outcomes" <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. Hiring algorithms can be an extension of "our opinions embedded in code" and further research highlights that algorithms reproduce existing societal, human bias <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. The people constructing hiring algorithms are in the tech industry, which is not very diverse. This leads to algorithms that are trained on non-diverse data, which extends human gender bias into the online job market <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. While creating algorithms, "biases creep in because human bias [influences] the algorithm" <ref name=cnbc> Rosenbaum, E. (2018, May 30). <i>Silicon Valley is stumped: A.I. cannot always remove bias from hiring</i>. Consumer News and Business Channel. https://www.cnbc.com/2018/05/30/silicon-valley-is-stumped-even-a-i-cannot-remove-bias-from-hiring.html</ref>. Humans build biased algorithms, so it is up to humans to notice the biases and fix them <ref name=cnbc></ref>.<br />
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==<big>Ethical Implications</big>==<br />
===Algorithms Blocking Opportunities===<br />
[[File:Men in tech.png |300px|thumbnail|right| Amazon's hiring algorithm was modeled after real-world data, where there are more men in the tech field. The difference in gender of employees is shown in the figure above <ref name=amazon> Dastin, J. (2018, October 10). <i>Amazon scraps secret AI recruiting tool that showed bias against women.</i> Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G</ref>.]]<br />
Algorithms in the online job search do not outright reject job seekers. Instead, they block certain groups of job seekers from seeing opportunities they are qualified for; as [[Wikipedia: Pauline Kim|Pauline Kim]], a legal scholar, stated, “not informing people of a job opportunity is a highly effective barrier” to job seekers <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. Qualified candidates cannot apply for a job if they have not been shown the opportunity. <br />
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[[Wikipedia: Amazon (company)|Amazon’s]] algorithmic recruiting tool was trained with 10 years’ worth of [[Wikipedia: Résumé|resumes]] that were sent to Amazon; however, because technology is a male-dominated field, most of the resumes were from male applicants, leading the algorithm to downvote women <ref name=amazon> Dastin, J. (2018, October 10). <i>Amazon scraps secret AI recruiting tool that showed bias against women.</i> Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G </ref>. This method of training taught the algorithm that men were preferred, therefore penalizing candidates who included the word “women’s” in their resume. For example, if the candidate listed an activity as “women’s team captain, ” their resume would be downgraded in the system <ref name=amazon> Dastin, J. (2018, October 10). <i>Amazon scraps secret AI recruiting tool that showed bias against women. </i> Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G </ref>. Amazon has since scrapped this recruiting algorithm <ref name=amazonscandal2> <i>Amazon scrapped 'sexist AI' tool</i>. (2018, October 10). British Broadcasting Corporation. https://www.bbc.com/news/technology-45809919 </ref>.<br />
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A test was also conducted on an ad-serving algorithm that displayed ads for jobs related to STEM. The algorithm was supposedly designed to display these ads to men and women equally and was tested in 191 different countries. The results showed that the ads were shown to around 20% more men than women. One of the explanations to the algorithm choosing to show the ads to more men than women comes from an economic standpoint. Online advertisers are constantly competing for users’ attention. A study has shown that on average, it is more expensive to get the attention of females over males when advertising online.<ref>Lambrecht A., Tucker C. (2019). [https://pubsonline-informs-org.proxy.lib.umich.edu/doi/pdf/10.1287/mnsc.2018.3093 "Algorithmic Bias? An Empirical Study of Apparent GenderBased Discrimination in the Display of STEM Career Ads"] Retrieved on 9 April 2021.</ref><br />
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===Traditional Gender Roles Affect Outcomes===<br />
It has been studied that women can have a better keyword match on their resume, yet not be selected for a job if a man has more experience than them <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. These hiring algorithms that are built and trained by humans do not take into account the time women must take off of work to have children or to take care of children <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. The author of a study done by the [[Wikipedia: University of Melbourne|University of Melbourne]] recounts that “women have less experience because they take time [off work] for caregiving, and that algorithm is going to bump men up and women down based on experience” <ref name=abc>Hanrahan, C. (2020, December 2. <i>Job recruitment algorithms can amplify unconscious bias favouring men, new research finds.</i> The ABC News. https://www.abc.net.au/news/2020-12-02/job-recruitment-algorithms-can-have-bias-against-women/12938870</ref>. Because women are more likely to experience a disruption in their career due to children, they will be viewed as a lesser candidate by the algorithm, even if they have more relevant experience than a male candidate <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. Hiring algorithms do not take into account gender roles, which include women taking time off to give birth. This replicates and reinforces gender bias in the online hiring process <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>.<br />
<br />
==<big>Reducing Bias</big>==<br />
[[File:WordEmbeddings.png |350px|thumbnail|left| Basic graphic of how researchers observed and evaluated gender bias of word embeddings in algorithms. <ref name=SunEtAl>Sun, T., et al. (2019, June 21). ''Mitigating Gender Bias in Natural Language Processing: Literature Review''. Cornell University. https://arxiv.org/pdf/1906.08976.pdf</ref>]]<br />
===Rethinking How Algorithms are Built===<br />
Vendors that build recruitment algorithms to target specific job seekers need to think beyond the minimum [[Wikipedia: Compliance requirements|compliance requirements]]; they have to consider whether or not the algorithm they are building is leading to more fair hiring outcomes <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. Additionally, the people stating that their algorithms will reduce bias in the hiring process have to build and test their algorithms while keeping that goal in mind, or else the technology will continue to undermine the online job search process <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. Re-thinking algorithms and how to build them will begin to reduce bias in the job search, as many factors need to be considered.<br />
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One specific aspect of gender bias can be found in [[Wikipedia: Word embedding|word embeddings]]. Word embeddings are [[Wikipedia: Binary|binary]], pre-trained models that assign words or phrases specific representations and meanings; these models have been found to reflect societal bias <ref name=WordEmbeddings>GeeksforGeeks. (2020, October 14). Word Embeddings in NLP. https://www.geeksforgeeks.org/word-embeddings-in-nlp/</ref>. For example, words like ''"[[Wikipedia: Receptionist|receptionist]]"'' and ''"[[Wikipedia: Nursing|nurse]]"'' are linked to ''"women"'' and ''"she"'' whereas words like ''"[[Wikipedia: Physician|doctor]]"'' and ''"[[Wikipedia: Computer scientist|computer scientist]]"'' are linked to ''"men"'' and ''"he"''. In addition, there has been a “prevailing idealized concept of femininity” in the past.<ref name = "gender_bias">Leavy S., Meaney G., Wade K., Greene D. (12 July 2020) [https://link-springer-com.proxy.lib.umich.edu/chapter/10.1007%2F978-3-030-52485-2_2 "Mitigating Gender Bias in Machine Learning Data Sets"] Retrieved on 9 April 2021</ref> The term “female” appears more than twice the amount of times the term “male” appears. This suggests that in most contexts, males are the default assumption over females when referring to someone.<ref name = "gender_bias"></ref> Researchers have explored potential solutions to de-bias word embeddings by using methods such as building a genderless framework as well as teaching the algorithm gender-neutral word embeddings <ref name=SunEtAl></ref>. Such methods aim to minimize the difference between gendered words (i.e. ''male'' versus ''female'') and maximize "the difference between the gender direction and other neutral dimensions” <ref name=SunEtAl></ref><ref name='Bolukbasi'>Bolukbasi, T., et al. (2016). Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. ''Advances in Neural Information Processing Systems 29 (NIPS 2016)''</ref>. This allows algorithms to use or neglect the gender dimensions.<br />
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===Balancing Humans and Algorithms===<br />
Implementing a balance between predictive algorithms and human insight is a promising solution for employers looking to use algorithms in their hiring process while reducing bias <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. Using artificial intelligence and algorithms to parse through large amounts of data or applicants works well for processing. Balancing the processing by algorithms with the "human ability to recognize more intangible realities of what that data might mean" is the second step in the process of limiting algorithmic bias <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. For a partnership between humans and algorithms to be successful within companies, they need to consciously and deliberately implement new practices <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. Both algorithms and humans still need to be held accountable for reducing bias, and working together would encourage a good short-term solution to the phenomenon of gender bias in the online job search <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>.<br />
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While aiming to strike a balance between humans and algorithms is a promising solution, there is an important question to answer. What is considered “fair” when trying to find qualified candidates for a job. Most conversations have be geared towards “treating similar individuals similarly.”<ref name = "tackling_bias">Silberg J., Manyika J. (6 June 2019). [https://www.mckinsey.com/featured-insights/artificial-intelligence/tackling-bias-in-artificial-intelligence-and-in-humans# "Tackling bias in artificial intelligence (and in humans)"] Retrieved on 9 April 2021</ref> However, a study has shown that a “model cannot conform to more than a few group fairness metrics at the same time.”<ref name = "tackling_bias"></ref><br />
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===Unintended Consequences of Bias Reduction===<br />
It has been suggested that algorithms de-biased in terms of gender could still produce the same biased outcome. Algorithms may still use online [[Wikipedia: Proxy|proxies]] in their scoring process to produce discriminatory results as these proxies serve as stand-ins for [[Wikipedia: Protected group|protected groups]], like gender <ref name='TechScience'>Larson, J., Mattu, S., & Angwin, J. (2015, August 31). Unintended Consequences of Geographic Targeting. ''Technology Science''. https://techscience.org/a/2015090103/</ref><ref name='Zarsky'>Zarsky, T. Z. (2014). Understanding Discrimination in the Scored Society. ''Washington Law Review'', 89(4), 1375-1412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2550248</ref>. For example, while algorithms may be de-biased on the terms of gender specifically, the algorithm may use stand-in factors such as height or weight as a proxy to determine a candidate's gender <ref name='TechScience'></ref>. This leaves room for the algorithm to produce bias results based on a candidate's gender.<br />
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Although there is a [[Wikipedia: Statistics|statistical]] process that is known to eliminate proxy discrimination, the process requires the algorithmic model to include "training data information on legally prohibited characteristics” <ref name='PrinceSchwarcz'>Prince, A. E.R. & Schwarcz, D. (2020). Proxy Discrimination in the Age of Artificial Intelligence and Big Data. ''Iowa Law Review'', 105(3). https://ilr.law.uiowa.edu/print/volume-105-issue-3/proxy-discrimination-in-the-age-of-artificial-intelligence-and-big-data/</ref>. Even if such legally prohibited information is obtained, characteristics would then be measured on their predictive power of the [[Wikipedia: Dependent and independent variables|target variable]]; this could result in unintended amplification of the initial proxy discrimination <ref name='PrinceSchwarcz'></ref>. For example, if height was measured as a highly predictive characteristic and height was used as a proxy for gender, then the algorithm would intentionally discriminate on the predictive basis of height thus unintentionally discriminating against gender.<br />
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== References ==<br />
<references/></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Gender_bias_in_the_Online_Job_Search&diff=101591Gender bias in the Online Job Search2021-04-09T19:23:10Z<p>Ptse: </p>
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<div>[[File:Hiringfunnel.png |250px|thumbnail|right| There are many stages to the hiring process, and algorithms are involved in almost all of them. <ref name=upturn>Bogen, M. & Rieke, A. (2018). <i>Help Wanted: An Examination of Hiring Algorithms, Equity, and Bias</i>. Upturn. https://www.upturn.org/static/reports/2018/hiring-algorithms/files/Upturn%20--%20Help%20Wanted%20-%20An%20Exploration%20of%20Hiring%20Algorithms,%20Equity%20and%20Bias.pdf</ref>]]<br />
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The advancement of [[Wikipedia: Technology|technology]] and [[Wikipedia: Algorithm|algorithms]] has led to companies recruiting and hiring potential employees through the use of [[Wikipedia: Big data|big data]] and [[Wikipedia: Artificial intelligence|artificial intelligence]], which can amplify gender [[Wikipedia: Bias|bias]] in the online job search <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>. Gender bias refers to the “unfair difference” in the way that both men and women are treated <ref name=biasDefinition>Cambridge Dictionary.(n.d.). Gender Bias. In <i>Cambridge English Dictionary</i>. https://dictionary.cambridge.org/us/dictionary/english/gender-bias</ref>. In the context of the online job search, gender bias is defined as the advantage male job seekers have versus female job seekers. The use of algorithms in the online job search process can perpetuate existing biases which result in ethical implications regarding blocked job opportunities for females, and the disadvantage for female job seekers due to systematic [[Wikipedia: Gender role|gender roles]].<br />
<br />
==<big> Artificial Intelligence in the Recruitment Process </big>==<br />
Artificial intelligence is being utilized in recruiting algorithms. The AI technology is learning how to recruit most effectively for the company using it <ref name=ai_guide> (2021, February 26). <i>Ai for recruiting: A definitive guide for hr professionals. </i> Ideal. https://ideal.com/ai-recruiting/#:~:text=AI%20for%20recruiting%20is%20the,repetitive%2C%20high%2Dvolume%20tasks. </ref>. The introduction of AI into the recruiting process makes candidates 14% more likely to pass interviews and receive offers, 18% more likely to accept the job, and they are 12% less likely to inform recruiters of competing job offer during the negotiation process <ref> Cowgill, B. (2018).<i> Bias and productivity in humans and algorithms: Theory and evidence from resume screening. </i> Columbia Business School, Columbia University, 29. http://conference.iza.org/conference_files/MacroEcon_2017/cowgill_b8981.pdf </ref>. This technology is mainly used with four general types of recruitment activities: outreach, screening, assessment, and coordination <ref name=ai_manage> Black, J., & Esch, P. (2019, December 31). <i> Ai-enabled recruiting: What is it and how should a manager use it? </i> https://www.sciencedirect.com/science/article/pii/S0007681319301612 </ref>. <br />
[[File:life_cycle.png |250px|thumbnail|right|The Steps of the Recruitment Life Cycle. Sourced from https://medium.com/@corprate.io/ultimate-6-steps-guide-in-recruitment-process-ae9a6bd70863]]<br />
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===Outreach===<br />
Artificial intelligence helps companies find the right applicants. These potential applicants consist of active candidates (those who are deliberately searching for a new job) and passive candidates (those who are not actively searching but would show interest for the right opportunity). The AI uses data from websites like LinkedIn, Facebook, Twitter, etc. to match candidates to jobs. After enough training, the AI will have learned the most efficient way to word and present jobs to potential candidates. <ref name=ai_manage> </ref><br />
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===Screening===<br />
AI is also used for the resume screening process of recruitment. AI can help companies reduce the time-to-hire. [[Wikipedia: Hilton_Hotels_%26_Resorts Hilton Hotels & Resorts| Hilton Hotels & Resorts]] implemented a screening tool that used AI and found an 88% decline in time-to-hire, or 42 days to 5 days. These AI screening tools can be more effective than humans because they can infer key terms from natural language. For example, instead of searching for the keyword, ‘persistence’, the AI can infer this term from other phrases or wording. <ref name=ai_manage> </ref><br />
<br />
===Assessing===<br />
AI assessments are used to narrow a candidate pool after the resume screening step. AI can be used in varying types of assessments. It can range from realistic [[Wikipedia: Chatbot|chatbot]] conversations in [[Wikipedia: Situational_judgement_test| situational judgement tests]] to making decisions based on an applicant’s responses to test questions <ref name=assess>(n.d.). <i> Artificial intelligence (ai) in assessment. </i> Aon. https://assessment.aon.com/en-us/online-assessment/ai-in-assessment </ref>. These assessments can be used as an initial interview or to informally test candidates for desired traits like an individual’s risk propensity. <ref name=ai_manage> </ref><br />
<br />
===Coordination===<br />
It is beneficial for companies to make their hiring process as positive of an experience as possible because a candidate might not be the right fit today, but they could be perfect in a year. AI can facilitate with this because it creates a more seamless, digital experience. Companies can use chatbots to update candidates on where they are in the process, fill in information gaps like the candidate’s potential start date, and answer candidate questions. <ref name=ai_manage> </ref> Also, a company’s openness with their usage of AI in the recruitment process increased the likelihood of a job application, as well as having a positive experience with the process <ref name=marketing> Esch, P., Black, J., & Ferolie, J. (2018, September 17). <i> Marketing ai recruitment: The next phase in job application and selection. </i> https://www.sciencedirect.com/science/article/pii/S0747563218304497#sec5 </ref>.<br />
<br />
==<big>Evidence of Bias</big>==<br />
[[File:LookalikeAudience.png |300px|thumbnail|left| Process of Facebook's lookalike audience tool. <ref name='Facebook'>Facebook. (n.d.). https://www.facebook.com/</ref>]]<br />
===Job Recruitment Algorithms===<br />
Job recruitment algorithms have been found to reinforce and perpetuate unconscious human gender bias <ref name=abc>Hanrahan, C. (2020, December 2. <i>Job recruitment algorithms can amplify unconscious bias favouring men, new research finds.</i> The ABC News. https://www.abc.net.au/news/2020-12-02/job-recruitment-algorithms-can-have-bias-against-women/12938870</ref>. Because job recruitment algorithms are trained on real-world data – and the real world is biased – the algorithms amplify this bias on a larger scale. Decision-making algorithms are “designed to mimic how a human would…choose a potential employee” and without careful consideration, algorithms can intensify bias in recruiting <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. <br />
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Utilizing real-world data to shape algorithms leads to algorithms producing biased outcomes. Algorithms make predictions by analyzing past data <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>. If the past data includes biased judgments, then the algorithm’s predictions will also be biased. [[Wikipedia: Facebook|Facebook’s]] tool called “[[Wikipedia: Lookalike audience|lookalike audience]]” allows advertisers – in this case, employers – to input a “[[Wikipedia: Target audience|source audience]]” that will dictate who Facebook advertises jobs to, based on a person’s similarities with this “source audience” <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>. This tool is meant to help employers predict which users are most likely to apply for jobs. If an employer provides the lookalike tool with a dataset that does not include a lot of women, then Facebook will not advertise the job to women. Employers could use this tool to deliberately exclude certain groups, but employers could also be unaware of the bias of their “source audience” <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>.<br />
<br />
===Job Recommendation Algorithms===<br />
Job recommendation algorithms within online platforms are built to find and reproduce patterns in user behavior, updating predictions or decisions as job seekers and employers interact <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. If the system within the platform recognizes that the employer interacts with mostly men, then the algorithm will look for those characteristics in potential job applicants and replicate the pattern <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. This pattern picked up by the algorithm can happen without specific instruction from the employer, which leads to biases going unnoticed.<br />
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Another problem that is encountered with job recommendation algorithms is the “lack of publicly available information.”<ref name = "mitigating_bias">Raghavan M., Barocas S., Kleinberg J., Levy K. (6 December 2019). [https://arxiv.org/abs/1906.09208 "Mitigating Bias in Algorithmic Hiring: Evaluating Claims and Practices"] Retrieved on 9 April 2021</ref> While companies can say that they are working to account for biases in the algorithm, the general public does not actually know how these problems are being tackled. However, the reason why this information is not public is due to the sensitivity of employee data that is used to train the algorithms. Because of this, the information that we can gather about practices in industry is limited.<ref name = "mitigating_bias"></ref><br />
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===Algorithms Extending Human Bias===<br />
Personal, human bias extends into [[Wikipedia: Algorithmic bias| algorithmic bias]]. A study conducted at the [[Wikipedia: University of California, Santa Barbara|University of California, Santa Barbara]] found that people’s own underlying biases were bigger determinants of their likelihood to apply to jobs than any gendered job posting <ref name=longitudinal> Tang, S., et al. (2017). Gender Bias in the Job Market: A Longitudinal Analysis. <i> ACM on the Human-Computer Interaction. </i>. https://dl.acm.org/doi/epdf/10.1145/3134734</ref>. Underlying human biases need to be reduced to work towards gender neutrality in the job market <ref name=longitudinal> Tang, S., et al. (2017). Gender Bias in the Job Market: A Longitudinal Analysis. <i> ACM on the Human-Computer Interaction. </i>. https://dl.acm.org/doi/epdf/10.1145/3134734</ref>. Humans choose the data to train algorithms with, and the "choice to use certain data inputs over others can lead to discriminatory outcomes" <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. Hiring algorithms can be an extension of "our opinions embedded in code" and further research highlights that algorithms reproduce existing societal, human bias <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. The people constructing hiring algorithms are in the tech industry, which is not very diverse. This leads to algorithms that are trained on non-diverse data, which extends human gender bias into the online job market <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. While creating algorithms, "biases creep in because human bias [influences] the algorithm" <ref name=cnbc> Rosenbaum, E. (2018, May 30). <i>Silicon Valley is stumped: A.I. cannot always remove bias from hiring</i>. Consumer News and Business Channel. https://www.cnbc.com/2018/05/30/silicon-valley-is-stumped-even-a-i-cannot-remove-bias-from-hiring.html</ref>. Humans build biased algorithms, so it is up to humans to notice the biases and fix them <ref name=cnbc></ref>.<br />
<br />
==<big>Ethical Implications</big>==<br />
===Algorithms Blocking Opportunities===<br />
[[File:Men in tech.png |300px|thumbnail|right| Amazon's hiring algorithm was modeled after real-world data, where there are more men in the tech field. The difference in gender of employees is shown in the figure above <ref name=amazon> Dastin, J. (2018, October 10). <i>Amazon scraps secret AI recruiting tool that showed bias against women.</i> Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G</ref>.]]<br />
Algorithms in the online job search do not outright reject job seekers. Instead, they block certain groups of job seekers from seeing opportunities they are qualified for; as [[Wikipedia: Pauline Kim|Pauline Kim]], a legal scholar, stated, “not informing people of a job opportunity is a highly effective barrier” to job seekers <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. Qualified candidates cannot apply for a job if they have not been shown the opportunity. <br />
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[[Wikipedia: Amazon (company)|Amazon’s]] algorithmic recruiting tool was trained with 10 years’ worth of [[Wikipedia: Résumé|resumes]] that were sent to Amazon; however, because technology is a male-dominated field, most of the resumes were from male applicants, leading the algorithm to downvote women <ref name=amazon> Dastin, J. (2018, October 10). <i>Amazon scraps secret AI recruiting tool that showed bias against women.</i> Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G </ref>. This method of training taught the algorithm that men were preferred, therefore penalizing candidates who included the word “women’s” in their resume. For example, if the candidate listed an activity as “women’s team captain, ” their resume would be downgraded in the system <ref name=amazon> Dastin, J. (2018, October 10). <i>Amazon scraps secret AI recruiting tool that showed bias against women. </i> Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G </ref>. Amazon has since scrapped this recruiting algorithm <ref name=amazonscandal2> <i>Amazon scrapped 'sexist AI' tool</i>. (2018, October 10). British Broadcasting Corporation. https://www.bbc.com/news/technology-45809919 </ref>.<br />
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A test was also conducted on an ad-serving algorithm that displayed ads for jobs related to STEM. The algorithm was supposedly designed to display these ads to men and women equally and was tested in 191 different countries. The results showed that the ads were shown to around 20% more men than women. One of the explanations to the algorithm choosing to show the ads to more men than women comes from an economic standpoint. Online advertisers are constantly competing for users’ attention. A study has shown that on average, it is more expensive to get the attention of females over males when advertising online.<ref>Lambrecht A., Tucker C. (2019). [https://pubsonline-informs-org.proxy.lib.umich.edu/doi/pdf/10.1287/mnsc.2018.3093 "Algorithmic Bias? An Empirical Study of Apparent GenderBased Discrimination in the Display of STEM Career Ads"] Retrieved on 9 April 2021.</ref><br />
<br />
===Traditional Gender Roles Affect Outcomes===<br />
It has been studied that women can have a better keyword match on their resume, yet not be selected for a job if a man has more experience than them <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. These hiring algorithms that are built and trained by humans do not take into account the time women must take off of work to have children or to take care of children <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. The author of a study done by the [[Wikipedia: University of Melbourne|University of Melbourne]] recounts that “women have less experience because they take time [off work] for caregiving, and that algorithm is going to bump men up and women down based on experience” <ref name=abc>Hanrahan, C. (2020, December 2. <i>Job recruitment algorithms can amplify unconscious bias favouring men, new research finds.</i> The ABC News. https://www.abc.net.au/news/2020-12-02/job-recruitment-algorithms-can-have-bias-against-women/12938870</ref>. Because women are more likely to experience a disruption in their career due to children, they will be viewed as a lesser candidate by the algorithm, even if they have more relevant experience than a male candidate <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. Hiring algorithms do not take into account gender roles, which include women taking time off to give birth. This replicates and reinforces gender bias in the online hiring process <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>.<br />
<br />
==<big>Reducing Bias</big>==<br />
[[File:WordEmbeddings.png |350px|thumbnail|left| Basic graphic of how researchers observed and evaluated gender bias of word embeddings in algorithms. <ref name=SunEtAl>Sun, T., et al. (2019, June 21). ''Mitigating Gender Bias in Natural Language Processing: Literature Review''. Cornell University. https://arxiv.org/pdf/1906.08976.pdf</ref>]]<br />
===Rethinking How Algorithms are Built===<br />
Vendors that build recruitment algorithms to target specific job seekers need to think beyond the minimum [[Wikipedia: Compliance requirements|compliance requirements]]; they have to consider whether or not the algorithm they are building is leading to more fair hiring outcomes <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. Additionally, the people stating that their algorithms will reduce bias in the hiring process have to build and test their algorithms while keeping that goal in mind, or else the technology will continue to undermine the online job search process <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. Re-thinking algorithms and how to build them will begin to reduce bias in the job search, as many factors need to be considered.<br />
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One specific aspect of gender bias can be found in [[Wikipedia: Word embedding|word embeddings]]. Word embeddings are [[Wikipedia: Binary|binary]], pre-trained models that assign words or phrases specific representations and meanings; these models have been found to reflect societal bias <ref name=WordEmbeddings>GeeksforGeeks. (2020, October 14). Word Embeddings in NLP. https://www.geeksforgeeks.org/word-embeddings-in-nlp/</ref>. For example, words like ''"[[Wikipedia: Receptionist|receptionist]]"'' and ''"[[Wikipedia: Nursing|nurse]]"'' are linked to ''"women"'' and ''"she"'' whereas words like ''"[[Wikipedia: Physician|doctor]]"'' and ''"[[Wikipedia: Computer scientist|computer scientist]]"'' are linked to ''"men"'' and ''"he"''. In addition, there has been a “prevailing idealized concept of femininity” in the past.<ref name = "gender_bias">Leavy S., Meaney G., Wade K., Greene D. (12 July 2020) [https://link-springer-com.proxy.lib.umich.edu/chapter/10.1007%2F978-3-030-52485-2_2 "Mitigating Gender Bias in Machine Learning Data Sets"] Retrieved on 9 April 2021</ref> The term “female” appears more than twice the amount of times the term “male” appears. This suggests that in most contexts, males are the default assumption over females when referring to someone.<ref name = "gender_bias"></ref> Researchers have explored potential solutions to de-bias word embeddings by using methods such as building a genderless framework as well as teaching the algorithm gender-neutral word embeddings <ref name=SunEtAl></ref>. Such methods aim to minimize the difference between gendered words (i.e. ''male'' versus ''female'') and maximize "the difference between the gender direction and other neutral dimensions” <ref name=SunEtAl></ref><ref name='Bolukbasi'>Bolukbasi, T., et al. (2016). Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. ''Advances in Neural Information Processing Systems 29 (NIPS 2016)''</ref>. This allows algorithms to use or neglect the gender dimensions.<br />
<br />
===Balancing Humans and Algorithms===<br />
Implementing a balance between predictive algorithms and human insight is a promising solution for employers looking to use algorithms in their hiring process while reducing bias <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. Using artificial intelligence and algorithms to parse through large amounts of data or applicants works well for processing. Balancing the processing by algorithms with the "human ability to recognize more intangible realities of what that data might mean" is the second step in the process of limiting algorithmic bias <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. For a partnership between humans and algorithms to be successful within companies, they need to consciously and deliberately implement new practices <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. Both algorithms and humans still need to be held accountable for reducing bias, and working together would encourage a good short-term solution to the phenomenon of gender bias in the online job search <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>.<br />
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===Unintended Consequences of Bias Reduction===<br />
It has been suggested that algorithms de-biased in terms of gender could still produce the same biased outcome. Algorithms may still use online [[Wikipedia: Proxy|proxies]] in their scoring process to produce discriminatory results as these proxies serve as stand-ins for [[Wikipedia: Protected group|protected groups]], like gender <ref name='TechScience'>Larson, J., Mattu, S., & Angwin, J. (2015, August 31). Unintended Consequences of Geographic Targeting. ''Technology Science''. https://techscience.org/a/2015090103/</ref><ref name='Zarsky'>Zarsky, T. Z. (2014). Understanding Discrimination in the Scored Society. ''Washington Law Review'', 89(4), 1375-1412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2550248</ref>. For example, while algorithms may be de-biased on the terms of gender specifically, the algorithm may use stand-in factors such as height or weight as a proxy to determine a candidate's gender <ref name='TechScience'></ref>. This leaves room for the algorithm to produce bias results based on a candidate's gender.<br />
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Although there is a [[Wikipedia: Statistics|statistical]] process that is known to eliminate proxy discrimination, the process requires the algorithmic model to include "training data information on legally prohibited characteristics” <ref name='PrinceSchwarcz'>Prince, A. E.R. & Schwarcz, D. (2020). Proxy Discrimination in the Age of Artificial Intelligence and Big Data. ''Iowa Law Review'', 105(3). https://ilr.law.uiowa.edu/print/volume-105-issue-3/proxy-discrimination-in-the-age-of-artificial-intelligence-and-big-data/</ref>. Even if such legally prohibited information is obtained, characteristics would then be measured on their predictive power of the [[Wikipedia: Dependent and independent variables|target variable]]; this could result in unintended amplification of the initial proxy discrimination <ref name='PrinceSchwarcz'></ref>. For example, if height was measured as a highly predictive characteristic and height was used as a proxy for gender, then the algorithm would intentionally discriminate on the predictive basis of height thus unintentionally discriminating against gender.<br />
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== References ==<br />
<references/></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Gender_bias_in_the_Online_Job_Search&diff=101590Gender bias in the Online Job Search2021-04-09T19:18:38Z<p>Ptse: </p>
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<div>[[File:Hiringfunnel.png |250px|thumbnail|right| There are many stages to the hiring process, and algorithms are involved in almost all of them. <ref name=upturn>Bogen, M. & Rieke, A. (2018). <i>Help Wanted: An Examination of Hiring Algorithms, Equity, and Bias</i>. Upturn. https://www.upturn.org/static/reports/2018/hiring-algorithms/files/Upturn%20--%20Help%20Wanted%20-%20An%20Exploration%20of%20Hiring%20Algorithms,%20Equity%20and%20Bias.pdf</ref>]]<br />
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The advancement of [[Wikipedia: Technology|technology]] and [[Wikipedia: Algorithm|algorithms]] has led to companies recruiting and hiring potential employees through the use of [[Wikipedia: Big data|big data]] and [[Wikipedia: Artificial intelligence|artificial intelligence]], which can amplify gender [[Wikipedia: Bias|bias]] in the online job search <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>. Gender bias refers to the “unfair difference” in the way that both men and women are treated <ref name=biasDefinition>Cambridge Dictionary.(n.d.). Gender Bias. In <i>Cambridge English Dictionary</i>. https://dictionary.cambridge.org/us/dictionary/english/gender-bias</ref>. In the context of the online job search, gender bias is defined as the advantage male job seekers have versus female job seekers. The use of algorithms in the online job search process can perpetuate existing biases which result in ethical implications regarding blocked job opportunities for females, and the disadvantage for female job seekers due to systematic [[Wikipedia: Gender role|gender roles]].<br />
<br />
==<big> Artificial Intelligence in the Recruitment Process </big>==<br />
Artificial intelligence is being utilized in recruiting algorithms. The AI technology is learning how to recruit most effectively for the company using it <ref name=ai_guide> (2021, February 26). <i>Ai for recruiting: A definitive guide for hr professionals. </i> Ideal. https://ideal.com/ai-recruiting/#:~:text=AI%20for%20recruiting%20is%20the,repetitive%2C%20high%2Dvolume%20tasks. </ref>. The introduction of AI into the recruiting process makes candidates 14% more likely to pass interviews and receive offers, 18% more likely to accept the job, and they are 12% less likely to inform recruiters of competing job offer during the negotiation process <ref> Cowgill, B. (2018).<i> Bias and productivity in humans and algorithms: Theory and evidence from resume screening. </i> Columbia Business School, Columbia University, 29. http://conference.iza.org/conference_files/MacroEcon_2017/cowgill_b8981.pdf </ref>. This technology is mainly used with four general types of recruitment activities: outreach, screening, assessment, and coordination <ref name=ai_manage> Black, J., & Esch, P. (2019, December 31). <i> Ai-enabled recruiting: What is it and how should a manager use it? </i> https://www.sciencedirect.com/science/article/pii/S0007681319301612 </ref>. <br />
[[File:life_cycle.png |250px|thumbnail|right|The Steps of the Recruitment Life Cycle. Sourced from https://medium.com/@corprate.io/ultimate-6-steps-guide-in-recruitment-process-ae9a6bd70863]]<br />
<br />
===Outreach===<br />
Artificial intelligence helps companies find the right applicants. These potential applicants consist of active candidates (those who are deliberately searching for a new job) and passive candidates (those who are not actively searching but would show interest for the right opportunity). The AI uses data from websites like LinkedIn, Facebook, Twitter, etc. to match candidates to jobs. After enough training, the AI will have learned the most efficient way to word and present jobs to potential candidates. <ref name=ai_manage> </ref><br />
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===Screening===<br />
AI is also used for the resume screening process of recruitment. AI can help companies reduce the time-to-hire. [[Wikipedia: Hilton_Hotels_%26_Resorts Hilton Hotels & Resorts| Hilton Hotels & Resorts]] implemented a screening tool that used AI and found an 88% decline in time-to-hire, or 42 days to 5 days. These AI screening tools can be more effective than humans because they can infer key terms from natural language. For example, instead of searching for the keyword, ‘persistence’, the AI can infer this term from other phrases or wording. <ref name=ai_manage> </ref><br />
<br />
===Assessing===<br />
AI assessments are used to narrow a candidate pool after the resume screening step. AI can be used in varying types of assessments. It can range from realistic [[Wikipedia: Chatbot|chatbot]] conversations in [[Wikipedia: Situational_judgement_test| situational judgement tests]] to making decisions based on an applicant’s responses to test questions <ref name=assess>(n.d.). <i> Artificial intelligence (ai) in assessment. </i> Aon. https://assessment.aon.com/en-us/online-assessment/ai-in-assessment </ref>. These assessments can be used as an initial interview or to informally test candidates for desired traits like an individual’s risk propensity. <ref name=ai_manage> </ref><br />
<br />
===Coordination===<br />
It is beneficial for companies to make their hiring process as positive of an experience as possible because a candidate might not be the right fit today, but they could be perfect in a year. AI can facilitate with this because it creates a more seamless, digital experience. Companies can use chatbots to update candidates on where they are in the process, fill in information gaps like the candidate’s potential start date, and answer candidate questions. <ref name=ai_manage> </ref> Also, a company’s openness with their usage of AI in the recruitment process increased the likelihood of a job application, as well as having a positive experience with the process <ref name=marketing> Esch, P., Black, J., & Ferolie, J. (2018, September 17). <i> Marketing ai recruitment: The next phase in job application and selection. </i> https://www.sciencedirect.com/science/article/pii/S0747563218304497#sec5 </ref>.<br />
<br />
==<big>Evidence of Bias</big>==<br />
[[File:LookalikeAudience.png |300px|thumbnail|left| Process of Facebook's lookalike audience tool. <ref name='Facebook'>Facebook. (n.d.). https://www.facebook.com/</ref>]]<br />
===Job Recruitment Algorithms===<br />
Job recruitment algorithms have been found to reinforce and perpetuate unconscious human gender bias <ref name=abc>Hanrahan, C. (2020, December 2. <i>Job recruitment algorithms can amplify unconscious bias favouring men, new research finds.</i> The ABC News. https://www.abc.net.au/news/2020-12-02/job-recruitment-algorithms-can-have-bias-against-women/12938870</ref>. Because job recruitment algorithms are trained on real-world data – and the real world is biased – the algorithms amplify this bias on a larger scale. Decision-making algorithms are “designed to mimic how a human would…choose a potential employee” and without careful consideration, algorithms can intensify bias in recruiting <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. <br />
<br />
Utilizing real-world data to shape algorithms leads to algorithms producing biased outcomes. Algorithms make predictions by analyzing past data <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>. If the past data includes biased judgments, then the algorithm’s predictions will also be biased. [[Wikipedia: Facebook|Facebook’s]] tool called “[[Wikipedia: Lookalike audience|lookalike audience]]” allows advertisers – in this case, employers – to input a “[[Wikipedia: Target audience|source audience]]” that will dictate who Facebook advertises jobs to, based on a person’s similarities with this “source audience” <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>. This tool is meant to help employers predict which users are most likely to apply for jobs. If an employer provides the lookalike tool with a dataset that does not include a lot of women, then Facebook will not advertise the job to women. Employers could use this tool to deliberately exclude certain groups, but employers could also be unaware of the bias of their “source audience” <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>.<br />
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===Job Recommendation Algorithms===<br />
Job recommendation algorithms within online platforms are built to find and reproduce patterns in user behavior, updating predictions or decisions as job seekers and employers interact <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. If the system within the platform recognizes that the employer interacts with mostly men, then the algorithm will look for those characteristics in potential job applicants and replicate the pattern <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. This pattern picked up by the algorithm can happen without specific instruction from the employer, which leads to biases going unnoticed.<br />
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Another problem that is encountered with job recommendation algorithms is the “lack of publicly available information.”<ref name = "mitigating_bias">Raghavan M., Barocas S., Kleinberg J., Levy K. (6 December 2019). [https://arxiv.org/abs/1906.09208 "Mitigating Bias in Algorithmic Hiring: Evaluating Claims and Practices"] Retrieved on 9 April 2021</ref> While companies can say that they are working to account for biases in the algorithm, the general public does not actually know how these problems are being tackled. However, the reason why this information is not public is due to the sensitivity of employee data that is used to train the algorithms. Because of this, the information that we can gather about practices in industry is limited.<ref name = "mitigating_bias"></ref><br />
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===Algorithms Extending Human Bias===<br />
Personal, human bias extends into [[Wikipedia: Algorithmic bias| algorithmic bias]]. A study conducted at the [[Wikipedia: University of California, Santa Barbara|University of California, Santa Barbara]] found that people’s own underlying biases were bigger determinants of their likelihood to apply to jobs than any gendered job posting <ref name=longitudinal> Tang, S., et al. (2017). Gender Bias in the Job Market: A Longitudinal Analysis. <i> ACM on the Human-Computer Interaction. </i>. https://dl.acm.org/doi/epdf/10.1145/3134734</ref>. Underlying human biases need to be reduced to work towards gender neutrality in the job market <ref name=longitudinal> Tang, S., et al. (2017). Gender Bias in the Job Market: A Longitudinal Analysis. <i> ACM on the Human-Computer Interaction. </i>. https://dl.acm.org/doi/epdf/10.1145/3134734</ref>. Humans choose the data to train algorithms with, and the "choice to use certain data inputs over others can lead to discriminatory outcomes" <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. Hiring algorithms can be an extension of "our opinions embedded in code" and further research highlights that algorithms reproduce existing societal, human bias <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. The people constructing hiring algorithms are in the tech industry, which is not very diverse. This leads to algorithms that are trained on non-diverse data, which extends human gender bias into the online job market <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. While creating algorithms, "biases creep in because human bias [influences] the algorithm" <ref name=cnbc> Rosenbaum, E. (2018, May 30). <i>Silicon Valley is stumped: A.I. cannot always remove bias from hiring</i>. Consumer News and Business Channel. https://www.cnbc.com/2018/05/30/silicon-valley-is-stumped-even-a-i-cannot-remove-bias-from-hiring.html</ref>. Humans build biased algorithms, so it is up to humans to notice the biases and fix them <ref name=cnbc></ref>.<br />
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==<big>Ethical Implications</big>==<br />
===Algorithms Blocking Opportunities===<br />
[[File:Men in tech.png |300px|thumbnail|right| Amazon's hiring algorithm was modeled after real-world data, where there are more men in the tech field. The difference in gender of employees is shown in the figure above <ref name=amazon> Dastin, J. (2018, October 10). <i>Amazon scraps secret AI recruiting tool that showed bias against women.</i> Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G</ref>.]]<br />
Algorithms in the online job search do not outright reject job seekers. Instead, they block certain groups of job seekers from seeing opportunities they are qualified for; as [[Wikipedia: Pauline Kim|Pauline Kim]], a legal scholar, stated, “not informing people of a job opportunity is a highly effective barrier” to job seekers <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. Qualified candidates cannot apply for a job if they have not been shown the opportunity. <br />
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[[Wikipedia: Amazon (company)|Amazon’s]] algorithmic recruiting tool was trained with 10 years’ worth of [[Wikipedia: Résumé|resumes]] that were sent to Amazon; however, because technology is a male-dominated field, most of the resumes were from male applicants, leading the algorithm to downvote women <ref name=amazon> Dastin, J. (2018, October 10). <i>Amazon scraps secret AI recruiting tool that showed bias against women.</i> Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G </ref>. This method of training taught the algorithm that men were preferred, therefore penalizing candidates who included the word “women’s” in their resume. For example, if the candidate listed an activity as “women’s team captain, ” their resume would be downgraded in the system <ref name=amazon> Dastin, J. (2018, October 10). <i>Amazon scraps secret AI recruiting tool that showed bias against women. </i> Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G </ref>. Amazon has since scrapped this recruiting algorithm <ref name=amazonscandal2> <i>Amazon scrapped 'sexist AI' tool</i>. (2018, October 10). British Broadcasting Corporation. https://www.bbc.com/news/technology-45809919 </ref>.<br />
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A test was also conducted on an ad-serving algorithm that displayed ads for jobs related to STEM. The algorithm was supposedly designed to display these ads to men and women equally and was tested in 191 different countries. The results showed that the ads were shown to around 20% more men than women. One of the explanations to the algorithm choosing to show the ads to more men than women comes from an economic standpoint. Online advertisers are constantly competing for users’ attention. A study has shown that on average, it is more expensive to get the attention of females over males when advertising online.<ref>Lambrecht A., Tucker C. (2019). [https://pubsonline-informs-org.proxy.lib.umich.edu/doi/pdf/10.1287/mnsc.2018.3093 "Algorithmic Bias? An Empirical Study of Apparent GenderBased Discrimination in the Display of STEM Career Ads"] Retrieved on 9 April 2021.</ref><br />
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===Traditional Gender Roles Affect Outcomes===<br />
It has been studied that women can have a better keyword match on their resume, yet not be selected for a job if a man has more experience than them <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. These hiring algorithms that are built and trained by humans do not take into account the time women must take off of work to have children or to take care of children <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. The author of a study done by the [[Wikipedia: University of Melbourne|University of Melbourne]] recounts that “women have less experience because they take time [off work] for caregiving, and that algorithm is going to bump men up and women down based on experience” <ref name=abc>Hanrahan, C. (2020, December 2. <i>Job recruitment algorithms can amplify unconscious bias favouring men, new research finds.</i> The ABC News. https://www.abc.net.au/news/2020-12-02/job-recruitment-algorithms-can-have-bias-against-women/12938870</ref>. Because women are more likely to experience a disruption in their career due to children, they will be viewed as a lesser candidate by the algorithm, even if they have more relevant experience than a male candidate <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. Hiring algorithms do not take into account gender roles, which include women taking time off to give birth. This replicates and reinforces gender bias in the online hiring process <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>.<br />
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==<big>Reducing Bias</big>==<br />
[[File:WordEmbeddings.png |350px|thumbnail|left| Basic graphic of how researchers observed and evaluated gender bias of word embeddings in algorithms. <ref name=SunEtAl>Sun, T., et al. (2019, June 21). ''Mitigating Gender Bias in Natural Language Processing: Literature Review''. Cornell University. https://arxiv.org/pdf/1906.08976.pdf</ref>]]<br />
===Rethinking How Algorithms are Built===<br />
Vendors that build recruitment algorithms to target specific job seekers need to think beyond the minimum [[Wikipedia: Compliance requirements|compliance requirements]]; they have to consider whether or not the algorithm they are building is leading to more fair hiring outcomes <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. Additionally, the people stating that their algorithms will reduce bias in the hiring process have to build and test their algorithms while keeping that goal in mind, or else the technology will continue to undermine the online job search process <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. Re-thinking algorithms and how to build them will begin to reduce bias in the job search, as many factors need to be considered.<br />
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One specific aspect of gender bias can be found in [[Wikipedia: Word embedding|word embeddings]]. Word embeddings are [[Wikipedia: Binary|binary]], pre-trained models that assign words or phrases specific representations and meanings; these models have been found to reflect societal bias <ref name=WordEmbeddings>GeeksforGeeks. (2020, October 14). Word Embeddings in NLP. https://www.geeksforgeeks.org/word-embeddings-in-nlp/</ref>. For example, words like ''"[[Wikipedia: Receptionist|receptionist]]"'' and ''"[[Wikipedia: Nursing|nurse]]"'' are linked to ''"women"'' and ''"she"'' whereas words like ''"[[Wikipedia: Physician|doctor]]"'' and ''"[[Wikipedia: Computer scientist|computer scientist]]"'' are linked to ''"men"'' and ''"he"''. Researchers have explored potential solutions to de-bias word embeddings by using methods such as building a genderless framework as well as teaching the algorithm gender-neutral word embeddings <ref name=SunEtAl></ref>. Such methods aim to minimize the difference between gendered words (i.e. ''male'' versus ''female'') and maximize "the difference between the gender direction and other neutral dimensions” <ref name=SunEtAl></ref><ref name='Bolukbasi'>Bolukbasi, T., et al. (2016). Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. ''Advances in Neural Information Processing Systems 29 (NIPS 2016)''</ref>. This allows algorithms to use or neglect the gender dimensions.<br />
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===Balancing Humans and Algorithms===<br />
Implementing a balance between predictive algorithms and human insight is a promising solution for employers looking to use algorithms in their hiring process while reducing bias <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. Using artificial intelligence and algorithms to parse through large amounts of data or applicants works well for processing. Balancing the processing by algorithms with the "human ability to recognize more intangible realities of what that data might mean" is the second step in the process of limiting algorithmic bias <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. For a partnership between humans and algorithms to be successful within companies, they need to consciously and deliberately implement new practices <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. Both algorithms and humans still need to be held accountable for reducing bias, and working together would encourage a good short-term solution to the phenomenon of gender bias in the online job search <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>.<br />
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===Unintended Consequences of Bias Reduction===<br />
It has been suggested that algorithms de-biased in terms of gender could still produce the same biased outcome. Algorithms may still use online [[Wikipedia: Proxy|proxies]] in their scoring process to produce discriminatory results as these proxies serve as stand-ins for [[Wikipedia: Protected group|protected groups]], like gender <ref name='TechScience'>Larson, J., Mattu, S., & Angwin, J. (2015, August 31). Unintended Consequences of Geographic Targeting. ''Technology Science''. https://techscience.org/a/2015090103/</ref><ref name='Zarsky'>Zarsky, T. Z. (2014). Understanding Discrimination in the Scored Society. ''Washington Law Review'', 89(4), 1375-1412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2550248</ref>. For example, while algorithms may be de-biased on the terms of gender specifically, the algorithm may use stand-in factors such as height or weight as a proxy to determine a candidate's gender <ref name='TechScience'></ref>. This leaves room for the algorithm to produce bias results based on a candidate's gender.<br />
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Although there is a [[Wikipedia: Statistics|statistical]] process that is known to eliminate proxy discrimination, the process requires the algorithmic model to include "training data information on legally prohibited characteristics” <ref name='PrinceSchwarcz'>Prince, A. E.R. & Schwarcz, D. (2020). Proxy Discrimination in the Age of Artificial Intelligence and Big Data. ''Iowa Law Review'', 105(3). https://ilr.law.uiowa.edu/print/volume-105-issue-3/proxy-discrimination-in-the-age-of-artificial-intelligence-and-big-data/</ref>. Even if such legally prohibited information is obtained, characteristics would then be measured on their predictive power of the [[Wikipedia: Dependent and independent variables|target variable]]; this could result in unintended amplification of the initial proxy discrimination <ref name='PrinceSchwarcz'></ref>. For example, if height was measured as a highly predictive characteristic and height was used as a proxy for gender, then the algorithm would intentionally discriminate on the predictive basis of height thus unintentionally discriminating against gender.<br />
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== References ==<br />
<references/></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Gender_bias_in_the_Online_Job_Search&diff=101589Gender bias in the Online Job Search2021-04-09T19:14:12Z<p>Ptse: </p>
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<div>[[File:Hiringfunnel.png |250px|thumbnail|right| There are many stages to the hiring process, and algorithms are involved in almost all of them. <ref name=upturn>Bogen, M. & Rieke, A. (2018). <i>Help Wanted: An Examination of Hiring Algorithms, Equity, and Bias</i>. Upturn. https://www.upturn.org/static/reports/2018/hiring-algorithms/files/Upturn%20--%20Help%20Wanted%20-%20An%20Exploration%20of%20Hiring%20Algorithms,%20Equity%20and%20Bias.pdf</ref>]]<br />
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The advancement of [[Wikipedia: Technology|technology]] and [[Wikipedia: Algorithm|algorithms]] has led to companies recruiting and hiring potential employees through the use of [[Wikipedia: Big data|big data]] and [[Wikipedia: Artificial intelligence|artificial intelligence]], which can amplify gender [[Wikipedia: Bias|bias]] in the online job search <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>. Gender bias refers to the “unfair difference” in the way that both men and women are treated <ref name=biasDefinition>Cambridge Dictionary.(n.d.). Gender Bias. In <i>Cambridge English Dictionary</i>. https://dictionary.cambridge.org/us/dictionary/english/gender-bias</ref>. In the context of the online job search, gender bias is defined as the advantage male job seekers have versus female job seekers. The use of algorithms in the online job search process can perpetuate existing biases which result in ethical implications regarding blocked job opportunities for females, and the disadvantage for female job seekers due to systematic [[Wikipedia: Gender role|gender roles]].<br />
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==<big> Artificial Intelligence in the Recruitment Process </big>==<br />
Artificial intelligence is being utilized in recruiting algorithms. The AI technology is learning how to recruit most effectively for the company using it <ref name=ai_guide> (2021, February 26). <i>Ai for recruiting: A definitive guide for hr professionals. </i> Ideal. https://ideal.com/ai-recruiting/#:~:text=AI%20for%20recruiting%20is%20the,repetitive%2C%20high%2Dvolume%20tasks. </ref>. The introduction of AI into the recruiting process makes candidates 14% more likely to pass interviews and receive offers, 18% more likely to accept the job, and they are 12% less likely to inform recruiters of competing job offer during the negotiation process <ref> Cowgill, B. (2018).<i> Bias and productivity in humans and algorithms: Theory and evidence from resume screening. </i> Columbia Business School, Columbia University, 29. http://conference.iza.org/conference_files/MacroEcon_2017/cowgill_b8981.pdf </ref>. This technology is mainly used with four general types of recruitment activities: outreach, screening, assessment, and coordination <ref name=ai_manage> Black, J., & Esch, P. (2019, December 31). <i> Ai-enabled recruiting: What is it and how should a manager use it? </i> https://www.sciencedirect.com/science/article/pii/S0007681319301612 </ref>. <br />
[[File:life_cycle.png |250px|thumbnail|right|The Steps of the Recruitment Life Cycle. Sourced from https://medium.com/@corprate.io/ultimate-6-steps-guide-in-recruitment-process-ae9a6bd70863]]<br />
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===Outreach===<br />
Artificial intelligence helps companies find the right applicants. These potential applicants consist of active candidates (those who are deliberately searching for a new job) and passive candidates (those who are not actively searching but would show interest for the right opportunity). The AI uses data from websites like LinkedIn, Facebook, Twitter, etc. to match candidates to jobs. After enough training, the AI will have learned the most efficient way to word and present jobs to potential candidates. <ref name=ai_manage> </ref><br />
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===Screening===<br />
AI is also used for the resume screening process of recruitment. AI can help companies reduce the time-to-hire. [[Wikipedia: Hilton_Hotels_%26_Resorts Hilton Hotels & Resorts| Hilton Hotels & Resorts]] implemented a screening tool that used AI and found an 88% decline in time-to-hire, or 42 days to 5 days. These AI screening tools can be more effective than humans because they can infer key terms from natural language. For example, instead of searching for the keyword, ‘persistence’, the AI can infer this term from other phrases or wording. <ref name=ai_manage> </ref><br />
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===Assessing===<br />
AI assessments are used to narrow a candidate pool after the resume screening step. AI can be used in varying types of assessments. It can range from realistic [[Wikipedia: Chatbot|chatbot]] conversations in [[Wikipedia: Situational_judgement_test| situational judgement tests]] to making decisions based on an applicant’s responses to test questions <ref name=assess>(n.d.). <i> Artificial intelligence (ai) in assessment. </i> Aon. https://assessment.aon.com/en-us/online-assessment/ai-in-assessment </ref>. These assessments can be used as an initial interview or to informally test candidates for desired traits like an individual’s risk propensity. <ref name=ai_manage> </ref><br />
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===Coordination===<br />
It is beneficial for companies to make their hiring process as positive of an experience as possible because a candidate might not be the right fit today, but they could be perfect in a year. AI can facilitate with this because it creates a more seamless, digital experience. Companies can use chatbots to update candidates on where they are in the process, fill in information gaps like the candidate’s potential start date, and answer candidate questions. <ref name=ai_manage> </ref> Also, a company’s openness with their usage of AI in the recruitment process increased the likelihood of a job application, as well as having a positive experience with the process <ref name=marketing> Esch, P., Black, J., & Ferolie, J. (2018, September 17). <i> Marketing ai recruitment: The next phase in job application and selection. </i> https://www.sciencedirect.com/science/article/pii/S0747563218304497#sec5 </ref>.<br />
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==<big>Evidence of Bias</big>==<br />
[[File:LookalikeAudience.png |300px|thumbnail|left| Process of Facebook's lookalike audience tool. <ref name='Facebook'>Facebook. (n.d.). https://www.facebook.com/</ref>]]<br />
===Job Recruitment Algorithms===<br />
Job recruitment algorithms have been found to reinforce and perpetuate unconscious human gender bias <ref name=abc>Hanrahan, C. (2020, December 2. <i>Job recruitment algorithms can amplify unconscious bias favouring men, new research finds.</i> The ABC News. https://www.abc.net.au/news/2020-12-02/job-recruitment-algorithms-can-have-bias-against-women/12938870</ref>. Because job recruitment algorithms are trained on real-world data – and the real world is biased – the algorithms amplify this bias on a larger scale. Decision-making algorithms are “designed to mimic how a human would…choose a potential employee” and without careful consideration, algorithms can intensify bias in recruiting <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. <br />
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Utilizing real-world data to shape algorithms leads to algorithms producing biased outcomes. Algorithms make predictions by analyzing past data <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>. If the past data includes biased judgments, then the algorithm’s predictions will also be biased. [[Wikipedia: Facebook|Facebook’s]] tool called “[[Wikipedia: Lookalike audience|lookalike audience]]” allows advertisers – in this case, employers – to input a “[[Wikipedia: Target audience|source audience]]” that will dictate who Facebook advertises jobs to, based on a person’s similarities with this “source audience” <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>. This tool is meant to help employers predict which users are most likely to apply for jobs. If an employer provides the lookalike tool with a dataset that does not include a lot of women, then Facebook will not advertise the job to women. Employers could use this tool to deliberately exclude certain groups, but employers could also be unaware of the bias of their “source audience” <ref name=paulineKim>Kim, P. T. (2019). Big data and artificial intelligence: New challenges for workplace equality. <i>University of Louisville Law Review</i>, 57(2), 313-328.</ref>.<br />
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===Job Recommendation Algorithms===<br />
Job recommendation algorithms within online platforms are built to find and reproduce patterns in user behavior, updating predictions or decisions as job seekers and employers interact <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. If the system within the platform recognizes that the employer interacts with mostly men, then the algorithm will look for those characteristics in potential job applicants and replicate the pattern <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. This pattern picked up by the algorithm can happen without specific instruction from the employer, which leads to biases going unnoticed.<br />
<br />
===Algorithms Extending Human Bias===<br />
Personal, human bias extends into [[Wikipedia: Algorithmic bias| algorithmic bias]]. A study conducted at the [[Wikipedia: University of California, Santa Barbara|University of California, Santa Barbara]] found that people’s own underlying biases were bigger determinants of their likelihood to apply to jobs than any gendered job posting <ref name=longitudinal> Tang, S., et al. (2017). Gender Bias in the Job Market: A Longitudinal Analysis. <i> ACM on the Human-Computer Interaction. </i>. https://dl.acm.org/doi/epdf/10.1145/3134734</ref>. Underlying human biases need to be reduced to work towards gender neutrality in the job market <ref name=longitudinal> Tang, S., et al. (2017). Gender Bias in the Job Market: A Longitudinal Analysis. <i> ACM on the Human-Computer Interaction. </i>. https://dl.acm.org/doi/epdf/10.1145/3134734</ref>. Humans choose the data to train algorithms with, and the "choice to use certain data inputs over others can lead to discriminatory outcomes" <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. Hiring algorithms can be an extension of "our opinions embedded in code" and further research highlights that algorithms reproduce existing societal, human bias <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. The people constructing hiring algorithms are in the tech industry, which is not very diverse. This leads to algorithms that are trained on non-diverse data, which extends human gender bias into the online job market <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. While creating algorithms, "biases creep in because human bias [influences] the algorithm" <ref name=cnbc> Rosenbaum, E. (2018, May 30). <i>Silicon Valley is stumped: A.I. cannot always remove bias from hiring</i>. Consumer News and Business Channel. https://www.cnbc.com/2018/05/30/silicon-valley-is-stumped-even-a-i-cannot-remove-bias-from-hiring.html</ref>. Humans build biased algorithms, so it is up to humans to notice the biases and fix them <ref name=cnbc></ref>.<br />
<br />
==<big>Ethical Implications</big>==<br />
===Algorithms Blocking Opportunities===<br />
[[File:Men in tech.png |300px|thumbnail|right| Amazon's hiring algorithm was modeled after real-world data, where there are more men in the tech field. The difference in gender of employees is shown in the figure above <ref name=amazon> Dastin, J. (2018, October 10). <i>Amazon scraps secret AI recruiting tool that showed bias against women.</i> Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G</ref>.]]<br />
Algorithms in the online job search do not outright reject job seekers. Instead, they block certain groups of job seekers from seeing opportunities they are qualified for; as [[Wikipedia: Pauline Kim|Pauline Kim]], a legal scholar, stated, “not informing people of a job opportunity is a highly effective barrier” to job seekers <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. Qualified candidates cannot apply for a job if they have not been shown the opportunity. <br />
<br />
[[Wikipedia: Amazon (company)|Amazon’s]] algorithmic recruiting tool was trained with 10 years’ worth of [[Wikipedia: Résumé|resumes]] that were sent to Amazon; however, because technology is a male-dominated field, most of the resumes were from male applicants, leading the algorithm to downvote women <ref name=amazon> Dastin, J. (2018, October 10). <i>Amazon scraps secret AI recruiting tool that showed bias against women.</i> Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G </ref>. This method of training taught the algorithm that men were preferred, therefore penalizing candidates who included the word “women’s” in their resume. For example, if the candidate listed an activity as “women’s team captain, ” their resume would be downgraded in the system <ref name=amazon> Dastin, J. (2018, October 10). <i>Amazon scraps secret AI recruiting tool that showed bias against women. </i> Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G </ref>. Amazon has since scrapped this recruiting algorithm <ref name=amazonscandal2> <i>Amazon scrapped 'sexist AI' tool</i>. (2018, October 10). British Broadcasting Corporation. https://www.bbc.com/news/technology-45809919 </ref>.<br />
<br />
A test was also conducted on an ad-serving algorithm that displayed ads for jobs related to STEM. The algorithm was supposedly designed to display these ads to men and women equally and was tested in 191 different countries. The results showed that the ads were shown to around 20% more men than women. One of the explanations to the algorithm choosing to show the ads to more men than women comes from an economic standpoint. Online advertisers are constantly competing for users’ attention. A study has shown that on average, it is more expensive to get the attention of females over males when advertising online.<ref>Lambrecht A., Tucker C. (2019). [https://pubsonline-informs-org.proxy.lib.umich.edu/doi/pdf/10.1287/mnsc.2018.3093 "Algorithmic Bias? An Empirical Study of Apparent GenderBased Discrimination in the Display of STEM Career Ads"] Retrieved on 9 April 2021.</ref><br />
<br />
===Traditional Gender Roles Affect Outcomes===<br />
It has been studied that women can have a better keyword match on their resume, yet not be selected for a job if a man has more experience than them <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. These hiring algorithms that are built and trained by humans do not take into account the time women must take off of work to have children or to take care of children <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. The author of a study done by the [[Wikipedia: University of Melbourne|University of Melbourne]] recounts that “women have less experience because they take time [off work] for caregiving, and that algorithm is going to bump men up and women down based on experience” <ref name=abc>Hanrahan, C. (2020, December 2. <i>Job recruitment algorithms can amplify unconscious bias favouring men, new research finds.</i> The ABC News. https://www.abc.net.au/news/2020-12-02/job-recruitment-algorithms-can-have-bias-against-women/12938870</ref>. Because women are more likely to experience a disruption in their career due to children, they will be viewed as a lesser candidate by the algorithm, even if they have more relevant experience than a male candidate <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>. Hiring algorithms do not take into account gender roles, which include women taking time off to give birth. This replicates and reinforces gender bias in the online hiring process <ref name=Melbourne>Cheong, M., et al. (n.d.). <i>Ethical Implications of AI Bias as a Result of Workforce Gender Imbalance</i>. The University of Melbourne. https://about.unimelb.edu.au/__data/assets/pdf_file/0024/186252/NEW-RESEARCH-REPORT-Ethical-Implications-of-AI-Bias-as-a-Result-of-Workforce-Gender-Imbalance-UniMelb,-UniBank.pdf</ref>.<br />
<br />
==<big>Reducing Bias</big>==<br />
[[File:WordEmbeddings.png |350px|thumbnail|left| Basic graphic of how researchers observed and evaluated gender bias of word embeddings in algorithms. <ref name=SunEtAl>Sun, T., et al. (2019, June 21). ''Mitigating Gender Bias in Natural Language Processing: Literature Review''. Cornell University. https://arxiv.org/pdf/1906.08976.pdf</ref>]]<br />
===Rethinking How Algorithms are Built===<br />
Vendors that build recruitment algorithms to target specific job seekers need to think beyond the minimum [[Wikipedia: Compliance requirements|compliance requirements]]; they have to consider whether or not the algorithm they are building is leading to more fair hiring outcomes <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. Additionally, the people stating that their algorithms will reduce bias in the hiring process have to build and test their algorithms while keeping that goal in mind, or else the technology will continue to undermine the online job search process <ref name=bogen>Bogen, M. (2019, May 6). All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias</ref>. Re-thinking algorithms and how to build them will begin to reduce bias in the job search, as many factors need to be considered.<br />
<br />
One specific aspect of gender bias can be found in [[Wikipedia: Word embedding|word embeddings]]. Word embeddings are [[Wikipedia: Binary|binary]], pre-trained models that assign words or phrases specific representations and meanings; these models have been found to reflect societal bias <ref name=WordEmbeddings>GeeksforGeeks. (2020, October 14). Word Embeddings in NLP. https://www.geeksforgeeks.org/word-embeddings-in-nlp/</ref>. For example, words like ''"[[Wikipedia: Receptionist|receptionist]]"'' and ''"[[Wikipedia: Nursing|nurse]]"'' are linked to ''"women"'' and ''"she"'' whereas words like ''"[[Wikipedia: Physician|doctor]]"'' and ''"[[Wikipedia: Computer scientist|computer scientist]]"'' are linked to ''"men"'' and ''"he"''. Researchers have explored potential solutions to de-bias word embeddings by using methods such as building a genderless framework as well as teaching the algorithm gender-neutral word embeddings <ref name=SunEtAl></ref>. Such methods aim to minimize the difference between gendered words (i.e. ''male'' versus ''female'') and maximize "the difference between the gender direction and other neutral dimensions” <ref name=SunEtAl></ref><ref name='Bolukbasi'>Bolukbasi, T., et al. (2016). Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. ''Advances in Neural Information Processing Systems 29 (NIPS 2016)''</ref>. This allows algorithms to use or neglect the gender dimensions.<br />
<br />
===Balancing Humans and Algorithms===<br />
Implementing a balance between predictive algorithms and human insight is a promising solution for employers looking to use algorithms in their hiring process while reducing bias <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. Using artificial intelligence and algorithms to parse through large amounts of data or applicants works well for processing. Balancing the processing by algorithms with the "human ability to recognize more intangible realities of what that data might mean" is the second step in the process of limiting algorithmic bias <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. For a partnership between humans and algorithms to be successful within companies, they need to consciously and deliberately implement new practices <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>. Both algorithms and humans still need to be held accountable for reducing bias, and working together would encourage a good short-term solution to the phenomenon of gender bias in the online job search <ref name=lawReview>Raub, M. (2018). Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices. <i>Arkansas Law Review</i>, 71(2), 529-570</ref>.<br />
<br />
===Unintended Consequences of Bias Reduction===<br />
It has been suggested that algorithms de-biased in terms of gender could still produce the same biased outcome. Algorithms may still use online [[Wikipedia: Proxy|proxies]] in their scoring process to produce discriminatory results as these proxies serve as stand-ins for [[Wikipedia: Protected group|protected groups]], like gender <ref name='TechScience'>Larson, J., Mattu, S., & Angwin, J. (2015, August 31). Unintended Consequences of Geographic Targeting. ''Technology Science''. https://techscience.org/a/2015090103/</ref><ref name='Zarsky'>Zarsky, T. Z. (2014). Understanding Discrimination in the Scored Society. ''Washington Law Review'', 89(4), 1375-1412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2550248</ref>. For example, while algorithms may be de-biased on the terms of gender specifically, the algorithm may use stand-in factors such as height or weight as a proxy to determine a candidate's gender <ref name='TechScience'></ref>. This leaves room for the algorithm to produce bias results based on a candidate's gender.<br />
<br />
Although there is a [[Wikipedia: Statistics|statistical]] process that is known to eliminate proxy discrimination, the process requires the algorithmic model to include "training data information on legally prohibited characteristics” <ref name='PrinceSchwarcz'>Prince, A. E.R. & Schwarcz, D. (2020). Proxy Discrimination in the Age of Artificial Intelligence and Big Data. ''Iowa Law Review'', 105(3). https://ilr.law.uiowa.edu/print/volume-105-issue-3/proxy-discrimination-in-the-age-of-artificial-intelligence-and-big-data/</ref>. Even if such legally prohibited information is obtained, characteristics would then be measured on their predictive power of the [[Wikipedia: Dependent and independent variables|target variable]]; this could result in unintended amplification of the initial proxy discrimination <ref name='PrinceSchwarcz'></ref>. For example, if height was measured as a highly predictive characteristic and height was used as a proxy for gender, then the algorithm would intentionally discriminate on the predictive basis of height thus unintentionally discriminating against gender.<br />
<br />
== References ==<br />
<references/></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brave_Browser&diff=100958Brave Browser2021-04-08T17:12:12Z<p>Ptse: </p>
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<div>{{SoftwareInfoBox<br />
|HEIGHT=720<br />
|NAME=Brave Browser<br />
|LOGO=Brave-logo.png<br />
|SCREENIMAGE=braveex.png<br />
|CAPTION=''"Brave Browser"''<br />
|IMAGEURL=https://brave.com/download/<br />
|TEXT=download link<br />
|PLATFORM=Windows<br>macOS<br>Linux<br>Android<br>iOS<br />
|PRODUCT=Brave Browser<br>BAT<br />
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|URLTEXT=www.brave.com<br />
|STATUS=Active<br />
|LAUNCH=2015<br />
}}<br />
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<br><br />
'''Brave Browser''' is an open-source browser application focused on prioritizing user privacy and democratizing online advertising. It has been developed using the [https://en.wikipedia.org/wiki/Chromium_(web_browser) Chromium web browser] as a foundation, like [https://en.wikipedia.org/wiki/Microsoft_Edge Microsoft Edge] and [https://en.wikipedia.org/wiki/Opera_(web_browser) Opera]. Brave is specifically focused on the user privacy niche and blocks all ads and trackers by default.<br />
Brave Software was co-founded in May 2015 by CEO Brendan Eich (creator of [https://en.wikipedia.org/wiki/JavaScript JavaScript] and former CEO of [https://en.wikipedia.org/wiki/Mozilla_Corporation Mozilla Corporation]) and CTO Brian Bondy.<ref name="founding"> Brian Bondy. [https://web.archive.org/web/20191119215054/https://brave.com/the-road-to-brave-one-dot-zero/] Retrieved on 11 March 2021. </ref><br />
Brave is headquartered in San Francisco, CA. As of February 2021, Brave Browser had over 25 million monthly active users. <ref name="MUA">Brave Browser. [https://brave.com/25m-mau/#:~:text=Brave%20Passes%2025%20Million%20Monthly%20Active%20Users "Brave Blog"] Retrieved on 11 March 2021.</ref><br />
<br />
__TOC__<br />
==Key Features==<br />
===Ad and Tracker Blocking=== <br />
On any given tab, the browser has an option to enable and disable a display showing how many items have been blocked or modified on that particular page, such as cross-site trackers, connections upgraded to HTTPS, and scripts blocked.<ref name="features"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> The Brave Browser does not serve individual user browsing data on its servers, unlike most other browsers; instead, all user data is aggregated before being returned to Brave's servers. The ads and trackers that are blocked by default can also be customized by the user at any time. <ref name="privacy"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> However, user browsing data is still saved on users' local devices in order to ensure that ads that they may opt-in to see are still relevant. Brave also advertises that the fact that all ads are blocked, enabling faster browsing times for the user.<br />
<br />
===Basic Attention Token (BAT)=== <br />
[[File:Batlogo.png|thumbnail|80px|thumb|left|BAT logo]]<br />
The Basic Attention Token (BAT) is an Ethereum based token that can be traded on a wallet embedded in the browser itself. BAT is the unit of exchange used for browser features such as Brave Rewards. BAT had its [https://en.wikipedia.org/wiki/Initial_coin_offering initial coin offering] (ICO) on May 31st, 2017.<ref name="ico"> [https://www.bitdegree.org/crypto/basic-attention-token#:~:text=The%20BAT%20ICO%20(Initial%20Coin,was%20the%20ERC%2D20%20token.&text=The%20complete%20amount%20of%20the,1%2C5%20billion%20BAT%20tokens.] Retrieved on 11 March 2021. </ref> In under 30 seconds, 1,000,000,000 BAT were sold for a total of 156,250 Ethereum.<ref name="icos">[https://techcrunch.com/2017/06/01/brave-ico-35-million-30-seconds-brendan-eich/] Retrieved on 11 March 2021. </ref> BAT improves the efficiency of digital advertising by creating a new unit of exchange between publishers, advertisers, and users. BAT allows users to have better control over the ads they see online: users can block ads, pay to see different ads, or view ads and earn BAT tokens in exchange.<ref name="batbene">[https://themerkle.com/what-is-basic-attention-token/] Retrieved on 11 March 2021. </ref> Advertisers also benefit from this model by achieving higher returns on advertising investment. This is delivered through better ad targeting (based on local user data) and reduced fraud. <br><br />
===Brave Rewards=== <br />
Brave Rewards has a two-pronged benefit: it allows users to support their favorite content creators, and it allows users to earn money. For the former, Brave allows users to send their favorite content creators (YouTubers, Twitter users, blog owners, etc.) BAT, which can be converted to cash. This practice is known as [https://brave.com/tips/#:~:text=When%20you%20visit%20Twitter%20in,Brave%20Rewards%20account%20within%20minutes. tipping]. Users can choose to either set up recurring payments or make a one-time payment. For the latter benefit, users can choose to earn money by opting in to view ads. Rather than traditional banner ads, Brave displays its ads as a push notification that users can choose to interact with. The aim of this ad format is to create a more engaging ad experience that benefits all parties involved.<br />
<br />
Currently, Brave has over 735,000 registered content creators with many notable names such as Philip DeFranco, The Washington Post, wikiHow, XXL, Vice, and The Guardian to name a few.<ref name="creators"> ''Brave'' (2019). [https://creators.brave.com/ "Earn more for content you publish to the web - Brave Creators"] Retrieved on 8 April 2021. </ref> In the current e-commerce system, digital content creators receive an estimated half of their revenue due to users who use ad-blocks. In addition, many digital ad platforms are monopolized by Google, Facebook, and Amazon.<ref name="mediapost"> Williams, R. (2019, August 23). [https://www.mediapost.com/publications/article/339624/google-publishers-lose-half-of-ad-revenue-from-co.html "Google: Publishers Lose Half Of Ad Revenue From Cookie Blocking"] ''Publishing Insider'' Retrieved on 8 April 2021. </ref> Thus, Brave Rewards is highly appealing to content creators as it attempts to equalize systemically disproportionate streams of revenue.<br />
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===IPFS Integration===<br />
IPFS is the protocol that Brave uses instead of HTTP, which is what most browsers use. IPFS is known as a peer-to-peer protocol. This is because it uses distributed nodes near the user to send data. This can result in faster web browsing in certain areas. In contrast, HTTP has a centralized server that transmits data to users. This can be slow in some areas if the distance from the user to the server is far.<br />
<br />
Another benefit to IPFS is that content restricted in some parts of the world, such as Turkey, Thailand, and China, are now available to them because of IPFS.<ref>Bonifacic, I. (2021, January 19). [https://www.engadget.com/brave-ipfs-update-190545662.html "Brave browser now supports peer-to-peer IPFS protocol"] Retrieved on 7 April 2021. </ref><br />
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===Other Features===<br />
* [https://en.wikipedia.org/wiki/Tor_(anonymity_network) Tor] integration for anonymous browsing by concealing user location and usage information<br />
* Auto-suggesting search terms and searching from the address bar<br />
* Option to use DuckDuckGo for private window search<br />
* Built-in password manager<br />
* [https://en.wikipedia.org/wiki/Fingerprint_(computing) Fingerprinting] prevention, cookie control, and HTTPS upgrading<br />
* Support for most Chrome extensions<br />
===Planned Features===<br />
According to Brave’s BAT roadmap of 2021, Brave developers are aiming to increase crypto and decentralized finance (DeFi) accessibility by creating their own cryptocurrency wallet using Ethereum, an open-source [[blockchain]] technology.<ref name="roadmap"> ''Brave'' (2021, February 22). [https://brave.com/bat-roadmap-2-0/ "BAT Roadmap 2.0"] Retrieved on 8 April 2021. </ref> The Brave Wallet will replace existing crypto wallets and have redesigned UI/UX as well as mobile support. A JavaScript Ethereum Provider API, used to connect web apps with Ethereum blockchain, will now be supplied to web pages by default and more options for buying crypto with fiat payment methods, currencies without use or instrinsic value, will be unlocked. Brave is also looking to support integrated NFT redemption usage(source) within its browser and enable payment of transaction fees through BAT. To further spread DeFi, Brave is creating a new decentralized exchange aggregator with monetary incentives for Brave/Bat users. Aside from future optimizations in accountability and anonymity, to achieve their final endgame of building a Decentralized Web, Brave is researching BAT use in search engines, e-commerce, VPN, IPNS-verified content, and IPFS content pinning. According to public IPFS documentation, IPFS refers to “a distributed system for storing and accessing files, websites, applications, and data.”<ref name="ipfs"> Schilling, J. (2019, December 3). [https://docs.ipfs.io/concepts/what-is-ipfs/ "What is IPFS? | IPFS Docs"] ''IPFS Docs'' Retrieved on 8 April 2021. </ref> IFPS uses content-based addressing while IPNS solves the issue of creating updatable addresses when content is updated. By tying BAT with multiple Decentralized Web systems, Brave is associating their browser and its reward system with other public efforts towards decentralization.<br />
<br />
==Ethical Considerations==<br />
[[File:bizmodel.png|thumb|left|Brave's advertising model]]<br />
===Data Privacy=== <br />
Data privacy while browsing online is a point of contention regarding Internet privacy in the modern day. Brave offers a robust feature list on metrics related to online privacy and data ethics. By keeping all data local and privatized, Brave does not monetize user data the way many browsers do. Instead, its primary revenue driver is its usage of BAT.<ref name="mainrevenue">https://gizmodo.com/brave-wants-to-destroy-the-ad-business-by-paying-you-to-1834283860] Retrieved on 11 March 2021. </ref> This business model allows them to monetize browsing while still returning 70% of revenue to Brave users themselves.<ref name="returntousers">https://social.techcrunch.com/2019/04/24/brave-ads/] Retrieved on 11 March 2021. </ref> This allows for incentive alignment with users who are focused on privacy and Brave's monetization strategy and business model.<br />
===Online Advertising Ecosystem===<br />
The main concern with Brave's lack of individualized user collection is whether or not users would see relevant ads if they chose to opt-in to see ads in order to earn BAT. Although Brave does not collect individualized user data, it still practices machine learning on aggregated and anonymized data to ensure that ads users see are relevant for them.<ref name="ads">https://brave.com/intro-to-brave-ads/] Retrieved on 11 March 2021. </ref> By approaching advertising this way, Brave addresses common ethical concerns of monetization user behavior data, while still employing machine learning as an effective tool to display relevant ads. By choosing to implement ads in-app instead of using a third-party ad service, Brave Browser also eliminates the 3rd party ad broker and allows for revenue to be returned to the users. <br />
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<br clear=all><br />
===User Expectations of Privacy===<br />
[[File:Brave-private-tab-tor.png|thumb|right|Brave's new tab disclosure]]<br />
Users frequently have misconceptions about online privacy and how private browser modes work.<ref>Wu, Y., Gupta, P., Wei, M., Acar, Y., Fahl, S., & Ur, B. (2018, April). Your secrets are safe: How browsers' explanations impact misconceptions about private browsing mode. In Proceedings of the 2018 World Wide Web Conference (pp. 217-226).<br />
</ref> These include overestimating the function of private browser modes, such as assuming protection against ISP tracking of browsing history. A study has suggested this causes a negative impact on user privacy when using the Brave Browser, as users may engage differently when they expect a certain degree of anonymity.<ref>Fehlhaber, A. L., Acar, Y., Fahl, S., Gutfleisch, M., Theis, D., & Wallkötter, F. Poster: When Brave Hurts Privacy: Why Too Many Choices do More Harm Than Good.</ref> This study also suggested that the new tab disclosure, which attempts to explain the difference between Brave’s two modes, is not effective at educating users on the impact on browsing privacy.<br />
<br />
===Failure of Privacy Promise===<br />
When Brave Browser was released, privacy was their main policy. By design, Brave Browser would inherently provide better privacy than other browsers. Brave addressed a big issue, surveillance capitalism, by “blocking trackers, invasive ads, and device fingerprinting.”<ref>Krill P. (19 November 2019) [https://bi-gale-com.proxy.lib.umich.edu/global/article/GALE%7CA606140924?u=umuser&sid=summon "'Privacy first' Brave browser exits beta."] Retrieved 7 April 2021.</ref> However, there have been some moments where Brave has failed to uphold their promises on privacy. There are multiple instances of the Brave Browser not delivering on its claim to provide privacy protection. One claim that has been found to be misleading is that all traces of browsing history are cleared on closure.<ref>Mahlous, A. R., & Mahlous, H. Private Browsing Forensic Analysis: A Case Study of Privacy Preservation in the Brave Browser.</ref> Fragments of browser data and activities are still accessible on RAM after closing the browser, though they are lost on computer shutdown. Another instance of compromised privacy was seen when a leak, originally seen in a patch introduced on October 14, 2020, was released in a stable build on November 20, 2020.<ref>Powers, B. (2021, February 23). Brave browser leak exposed user domain info for months. Retrieved March 18, 2021, from [https://www.coindesk.com/brave-browser-leak-exposed-user-domain-info-months]<br />
</ref> This leak revealed DNS information and server logs that could be traceable through high-level network access, such as law enforcement, posing a potential safety concern for users in regions with browsing restrictions. The leak was fixed on February 4, 2021 after being present in the stable build for 91 days. In another study, the Brave Browser was found to be vulnerable to the same attacks as Chrome, as it is built off of Chromium, which can reveal some browsing history information through CSS and Javascript weaknesses.<ref>Smith, M., Disselkoen, C., Narayan, S., Brown, F., & Stefan, D. (2018). Browser history re: visited. In 12th {USENIX} Workshop on Offensive Technologies ({WOOT} 18).</ref><br />
<br clear=all><br />
<br />
[[File:BraveTweet.png|thumb|right|User who discovered Brave Browser auto-completing links<ref>Davenport C. (7, June 2020) [https://www.androidpolice.com/2020/06/07/brave-browser-caught-adding-its-own-referral-codes-to-some-cryptcurrency-trading-sites/ "Brave Browser caught adding its own referral codes to some cryptocurrency trading sites"] Retrieved 8 April 2020</ref>]]<br />
<br />
Another time that Brave Browser did not uphold their promises on privacy was their addition to auto-completing links to redirect users to affiliate links, “presumably for profit.” One user reported that when typing in “binance.us” to Brave Browser, it was auto-completed with "binance.us/en?ref=35089877." While the auto-completing of this link actually sent users to the right place, this incident rubbed users the wrong way. Because Brave Browser gives users the option to keep or remove ads, users were not pleased that Brave Browser was auto-completing links without notifying users that they were doing so.<ref>Engadget HD. (8, June 2020). [https://go-gale-com.proxy.lib.umich.edu/ps/i.do?p=STND&u=umuser&id=GALE%7CA655333954&v=2.1&it=r&sid=summon "Brave privacy browser 'mistake' added affiliate links to crypto URLs."] Retrieved 7 April 2021.</ref><br />
<br />
A third incident that Brave Browser had was because of their Tor browsing mode. Tor’s main objective is to conceal a user’s location when browsing online. Brave Browser had a bug that caused the website being visited to send a DNS query to your local device, which makes it possible for others to find your location. This bug was able to be verified by using an application, Wireshark, to analyze DNS traffic.<ref>Abrams L. (19, February, 2021) [https://www.bleepingcomputer.com/news/security/brave-privacy-bug-exposes-tor-onion-urls-to-your-dns-provider/ "Brave privacy bug exposes Tor onion URLs to your DNS provider"] Retrieved 7 April 2021</ref><br />
<br />
<br />
<br />
<br />
==References==<br />
<div style="clear: both; margin: 1em 0 0 0; padding: 5px; border: 1px solid #AAA; background: #F0F8FF"><br />
<references /><br />
</div></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brave_Browser&diff=100944Brave Browser2021-04-08T16:58:14Z<p>Ptse: </p>
<hr />
<div>{{SoftwareInfoBox<br />
|HEIGHT=720<br />
|NAME=Brave Browser<br />
|LOGO=Brave-logo.png<br />
|SCREENIMAGE=braveex.png<br />
|CAPTION=''"Brave Browser"''<br />
|IMAGEURL=https://brave.com/download/<br />
|TEXT=download link<br />
|PLATFORM=Windows<br>macOS<br>Linux<br>Android<br>iOS<br />
|PRODUCT=Brave Browser<br>BAT<br />
|TYPE=Web Browser<br />
|SITEURL=http://brave.com<br />
|URLTEXT=www.brave.com<br />
|STATUS=Active<br />
|LAUNCH=2015<br />
}}<br />
<br />
<br><br />
'''Brave Browser''' is an open-source browser application focused on prioritizing user privacy and democratizing online advertising. It has been developed using the [https://en.wikipedia.org/wiki/Chromium_(web_browser) Chromium web browser] as a foundation, like [https://en.wikipedia.org/wiki/Microsoft_Edge Microsoft Edge] and [https://en.wikipedia.org/wiki/Opera_(web_browser) Opera]. Brave is specifically focused on the user privacy niche and blocks all ads and trackers by default.<br />
Brave Software was co-founded in May 2015 by CEO Brendan Eich (creator of [https://en.wikipedia.org/wiki/JavaScript JavaScript] and former CEO of [https://en.wikipedia.org/wiki/Mozilla_Corporation Mozilla Corporation]) and CTO Brian Bondy.<ref name="founding"> Brian Bondy. [https://web.archive.org/web/20191119215054/https://brave.com/the-road-to-brave-one-dot-zero/] Retrieved on 11 March 2021. </ref><br />
Brave is headquartered in San Francisco, CA. As of February 2021, Brave Browser had over 25 million monthly active users. <ref name="MUA">Brave Browser. [https://brave.com/25m-mau/#:~:text=Brave%20Passes%2025%20Million%20Monthly%20Active%20Users "Brave Blog"] Retrieved on 11 March 2021.</ref><br />
<br />
__TOC__<br />
==Key Features==<br />
===Ad and Tracker Blocking=== <br />
Brave Browser blocks all ads and third-party trackers by default. On any given tab, the browser has an option to enable and disable a display showing how many items have been blocked or modified on that particular page, such as cross-site trackers, connections upgraded to HTTPS, and scripts blocked.<ref name="features"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> The Brave Browser does not serve individual user browsing data on its servers, unlike most other browsers; instead, all user data is aggregated before being returned to Brave's servers. The ads and trackers that are blocked by default can also be customized by the user at any time. <ref name="privacy"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> However, user browsing data is still saved on users' local devices in order to ensure that ads that they may opt-in to see are still relevant. Brave also advertises that the fact that all ads are blocked, enabling faster browsing times for the user.<br />
<br />
===Basic Attention Token (BAT)=== <br />
[[File:Batlogo.png|thumbnail|80px|thumb|left|BAT logo]]<br />
The Basic Attention Token (BAT) is an Ethereum based token that can be traded on a wallet embedded in the browser itself. BAT is the unit of exchange used for browser features such as Brave Rewards. BAT had its [https://en.wikipedia.org/wiki/Initial_coin_offering initial coin offering] (ICO) on May 31st, 2017.<ref name="ico"> [https://www.bitdegree.org/crypto/basic-attention-token#:~:text=The%20BAT%20ICO%20(Initial%20Coin,was%20the%20ERC%2D20%20token.&text=The%20complete%20amount%20of%20the,1%2C5%20billion%20BAT%20tokens.] Retrieved on 11 March 2021. </ref> In under 30 seconds, 1,000,000,000 BAT were sold for a total of 156,250 Ethereum.<ref name="icos">[https://techcrunch.com/2017/06/01/brave-ico-35-million-30-seconds-brendan-eich/] Retrieved on 11 March 2021. </ref> BAT improves the efficiency of digital advertising by creating a new unit of exchange between publishers, advertisers, and users. BAT allows users to have greater agency over the ads they see online: users can block ads, pay to see different ads, or view ads and earn BAT tokens in exchange.<ref name="batbene">[https://themerkle.com/what-is-basic-attention-token/] Retrieved on 11 March 2021. </ref> Advertisers also benefit from this model by achieving higher returns on advertising investment. This is delivered through better ad targeting (based on local user data) and reduced fraud. <br><br />
===Brave Rewards=== <br />
Brave Rewards has a two-pronged benefit: it allows users to support their favorite content creators, and it allows users to earn money. For the former, Brave allows users to send their favorite content creators (YouTubers, Twitter users, blog owners, etc.) BAT, which can be converted to cash. This practice is known as [https://brave.com/tips/#:~:text=When%20you%20visit%20Twitter%20in,Brave%20Rewards%20account%20within%20minutes. tipping]. Users can choose to either set up recurring payments or make a one-time payment. For the latter benefit, users can choose to earn money by opting in to view ads. Rather than traditional banner ads, Brave displays its ads as a push notification that users can choose to interact with. The aim of this ad format is to create a more engaging ad experience that benefits all parties involved.<br />
<br />
Currently, Brave has over 735,000 registered content creators with many notable names such as Philip DeFranco, The Washington Post, wikiHow, XXL, Vice, and The Guardian to name a few.<ref name="creators"> ''Brave'' (2019). [https://creators.brave.com/ "Earn more for content you publish to the web - Brave Creators"] Retrieved on 8 April 2021. </ref> In the current e-commerce system, digital content creators receive an estimated half of their revenue due to ad-blocking users and many digital ad platforms are monopolized by Google, Facebook, and Amazon.<ref name="mediapost"> Williams, R. (2019, August 23). [https://www.mediapost.com/publications/article/339624/google-publishers-lose-half-of-ad-revenue-from-co.html "Google: Publishers Lose Half Of Ad Revenue From Cookie Blocking"] ''Publishing Insider'' Retrieved on 8 April 2021. </ref> Thus, Brave Rewards is highly appealing to content creators as it attempts to equalize systemically disproportionate streams of revenue.<br />
<br />
===IPFS Integration===<br />
IPFS is the protocol that Brave uses instead of HTTP, which is what most browsers use. IPFS is known as a peer-to-peer protocol. This is because it uses distributed nodes near the user to send data. This can result in faster web browsing in certain areas. In contrast, HTTP has a centralized server that transmits data to users. This can be slow in some areas if the distance from the user to the server is far.<br />
<br />
Another benefit to IPFS is that content restricted in some parts of the world, such as Turkey, Thailand, and China, are now available to them because of IPFS.<ref>Bonifacic, I. (2021, January 19). [https://www.engadget.com/brave-ipfs-update-190545662.html "Brave browser now supports peer-to-peer IPFS protocol"] Retrieved on 7 April 2021. </ref><br />
<br />
===Other Features===<br />
* [https://en.wikipedia.org/wiki/Tor_(anonymity_network) Tor] integration for anonymous browsing by concealing user location and usage information<br />
* Auto-suggesting search terms and searching from the address bar<br />
* Option to use DuckDuckGo for private window search<br />
* Built-in password manager<br />
* [https://en.wikipedia.org/wiki/Fingerprint_(computing) Fingerprinting] prevention, cookie control, and HTTPS upgrading<br />
* Support for most Chrome extensions<br />
===Planned Features===<br />
According to Brave’s BAT roadmap of 2021, Brave developers are aiming to increase crypto and decentralized finance (DeFi) accessibility by creating their own cryptocurrency wallet using Ethereum, an open-source [[blockchain]] technology.<ref name="roadmap"> ''Brave'' (2021, February 22). [https://brave.com/bat-roadmap-2-0/ "BAT Roadmap 2.0"] Retrieved on 8 April 2021. </ref> The Brave Wallet will replace existing crypto wallets and have redesigned UI/UX as well as mobile support. A JavaScript Ethereum Provider API, used to connect web apps with Ethereum blockchain, will now be supplied to web pages by default and more options for buying crypto with fiat payment methods, currencies without intrinsic or use value, will be unlocked. Brave is also looking to support integrated NFT redemption usage(source) within its browser and enable payment of transaction fees through BAT. To further spread DeFi, Brave is creating a new decentralized exchange aggregator with monetary incentives for Brave/Bat users. Aside from future optimizations in accountability and anonymity, to achieve their final endgame of building a Decentralized Web, Brave is researching BAT use in search engines, e-commerce, VPN, IPNS-verified content, and IPFS content pinning. According to public IPFS documentation, IPFS refers to “a distributed system for storing and accessing files, websites, applications, and data.”<ref name="ipfs"> Schilling, J. (2019, December 3). [https://docs.ipfs.io/concepts/what-is-ipfs/ "What is IPFS? | IPFS Docs"] ''IPFS Docs'' Retrieved on 8 April 2021. </ref> IFPS uses content-based addressing while IPNS solves the issue of creating updatable addresses when content is updated. By tying BAT with multiple Decentralized Web systems, Brave is associating their browser and its reward system with other public efforts towards decentralization.<br />
<br />
==Ethical Considerations==<br />
[[File:bizmodel.png|thumb|left|Brave's advertising model]]<br />
===Data Privacy=== <br />
Data privacy while browsing online is a point of contention regarding Internet privacy in the modern-day. Brave offers a robust feature list on metrics related to online privacy and data ethics. By keeping all data local and privatized, Brave does not monetize user data the way many browsers do. Instead, its primary revenue driver is its usage of BAT.<ref name="mainrevenue">https://gizmodo.com/brave-wants-to-destroy-the-ad-business-by-paying-you-to-1834283860] Retrieved on 11 March 2021. </ref> This business model allows them to monetize browsing while still returning 70% of revenue to Brave users themselves.<ref name="returntousers">https://social.techcrunch.com/2019/04/24/brave-ads/] Retrieved on 11 March 2021. </ref> This allows for incentive alignment with users who are focused on privacy and Brave's monetization strategy and business model.<br />
===Online Advertising Ecosystem===<br />
The main concern with Brave's lack of individualized user collection is whether or not users would see relevant ads if they chose to opt-in to see ads in order to earn BAT. Although Brave does not collect individualized user data, it still practices machine learning on aggregated and anonymized data to ensure that ads users see are relevant for them.<ref name="ads">https://brave.com/intro-to-brave-ads/] Retrieved on 11 March 2021. </ref> By approaching advertising this way, Brave addresses common ethical concerns of monetization user behavior data, while still employing machine learning as an effective tool to display relevant ads. By choosing to implement ads in-app instead of using a third-party ad service, Brave Browser also eliminates the 3rd party ad broker and allows for revenue to be returned to the users. <br />
<br />
<br clear=all><br />
===User Expectations of Privacy===<br />
[[File:Brave-private-tab-tor.png|thumb|right|Brave's new tab disclosure]]<br />
Users frequently have misconceptions about online privacy and how private browser modes work.<ref>Wu, Y., Gupta, P., Wei, M., Acar, Y., Fahl, S., & Ur, B. (2018, April). Your secrets are safe: How browsers' explanations impact misconceptions about private browsing mode. In Proceedings of the 2018 World Wide Web Conference (pp. 217-226).<br />
</ref> These include overestimating the function of private browser modes, such as assuming protection against ISP tracking of browsing history. A study has suggested this causes a negative impact on user privacy when using the Brave Browser, as users may engage differently when they expect a certain degree of anonymity.<ref>Fehlhaber, A. L., Acar, Y., Fahl, S., Gutfleisch, M., Theis, D., & Wallkötter, F. Poster: When Brave Hurts Privacy: Why Too Many Choices do More Harm Than Good.</ref> This study also suggested that the new tab disclosure, which attempts to explain the difference between Brave’s two modes, is not effective at educating users on the impact on browsing privacy.<br />
<br />
===Failure of Privacy Promise===<br />
When Brave Browser was released, privacy was their main policy. By design, Brave Browser would inherently provide better privacy than other browsers. Brave addressed a big issue, surveillance capitalism, by “blocking trackers, invasive ads, and device fingerprinting.”<ref>Krill P. (19 November 2019) [https://bi-gale-com.proxy.lib.umich.edu/global/article/GALE%7CA606140924?u=umuser&sid=summon "'Privacy first' Brave browser exits beta."] Retrieved 7 April 2021.</ref> However, there have been some moments where Brave has failed to uphold their promises on privacy. There are multiple instances of the Brave Browser not delivering on its claim to provide privacy protection. One claim that has been found to be misleading is that all traces of browsing history are cleared on closure.<ref>Mahlous, A. R., & Mahlous, H. Private Browsing Forensic Analysis: A Case Study of Privacy Preservation in the Brave Browser.</ref> Fragments of browser data and activities are still accessible on RAM after closing the browser, though they are lost on computer shutdown. Another instance of compromised privacy was seen when a leak, originally seen in a patch introduced on October 14, 2020, was released in a stable build on November 20, 2020.<ref>Powers, B. (2021, February 23). Brave browser leak exposed user domain info for months. Retrieved March 18, 2021, from [https://www.coindesk.com/brave-browser-leak-exposed-user-domain-info-months]<br />
</ref> This leak revealed DNS information and server logs that could be traceable through high-level network access, such as law enforcement, posing a potential safety concern for users in regions with browsing restrictions. The leak was fixed on February 4, 2021 after being present in the stable build for 91 days. In another study, the Brave Browser was found to be vulnerable to the same attacks as Chrome, as it is built off of Chromium, which can reveal some browsing history information through CSS and Javascript weaknesses.<ref>Smith, M., Disselkoen, C., Narayan, S., Brown, F., & Stefan, D. (2018). Browser history re: visited. In 12th {USENIX} Workshop on Offensive Technologies ({WOOT} 18).</ref><br />
<br clear=all><br />
<br />
[[File:BraveTweet.png|thumb|right|User who discovered Brave Browser auto-completing links<ref>Davenport C. (7, June 2020) [https://www.androidpolice.com/2020/06/07/brave-browser-caught-adding-its-own-referral-codes-to-some-cryptcurrency-trading-sites/ "Brave Browser caught adding its own referral codes to some cryptocurrency trading sites"] Retrieved 8 April 2020</ref>]]<br />
<br />
Another time that Brave Browser did not uphold their promises on privacy was their addition to auto-completing links to redirect users to affiliate links, “presumably for profit.” One user reported that when typing in “binance.us” to Brave Browser, it was auto-completed with "binance.us/en?ref=35089877." While the auto-completing of this link actually sent users to the right place, this incident rubbed users the wrong way. Because Brave Browser gives users the option to keep or remove ads, users were not pleased that Brave Browser was auto-completing links without notifying users that they were doing so.<ref>Engadget HD. (8, June 2020). [https://go-gale-com.proxy.lib.umich.edu/ps/i.do?p=STND&u=umuser&id=GALE%7CA655333954&v=2.1&it=r&sid=summon "Brave privacy browser 'mistake' added affiliate links to crypto URLs."] Retrieved 7 April 2021.</ref><br />
<br />
A third incident that Brave Browser had was because of their Tor browsing mode. Tor’s main objective is to conceal a user’s location when browsing online. Brave Browser had a bug that caused the website being visited to send a DNS query to your local device, which makes it possible for others to find your location. This bug was able to be verified by using an application, Wireshark, to analyze DNS traffic.<ref>Abrams L. (19, February, 2021) [https://www.bleepingcomputer.com/news/security/brave-privacy-bug-exposes-tor-onion-urls-to-your-dns-provider/ "Brave privacy bug exposes Tor onion URLs to your DNS provider"] Retrieved 7 April 2021</ref><br />
<br />
<br />
<br />
<br />
==References==<br />
<div style="clear: both; margin: 1em 0 0 0; padding: 5px; border: 1px solid #AAA; background: #F0F8FF"><br />
<references /><br />
</div></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brave_Browser&diff=100941Brave Browser2021-04-08T16:56:07Z<p>Ptse: </p>
<hr />
<div>{{SoftwareInfoBox<br />
|HEIGHT=720<br />
|NAME=Brave Browser<br />
|LOGO=Brave-logo.png<br />
|SCREENIMAGE=braveex.png<br />
|CAPTION=''"Brave Browser"''<br />
|IMAGEURL=https://brave.com/download/<br />
|TEXT=download link<br />
|PLATFORM=Windows<br>macOS<br>Linux<br>Android<br>iOS<br />
|PRODUCT=Brave Browser<br>BAT<br />
|TYPE=Web Browser<br />
|SITEURL=http://brave.com<br />
|URLTEXT=www.brave.com<br />
|STATUS=Active<br />
|LAUNCH=2015<br />
}}<br />
<br />
<br><br />
'''Brave Browser''' is an open-source browser application focused on prioritizing user privacy and democratizing online advertising. It has been developed using the [https://en.wikipedia.org/wiki/Chromium_(web_browser) Chromium web browser] as a foundation, like [https://en.wikipedia.org/wiki/Microsoft_Edge Microsoft Edge] and [https://en.wikipedia.org/wiki/Opera_(web_browser) Opera]. Brave is specifically focused on the user privacy niche and blocks all ads and trackers by default.<br />
Brave Software was co-founded in May 2015 by CEO Brendan Eich (creator of [https://en.wikipedia.org/wiki/JavaScript JavaScript] and former CEO of [https://en.wikipedia.org/wiki/Mozilla_Corporation Mozilla Corporation]) and CTO Brian Bondy.<ref name="founding"> Brian Bondy. [https://web.archive.org/web/20191119215054/https://brave.com/the-road-to-brave-one-dot-zero/] Retrieved on 11 March 2021. </ref><br />
Brave is headquartered in San Francisco, CA. As of February 2021, Brave Browser had over 25 million monthly active users. <ref name="MUA">Brave Browser. [https://brave.com/25m-mau/#:~:text=Brave%20Passes%2025%20Million%20Monthly%20Active%20Users "Brave Blog"] Retrieved on 11 March 2021.</ref><br />
<br />
__TOC__<br />
==Key Features==<br />
===Ad and Tracker Blocking=== <br />
Brave Browser blocks all ads and third-party trackers by default. On any given tab, the browser has an option to enable and disable a display showing how many items have been blocked or modified on that particular page, such as cross-site trackers, connections upgraded to HTTPS, and scripts blocked.<ref name="features"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> The Brave Browser does not serve individual user browsing data on its servers, unlike most other browsers; instead, all user data is aggregated before being returned to Brave's servers. The ads and trackers that are blocked by default can also be customized by the user at any time. <ref name="privacy"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> However, user browsing data is still saved on users' local devices in order to ensure that ads that they may opt-in to see are still relevant. Brave also advertises that the fact that all ads are blocked, enabling faster browsing times for the user.<br />
<br />
===Basic Attention Token (BAT)=== <br />
[[File:Batlogo.png|thumbnail|80px|thumb|left|BAT logo]]<br />
The Basic Attention Token (BAT) is an Ethereum based token that can be traded on a wallet embedded in the browser itself. BAT is the unit of exchange used for browser features such as Brave Rewards. BAT had its [https://en.wikipedia.org/wiki/Initial_coin_offering initial coin offering] (ICO) on May 31st, 2017.<ref name="ico"> [https://www.bitdegree.org/crypto/basic-attention-token#:~:text=The%20BAT%20ICO%20(Initial%20Coin,was%20the%20ERC%2D20%20token.&text=The%20complete%20amount%20of%20the,1%2C5%20billion%20BAT%20tokens.] Retrieved on 11 March 2021. </ref> In under 30 seconds, 1,000,000,000 BAT were sold for a total of 156,250 Ethereum.<ref name="icos">[https://techcrunch.com/2017/06/01/brave-ico-35-million-30-seconds-brendan-eich/] Retrieved on 11 March 2021. </ref> BAT improves the efficiency of digital advertising by creating a new unit of exchange between publishers, advertisers, and users. BAT allows users to have greater agency over the ads they see online: users can block ads, pay to see different ads, or view ads and earn BAT tokens in exchange.<ref name="batbene">[https://themerkle.com/what-is-basic-attention-token/] Retrieved on 11 March 2021. </ref> Advertisers also benefit from this model by achieving higher returns on advertising investment. This is delivered through better ad targeting (based on local user data) and reduced fraud. <br><br />
===Brave Rewards=== <br />
Brave Rewards has a two-pronged benefit: it allows users to support their favorite content creators, and it allows users to earn money. For the former, Brave allows users to send their favorite content creators (YouTubers, Twitter users, blog owners, etc.) BAT, which can be converted to cash. This practice is known as [https://brave.com/tips/#:~:text=When%20you%20visit%20Twitter%20in,Brave%20Rewards%20account%20within%20minutes. tipping]. Users can choose to either set up recurring payments or make a one-time payment. For the latter benefit, users can choose to earn money by opting in to view ads. Rather than traditional banner ads, Brave displays its ads as a push notification that users can choose to interact with. The aim of this ad format is to create a more engaging ad experience that benefits all parties involved.<br />
<br />
Currently, Brave has over 735,000 registered content creators with many notable names such as Philip DeFranco, The Washington Post, wikiHow, XXL, Vice, and The Guardian to name a few.<ref name="creators"> ''Brave'' (2019). [https://creators.brave.com/ "Earn more for content you publish to the web - Brave Creators"] Retrieved on 8 April 2021. </ref> In the current e-commerce system, digital content creators receive an estimated half of their revenue due to ad-blocking users and many digital ad platforms are monopolized by Google, Facebook, and Amazon.<ref name="mediapost"> Williams, R. (2019, August 23). [https://www.mediapost.com/publications/article/339624/google-publishers-lose-half-of-ad-revenue-from-co.html "Google: Publishers Lose Half Of Ad Revenue From Cookie Blocking"] ''Publishing Insider'' Retrieved on 8 April 2021. </ref> Thus, Brave Rewards is highly appealing to content creators as it attempts to equalize systemically disproportionate streams of revenue.<br />
<br />
===IPFS Integration===<br />
IPFS is the protocol that Brave uses instead of HTTP, which is what most browsers use. IPFS is known as a peer-to-peer protocol. This is because it uses distributed nodes near the user to send data. This can result in faster web browsing in certain areas. In contrast, HTTP has a centralized server that transmits data to users. This can be slow in some areas if the distance from the user to the server is far.<br />
<br />
Another benefit to IPFS is that content restricted in some parts of the world, such as Turkey, Thailand, and China, are now available to them because of IPFS.<ref>Bonifacic, I. (2021, January 19). [https://www.engadget.com/brave-ipfs-update-190545662.html "Brave browser now supports peer-to-peer IPFS protocol"] Retrieved on 7 April 2021. </ref><br />
<br />
===Other Features===<br />
* [https://en.wikipedia.org/wiki/Tor_(anonymity_network) Tor] integration for anonymous browsing by concealing user location and usage information<br />
* Auto-suggesting search terms and searching from the address bar<br />
* Option to use DuckDuckGo for private window search<br />
* Built-in password manager<br />
* [https://en.wikipedia.org/wiki/Fingerprint_(computing) Fingerprinting] prevention, cookie control, and HTTPS upgrading<br />
* Support for most Chrome extensions<br />
===Planned Features===<br />
According to Brave’s BAT roadmap of 2021, Brave developers are aiming to increase crypto and decentralized finance (DeFi) accessibility by creating their own cryptocurrency wallet using Ethereum, an open-source [[blockchain]] technology.<ref name="roadmap"> ''Brave'' (2021, February 22). [https://brave.com/bat-roadmap-2-0/ "BAT Roadmap 2.0"] Retrieved on 8 April 2021. </ref> The Brave Wallet will replace existing crypto wallets and have redesigned UI/UX as well as mobile support. A JavaScript Ethereum Provider API, used to connect web apps with Ethereum blockchain, will now be supplied to web pages by default and more options for buying crypto with fiat payment methods, currencies without intrinsic or use value, will be unlocked. Brave is also looking to support integrated NFT redemption usage(source) within its browser and enable payment of transaction fees through BAT. To further spread DeFi, Brave is creating a new decentralized exchange aggregator with monetary incentives for Brave/Bat users. Aside from future optimizations in accountability and anonymity, to achieve their final endgame of building a Decentralized Web, Brave is researching BAT use in search engines, e-commerce, VPN, IPNS-verified content, and IPFS content pinning. According to public IPFS documentation, IPFS refers to “a distributed system for storing and accessing files, websites, applications, and data.”<ref name="ipfs"> Schilling, J. (2019, December 3). [https://docs.ipfs.io/concepts/what-is-ipfs/ "What is IPFS? | IPFS Docs"] ''IPFS Docs'' Retrieved on 8 April 2021. </ref> IFPS uses content-based addressing while IPNS solves the issue of creating updatable addresses when content is updated. By tying BAT with multiple Decentralized Web systems, Brave is associating their browser and its reward system with other public efforts towards decentralization.<br />
<br />
==Ethical Considerations==<br />
[[File:bizmodel.png|thumb|left|Brave's advertising model]]<br />
===Data Privacy=== <br />
Data privacy while browsing online is a point of contention regarding Internet privacy in the modern-day. Brave offers a robust feature list on metrics related to online privacy and data ethics. By keeping all data local and privatized, Brave does not monetize user data the way many browsers do. Instead, its primary revenue driver is its usage of BAT.<ref name="mainrevenue">https://gizmodo.com/brave-wants-to-destroy-the-ad-business-by-paying-you-to-1834283860] Retrieved on 11 March 2021. </ref> This business model allows them to monetize browsing while still returning 70% of revenue to Brave users themselves.<ref name="returntousers">https://social.techcrunch.com/2019/04/24/brave-ads/] Retrieved on 11 March 2021. </ref> This allows for incentive alignment with users who are focused on privacy and Brave's monetization strategy and business model.<br />
===Online Advertising Ecosystem===<br />
The main concern with Brave's lack of individualized user collection is whether or not users would see relevant ads if they chose to opt-in to see ads in order to earn BAT. Although Brave does not collect individualized user data, it still practices machine learning on aggregated and anonymized data to ensure that ads users see are relevant for them.<ref name="ads">https://brave.com/intro-to-brave-ads/] Retrieved on 11 March 2021. </ref> By approaching advertising this way, Brave addresses common ethical concerns of monetization user behavior data, while still employing machine learning as an effective tool to display relevant ads. By choosing to implement ads in-app instead of using a third-party ad service, Brave Browser also eliminates the 3rd party ad broker and allows for revenue to be returned to the users. <br />
<br />
<br clear=all><br />
===User Expectations of Privacy===<br />
[[File:Brave-private-tab-tor.png|thumb|right|Brave's new tab disclosure]]<br />
Users frequently have misconceptions about online privacy and how private browser modes work.<ref>Wu, Y., Gupta, P., Wei, M., Acar, Y., Fahl, S., & Ur, B. (2018, April). Your secrets are safe: How browsers' explanations impact misconceptions about private browsing mode. In Proceedings of the 2018 World Wide Web Conference (pp. 217-226).<br />
</ref> These include overestimating the function of private browser modes, such as assuming protection against ISP tracking of browsing history. A study has suggested this causes a negative impact on user privacy when using the Brave Browser, as users may engage differently when they expect a certain degree of anonymity.<ref>Fehlhaber, A. L., Acar, Y., Fahl, S., Gutfleisch, M., Theis, D., & Wallkötter, F. Poster: When Brave Hurts Privacy: Why Too Many Choices do More Harm Than Good.</ref> This study also suggested that the new tab disclosure, which attempts to explain the difference between Brave’s two modes, is not effective at educating users on the impact on browsing privacy.<br />
<br />
===Failure of Privacy Promise===<br />
When Brave Browser was released, privacy was their main policy. By design, Brave Browser would inherently provide better privacy than other browsers. Brave addressed a big issue, surveillance capitalism, by “blocking trackers, invasive ads, and device fingerprinting.”<ref>Krill P. (19 November 2019) [https://bi-gale-com.proxy.lib.umich.edu/global/article/GALE%7CA606140924?u=umuser&sid=summon "'Privacy first' Brave browser exits beta."] Retrieved 7 April 2021.</ref> However, there have been some moments where Brave has failed to uphold their promises on privacy. There are multiple instances of the Brave Browser not delivering on its claim to provide privacy protection. One claim that has been found to be misleading is that all traces of browsing history are cleared on closure.<ref>Mahlous, A. R., & Mahlous, H. Private Browsing Forensic Analysis: A Case Study of Privacy Preservation in the Brave Browser.</ref> Fragments of browser data and activities are still accessible on RAM after closing the browser, though they are lost on computer shutdown. Another instance of compromised privacy was seen when a leak, originally seen in a patch introduced on October 14, 2020, was released in a stable build on November 20, 2020.<ref>Powers, B. (2021, February 23). Brave browser leak exposed user domain info for months. Retrieved March 18, 2021, from [https://www.coindesk.com/brave-browser-leak-exposed-user-domain-info-months]<br />
</ref> This leak revealed DNS information and server logs that could be traceable through high-level network access, such as law enforcement, posing a potential safety concern for users in regions with browsing restrictions. The leak was fixed on February 4, 2021 after being present in the stable build for 91 days. In another study, the Brave Browser was found to be vulnerable to the same attacks as Chrome, as it is built off of Chromium, which can reveal some browsing history information through CSS and Javascript weaknesses.<ref>Smith, M., Disselkoen, C., Narayan, S., Brown, F., & Stefan, D. (2018). Browser history re: visited. In 12th {USENIX} Workshop on Offensive Technologies ({WOOT} 18).</ref><br />
<br clear=all><br />
<br />
Another time that Brave Browser did not uphold their promises on privacy was their addition to auto-completing links to redirect users to affiliate links, “presumably for profit.” One user reported that when typing in “binance.us” to Brave Browser, it was auto-completed with "binance.us/en?ref=35089877." While the auto-completing of this link actually sent users to the right place, this incident rubbed users the wrong way. Because Brave Browser gives users the option to keep or remove ads, users were not pleased that Brave Browser was auto-completing links without notifying users that they were doing so.<ref>Engadget HD. (8, June 2020). [https://go-gale-com.proxy.lib.umich.edu/ps/i.do?p=STND&u=umuser&id=GALE%7CA655333954&v=2.1&it=r&sid=summon "Brave privacy browser 'mistake' added affiliate links to crypto URLs."] Retrieved 7 April 2021.</ref><br />
<br />
[[File:BraveTweet.png|thumb|right|User who discovered Brave Browser auto-completing links]]<br />
<br />
A third incident that Brave Browser had was because of their Tor browsing mode. Tor’s main objective is to conceal a user’s location when browsing online. Brave Browser had a bug that caused the website being visited to send a DNS query to your local device, which makes it possible for others to find your location. This bug was able to be verified by using an application, Wireshark, to analyze DNS traffic.<ref>Abrams L. (19, February, 2021) [https://www.bleepingcomputer.com/news/security/brave-privacy-bug-exposes-tor-onion-urls-to-your-dns-provider/ "Brave privacy bug exposes Tor onion URLs to your DNS provider"] Retrieved 7 April 2021</ref><br />
<br />
<br />
<br />
<br />
==References==<br />
<div style="clear: both; margin: 1em 0 0 0; padding: 5px; border: 1px solid #AAA; background: #F0F8FF"><br />
<references /><br />
</div></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brave_Browser&diff=100940Brave Browser2021-04-08T16:55:41Z<p>Ptse: </p>
<hr />
<div>{{SoftwareInfoBox<br />
|HEIGHT=720<br />
|NAME=Brave Browser<br />
|LOGO=Brave-logo.png<br />
|SCREENIMAGE=braveex.png<br />
|CAPTION=''"Brave Browser"''<br />
|IMAGEURL=https://brave.com/download/<br />
|TEXT=download link<br />
|PLATFORM=Windows<br>macOS<br>Linux<br>Android<br>iOS<br />
|PRODUCT=Brave Browser<br>BAT<br />
|TYPE=Web Browser<br />
|SITEURL=http://brave.com<br />
|URLTEXT=www.brave.com<br />
|STATUS=Active<br />
|LAUNCH=2015<br />
}}<br />
<br />
<br><br />
'''Brave Browser''' is an open-source browser application focused on prioritizing user privacy and democratizing online advertising. It has been developed using the [https://en.wikipedia.org/wiki/Chromium_(web_browser) Chromium web browser] as a foundation, like [https://en.wikipedia.org/wiki/Microsoft_Edge Microsoft Edge] and [https://en.wikipedia.org/wiki/Opera_(web_browser) Opera]. Brave is specifically focused on the user privacy niche and blocks all ads and trackers by default.<br />
Brave Software was co-founded in May 2015 by CEO Brendan Eich (creator of [https://en.wikipedia.org/wiki/JavaScript JavaScript] and former CEO of [https://en.wikipedia.org/wiki/Mozilla_Corporation Mozilla Corporation]) and CTO Brian Bondy.<ref name="founding"> Brian Bondy. [https://web.archive.org/web/20191119215054/https://brave.com/the-road-to-brave-one-dot-zero/] Retrieved on 11 March 2021. </ref><br />
Brave is headquartered in San Francisco, CA. As of February 2021, Brave Browser had over 25 million monthly active users. <ref name="MUA">Brave Browser. [https://brave.com/25m-mau/#:~:text=Brave%20Passes%2025%20Million%20Monthly%20Active%20Users "Brave Blog"] Retrieved on 11 March 2021.</ref><br />
<br />
__TOC__<br />
==Key Features==<br />
===Ad and Tracker Blocking=== <br />
Brave Browser blocks all ads and third-party trackers by default. On any given tab, the browser has an option to enable and disable a display showing how many items have been blocked or modified on that particular page, such as cross-site trackers, connections upgraded to HTTPS, and scripts blocked.<ref name="features"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> The Brave Browser does not serve individual user browsing data on its servers, unlike most other browsers; instead, all user data is aggregated before being returned to Brave's servers. The ads and trackers that are blocked by default can also be customized by the user at any time. <ref name="privacy"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> However, user browsing data is still saved on users' local devices in order to ensure that ads that they may opt-in to see are still relevant. Brave also advertises that the fact that all ads are blocked, enabling faster browsing times for the user.<br />
<br />
===Basic Attention Token (BAT)=== <br />
[[File:Batlogo.png|thumbnail|80px|thumb|left|BAT logo]]<br />
The Basic Attention Token (BAT) is an Ethereum based token that can be traded on a wallet embedded in the browser itself. BAT is the unit of exchange used for browser features such as Brave Rewards. BAT had its [https://en.wikipedia.org/wiki/Initial_coin_offering initial coin offering] (ICO) on May 31st, 2017.<ref name="ico"> [https://www.bitdegree.org/crypto/basic-attention-token#:~:text=The%20BAT%20ICO%20(Initial%20Coin,was%20the%20ERC%2D20%20token.&text=The%20complete%20amount%20of%20the,1%2C5%20billion%20BAT%20tokens.] Retrieved on 11 March 2021. </ref> In under 30 seconds, 1,000,000,000 BAT were sold for a total of 156,250 Ethereum.<ref name="icos">[https://techcrunch.com/2017/06/01/brave-ico-35-million-30-seconds-brendan-eich/] Retrieved on 11 March 2021. </ref> BAT improves the efficiency of digital advertising by creating a new unit of exchange between publishers, advertisers, and users. BAT allows users to have greater agency over the ads they see online: users can block ads, pay to see different ads, or view ads and earn BAT tokens in exchange.<ref name="batbene">[https://themerkle.com/what-is-basic-attention-token/] Retrieved on 11 March 2021. </ref> Advertisers also benefit from this model by achieving higher returns on advertising investment. This is delivered through better ad targeting (based on local user data) and reduced fraud. <br><br />
===Brave Rewards=== <br />
Brave Rewards has a two-pronged benefit: it allows users to support their favorite content creators, and it allows users to earn money. For the former, Brave allows users to send their favorite content creators (YouTubers, Twitter users, blog owners, etc.) BAT, which can be converted to cash. This practice is known as [https://brave.com/tips/#:~:text=When%20you%20visit%20Twitter%20in,Brave%20Rewards%20account%20within%20minutes. tipping]. Users can choose to either set up recurring payments or make a one-time payment. For the latter benefit, users can choose to earn money by opting in to view ads. Rather than traditional banner ads, Brave displays its ads as a push notification that users can choose to interact with. The aim of this ad format is to create a more engaging ad experience that benefits all parties involved.<br />
<br />
Currently, Brave has over 735,000 registered content creators with many notable names such as Philip DeFranco, The Washington Post, wikiHow, XXL, Vice, and The Guardian to name a few.<ref name="creators"> ''Brave'' (2019). [https://creators.brave.com/ "Earn more for content you publish to the web - Brave Creators"] Retrieved on 8 April 2021. </ref> In the current e-commerce system, digital content creators receive an estimated half of their revenue due to ad-blocking users and many digital ad platforms are monopolized by Google, Facebook, and Amazon.<ref name="mediapost"> Williams, R. (2019, August 23). [https://www.mediapost.com/publications/article/339624/google-publishers-lose-half-of-ad-revenue-from-co.html "Google: Publishers Lose Half Of Ad Revenue From Cookie Blocking"] ''Publishing Insider'' Retrieved on 8 April 2021. </ref> Thus, Brave Rewards is highly appealing to content creators as it attempts to equalize systemically disproportionate streams of revenue.<br />
<br />
===IPFS Integration===<br />
IPFS is the protocol that Brave uses instead of HTTP, which is what most browsers use. IPFS is known as a peer-to-peer protocol. This is because it uses distributed nodes near the user to send data. This can result in faster web browsing in certain areas. In contrast, HTTP has a centralized server that transmits data to users. This can be slow in some areas if the distance from the user to the server is far.<br />
<br />
Another benefit to IPFS is that content restricted in some parts of the world, such as Turkey, Thailand, and China, are now available to them because of IPFS.<ref>Bonifacic, I. (2021, January 19). [https://www.engadget.com/brave-ipfs-update-190545662.html "Brave browser now supports peer-to-peer IPFS protocol"] Retrieved on 7 April 2021. </ref><br />
<br />
===Other Features===<br />
* [https://en.wikipedia.org/wiki/Tor_(anonymity_network) Tor] integration for anonymous browsing by concealing user location and usage information<br />
* Auto-suggesting search terms and searching from the address bar<br />
* Option to use DuckDuckGo for private window search<br />
* Built-in password manager<br />
* [https://en.wikipedia.org/wiki/Fingerprint_(computing) Fingerprinting] prevention, cookie control, and HTTPS upgrading<br />
* Support for most Chrome extensions<br />
===Planned Features===<br />
According to Brave’s BAT roadmap of 2021, Brave developers are aiming to increase crypto and decentralized finance (DeFi) accessibility by creating their own cryptocurrency wallet using Ethereum, an open-source [[blockchain]] technology.<ref name="roadmap"> ''Brave'' (2021, February 22). [https://brave.com/bat-roadmap-2-0/ "BAT Roadmap 2.0"] Retrieved on 8 April 2021. </ref> The Brave Wallet will replace existing crypto wallets and have redesigned UI/UX as well as mobile support. A JavaScript Ethereum Provider API, used to connect web apps with Ethereum blockchain, will now be supplied to web pages by default and more options for buying crypto with fiat payment methods, currencies without intrinsic or use value, will be unlocked. Brave is also looking to support integrated NFT redemption usage(source) within its browser and enable payment of transaction fees through BAT. To further spread DeFi, Brave is creating a new decentralized exchange aggregator with monetary incentives for Brave/Bat users. Aside from future optimizations in accountability and anonymity, to achieve their final endgame of building a Decentralized Web, Brave is researching BAT use in search engines, e-commerce, VPN, IPNS-verified content, and IPFS content pinning. According to public IPFS documentation, IPFS refers to “a distributed system for storing and accessing files, websites, applications, and data.”<ref name="ipfs"> Schilling, J. (2019, December 3). [https://docs.ipfs.io/concepts/what-is-ipfs/ "What is IPFS? | IPFS Docs"] ''IPFS Docs'' Retrieved on 8 April 2021. </ref> IFPS uses content-based addressing while IPNS solves the issue of creating updatable addresses when content is updated. By tying BAT with multiple Decentralized Web systems, Brave is associating their browser and its reward system with other public efforts towards decentralization.<br />
<br />
==Ethical Considerations==<br />
[[File:bizmodel.png|thumb|left|Brave's advertising model]]<br />
===Data Privacy=== <br />
Data privacy while browsing online is a point of contention regarding Internet privacy in the modern-day. Brave offers a robust feature list on metrics related to online privacy and data ethics. By keeping all data local and privatized, Brave does not monetize user data the way many browsers do. Instead, its primary revenue driver is its usage of BAT.<ref name="mainrevenue">https://gizmodo.com/brave-wants-to-destroy-the-ad-business-by-paying-you-to-1834283860] Retrieved on 11 March 2021. </ref> This business model allows them to monetize browsing while still returning 70% of revenue to Brave users themselves.<ref name="returntousers">https://social.techcrunch.com/2019/04/24/brave-ads/] Retrieved on 11 March 2021. </ref> This allows for incentive alignment with users who are focused on privacy and Brave's monetization strategy and business model.<br />
===Online Advertising Ecosystem===<br />
The main concern with Brave's lack of individualized user collection is whether or not users would see relevant ads if they chose to opt-in to see ads in order to earn BAT. Although Brave does not collect individualized user data, it still practices machine learning on aggregated and anonymized data to ensure that ads users see are relevant for them.<ref name="ads">https://brave.com/intro-to-brave-ads/] Retrieved on 11 March 2021. </ref> By approaching advertising this way, Brave addresses common ethical concerns of monetization user behavior data, while still employing machine learning as an effective tool to display relevant ads. By choosing to implement ads in-app instead of using a third-party ad service, Brave Browser also eliminates the 3rd party ad broker and allows for revenue to be returned to the users. <br />
<br />
<br clear=all><br />
===User Expectations of Privacy===<br />
[[File:Brave-private-tab-tor.png|thumb|right|Brave's new tab disclosure]]<br />
Users frequently have misconceptions about online privacy and how private browser modes work.<ref>Wu, Y., Gupta, P., Wei, M., Acar, Y., Fahl, S., & Ur, B. (2018, April). Your secrets are safe: How browsers' explanations impact misconceptions about private browsing mode. In Proceedings of the 2018 World Wide Web Conference (pp. 217-226).<br />
</ref> These include overestimating the function of private browser modes, such as assuming protection against ISP tracking of browsing history. A study has suggested this causes a negative impact on user privacy when using the Brave Browser, as users may engage differently when they expect a certain degree of anonymity.<ref>Fehlhaber, A. L., Acar, Y., Fahl, S., Gutfleisch, M., Theis, D., & Wallkötter, F. Poster: When Brave Hurts Privacy: Why Too Many Choices do More Harm Than Good.</ref> This study also suggested that the new tab disclosure, which attempts to explain the difference between Brave’s two modes, is not effective at educating users on the impact on browsing privacy.<br />
<br />
===Failure of Privacy Promise===<br />
When Brave Browser was released, privacy was their main policy. By design, Brave Browser would inherently provide better privacy than other browsers. Brave addressed a big issue, surveillance capitalism, by “blocking trackers, invasive ads, and device fingerprinting.”<ref>Krill P. (19 November 2019) [https://bi-gale-com.proxy.lib.umich.edu/global/article/GALE%7CA606140924?u=umuser&sid=summon "'Privacy first' Brave browser exits beta."] Retrieved 7 April 2021.</ref> However, there have been some moments where Brave has failed to uphold their promises on privacy. There are multiple instances of the Brave Browser not delivering on its claim to provide privacy protection. One claim that has been found to be misleading is that all traces of browsing history are cleared on closure.<ref>Mahlous, A. R., & Mahlous, H. Private Browsing Forensic Analysis: A Case Study of Privacy Preservation in the Brave Browser.</ref> Fragments of browser data and activities are still accessible on RAM after closing the browser, though they are lost on computer shutdown. Another instance of compromised privacy was seen when a leak, originally seen in a patch introduced on October 14, 2020, was released in a stable build on November 20, 2020.<ref>Powers, B. (2021, February 23). Brave browser leak exposed user domain info for months. Retrieved March 18, 2021, from [https://www.coindesk.com/brave-browser-leak-exposed-user-domain-info-months]<br />
</ref> This leak revealed DNS information and server logs that could be traceable through high-level network access, such as law enforcement, posing a potential safety concern for users in regions with browsing restrictions. The leak was fixed on February 4, 2021 after being present in the stable build for 91 days. In another study, the Brave Browser was found to be vulnerable to the same attacks as Chrome, as it is built off of Chromium, which can reveal some browsing history information through CSS and Javascript weaknesses.<ref>Smith, M., Disselkoen, C., Narayan, S., Brown, F., & Stefan, D. (2018). Browser history re: visited. In 12th {USENIX} Workshop on Offensive Technologies ({WOOT} 18).</ref><br />
<br clear=all><br />
<br />
Another time that Brave Browser did not uphold their promises on privacy was their addition to auto-completing links to redirect users to affiliate links, “presumably for profit.” One user reported that when typing in “binance.us” to Brave Browser, it was auto-completed with "binance.us/en?ref=35089877." While the auto-completing of this link actually sent users to the right place, this incident rubbed users the wrong way. Because Brave Browser gives users the option to keep or remove ads, users were not pleased that Brave Browser was auto-completing links without notifying users that they were doing so.<ref>Engadget HD. (8, June 2020). [https://go-gale-com.proxy.lib.umich.edu/ps/i.do?p=STND&u=umuser&id=GALE%7CA655333954&v=2.1&it=r&sid=summon "Brave privacy browser 'mistake' added affiliate links to crypto URLs."] Retrieved 7 April 2021.</ref><br />
<br />
[[File:BraveTweet.jpg|thumb|right|User who discovered Brave Browser auto-completing links]]<br />
<br />
A third incident that Brave Browser had was because of their Tor browsing mode. Tor’s main objective is to conceal a user’s location when browsing online. Brave Browser had a bug that caused the website being visited to send a DNS query to your local device, which makes it possible for others to find your location. This bug was able to be verified by using an application, Wireshark, to analyze DNS traffic.<ref>Abrams L. (19, February, 2021) [https://www.bleepingcomputer.com/news/security/brave-privacy-bug-exposes-tor-onion-urls-to-your-dns-provider/ "Brave privacy bug exposes Tor onion URLs to your DNS provider"] Retrieved 7 April 2021</ref><br />
<br />
<br />
<br />
<br />
==References==<br />
<div style="clear: both; margin: 1em 0 0 0; padding: 5px; border: 1px solid #AAA; background: #F0F8FF"><br />
<references /><br />
</div></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=File:BraveTweet.png&diff=100938File:BraveTweet.png2021-04-08T16:54:54Z<p>Ptse: tweet about Brave auto-completing links</p>
<hr />
<div>tweet about Brave auto-completing links</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brave_Browser&diff=100933Brave Browser2021-04-08T16:51:32Z<p>Ptse: </p>
<hr />
<div>{{SoftwareInfoBox<br />
|HEIGHT=720<br />
|NAME=Brave Browser<br />
|LOGO=Brave-logo.png<br />
|SCREENIMAGE=braveex.png<br />
|CAPTION=''"Brave Browser"''<br />
|IMAGEURL=https://brave.com/download/<br />
|TEXT=download link<br />
|PLATFORM=Windows<br>macOS<br>Linux<br>Android<br>iOS<br />
|PRODUCT=Brave Browser<br>BAT<br />
|TYPE=Web Browser<br />
|SITEURL=http://brave.com<br />
|URLTEXT=www.brave.com<br />
|STATUS=Active<br />
|LAUNCH=2015<br />
}}<br />
<br />
<br><br />
'''Brave Browser''' is an open-source browser application focused on prioritizing user privacy and democratizing online advertising. It has been developed using the [https://en.wikipedia.org/wiki/Chromium_(web_browser) Chromium web browser] as a foundation, like [https://en.wikipedia.org/wiki/Microsoft_Edge Microsoft Edge] and [https://en.wikipedia.org/wiki/Opera_(web_browser) Opera]. Brave is specifically focused on the user privacy niche and blocks all ads and trackers by default.<br />
Brave Software was co-founded in May 2015 by CEO Brendan Eich (creator of [https://en.wikipedia.org/wiki/JavaScript JavaScript] and former CEO of [https://en.wikipedia.org/wiki/Mozilla_Corporation Mozilla Corporation]) and CTO Brian Bondy.<ref name="founding"> Brian Bondy. [https://web.archive.org/web/20191119215054/https://brave.com/the-road-to-brave-one-dot-zero/] Retrieved on 11 March 2021. </ref><br />
Brave is headquartered in San Francisco, CA. As of February 2021, Brave Browser had over 25 million monthly active users. <ref name="MUA">Brave Browser. [https://brave.com/25m-mau/#:~:text=Brave%20Passes%2025%20Million%20Monthly%20Active%20Users "Brave Blog"] Retrieved on 11 March 2021.</ref><br />
<br />
__TOC__<br />
==Key Features==<br />
===Ad and Tracker Blocking=== <br />
Brave Browser blocks all ads and third-party trackers by default. On any given tab, the browser has an option to enable and disable a display showing how many items have been blocked or modified on that particular page, such as cross-site trackers, connections upgraded to HTTPS, and scripts blocked.<ref name="features"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> The Brave Browser does not serve individual user browsing data on its servers, unlike most other browsers; instead, all user data is aggregated before being returned to Brave's servers. The ads and trackers that are blocked by default can also be customized by the user at any time. <ref name="privacy"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> However, user browsing data is still saved on users' local devices in order to ensure that ads that they may opt-in to see are still relevant. Brave also advertises that the fact that all ads are blocked, enabling faster browsing times for the user.<br />
<br />
===Basic Attention Token (BAT)=== <br />
[[File:Batlogo.png|thumbnail|80px|thumb|left|BAT logo]]<br />
The Basic Attention Token (BAT) is an Ethereum based token that can be traded on a wallet embedded in the browser itself. BAT is the unit of exchange used for browser features such as Brave Rewards. BAT had its [https://en.wikipedia.org/wiki/Initial_coin_offering initial coin offering] (ICO) on May 31st, 2017.<ref name="ico"> [https://www.bitdegree.org/crypto/basic-attention-token#:~:text=The%20BAT%20ICO%20(Initial%20Coin,was%20the%20ERC%2D20%20token.&text=The%20complete%20amount%20of%20the,1%2C5%20billion%20BAT%20tokens.] Retrieved on 11 March 2021. </ref> In under 30 seconds, 1,000,000,000 BAT were sold for a total of 156,250 Ethereum.<ref name="icos">[https://techcrunch.com/2017/06/01/brave-ico-35-million-30-seconds-brendan-eich/] Retrieved on 11 March 2021. </ref> BAT improves the efficiency of digital advertising by creating a new unit of exchange between publishers, advertisers, and users. BAT allows users to have greater agency over the ads they see online: users can block ads, pay to see different ads, or view ads and earn BAT tokens in exchange.<ref name="batbene">[https://themerkle.com/what-is-basic-attention-token/] Retrieved on 11 March 2021. </ref> Advertisers also benefit from this model by achieving higher returns on advertising investment. This is delivered through better ad targeting (based on local user data) and reduced fraud. <br><br />
===Brave Rewards=== <br />
Brave Rewards has a two-pronged benefit: it allows users to support their favorite content creators, and it allows users to earn money. For the former, Brave allows users to send their favorite content creators (YouTubers, Twitter users, blog owners, etc.) BAT, which can be converted to cash. This practice is known as [https://brave.com/tips/#:~:text=When%20you%20visit%20Twitter%20in,Brave%20Rewards%20account%20within%20minutes. tipping]. Users can choose to either set up recurring payments or make a one-time payment. For the latter benefit, users can choose to earn money by opting in to view ads. Rather than traditional banner ads, Brave displays its ads as a push notification that users can choose to interact with. The aim of this ad format is to create a more engaging ad experience that benefits all parties involved.<br />
<br />
Currently, Brave has over 735,000 registered content creators with many notable names such as Philip DeFranco, The Washington Post, wikiHow, XXL, Vice, and The Guardian to name a few.<ref name="creators"> ''Brave'' (2019). [https://creators.brave.com/ "Earn more for content you publish to the web - Brave Creators"] Retrieved on 8 April 2021. </ref> In the current e-commerce system, digital content creators receive an estimated half of their revenue due to ad-blocking users and many digital ad platforms are monopolized by Google, Facebook, and Amazon.<ref name="mediapost"> Williams, R. (2019, August 23). [https://www.mediapost.com/publications/article/339624/google-publishers-lose-half-of-ad-revenue-from-co.html "Google: Publishers Lose Half Of Ad Revenue From Cookie Blocking"] ''Publishing Insider'' Retrieved on 8 April 2021. </ref> Thus, Brave Rewards is highly appealing to content creators as it attempts to equalize systemically disproportionate streams of revenue.<br />
<br />
===IPFS Integration===<br />
IPFS is the protocol that Brave uses instead of HTTP, which is what most browsers use. IPFS is known as a peer-to-peer protocol. This is because it uses distributed nodes near the user to send data. This can result in faster web browsing in certain areas. In contrast, HTTP has a centralized server that transmits data to users. This can be slow in some areas if the distance from the user to the server is far.<br />
<br />
Another benefit to IPFS is that content restricted in some parts of the world, such as Turkey, Thailand, and China, are now available to them because of IPFS.<ref>Bonifacic, I. (2021, January 19). [https://www.engadget.com/brave-ipfs-update-190545662.html "Brave browser now supports peer-to-peer IPFS protocol"] Retrieved on 7 April 2021. </ref><br />
<br />
===Other Features===<br />
* [https://en.wikipedia.org/wiki/Tor_(anonymity_network) Tor] integration for anonymous browsing by concealing user location and usage information<br />
* Auto-suggesting search terms and searching from the address bar<br />
* Option to use DuckDuckGo for private window search<br />
* Built-in password manager<br />
* [https://en.wikipedia.org/wiki/Fingerprint_(computing) Fingerprinting] prevention, cookie control, and HTTPS upgrading<br />
* Support for most Chrome extensions<br />
===Planned Features===<br />
According to Brave’s BAT roadmap of 2021, Brave developers are aiming to increase crypto and decentralized finance (DeFi) accessibility by creating their own cryptocurrency wallet using Ethereum, an open-source [[blockchain]] technology.<ref name="roadmap"> ''Brave'' (2021, February 22). [https://brave.com/bat-roadmap-2-0/ "BAT Roadmap 2.0"] Retrieved on 8 April 2021. </ref> The Brave Wallet will replace existing crypto wallets and have redesigned UI/UX as well as mobile support. A JavaScript Ethereum Provider API, used to connect web apps with Ethereum blockchain, will now be supplied to web pages by default and more options for buying crypto with fiat payment methods, currencies without intrinsic or use value, will be unlocked. Brave is also looking to support integrated NFT redemption usage(source) within its browser and enable payment of transaction fees through BAT. To further spread DeFi, Brave is creating a new decentralized exchange aggregator with monetary incentives for Brave/Bat users. Aside from future optimizations in accountability and anonymity, to achieve their final endgame of building a Decentralized Web, Brave is researching BAT use in search engines, e-commerce, VPN, IPNS-verified content, and IPFS content pinning. According to public IPFS documentation, IPFS refers to “a distributed system for storing and accessing files, websites, applications, and data.”<ref name="ipfs"> Schilling, J. (2019, December 3). [https://docs.ipfs.io/concepts/what-is-ipfs/ "What is IPFS? | IPFS Docs"] ''IPFS Docs'' Retrieved on 8 April 2021. </ref> IFPS uses content-based addressing while IPNS solves the issue of creating updatable addresses when content is updated. By tying BAT with multiple Decentralized Web systems, Brave is associating their browser and its reward system with other public efforts towards decentralization.<br />
<br />
==Ethical Considerations==<br />
[[File:bizmodel.png|thumb|left|Brave's advertising model]]<br />
===Data Privacy=== <br />
Data privacy while browsing online is a point of contention regarding Internet privacy in the modern-day. Brave offers a robust feature list on metrics related to online privacy and data ethics. By keeping all data local and privatized, Brave does not monetize user data the way many browsers do. Instead, its primary revenue driver is its usage of BAT.<ref name="mainrevenue">https://gizmodo.com/brave-wants-to-destroy-the-ad-business-by-paying-you-to-1834283860] Retrieved on 11 March 2021. </ref> This business model allows them to monetize browsing while still returning 70% of revenue to Brave users themselves.<ref name="returntousers">https://social.techcrunch.com/2019/04/24/brave-ads/] Retrieved on 11 March 2021. </ref> This allows for incentive alignment with users who are focused on privacy and Brave's monetization strategy and business model.<br />
===Online Advertising Ecosystem===<br />
The main concern with Brave's lack of individualized user collection is whether or not users would see relevant ads if they chose to opt-in to see ads in order to earn BAT. Although Brave does not collect individualized user data, it still practices machine learning on aggregated and anonymized data to ensure that ads users see are relevant for them.<ref name="ads">https://brave.com/intro-to-brave-ads/] Retrieved on 11 March 2021. </ref> By approaching advertising this way, Brave addresses common ethical concerns of monetization user behavior data, while still employing machine learning as an effective tool to display relevant ads. By choosing to implement ads in-app instead of using a third-party ad service, Brave Browser also eliminates the 3rd party ad broker and allows for revenue to be returned to the users. <br />
<br />
<br clear=all><br />
===User Expectations of Privacy===<br />
[[File:Brave-private-tab-tor.png|thumb|right|Brave's new tab disclosure]]<br />
Users frequently have misconceptions about online privacy and how private browser modes work.<ref>Wu, Y., Gupta, P., Wei, M., Acar, Y., Fahl, S., & Ur, B. (2018, April). Your secrets are safe: How browsers' explanations impact misconceptions about private browsing mode. In Proceedings of the 2018 World Wide Web Conference (pp. 217-226).<br />
</ref> These include overestimating the function of private browser modes, such as assuming protection against ISP tracking of browsing history. A study has suggested this causes a negative impact on user privacy when using the Brave Browser, as users may engage differently when they expect a certain degree of anonymity.<ref>Fehlhaber, A. L., Acar, Y., Fahl, S., Gutfleisch, M., Theis, D., & Wallkötter, F. Poster: When Brave Hurts Privacy: Why Too Many Choices do More Harm Than Good.</ref> This study also suggested that the new tab disclosure, which attempts to explain the difference between Brave’s two modes, is not effective at educating users on the impact on browsing privacy.<br />
<br />
===Failure of Privacy Promise===<br />
When Brave Browser was released, privacy was their main policy. By design, Brave Browser would inherently provide better privacy than other browsers. Brave addressed a big issue, surveillance capitalism, by “blocking trackers, invasive ads, and device fingerprinting.”<ref>Krill P. (19 November 2019) [https://bi-gale-com.proxy.lib.umich.edu/global/article/GALE%7CA606140924?u=umuser&sid=summon "'Privacy first' Brave browser exits beta."] Retrieved 7 April 2021.</ref> However, there have been some moments where Brave has failed to uphold their promises on privacy. There are multiple instances of the Brave Browser not delivering on its claim to provide privacy protection. One claim that has been found to be misleading is that all traces of browsing history are cleared on closure.<ref>Mahlous, A. R., & Mahlous, H. Private Browsing Forensic Analysis: A Case Study of Privacy Preservation in the Brave Browser.</ref> Fragments of browser data and activities are still accessible on RAM after closing the browser, though they are lost on computer shutdown. Another instance of compromised privacy was seen when a leak, originally seen in a patch introduced on October 14, 2020, was released in a stable build on November 20, 2020.<ref>Powers, B. (2021, February 23). Brave browser leak exposed user domain info for months. Retrieved March 18, 2021, from [https://www.coindesk.com/brave-browser-leak-exposed-user-domain-info-months]<br />
</ref> This leak revealed DNS information and server logs that could be traceable through high-level network access, such as law enforcement, posing a potential safety concern for users in regions with browsing restrictions. The leak was fixed on February 4, 2021 after being present in the stable build for 91 days. In another study, the Brave Browser was found to be vulnerable to the same attacks as Chrome, as it is built off of Chromium, which can reveal some browsing history information through CSS and Javascript weaknesses.<ref>Smith, M., Disselkoen, C., Narayan, S., Brown, F., & Stefan, D. (2018). Browser history re: visited. In 12th {USENIX} Workshop on Offensive Technologies ({WOOT} 18).</ref><br />
<br clear=all><br />
<br />
Another time that Brave Browser did not uphold their promises on privacy was their addition to auto-completing links to redirect users to affiliate links, “presumably for profit.” One user reported that when typing in “binance.us” to Brave Browser, it was auto-completed with "binance.us/en?ref=35089877." While the auto-completing of this link actually sent users to the right place, this incident rubbed users the wrong way. Because Brave Browser gives users the option to keep or remove ads, users were not pleased that Brave Browser was auto-completing links without notifying users that they were doing so.<ref>Engadget HD. (8, June 2020). [https://go-gale-com.proxy.lib.umich.edu/ps/i.do?p=STND&u=umuser&id=GALE%7CA655333954&v=2.1&it=r&sid=summon "Brave privacy browser 'mistake' added affiliate links to crypto URLs."] Retrieved 7 April 2021.</ref><br />
<br />
[[File:Brave_Tweet.jpg|thumb|right|Brave's new tab disclosure]]<br />
<br />
A third incident that Brave Browser had was because of their Tor browsing mode. Tor’s main objective is to conceal a user’s location when browsing online. Brave Browser had a bug that caused the website being visited to send a DNS query to your local device, which makes it possible for others to find your location. This bug was able to be verified by using an application, Wireshark, to analyze DNS traffic.<ref>Abrams L. (19, February, 2021) [https://www.bleepingcomputer.com/news/security/brave-privacy-bug-exposes-tor-onion-urls-to-your-dns-provider/ "Brave privacy bug exposes Tor onion URLs to your DNS provider"] Retrieved 7 April 2021</ref><br />
<br />
<br />
<br />
<br />
==References==<br />
<div style="clear: both; margin: 1em 0 0 0; padding: 5px; border: 1px solid #AAA; background: #F0F8FF"><br />
<references /><br />
</div></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brave_Browser&diff=100929Brave Browser2021-04-08T16:48:03Z<p>Ptse: </p>
<hr />
<div>{{SoftwareInfoBox<br />
|HEIGHT=720<br />
|NAME=Brave Browser<br />
|LOGO=Brave-logo.png<br />
|SCREENIMAGE=braveex.png<br />
|CAPTION=''"Brave Browser"''<br />
|IMAGEURL=https://brave.com/download/<br />
|TEXT=download link<br />
|PLATFORM=Windows<br>macOS<br>Linux<br>Android<br>iOS<br />
|PRODUCT=Brave Browser<br>BAT<br />
|TYPE=Web Browser<br />
|SITEURL=http://brave.com<br />
|URLTEXT=www.brave.com<br />
|STATUS=Active<br />
|LAUNCH=2015<br />
}}<br />
<br />
<br><br />
'''Brave Browser''' is an open-source browser application focused on prioritizing user privacy and democratizing online advertising. It has been developed using the [https://en.wikipedia.org/wiki/Chromium_(web_browser) Chromium web browser] as a foundation, like [https://en.wikipedia.org/wiki/Microsoft_Edge Microsoft Edge] and [https://en.wikipedia.org/wiki/Opera_(web_browser) Opera]. Brave is specifically focused on the user privacy niche and blocks all ads and trackers by default.<br />
Brave Software was co-founded in May 2015 by CEO Brendan Eich (creator of [https://en.wikipedia.org/wiki/JavaScript JavaScript] and former CEO of [https://en.wikipedia.org/wiki/Mozilla_Corporation Mozilla Corporation]) and CTO Brian Bondy.<ref name="founding"> Brian Bondy. [https://web.archive.org/web/20191119215054/https://brave.com/the-road-to-brave-one-dot-zero/] Retrieved on 11 March 2021. </ref><br />
Brave is headquartered in San Francisco, CA. As of February 2021, Brave Browser had over 25 million monthly active users. <ref name="MUA">Brave Browser. [https://brave.com/25m-mau/#:~:text=Brave%20Passes%2025%20Million%20Monthly%20Active%20Users "Brave Blog"] Retrieved on 11 March 2021.</ref><br />
<br />
__TOC__<br />
==Key Features==<br />
===Ad and Tracker Blocking=== <br />
Brave Browser blocks all ads and third-party trackers by default. On any given tab, the browser has an option to enable and disable a display showing how many items have been blocked or modified on that particular page, such as cross-site trackers, connections upgraded to HTTPS, and scripts blocked.<ref name="features"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> The Brave Browser does not serve individual user browsing data on its servers, unlike most other browsers; instead, all user data is aggregated before being returned to Brave's servers. The ads and trackers that are blocked by default can also be customized by the user at any time. <ref name="privacy"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> However, user browsing data is still saved on users' local devices in order to ensure that ads that they may opt-in to see are still relevant. Brave also advertises that the fact that all ads are blocked, enabling faster browsing times for the user.<br />
<br />
===Basic Attention Token (BAT)=== <br />
[[File:Batlogo.png|thumbnail|80px|thumb|left|BAT logo]]<br />
The Basic Attention Token (BAT) is an Ethereum based token that can be traded on a wallet embedded in the browser itself. BAT is the unit of exchange used for browser features such as Brave Rewards. BAT had its [https://en.wikipedia.org/wiki/Initial_coin_offering initial coin offering] (ICO) on May 31st, 2017.<ref name="ico"> [https://www.bitdegree.org/crypto/basic-attention-token#:~:text=The%20BAT%20ICO%20(Initial%20Coin,was%20the%20ERC%2D20%20token.&text=The%20complete%20amount%20of%20the,1%2C5%20billion%20BAT%20tokens.] Retrieved on 11 March 2021. </ref> In under 30 seconds, 1,000,000,000 BAT were sold for a total of 156,250 Ethereum.<ref name="icos">[https://techcrunch.com/2017/06/01/brave-ico-35-million-30-seconds-brendan-eich/] Retrieved on 11 March 2021. </ref> BAT improves the efficiency of digital advertising by creating a new unit of exchange between publishers, advertisers, and users. BAT allows users to have greater agency over the ads they see online: users can block ads, pay to see different ads, or view ads and earn BAT tokens in exchange.<ref name="batbene">[https://themerkle.com/what-is-basic-attention-token/] Retrieved on 11 March 2021. </ref> Advertisers also benefit from this model by achieving higher returns on advertising investment. This is delivered through better ad targeting (based on local user data) and reduced fraud. <br><br />
===Brave Rewards=== <br />
Brave Rewards has a two-pronged benefit: it allows users to support their favorite content creators, and it allows users to earn money. For the former, Brave allows users to send their favorite content creators (YouTubers, Twitter users, blog owners, etc.) BAT, which can be converted to cash. This practice is known as [https://brave.com/tips/#:~:text=When%20you%20visit%20Twitter%20in,Brave%20Rewards%20account%20within%20minutes. tipping]. Users can choose to either set up recurring payments or make a one-time payment. For the latter benefit, users can choose to earn money by opting in to view ads. Rather than traditional banner ads, Brave displays its ads as a push notification that users can choose to interact with. The aim of this ad format is to create a more engaging ad experience that benefits all parties involved.<br />
<br />
Currently, Brave has over 735,000 registered content creators with many notable names such as Philip DeFranco, The Washington Post, wikiHow, XXL, Vice, and The Guardian to name a few.<ref name="creators"> ''Brave'' (2019). [https://creators.brave.com/ "Earn more for content you publish to the web - Brave Creators"] Retrieved on 8 April 2021. </ref> In the current e-commerce system, digital content creators receive an estimated half of their revenue due to ad-blocking users and many digital ad platforms are monopolized by Google, Facebook, and Amazon.<ref name="mediapost"> Williams, R. (2019, August 23). [https://www.mediapost.com/publications/article/339624/google-publishers-lose-half-of-ad-revenue-from-co.html "Google: Publishers Lose Half Of Ad Revenue From Cookie Blocking"] ''Publishing Insider'' Retrieved on 8 April 2021. </ref> Thus, Brave Rewards is highly appealing to content creators as it attempts to equalize systemically disproportionate streams of revenue.<br />
<br />
===IPFS Integration===<br />
IPFS is the protocol that Brave uses instead of HTTP, which is what most browsers use. IPFS is known as a peer-to-peer protocol. This is because it uses distributed nodes near the user to send data. This can result in faster web browsing in certain areas. In contrast, HTTP has a centralized server that transmits data to users. This can be slow in some areas if the distance from the user to the server is far.<br />
<br />
Another benefit to IPFS is that content restricted in some parts of the world, such as Turkey, Thailand, and China, are now available to them because of IPFS.<ref>Bonifacic, I. (2021, January 19). [https://www.engadget.com/brave-ipfs-update-190545662.html "Brave browser now supports peer-to-peer IPFS protocol"] Retrieved on 7 April 2021. </ref><br />
<br />
===Other Features===<br />
* [https://en.wikipedia.org/wiki/Tor_(anonymity_network) Tor] integration for anonymous browsing by concealing user location and usage information<br />
* Auto-suggesting search terms and searching from the address bar<br />
* Option to use DuckDuckGo for private window search<br />
* Built-in password manager<br />
* [https://en.wikipedia.org/wiki/Fingerprint_(computing) Fingerprinting] prevention, cookie control, and HTTPS upgrading<br />
* Support for most Chrome extensions<br />
===Planned Features===<br />
According to Brave’s BAT roadmap of 2021, Brave developers are aiming to increase crypto and decentralized finance (DeFi) accessibility by creating their own cryptocurrency wallet using Ethereum, an open-source [[blockchain]] technology.<ref name="roadmap"> ''Brave'' (2021, February 22). [https://brave.com/bat-roadmap-2-0/ "BAT Roadmap 2.0"] Retrieved on 8 April 2021. </ref> The Brave Wallet will replace existing crypto wallets and have redesigned UI/UX as well as mobile support. A JavaScript Ethereum Provider API, used to connect web apps with Ethereum blockchain, will now be supplied to web pages by default and more options for buying crypto with fiat payment methods, currencies without intrinsic or use value, will be unlocked. Brave is also looking to support integrated NFT redemption usage(source) within its browser and enable payment of transaction fees through BAT. To further spread DeFi, Brave is creating a new decentralized exchange aggregator with monetary incentives for Brave/Bat users. Aside from future optimizations in accountability and anonymity, to achieve their final endgame of building a Decentralized Web, Brave is researching BAT use in search engines, e-commerce, VPN, IPNS-verified content, and IPFS content pinning. According to public IPFS documentation, IPFS refers to “a distributed system for storing and accessing files, websites, applications, and data.”<ref name="ipfs"> Schilling, J. (2019, December 3). [https://docs.ipfs.io/concepts/what-is-ipfs/ "What is IPFS? | IPFS Docs"] ''IPFS Docs'' Retrieved on 8 April 2021. </ref> IFPS uses content-based addressing while IPNS solves the issue of creating updatable addresses when content is updated. By tying BAT with multiple Decentralized Web systems, Brave is associating their browser and its reward system with other public efforts towards decentralization.<br />
<br />
==Ethical Considerations==<br />
[[File:bizmodel.png|thumb|left|Brave's advertising model]]<br />
===Data Privacy=== <br />
Data privacy while browsing online is a point of contention regarding Internet privacy in the modern-day. Brave offers a robust feature list on metrics related to online privacy and data ethics. By keeping all data local and privatized, Brave does not monetize user data the way many browsers do. Instead, its primary revenue driver is its usage of BAT.<ref name="mainrevenue">https://gizmodo.com/brave-wants-to-destroy-the-ad-business-by-paying-you-to-1834283860] Retrieved on 11 March 2021. </ref> This business model allows them to monetize browsing while still returning 70% of revenue to Brave users themselves.<ref name="returntousers">https://social.techcrunch.com/2019/04/24/brave-ads/] Retrieved on 11 March 2021. </ref> This allows for incentive alignment with users who are focused on privacy and Brave's monetization strategy and business model.<br />
===Online Advertising Ecosystem===<br />
The main concern with Brave's lack of individualized user collection is whether or not users would see relevant ads if they chose to opt-in to see ads in order to earn BAT. Although Brave does not collect individualized user data, it still practices machine learning on aggregated and anonymized data to ensure that ads users see are relevant for them.<ref name="ads">https://brave.com/intro-to-brave-ads/] Retrieved on 11 March 2021. </ref> By approaching advertising this way, Brave addresses common ethical concerns of monetization user behavior data, while still employing machine learning as an effective tool to display relevant ads. By choosing to implement ads in-app instead of using a third-party ad service, Brave Browser also eliminates the 3rd party ad broker and allows for revenue to be returned to the users. <br />
<br />
<br clear=all><br />
===User Expectations of Privacy===<br />
[[File:Brave-private-tab-tor.png|thumb|right|Brave's new tab disclosure]]<br />
Users frequently have misconceptions about online privacy and how private browser modes work.<ref>Wu, Y., Gupta, P., Wei, M., Acar, Y., Fahl, S., & Ur, B. (2018, April). Your secrets are safe: How browsers' explanations impact misconceptions about private browsing mode. In Proceedings of the 2018 World Wide Web Conference (pp. 217-226).<br />
</ref> These include overestimating the function of private browser modes, such as assuming protection against ISP tracking of browsing history. A study has suggested this causes a negative impact on user privacy when using the Brave Browser, as users may engage differently when they expect a certain degree of anonymity.<ref>Fehlhaber, A. L., Acar, Y., Fahl, S., Gutfleisch, M., Theis, D., & Wallkötter, F. Poster: When Brave Hurts Privacy: Why Too Many Choices do More Harm Than Good.</ref> This study also suggested that the new tab disclosure, which attempts to explain the difference between Brave’s two modes, is not effective at educating users on the impact on browsing privacy.<br />
<br />
===Failure of Privacy Promise===<br />
When Brave Browser was released, privacy was their main policy. By design, Brave Browser would inherently provide better privacy than other browsers. Brave addressed a big issue, surveillance capitalism, by “blocking trackers, invasive ads, and device fingerprinting.”<ref>Krill P. (19 November 2019) [https://bi-gale-com.proxy.lib.umich.edu/global/article/GALE%7CA606140924?u=umuser&sid=summon "'Privacy first' Brave browser exits beta."] Retrieved 7 April 2021.</ref> However, there have been some moments where Brave has failed to uphold their promises on privacy. There are multiple instances of the Brave Browser not delivering on its claim to provide privacy protection. One claim that has been found to be misleading is that all traces of browsing history are cleared on closure.<ref>Mahlous, A. R., & Mahlous, H. Private Browsing Forensic Analysis: A Case Study of Privacy Preservation in the Brave Browser.</ref> Fragments of browser data and activities are still accessible on RAM after closing the browser, though they are lost on computer shutdown. Another instance of compromised privacy was seen when a leak, originally seen in a patch introduced on October 14, 2020, was released in a stable build on November 20, 2020.<ref>Powers, B. (2021, February 23). Brave browser leak exposed user domain info for months. Retrieved March 18, 2021, from [https://www.coindesk.com/brave-browser-leak-exposed-user-domain-info-months]<br />
</ref> This leak revealed DNS information and server logs that could be traceable through high-level network access, such as law enforcement, posing a potential safety concern for users in regions with browsing restrictions. The leak was fixed on February 4, 2021 after being present in the stable build for 91 days. In another study, the Brave Browser was found to be vulnerable to the same attacks as Chrome, as it is built off of Chromium, which can reveal some browsing history information through CSS and Javascript weaknesses.<ref>Smith, M., Disselkoen, C., Narayan, S., Brown, F., & Stefan, D. (2018). Browser history re: visited. In 12th {USENIX} Workshop on Offensive Technologies ({WOOT} 18).</ref><br />
<br clear=all><br />
<br />
Another time that Brave Browser did not uphold their promises on privacy was their addition to auto-completing links to redirect users to affiliate links, “presumably for profit.” One user reported that when typing in “binance.us” to Brave Browser, it was auto-completed with "binance.us/en?ref=35089877." While the auto-completing of this link actually sent users to the right place, this incident rubbed users the wrong way. Because Brave Browser gives users the option to keep or remove ads, users were not pleased that Brave Browser was auto-completing links without notifying users that they were doing so.<ref>Engadget HD. (8, June 2020). [https://go-gale-com.proxy.lib.umich.edu/ps/i.do?p=STND&u=umuser&id=GALE%7CA655333954&v=2.1&it=r&sid=summon "Brave privacy browser 'mistake' added affiliate links to crypto URLs."] Retrieved 7 April 2021.</ref><br />
<br />
A third incident that Brave Browser had was because of their Tor browsing mode. Tor’s main objective is to conceal a user’s location when browsing online. Brave Browser had a bug that caused the website being visited to send a DNS query to your local device, which makes it possible for others to find your location. This bug was able to be verified by using an application, Wireshark, to analyze DNS traffic.<ref>Abrams L. (19, February, 2021) [https://www.bleepingcomputer.com/news/security/brave-privacy-bug-exposes-tor-onion-urls-to-your-dns-provider/ "Brave privacy bug exposes Tor onion URLs to your DNS provider"] Retrieved 7 April 2021</ref><br />
<br />
<br />
<br />
<br />
==References==<br />
<div style="clear: both; margin: 1em 0 0 0; padding: 5px; border: 1px solid #AAA; background: #F0F8FF"><br />
<references /><br />
</div></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brave_Browser&diff=100928Brave Browser2021-04-08T16:47:30Z<p>Ptse: </p>
<hr />
<div>{{SoftwareInfoBox<br />
|HEIGHT=720<br />
|NAME=Brave Browser<br />
|LOGO=Brave-logo.png<br />
|SCREENIMAGE=braveex.png<br />
|CAPTION=''"Brave Browser"''<br />
|IMAGEURL=https://brave.com/download/<br />
|TEXT=download link<br />
|PLATFORM=Windows<br>macOS<br>Linux<br>Android<br>iOS<br />
|PRODUCT=Brave Browser<br>BAT<br />
|TYPE=Web Browser<br />
|SITEURL=http://brave.com<br />
|URLTEXT=www.brave.com<br />
|STATUS=Active<br />
|LAUNCH=2015<br />
}}<br />
<br />
<br><br />
'''Brave Browser''' is an open-source browser application focused on prioritizing user privacy and democratizing online advertising. It has been developed using the [https://en.wikipedia.org/wiki/Chromium_(web_browser) Chromium web browser] as a foundation, like [https://en.wikipedia.org/wiki/Microsoft_Edge Microsoft Edge] and [https://en.wikipedia.org/wiki/Opera_(web_browser) Opera]. Brave is specifically focused on the user privacy niche and blocks all ads and trackers by default.<br />
Brave Software was co-founded in May 2015 by CEO Brendan Eich (creator of [https://en.wikipedia.org/wiki/JavaScript JavaScript] and former CEO of [https://en.wikipedia.org/wiki/Mozilla_Corporation Mozilla Corporation]) and CTO Brian Bondy.<ref name="founding"> Brian Bondy. [https://web.archive.org/web/20191119215054/https://brave.com/the-road-to-brave-one-dot-zero/] Retrieved on 11 March 2021. </ref><br />
Brave is headquartered in San Francisco, CA. As of February 2021, Brave Browser had over 25 million monthly active users. <ref name="MUA">Brave Browser. [https://brave.com/25m-mau/#:~:text=Brave%20Passes%2025%20Million%20Monthly%20Active%20Users "Brave Blog"] Retrieved on 11 March 2021.</ref><br />
<br />
__TOC__<br />
==Key Features==<br />
===Ad and Tracker Blocking=== <br />
Brave Browser blocks all ads and third-party trackers by default. On any given tab, the browser has an option to enable and disable a display showing how many items have been blocked or modified on that particular page, such as cross-site trackers, connections upgraded to HTTPS, and scripts blocked.<ref name="features"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> The Brave Browser does not serve individual user browsing data on its servers, unlike most other browsers; instead, all user data is aggregated before being returned to Brave's servers. The ads and trackers that are blocked by default can also be customized by the user at any time. <ref name="privacy"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> However, user browsing data is still saved on users' local devices in order to ensure that ads that they may opt-in to see are still relevant. Brave also advertises that the fact that all ads are blocked, enabling faster browsing times for the user.<br />
<br />
===Basic Attention Token (BAT)=== <br />
[[File:Batlogo.png|thumbnail|80px|thumb|left|BAT logo]]<br />
The Basic Attention Token (BAT) is an Ethereum based token that can be traded on a wallet embedded in the browser itself. BAT is the unit of exchange used for browser features such as Brave Rewards. BAT had its [https://en.wikipedia.org/wiki/Initial_coin_offering initial coin offering] (ICO) on May 31st, 2017.<ref name="ico"> [https://www.bitdegree.org/crypto/basic-attention-token#:~:text=The%20BAT%20ICO%20(Initial%20Coin,was%20the%20ERC%2D20%20token.&text=The%20complete%20amount%20of%20the,1%2C5%20billion%20BAT%20tokens.] Retrieved on 11 March 2021. </ref> In under 30 seconds, 1,000,000,000 BAT were sold for a total of 156,250 Ethereum.<ref name="icos">[https://techcrunch.com/2017/06/01/brave-ico-35-million-30-seconds-brendan-eich/] Retrieved on 11 March 2021. </ref> BAT improves the efficiency of digital advertising by creating a new unit of exchange between publishers, advertisers, and users. BAT allows users to have greater agency over the ads they see online: users can block ads, pay to see different ads, or view ads and earn BAT tokens in exchange.<ref name="batbene">[https://themerkle.com/what-is-basic-attention-token/] Retrieved on 11 March 2021. </ref> Advertisers also benefit from this model by achieving higher returns on advertising investment. This is delivered through better ad targeting (based on local user data) and reduced fraud. <br><br />
===Brave Rewards=== <br />
Brave Rewards has a two-pronged benefit: it allows users to support their favorite content creators, and it allows users to earn money. For the former, Brave allows users to send their favorite content creators (YouTubers, Twitter users, blog owners, etc.) BAT, which can be converted to cash. This practice is known as [https://brave.com/tips/#:~:text=When%20you%20visit%20Twitter%20in,Brave%20Rewards%20account%20within%20minutes. tipping]. Users can choose to either set up recurring payments or make a one-time payment. For the latter benefit, users can choose to earn money by opting in to view ads. Rather than traditional banner ads, Brave displays its ads as a push notification that users can choose to interact with. The aim of this ad format is to create a more engaging ad experience that benefits all parties involved.<br />
<br />
Currently, Brave has over 735,000 registered content creators with many notable names such as Philip DeFranco, The Washington Post, wikiHow, XXL, Vice, and The Guardian to name a few.<ref name="creators"> ''Brave'' (2019). [https://creators.brave.com/ "Earn more for content you publish to the web - Brave Creators"] Retrieved on 8 April 2021. </ref> In the current e-commerce system, digital content creators receive an estimated half of their revenue due to ad-blocking users and many digital ad platforms are monopolized by Google, Facebook, and Amazon.<ref name="mediapost"> Williams, R. (2019, August 23). [https://www.mediapost.com/publications/article/339624/google-publishers-lose-half-of-ad-revenue-from-co.html "Google: Publishers Lose Half Of Ad Revenue From Cookie Blocking"] ''Publishing Insider'' Retrieved on 8 April 2021. </ref> Thus, Brave Rewards is highly appealing to content creators as it attempts to equalize systemically disproportionate streams of revenue.<br />
<br />
===IPFS Integration===<br />
IPFS is the protocol that Brave uses instead of HTTP, which is what most browsers use. IPFS is known as a peer-to-peer protocol. This is because it uses distributed nodes near the user to send data. This can result in faster web browsing in certain areas. In contrast, HTTP has a centralized server that transmits data to users. This can be slow in some areas if the distance from the user to the server is far.<br />
<br />
Another benefit to IPFS is that content restricted in some parts of the world, such as Turkey, Thailand, and China, are now available to them because of IPFS.<ref>Bonifacic, I. (2021, January 19). [https://www.engadget.com/brave-ipfs-update-190545662.html "Brave browser now supports peer-to-peer IPFS protocol"] Retrieved on 7 April 2021. </ref><br />
<br />
===Other Features===<br />
* [https://en.wikipedia.org/wiki/Tor_(anonymity_network) Tor] integration for anonymous browsing by concealing user location and usage information<br />
* Auto-suggesting search terms and searching from the address bar<br />
* Option to use DuckDuckGo for private window search<br />
* Built-in password manager<br />
* [https://en.wikipedia.org/wiki/Fingerprint_(computing) Fingerprinting] prevention, cookie control, and HTTPS upgrading<br />
* Support for most Chrome extensions<br />
===Planned Features===<br />
According to Brave’s BAT roadmap of 2021, Brave developers are aiming to increase crypto and decentralized finance (DeFi) accessibility by creating their own cryptocurrency wallet using Ethereum, an open-source [[blockchain]] technology.<ref name="roadmap"> ''Brave'' (2021, February 22). [https://brave.com/bat-roadmap-2-0/ "BAT Roadmap 2.0"] Retrieved on 8 April 2021. </ref> The Brave Wallet will replace existing crypto wallets and have redesigned UI/UX as well as mobile support. A JavaScript Ethereum Provider API, used to connect web apps with Ethereum blockchain, will now be supplied to web pages by default and more options for buying crypto with fiat payment methods, currencies without intrinsic or use value, will be unlocked. Brave is also looking to support integrated NFT redemption usage(source) within its browser and enable payment of transaction fees through BAT. To further spread DeFi, Brave is creating a new decentralized exchange aggregator with monetary incentives for Brave/Bat users. Aside from future optimizations in accountability and anonymity, to achieve their final endgame of building a Decentralized Web, Brave is researching BAT use in search engines, e-commerce, VPN, IPNS-verified content, and IPFS content pinning. According to public IPFS documentation, IPFS refers to “a distributed system for storing and accessing files, websites, applications, and data.”<ref name="ipfs"> Schilling, J. (2019, December 3). [https://docs.ipfs.io/concepts/what-is-ipfs/ "What is IPFS? | IPFS Docs"] ''IPFS Docs'' Retrieved on 8 April 2021. </ref> IFPS uses content-based addressing while IPNS solves the issue of creating updatable addresses when content is updated. By tying BAT with multiple Decentralized Web systems, Brave is associating their browser and its reward system with other public efforts towards decentralization.<br />
<br />
==Ethical Considerations==<br />
[[File:bizmodel.png|thumb|left|Brave's advertising model]]<br />
===Data Privacy=== <br />
Data privacy while browsing online is a point of contention regarding Internet privacy in the modern-day. Brave offers a robust feature list on metrics related to online privacy and data ethics. By keeping all data local and privatized, Brave does not monetize user data the way many browsers do. Instead, its primary revenue driver is its usage of BAT.<ref name="mainrevenue">https://gizmodo.com/brave-wants-to-destroy-the-ad-business-by-paying-you-to-1834283860] Retrieved on 11 March 2021. </ref> This business model allows them to monetize browsing while still returning 70% of revenue to Brave users themselves.<ref name="returntousers">https://social.techcrunch.com/2019/04/24/brave-ads/] Retrieved on 11 March 2021. </ref> This allows for incentive alignment with users who are focused on privacy and Brave's monetization strategy and business model.<br />
===Online Advertising Ecosystem===<br />
The main concern with Brave's lack of individualized user collection is whether or not users would see relevant ads if they chose to opt-in to see ads in order to earn BAT. Although Brave does not collect individualized user data, it still practices machine learning on aggregated and anonymized data to ensure that ads users see are relevant for them.<ref name="ads">https://brave.com/intro-to-brave-ads/] Retrieved on 11 March 2021. </ref> By approaching advertising this way, Brave addresses common ethical concerns of monetization user behavior data, while still employing machine learning as an effective tool to display relevant ads. By choosing to implement ads in-app instead of using a third-party ad service, Brave Browser also eliminates the 3rd party ad broker and allows for revenue to be returned to the users. <br />
<br />
<br clear=all><br />
===User Expectations of Privacy===<br />
[[File:Brave-private-tab-tor.png|thumb|right|Brave's new tab disclosure]]<br />
Users frequently have misconceptions about online privacy and how private browser modes work.<ref>Wu, Y., Gupta, P., Wei, M., Acar, Y., Fahl, S., & Ur, B. (2018, April). Your secrets are safe: How browsers' explanations impact misconceptions about private browsing mode. In Proceedings of the 2018 World Wide Web Conference (pp. 217-226).<br />
</ref> These include overestimating the function of private browser modes, such as assuming protection against ISP tracking of browsing history. A study has suggested this causes a negative impact on user privacy when using the Brave Browser, as users may engage differently when they expect a certain degree of anonymity.<ref>Fehlhaber, A. L., Acar, Y., Fahl, S., Gutfleisch, M., Theis, D., & Wallkötter, F. Poster: When Brave Hurts Privacy: Why Too Many Choices do More Harm Than Good.</ref> This study also suggested that the new tab disclosure, which attempts to explain the difference between Brave’s two modes, is not effective at educating users on the impact on browsing privacy.<br />
<br />
===Failure of Privacy Promise===<br />
When Brave Browser was released, privacy was their main policy. By design, Brave Browser would inherently provide better privacy than other browsers. Brave addressed a big issue, surveillance capitalism, by “blocking trackers, invasive ads, and device fingerprinting.”<ref>Krill P. (19 November 2019) [https://bi-gale-com.proxy.lib.umich.edu/global/article/GALE%7CA606140924?u=umuser&sid=summon "'Privacy first' Brave browser exits beta."] Retrieved 7 April 2021.</ref> However, there have been some moments where Brave has failed to uphold their promises on privacy. There are multiple instances of the Brave Browser not delivering on its claim to provide privacy protection. One claim that has been found to be misleading is that all traces of browsing history are cleared on closure.<ref>Mahlous, A. R., & Mahlous, H. Private Browsing Forensic Analysis: A Case Study of Privacy Preservation in the Brave Browser.</ref> Fragments of browser data and activities are still accessible on RAM after closing the browser, though they are lost on computer shutdown. Another instance of compromised privacy was seen when a leak, originally seen in a patch introduced on October 14, 2020, was released in a stable build on November 20, 2020.<ref>Powers, B. (2021, February 23). Brave browser leak exposed user domain info for months. Retrieved March 18, 2021, from [https://www.coindesk.com/brave-browser-leak-exposed-user-domain-info-months]<br />
</ref> This leak revealed DNS information and server logs that could be traceable through high-level network access, such as law enforcement, posing a potential safety concern for users in regions with browsing restrictions. The leak was fixed on February 4, 2021 after being present in the stable build for 91 days. In another study, the Brave Browser was found to be vulnerable to the same attacks as Chrome, as it is built off of Chromium, which can reveal some browsing history information through CSS and Javascript weaknesses.<ref>Smith, M., Disselkoen, C., Narayan, S., Brown, F., & Stefan, D. (2018). Browser history re: visited. In 12th {USENIX} Workshop on Offensive Technologies ({WOOT} 18).</ref><br />
<br clear=all><br />
<br />
Another time that Brave Browser did not uphold their promises on privacy was their addition to auto-completing links to redirect users to affiliate links, “presumably for profit.” One user reported that when typing in “binance.us” to Brave Browser, it was auto-completed with "binance.us/en?ref=35089877." While the auto-completing of this link actually sent users to the right place, this incident rubbed users the wrong way. Because Brave Browser gives users the option to keep or remove ads, users were not pleased that Brave Browser was auto-completing links without notifying users that they were doing so.<ref>Engadget HD. (8, June 2020). [] Retrieved 7 April 2021. [https://go-gale-com.proxy.lib.umich.edu/ps/i.do?p=STND&u=umuser&id=GALE%7CA655333954&v=2.1&it=r&sid=summon "Brave privacy browser 'mistake' added affiliate links to crypto URLs."]</ref><br />
<br />
A third incident that Brave Browser had was because of their Tor browsing mode. Tor’s main objective is to conceal a user’s location when browsing online. Brave Browser had a bug that caused the website being visited to send a DNS query to your local device, which makes it possible for others to find your location. This bug was able to be verified by using an application, Wireshark, to analyze DNS traffic.<ref>Abrams L. (19, February, 2021) [https://www.bleepingcomputer.com/news/security/brave-privacy-bug-exposes-tor-onion-urls-to-your-dns-provider/ "Brave privacy bug exposes Tor onion URLs to your DNS provider"] Retrieved 7 April 2021</ref><br />
<br />
<br />
<br />
<br />
==References==<br />
<div style="clear: both; margin: 1em 0 0 0; padding: 5px; border: 1px solid #AAA; background: #F0F8FF"><br />
<references /><br />
</div></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brave_Browser&diff=100925Brave Browser2021-04-08T16:41:33Z<p>Ptse: </p>
<hr />
<div>{{SoftwareInfoBox<br />
|HEIGHT=720<br />
|NAME=Brave Browser<br />
|LOGO=Brave-logo.png<br />
|SCREENIMAGE=braveex.png<br />
|CAPTION=''"Brave Browser"''<br />
|IMAGEURL=https://brave.com/download/<br />
|TEXT=download link<br />
|PLATFORM=Windows<br>macOS<br>Linux<br>Android<br>iOS<br />
|PRODUCT=Brave Browser<br>BAT<br />
|TYPE=Web Browser<br />
|SITEURL=http://brave.com<br />
|URLTEXT=www.brave.com<br />
|STATUS=Active<br />
|LAUNCH=2015<br />
}}<br />
<br />
<br><br />
'''Brave Browser''' is an open-source browser application focused on prioritizing user privacy and democratizing online advertising. It has been developed using the [https://en.wikipedia.org/wiki/Chromium_(web_browser) Chromium web browser] as a foundation, like [https://en.wikipedia.org/wiki/Microsoft_Edge Microsoft Edge] and [https://en.wikipedia.org/wiki/Opera_(web_browser) Opera]. Brave is specifically focused on the user privacy niche and blocks all ads and trackers by default.<br />
Brave Software was co-founded in May 2015 by CEO Brendan Eich (creator of [https://en.wikipedia.org/wiki/JavaScript JavaScript] and former CEO of [https://en.wikipedia.org/wiki/Mozilla_Corporation Mozilla Corporation]) and CTO Brian Bondy.<ref name="founding"> Brian Bondy. [https://web.archive.org/web/20191119215054/https://brave.com/the-road-to-brave-one-dot-zero/] Retrieved on 11 March 2021. </ref><br />
Brave is headquartered in San Francisco, CA. As of February 2021, Brave Browser had over 25 million monthly active users. <ref name="MUA">Brave Browser. [https://brave.com/25m-mau/#:~:text=Brave%20Passes%2025%20Million%20Monthly%20Active%20Users "Brave Blog"] Retrieved on 11 March 2021.</ref><br />
<br />
__TOC__<br />
==Key Features==<br />
===Ad and Tracker Blocking=== <br />
Brave Browser blocks all ads and third-party trackers by default. On any given tab, the browser has an option to enable and disable a display showing how many items have been blocked or modified on that particular page, such as cross-site trackers, connections upgraded to HTTPS, and scripts blocked.<ref name="features"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> The Brave Browser does not serve individual user browsing data on its servers, unlike most other browsers; instead, all user data is aggregated before being returned to Brave's servers. The ads and trackers that are blocked by default can also be customized by the user at any time. <ref name="privacy"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> However, user browsing data is still saved on users' local devices in order to ensure that ads that they may opt-in to see are still relevant. Brave also advertises that the fact that all ads are blocked, enabling faster browsing times for the user.<br />
<br />
===Basic Attention Token (BAT)=== <br />
[[File:Batlogo.png|thumbnail|80px|thumb|left|BAT logo]]<br />
The Basic Attention Token (BAT) is an Ethereum based token that can be traded on a wallet embedded in the browser itself. BAT is the unit of exchange used for browser features such as Brave Rewards. BAT had its [https://en.wikipedia.org/wiki/Initial_coin_offering initial coin offering] (ICO) on May 31st, 2017.<ref name="ico"> [https://www.bitdegree.org/crypto/basic-attention-token#:~:text=The%20BAT%20ICO%20(Initial%20Coin,was%20the%20ERC%2D20%20token.&text=The%20complete%20amount%20of%20the,1%2C5%20billion%20BAT%20tokens.] Retrieved on 11 March 2021. </ref> In under 30 seconds, 1,000,000,000 BAT were sold for a total of 156,250 Ethereum.<ref name="icos">[https://techcrunch.com/2017/06/01/brave-ico-35-million-30-seconds-brendan-eich/] Retrieved on 11 March 2021. </ref> BAT improves the efficiency of digital advertising by creating a new unit of exchange between publishers, advertisers, and users. BAT allows users to have greater agency over the ads they see online: users can block ads, pay to see different ads, or view ads and earn BAT tokens in exchange.<ref name="batbene">[https://themerkle.com/what-is-basic-attention-token/] Retrieved on 11 March 2021. </ref> Advertisers also benefit from this model by achieving higher returns on advertising investment. This is delivered through better ad targeting (based on local user data) and reduced fraud. <br><br />
===Brave Rewards=== <br />
Brave Rewards has a two-pronged benefit: it allows users to support their favorite content creators, and it allows users to earn money. For the former, Brave allows users to send their favorite content creators (YouTubers, Twitter users, blog owners, etc.) BAT, which can be converted to cash. This practice is known as [https://brave.com/tips/#:~:text=When%20you%20visit%20Twitter%20in,Brave%20Rewards%20account%20within%20minutes. tipping]. Users can choose to either set up recurring payments or make a one-time payment. For the latter benefit, users can choose to earn money by opting in to view ads. Rather than traditional banner ads, Brave displays its ads as a push notification that users can choose to interact with. The aim of this ad format is to create a more engaging ad experience that benefits all parties involved.<br />
<br />
Currently, Brave has over 735,000 registered content creators with many notable names such as Philip DeFranco, The Washington Post, wikiHow, XXL, Vice, and The Guardian to name a few.<ref name="creators"> ''Brave'' (2019). [https://creators.brave.com/ "Earn more for content you publish to the web - Brave Creators"] Retrieved on 8 April 2021. </ref> In the current e-commerce system, digital content creators receive an estimated half of their revenue due to ad-blocking users and many digital ad platforms are monopolized by Google, Facebook, and Amazon.<ref name="mediapost"> Williams, R. (2019, August 23). [https://www.mediapost.com/publications/article/339624/google-publishers-lose-half-of-ad-revenue-from-co.html "Google: Publishers Lose Half Of Ad Revenue From Cookie Blocking"] ''Publishing Insider'' Retrieved on 8 April 2021. </ref> Thus, Brave Rewards is highly appealing to content creators as it attempts to equalize systemically disproportionate streams of revenue.<br />
<br />
===IPFS Integration===<br />
IPFS is the protocol that Brave uses instead of HTTP, which is what most browsers use. IPFS is known as a peer-to-peer protocol. This is because it uses distributed nodes near the user to send data. This can result in faster web browsing in certain areas. In contrast, HTTP has a centralized server that transmits data to users. This can be slow in some areas if the distance from the user to the server is far.<br />
<br />
Another benefit to IPFS is that content restricted in some parts of the world, such as Turkey, Thailand, and China, are now available to them because of IPFS.<ref>Bonifacic, I. (2021, January 19). [https://www.engadget.com/brave-ipfs-update-190545662.html "Brave browser now supports peer-to-peer IPFS protocol"] Retrieved on 7 April 2021. </ref><br />
<br />
===Other Features===<br />
* [https://en.wikipedia.org/wiki/Tor_(anonymity_network) Tor] integration for anonymous browsing by concealing user location and usage information<br />
* Auto-suggesting search terms and searching from the address bar<br />
* Option to use DuckDuckGo for private window search<br />
* Built-in password manager<br />
* [https://en.wikipedia.org/wiki/Fingerprint_(computing) Fingerprinting] prevention, cookie control, and HTTPS upgrading<br />
* Support for most Chrome extensions<br />
===Planned Features===<br />
According to Brave’s BAT roadmap of 2021, Brave developers are aiming to increase crypto and decentralized finance (DeFi) accessibility by creating their own cryptocurrency wallet using Ethereum, an open-source [[blockchain]] technology.<ref name="roadmap"> ''Brave'' (2021, February 22). [https://brave.com/bat-roadmap-2-0/ "BAT Roadmap 2.0"] Retrieved on 8 April 2021. </ref> The Brave Wallet will replace existing crypto wallets and have redesigned UI/UX as well as mobile support. A JavaScript Ethereum Provider API, used to connect web apps with Ethereum blockchain, will now be supplied to web pages by default and more options for buying crypto with fiat payment methods, currencies without intrinsic or use value, will be unlocked. Brave is also looking to support integrated NFT redemption usage(source) within its browser and enable payment of transaction fees through BAT. To further spread DeFi, Brave is creating a new decentralized exchange aggregator with monetary incentives for Brave/Bat users. Aside from future optimizations in accountability and anonymity, to achieve their final endgame of building a Decentralized Web, Brave is researching BAT use in search engines, e-commerce, VPN, IPNS-verified content, and IPFS content pinning. According to public IPFS documentation, IPFS refers to “a distributed system for storing and accessing files, websites, applications, and data.”<ref name="ipfs"> Schilling, J. (2019, December 3). [https://docs.ipfs.io/concepts/what-is-ipfs/ "What is IPFS? | IPFS Docs"] ''IPFS Docs'' Retrieved on 8 April 2021. </ref> IFPS uses content-based addressing while IPNS solves the issue of creating updatable addresses when content is updated. By tying BAT with multiple Decentralized Web systems, Brave is associating their browser and its reward system with other public efforts towards decentralization.<br />
<br />
==Ethical Considerations==<br />
[[File:bizmodel.png|thumb|left|Brave's advertising model]]<br />
===Data Privacy=== <br />
Data privacy while browsing online is a point of contention regarding Internet privacy in the modern-day. Brave offers a robust feature list on metrics related to online privacy and data ethics. By keeping all data local and privatized, Brave does not monetize user data the way many browsers do. Instead, its primary revenue driver is its usage of BAT.<ref name="mainrevenue">https://gizmodo.com/brave-wants-to-destroy-the-ad-business-by-paying-you-to-1834283860] Retrieved on 11 March 2021. </ref> This business model allows them to monetize browsing while still returning 70% of revenue to Brave users themselves.<ref name="returntousers">https://social.techcrunch.com/2019/04/24/brave-ads/] Retrieved on 11 March 2021. </ref> This allows for incentive alignment with users who are focused on privacy and Brave's monetization strategy and business model.<br />
===Online Advertising Ecosystem===<br />
The main concern with Brave's lack of individualized user collection is whether or not users would see relevant ads if they chose to opt-in to see ads in order to earn BAT. Although Brave does not collect individualized user data, it still practices machine learning on aggregated and anonymized data to ensure that ads users see are relevant for them.<ref name="ads">https://brave.com/intro-to-brave-ads/] Retrieved on 11 March 2021. </ref> By approaching advertising this way, Brave addresses common ethical concerns of monetization user behavior data, while still employing machine learning as an effective tool to display relevant ads. By choosing to implement ads in-app instead of using a third-party ad service, Brave Browser also eliminates the 3rd party ad broker and allows for revenue to be returned to the users. <br />
<br />
<br clear=all><br />
===User Expectations of Privacy===<br />
[[File:Brave-private-tab-tor.png|thumb|right|Brave's new tab disclosure]]<br />
Users frequently have misconceptions about online privacy and how private browser modes work.<ref>Wu, Y., Gupta, P., Wei, M., Acar, Y., Fahl, S., & Ur, B. (2018, April). Your secrets are safe: How browsers' explanations impact misconceptions about private browsing mode. In Proceedings of the 2018 World Wide Web Conference (pp. 217-226).<br />
</ref> These include overestimating the function of private browser modes, such as assuming protection against ISP tracking of browsing history. A study has suggested this causes a negative impact on user privacy when using the Brave Browser, as users may engage differently when they expect a certain degree of anonymity.<ref>Fehlhaber, A. L., Acar, Y., Fahl, S., Gutfleisch, M., Theis, D., & Wallkötter, F. Poster: When Brave Hurts Privacy: Why Too Many Choices do More Harm Than Good.</ref> This study also suggested that the new tab disclosure, which attempts to explain the difference between Brave’s two modes, is not effective at educating users on the impact on browsing privacy.<br />
<br />
===Failure of Privacy Promise===<br />
When Brave Browser was released, privacy was their main policy. By design, Brave Browser would inherently provide better privacy than other browsers. Brave addressed a big issue, surveillance capitalism, by “blocking trackers, invasive ads, and device fingerprinting.”<ref>Krill P. (19 November 2019) [https://bi-gale-com.proxy.lib.umich.edu/global/article/GALE%7CA606140924?u=umuser&sid=summon "'Privacy first' Brave browser exits beta."] Retrieved 7 April 2021.</ref> However, there have been some moments where Brave has failed to uphold their promises on privacy. There are multiple instances of the Brave Browser not delivering on its claim to provide privacy protection. One claim that has been found to be misleading is that all traces of browsing history are cleared on closure.<ref>Mahlous, A. R., & Mahlous, H. Private Browsing Forensic Analysis: A Case Study of Privacy Preservation in the Brave Browser.</ref> Fragments of browser data and activities are still accessible on RAM after closing the browser, though they are lost on computer shutdown. Another instance of compromised privacy was seen when a leak, originally seen in a patch introduced on October 14, 2020, was released in a stable build on November 20, 2020.<ref>Powers, B. (2021, February 23). Brave browser leak exposed user domain info for months. Retrieved March 18, 2021, from [https://www.coindesk.com/brave-browser-leak-exposed-user-domain-info-months]<br />
</ref> This leak revealed DNS information and server logs that could be traceable through high-level network access, such as law enforcement, posing a potential safety concern for users in regions with browsing restrictions. The leak was fixed on February 4, 2021 after being present in the stable build for 91 days. In another study, the Brave Browser was found to be vulnerable to the same attacks as Chrome, as it is built off of Chromium, which can reveal some browsing history information through CSS and Javascript weaknesses.<ref>Smith, M., Disselkoen, C., Narayan, S., Brown, F., & Stefan, D. (2018). Browser history re: visited. In 12th {USENIX} Workshop on Offensive Technologies ({WOOT} 18).</ref><br />
<br clear=all><br />
<br />
Another time that Brave Browser did not uphold their promises on privacy was their addition to auto-completing links to redirect users to affiliate links, “presumably for profit.” One user reported that when typing in “binance.us” to Brave Browser, it was auto-completed with "binance.us/en?ref=35089877." While the auto-completing of this link actually sent users to the right place, this incident rubbed users the wrong way. Because Brave Browser gives users the option to keep or remove ads, users were not pleased that Brave Browser was auto-completing links without notifying users that they were doing so.[3]<br />
<br />
A third incident that Brave Browser had was because of their Tor browsing mode. Tor’s main objective is to conceal a user’s location when browsing online. Brave Browser had a bug that caused the website being visited to send a DNS query to your local device, which makes it possible for others to find your location. This bug was able to be verified by using an application, Wireshark, to analyze DNS traffic.[4]<br />
<br />
<br />
<br />
<br />
==References==<br />
<div style="clear: both; margin: 1em 0 0 0; padding: 5px; border: 1px solid #AAA; background: #F0F8FF"><br />
<references /><br />
</div></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brave_Browser&diff=100921Brave Browser2021-04-08T16:34:26Z<p>Ptse: </p>
<hr />
<div>{{SoftwareInfoBox<br />
|HEIGHT=720<br />
|NAME=Brave Browser<br />
|LOGO=Brave-logo.png<br />
|SCREENIMAGE=braveex.png<br />
|CAPTION=''"Brave Browser"''<br />
|IMAGEURL=https://brave.com/download/<br />
|TEXT=download link<br />
|PLATFORM=Windows<br>macOS<br>Linux<br>Android<br>iOS<br />
|PRODUCT=Brave Browser<br>BAT<br />
|TYPE=Web Browser<br />
|SITEURL=http://brave.com<br />
|URLTEXT=www.brave.com<br />
|STATUS=Active<br />
|LAUNCH=2015<br />
}}<br />
<br />
<br><br />
'''Brave Browser''' is an open-source browser application focused on prioritizing user privacy and democratizing online advertising. It has been developed using the [https://en.wikipedia.org/wiki/Chromium_(web_browser) Chromium web browser] as a foundation, like [https://en.wikipedia.org/wiki/Microsoft_Edge Microsoft Edge] and [https://en.wikipedia.org/wiki/Opera_(web_browser) Opera]. Brave is specifically focused on the user privacy niche and blocks all ads and trackers by default.<br />
Brave Software was co-founded in May 2015 by CEO Brendan Eich (creator of [https://en.wikipedia.org/wiki/JavaScript JavaScript] and former CEO of [https://en.wikipedia.org/wiki/Mozilla_Corporation Mozilla Corporation]) and CTO Brian Bondy.<ref name="founding"> Brian Bondy. [https://web.archive.org/web/20191119215054/https://brave.com/the-road-to-brave-one-dot-zero/] Retrieved on 11 March 2021. </ref><br />
Brave is headquartered in San Francisco, CA. As of February 2021, Brave Browser had over 25 million monthly active users. <ref name="MUA">Brave Browser. [https://brave.com/25m-mau/#:~:text=Brave%20Passes%2025%20Million%20Monthly%20Active%20Users "Brave Blog"] Retrieved on 11 March 2021.</ref><br />
<br />
__TOC__<br />
==Key Features==<br />
===Ad and Tracker Blocking=== <br />
Brave Browser blocks all ads and third-party trackers by default. On any given tab, the browser has an option to enable and disable a display showing how many items have been blocked or modified on that particular page, such as cross-site trackers, connections upgraded to HTTPS, and scripts blocked.<ref name="features"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> The Brave Browser does not serve individual user browsing data on its servers, unlike most other browsers; instead, all user data is aggregated before being returned to Brave's servers. The ads and trackers that are blocked by default can also be customized by the user at any time. <ref name="privacy"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> However, user browsing data is still saved on users' local devices in order to ensure that ads that they may opt-in to see are still relevant. Brave also advertises that the fact that all ads are blocked, enabling faster browsing times for the user.<br />
<br />
===Basic Attention Token (BAT)=== <br />
[[File:Batlogo.png|thumbnail|80px|thumb|left|BAT logo]]<br />
The Basic Attention Token (BAT) is an Ethereum based token that can be traded on a wallet embedded in the browser itself. BAT is the unit of exchange used for browser features such as Brave Rewards. BAT had its [https://en.wikipedia.org/wiki/Initial_coin_offering initial coin offering] (ICO) on May 31st, 2017.<ref name="ico"> [https://www.bitdegree.org/crypto/basic-attention-token#:~:text=The%20BAT%20ICO%20(Initial%20Coin,was%20the%20ERC%2D20%20token.&text=The%20complete%20amount%20of%20the,1%2C5%20billion%20BAT%20tokens.] Retrieved on 11 March 2021. </ref> In under 30 seconds, 1,000,000,000 BAT were sold for a total of 156,250 Ethereum.<ref name="icos">[https://techcrunch.com/2017/06/01/brave-ico-35-million-30-seconds-brendan-eich/] Retrieved on 11 March 2021. </ref> BAT improves the efficiency of digital advertising by creating a new unit of exchange between publishers, advertisers, and users. BAT allows users to have greater agency over the ads they see online: users can block ads, pay to see different ads, or view ads and earn BAT tokens in exchange.<ref name="batbene">[https://themerkle.com/what-is-basic-attention-token/] Retrieved on 11 March 2021. </ref> Advertisers also benefit from this model by achieving higher returns on advertising investment. This is delivered through better ad targeting (based on local user data) and reduced fraud. <br><br />
===Brave Rewards=== <br />
Brave Rewards has a two-pronged benefit: it allows users to support their favorite content creators, and it allows users to earn money. For the former, Brave allows users to send their favorite content creators (YouTubers, Twitter users, blog owners, etc.) BAT, which can be converted to cash. This practice is known as [https://brave.com/tips/#:~:text=When%20you%20visit%20Twitter%20in,Brave%20Rewards%20account%20within%20minutes. tipping]. Users can choose to either set up recurring payments or make a one-time payment. For the latter benefit, users can choose to earn money by opting in to view ads. Rather than traditional banner ads, Brave displays its ads as a push notification that users can choose to interact with. The aim of this ad format is to create a more engaging ad experience that benefits all parties involved.<br />
<br />
Currently, Brave has over 735,000 registered content creators with many notable names such as Philip DeFranco, The Washington Post, wikiHow, XXL, Vice, and The Guardian to name a few.<ref name="creators"> ''Brave'' (2019). [https://creators.brave.com/ "Earn more for content you publish to the web - Brave Creators"] Retrieved on 8 April 2021. </ref> In the current e-commerce system, digital content creators receive an estimated half of their revenue due to ad-blocking users and many digital ad platforms are monopolized by Google, Facebook, and Amazon.<ref name="mediapost"> Williams, R. (2019, August 23). [https://www.mediapost.com/publications/article/339624/google-publishers-lose-half-of-ad-revenue-from-co.html "Google: Publishers Lose Half Of Ad Revenue From Cookie Blocking"] ''Publishing Insider'' Retrieved on 8 April 2021. </ref> Thus, Brave Rewards is highly appealing to content creators as it attempts to equalize systemically disproportionate streams of revenue.<br />
<br />
===IPFS Integration===<br />
IPFS is the protocol that Brave uses instead of HTTP, which is what most browsers use. IPFS is known as a peer-to-peer protocol. This is because it uses distributed nodes near the user to send data. This can result in faster web browsing in certain areas. In contrast, HTTP has a centralized server that transmits data to users. This can be slow in some areas if the distance from the user to the server is far.<br />
<br />
Another benefit to IPFS is that content restricted in some parts of the world, such as Turkey, Thailand, and China, are now available to them because of IPFS.<ref>Bonifacic, I. (2021, January 19). [https://www.engadget.com/brave-ipfs-update-190545662.html] Retrieved on 7 April 2021. </ref><br />
<br />
===Other Features===<br />
* [https://en.wikipedia.org/wiki/Tor_(anonymity_network) Tor] integration for anonymous browsing by concealing user location and usage information<br />
* Auto-suggesting search terms and searching from the address bar<br />
* Option to use DuckDuckGo for private window search<br />
* Built-in password manager<br />
* [https://en.wikipedia.org/wiki/Fingerprint_(computing) Fingerprinting] prevention, cookie control, and HTTPS upgrading<br />
* Support for most Chrome extensions<br />
===Planned Features===<br />
According to Brave’s BAT roadmap of 2021, Brave developers are aiming to increase crypto and decentralized finance (DeFi) accessibility by creating their own cryptocurrency wallet using Ethereum, an open-source [[blockchain]] technology.<ref name="roadmap"> ''Brave'' (2021, February 22). [https://brave.com/bat-roadmap-2-0/ "BAT Roadmap 2.0"] Retrieved on 8 April 2021. </ref> The Brave Wallet will replace existing crypto wallets and have redesigned UI/UX as well as mobile support. A JavaScript Ethereum Provider API, used to connect web apps with Ethereum blockchain, will now be supplied to web pages by default and more options for buying crypto with fiat payment methods, currencies without intrinsic or use value, will be unlocked. Brave is also looking to support integrated NFT redemption usage(source) within its browser and enable payment of transaction fees through BAT. To further spread DeFi, Brave is creating a new decentralized exchange aggregator with monetary incentives for Brave/Bat users. Aside from future optimizations in accountability and anonymity, to achieve their final endgame of building a Decentralized Web, Brave is researching BAT use in search engines, e-commerce, VPN, IPNS-verified content, and IPFS content pinning. According to public IPFS documentation, IPFS refers to “a distributed system for storing and accessing files, websites, applications, and data.”<ref name="ipfs"> Schilling, J. (2019, December 3). [https://docs.ipfs.io/concepts/what-is-ipfs/ "What is IPFS? | IPFS Docs"] ''IPFS Docs'' Retrieved on 8 April 2021. </ref> IFPS uses content-based addressing while IPNS solves the issue of creating updatable addresses when content is updated. By tying BAT with multiple Decentralized Web systems, Brave is associating their browser and its reward system with other public efforts towards decentralization.<br />
<br />
==Ethical Considerations==<br />
[[File:bizmodel.png|thumb|left|Brave's advertising model]]<br />
===Data Privacy=== <br />
Data privacy while browsing online is a point of contention regarding Internet privacy in the modern-day. Brave offers a robust feature list on metrics related to online privacy and data ethics. By keeping all data local and privatized, Brave does not monetize user data the way many browsers do. Instead, its primary revenue driver is its usage of BAT.<ref name="mainrevenue">https://gizmodo.com/brave-wants-to-destroy-the-ad-business-by-paying-you-to-1834283860] Retrieved on 11 March 2021. </ref> This business model allows them to monetize browsing while still returning 70% of revenue to Brave users themselves.<ref name="returntousers">https://social.techcrunch.com/2019/04/24/brave-ads/] Retrieved on 11 March 2021. </ref> This allows for incentive alignment with users who are focused on privacy and Brave's monetization strategy and business model.<br />
===Online Advertising Ecosystem===<br />
The main concern with Brave's lack of individualized user collection is whether or not users would see relevant ads if they chose to opt-in to see ads in order to earn BAT. Although Brave does not collect individualized user data, it still practices machine learning on aggregated and anonymized data to ensure that ads users see are relevant for them.<ref name="ads">https://brave.com/intro-to-brave-ads/] Retrieved on 11 March 2021. </ref> By approaching advertising this way, Brave addresses common ethical concerns of monetization user behavior data, while still employing machine learning as an effective tool to display relevant ads. By choosing to implement ads in-app instead of using a third-party ad service, Brave Browser also eliminates the 3rd party ad broker and allows for revenue to be returned to the users. <br />
<br />
<br clear=all><br />
===User Expectations of Privacy===<br />
[[File:Brave-private-tab-tor.png|thumb|right|Brave's new tab disclosure]]<br />
Users frequently have misconceptions about online privacy and how private browser modes work.<ref>Wu, Y., Gupta, P., Wei, M., Acar, Y., Fahl, S., & Ur, B. (2018, April). Your secrets are safe: How browsers' explanations impact misconceptions about private browsing mode. In Proceedings of the 2018 World Wide Web Conference (pp. 217-226).<br />
</ref> These include overestimating the function of private browser modes, such as assuming protection against ISP tracking of browsing history. A study has suggested this causes a negative impact to user privacy when using the Brave Browser, as users may engage differently when they expect a certain degree of anonymity.<ref>Fehlhaber, A. L., Acar, Y., Fahl, S., Gutfleisch, M., Theis, D., & Wallkötter, F. Poster: When Brave Hurts Privacy: Why Too Many Choices do More Harm Than Good.</ref> This study also suggested that the new tab disclosure, which attempts to explain the difference between Brave’s two modes, is not effective at educating users on the impact to browsing privacy.<br />
<br />
===Failure of Privacy Promise===<br />
When Brave Browser was released, privacy was their main policy. By design, Brave Browser would inherently provide better privacy than other browsers. Brave addressed a big issue, surveillance capitalism, by “blocking trackers, invasive ads, and device fingerprinting.”[2] However, there have been some moments where Brave has failed to uphold their promises on privacy. There are multiple instances of the Brave Browser not delivering on its claim to provide privacy protection. One claim that has been found to be misleading is that all traces of browsing history are cleared on closure.<ref>Mahlous, A. R., & Mahlous, H. Private Browsing Forensic Analysis: A Case Study of Privacy Preservation in the Brave Browser.</ref> Fragments of browser data and activities are still accessible on RAM after closing the browser, though they are lost on computer shutdown. Another instance of compromised privacy was seen when a leak, originally seen in a patch introduced on October 14, 2020, was released in a stable build on November 20, 2020.<ref>Powers, B. (2021, February 23). Brave browser leak exposed user domain info for months. Retrieved March 18, 2021, from [https://www.coindesk.com/brave-browser-leak-exposed-user-domain-info-months]<br />
</ref> This leak revealed DNS information and server logs that could be traceable through high-level network access, such as law enforcement, posing a potential safety concern for users in regions with browsing restrictions. The leak was fixed on February 4, 2021 after being present in the stable build for 91 days. In another study, the Brave Browser was found to be vulnerable to the same attacks as Chrome, as it is built off of Chromium, which can reveal some browsing history information through CSS and Javascript weaknesses.<ref>Smith, M., Disselkoen, C., Narayan, S., Brown, F., & Stefan, D. (2018). Browser history re: visited. In 12th {USENIX} Workshop on Offensive Technologies ({WOOT} 18).</ref><br />
<br clear=all><br />
<br />
<br />
<br />
==References==<br />
<div style="clear: both; margin: 1em 0 0 0; padding: 5px; border: 1px solid #AAA; background: #F0F8FF"><br />
<references /><br />
</div></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brave_Browser&diff=100920Brave Browser2021-04-08T16:29:27Z<p>Ptse: </p>
<hr />
<div>{{SoftwareInfoBox<br />
|HEIGHT=720<br />
|NAME=Brave Browser<br />
|LOGO=Brave-logo.png<br />
|SCREENIMAGE=braveex.png<br />
|CAPTION=''"Brave Browser"''<br />
|IMAGEURL=https://brave.com/download/<br />
|TEXT=download link<br />
|PLATFORM=Windows<br>macOS<br>Linux<br>Android<br>iOS<br />
|PRODUCT=Brave Browser<br>BAT<br />
|TYPE=Web Browser<br />
|SITEURL=http://brave.com<br />
|URLTEXT=www.brave.com<br />
|STATUS=Active<br />
|LAUNCH=2015<br />
}}<br />
<br />
<br><br />
'''Brave Browser''' is an open-source browser application focused on prioritizing user privacy and democratizing online advertising. It has been developed using the [https://en.wikipedia.org/wiki/Chromium_(web_browser) Chromium web browser] as a foundation, like [https://en.wikipedia.org/wiki/Microsoft_Edge Microsoft Edge] and [https://en.wikipedia.org/wiki/Opera_(web_browser) Opera]. Brave is specifically focused on the user privacy niche and blocks all ads and trackers by default.<br />
Brave Software was co-founded in May 2015 by CEO Brendan Eich (creator of [https://en.wikipedia.org/wiki/JavaScript JavaScript] and former CEO of [https://en.wikipedia.org/wiki/Mozilla_Corporation Mozilla Corporation]) and CTO Brian Bondy.<ref name="founding"> Brian Bondy. [https://web.archive.org/web/20191119215054/https://brave.com/the-road-to-brave-one-dot-zero/] Retrieved on 11 March 2021. </ref><br />
Brave is headquartered in San Francisco, CA. As of February 2021, Brave Browser had over 25 million monthly active users. <ref name="MUA">Brave Browser. [https://brave.com/25m-mau/#:~:text=Brave%20Passes%2025%20Million%20Monthly%20Active%20Users "Brave Blog"] Retrieved on 11 March 2021.</ref><br />
<br />
__TOC__<br />
==Key Features==<br />
===Ad and Tracker Blocking=== <br />
Brave Browser blocks all ads and third-party trackers by default. On any given tab, the browser has an option to enable and disable a display showing how many items have been blocked or modified on that particular page, such as cross-site trackers, connections upgraded to HTTPS, and scripts blocked.<ref name="features"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> The Brave Browser does not serve individual user browsing data on its servers, unlike most other browsers; instead, all user data is aggregated before being returned to Brave's servers. The ads and trackers that are blocked by default can also be customized by the user at any time. <ref name="privacy"> Brave website. [https://brave.com/features/] "Blog] Retrieved on 11 March 2021. </ref> However, user browsing data is still saved on users' local devices in order to ensure that ads that they may opt-in to see are still relevant. Brave also advertises that the fact that all ads are blocked, enabling faster browsing times for the user.<br />
<br />
===Basic Attention Token (BAT)=== <br />
[[File:Batlogo.png|thumbnail|80px|thumb|left|BAT logo]]<br />
The Basic Attention Token (BAT) is an Ethereum based token that can be traded on a wallet embedded in the browser itself. BAT is the unit of exchange used for browser features such as Brave Rewards. BAT had its [https://en.wikipedia.org/wiki/Initial_coin_offering initial coin offering] (ICO) on May 31st, 2017.<ref name="ico"> [https://www.bitdegree.org/crypto/basic-attention-token#:~:text=The%20BAT%20ICO%20(Initial%20Coin,was%20the%20ERC%2D20%20token.&text=The%20complete%20amount%20of%20the,1%2C5%20billion%20BAT%20tokens.] Retrieved on 11 March 2021. </ref> In under 30 seconds, 1,000,000,000 BAT were sold for a total of 156,250 Ethereum.<ref name="icos">[https://techcrunch.com/2017/06/01/brave-ico-35-million-30-seconds-brendan-eich/] Retrieved on 11 March 2021. </ref> BAT improves the efficiency of digital advertising by creating a new unit of exchange between publishers, advertisers, and users. BAT allows users to have greater agency over the ads they see online: users can block ads, pay to see different ads, or view ads and earn BAT tokens in exchange.<ref name="batbene">[https://themerkle.com/what-is-basic-attention-token/] Retrieved on 11 March 2021. </ref> Advertisers also benefit from this model by achieving higher returns on advertising investment. This is delivered through better ad targeting (based on local user data) and reduced fraud. <br><br />
===Brave Rewards=== <br />
Brave Rewards has a two-pronged benefit: it allows users to support their favorite content creators, and it allows users to earn money. For the former, Brave allows users to send their favorite content creators (YouTubers, Twitter users, blog owners, etc.) BAT, which can be converted to cash. This practice is known as [https://brave.com/tips/#:~:text=When%20you%20visit%20Twitter%20in,Brave%20Rewards%20account%20within%20minutes. tipping]. Users can choose to either set up recurring payments or make a one-time payment. For the latter benefit, users can choose to earn money by opting in to view ads. Rather than traditional banner ads, Brave displays its ads as a push notification that users can choose to interact with. The aim of this ad format is to create a more engaging ad experience that benefits all parties involved.<br />
<br />
Currently, Brave has over 735,000 registered content creators with many notable names such as Philip DeFranco, The Washington Post, wikiHow, XXL, Vice, and The Guardian to name a few.<ref name="creators"> ''Brave'' (2019). [https://creators.brave.com/ "Earn more for content you publish to the web - Brave Creators"] Retrieved on 8 April 2021. </ref> In the current e-commerce system, digital content creators receive an estimated half of their revenue due to ad-blocking users and many digital ad platforms are monopolized by Google, Facebook, and Amazon.<ref name="mediapost"> Williams, R. (2019, August 23). [https://www.mediapost.com/publications/article/339624/google-publishers-lose-half-of-ad-revenue-from-co.html "Google: Publishers Lose Half Of Ad Revenue From Cookie Blocking"] ''Publishing Insider'' Retrieved on 8 April 2021. </ref> Thus, Brave Rewards is highly appealing to content creators as it attempts to equalize systemically disproportionate streams of revenue.<br />
<br />
===IPFS Integration===<br />
IPFS is the protocol that Brave uses instead of HTTP, which is what most browsers use. IPFS is known as a peer-to-peer protocol. This is because it uses distributed nodes near the user to send data. This can result in faster web browsing in certain areas. In contrast, HTTP has a centralized server that transmits data to users. This can be slow in some areas if the distance from the user to the server is far.<br />
<br />
Another benefit to IPFS is that content restricted in some parts of the world, such as Turkey, Thailand, and China, are now available to them because of IPFS.<ref>Bonifacic, I. (2021, January 19). [https://www.engadget.com/brave-ipfs-update-190545662.html] Retrieved on 7 April 2021. </ref><br />
<br />
===Other Features===<br />
* [https://en.wikipedia.org/wiki/Tor_(anonymity_network) Tor] integration for anonymous browsing by concealing user location and usage information<br />
* Auto-suggesting search terms and searching from the address bar<br />
* Option to use DuckDuckGo for private window search<br />
* Built-in password manager<br />
* [https://en.wikipedia.org/wiki/Fingerprint_(computing) Fingerprinting] prevention, cookie control, and HTTPS upgrading<br />
* Support for most Chrome extensions<br />
===Planned Features===<br />
According to Brave’s BAT roadmap of 2021, Brave developers are aiming to increase crypto and decentralized finance (DeFi) accessibility by creating their own cryptocurrency wallet using Ethereum, an open-source [[blockchain]] technology.<ref name="roadmap"> ''Brave'' (2021, February 22). [https://brave.com/bat-roadmap-2-0/ "BAT Roadmap 2.0"] Retrieved on 8 April 2021. </ref> The Brave Wallet will replace existing crypto wallets and have redesigned UI/UX as well as mobile support. A JavaScript Ethereum Provider API, used to connect web apps with Ethereum blockchain, will now be supplied to web pages by default and more options for buying crypto with fiat payment methods, currencies without intrinsic or use value, will be unlocked. Brave is also looking to support integrated NFT redemption usage(source) within its browser and enable payment of transaction fees through BAT. To further spread DeFi, Brave is creating a new decentralized exchange aggregator with monetary incentives for Brave/Bat users. Aside from future optimizations in accountability and anonymity, to achieve their final endgame of building a Decentralized Web, Brave is researching BAT use in search engines, e-commerce, VPN, IPNS-verified content, and IPFS content pinning. According to public IPFS documentation, IPFS refers to “a distributed system for storing and accessing files, websites, applications, and data.”<ref name="ipfs"> Schilling, J. (2019, December 3). [https://docs.ipfs.io/concepts/what-is-ipfs/ "What is IPFS? | IPFS Docs"] ''IPFS Docs'' Retrieved on 8 April 2021. </ref> IFPS uses content-based addressing while IPNS solves the issue of creating updatable addresses when content is updated. By tying BAT with multiple Decentralized Web systems, Brave is associating their browser and its reward system with other public efforts towards decentralization.<br />
<br />
==Ethical Considerations==<br />
[[File:bizmodel.png|thumb|left|Brave's advertising model]]<br />
===Data Privacy=== <br />
Data privacy while browsing online is a point of contention regarding Internet privacy in the modern-day. Brave offers a robust feature list on metrics related to online privacy and data ethics. By keeping all data local and privatized, Brave does not monetize user data the way many browsers do. Instead, its primary revenue driver is its usage of BAT.<ref name="mainrevenue">https://gizmodo.com/brave-wants-to-destroy-the-ad-business-by-paying-you-to-1834283860] Retrieved on 11 March 2021. </ref> This business model allows them to monetize browsing while still returning 70% of revenue to Brave users themselves.<ref name="returntousers">https://social.techcrunch.com/2019/04/24/brave-ads/] Retrieved on 11 March 2021. </ref> This allows for incentive alignment with users who are focused on privacy and Brave's monetization strategy and business model.<br />
===Online Advertising Ecosystem===<br />
The main concern with Brave's lack of individualized user collection is whether or not users would see relevant ads if they chose to opt-in to see ads in order to earn BAT. Although Brave does not collect individualized user data, it still practices machine learning on aggregated and anonymized data to ensure that ads users see are relevant for them.<ref name="ads">https://brave.com/intro-to-brave-ads/] Retrieved on 11 March 2021. </ref> By approaching advertising this way, Brave addresses common ethical concerns of monetization user behavior data, while still employing machine learning as an effective tool to display relevant ads. By choosing to implement ads in-app instead of using a third-party ad service, Brave Browser also eliminates the 3rd party ad broker and allows for revenue to be returned to the users. <br />
<br />
<br clear=all><br />
===User Expectations of Privacy===<br />
[[File:Brave-private-tab-tor.png|thumb|right|Brave's new tab disclosure]]<br />
Users frequently have misconceptions about online privacy and how private browser modes work.<ref>Wu, Y., Gupta, P., Wei, M., Acar, Y., Fahl, S., & Ur, B. (2018, April). Your secrets are safe: How browsers' explanations impact misconceptions about private browsing mode. In Proceedings of the 2018 World Wide Web Conference (pp. 217-226).<br />
</ref> These include overestimating the function of private browser modes, such as assuming protection against ISP tracking of browsing history. A study has suggested this causes a negative impact to user privacy when using the Brave Browser, as users may engage differently when they expect a certain degree of anonymity.<ref>Fehlhaber, A. L., Acar, Y., Fahl, S., Gutfleisch, M., Theis, D., & Wallkötter, F. Poster: When Brave Hurts Privacy: Why Too Many Choices do More Harm Than Good.</ref> This study also suggested that the new tab disclosure, which attempts to explain the difference between Brave’s two modes, is not effective at educating users on the impact to browsing privacy.<br />
<br />
===Failure of Privacy Promise===<br />
There are multiple instances of the Brave Browser not delivering on its claim to provide privacy protection. One claim that has been found to be misleading is that all traces of browsing history are cleared on closure.<ref>Mahlous, A. R., & Mahlous, H. Private Browsing Forensic Analysis: A Case Study of Privacy Preservation in the Brave Browser.</ref> Fragments of browser data and activities are still accessible on RAM after closing the browser, though they are lost on computer shutdown. Another instance of compromised privacy was seen when a leak, originally seen in a patch introduced on October 14, 2020, was released in a stable build on November 20, 2020.<ref>Powers, B. (2021, February 23). Brave browser leak exposed user domain info for months. Retrieved March 18, 2021, from [https://www.coindesk.com/brave-browser-leak-exposed-user-domain-info-months]<br />
</ref> This leak revealed DNS information and server logs that could be traceable through high-level network access, such as law enforcement, posing a potential safety concern for users in regions with browsing restrictions. The leak was fixed on February 4, 2021 after being present in the stable build for 91 days. In another study, the Brave Browser was found to be vulnerable to the same attacks as Chrome, as it is built off of Chromium, which can reveal some browsing history information through CSS and Javascript weaknesses.<ref>Smith, M., Disselkoen, C., Narayan, S., Brown, F., & Stefan, D. (2018). Browser history re: visited. In 12th {USENIX} Workshop on Offensive Technologies ({WOOT} 18).</ref><br />
<br clear=all><br />
<br />
==References==<br />
<div style="clear: both; margin: 1em 0 0 0; padding: 5px; border: 1px solid #AAA; background: #F0F8FF"><br />
<references /><br />
</div></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brawl_Stars&diff=98735Brawl Stars2021-03-25T18:29:14Z<p>Ptse: </p>
<hr />
<div>Brawl Stars is a multiplayer mobile game created by Supercell.<ref>Supercell https://supercell.com/en/our-story/</ref> Supercell has made many successful mobile games in the past, such as Clash of Clans<ref>https://supercell.com/en/games/clashofclans/</ref>, Clash Royale<ref> https://supercell.com/en/games/clashroyale/ </ref>, Hay Day<ref>https://supercell.com/en/games/hayday/</ref>, and Boom Beach<ref>https://supercell.com/en/games/boombeach/</ref>. Brawl Stars had its beta release on June 14, 2017 and was released worldwide over a year later on December 12, 2018.<ref> Asarch, S. (2018, November 20). 'Brawl Stars' Game Lead Talks Lessons Learned After 522-day Soft Launch. Retrieved from https://www.newsweek.com/brawl-stars-interview-release-game-director-spike-supercell-mobile-1224546 </ref> It is Supercell's most recent release and has been met with overwhelming success. In the four months after its release, the game amassed over 87 million players and 200 million dollars in revenue.<ref> Valdes G. (2019, April 16). Sensor Tower: Supercell’s Brawl Stars earns $200 million in its first four months. Retrieved from https://venturebeat.com/2019/04/16/sensor-tower-supercells-brawl-stars-earns-200-million-in-its-first-four-months/#:~:text=So%20far%2C%20Brawl%20Stars%20has,South%20Korea%20(%2438%20million) </ref>. By the end of December 2020, two years after its worldwide release, Brawl Stars earned a lifetime gross revenue of over $1 billion<ref>https://sensortower.com/blog/brawl-stars-revenue-one-billion</ref>. <br />
<br />
== '''Gameplay''' ==<br />
[[File:Gem grab.jpg|thumbnail|right|Picture from gamewith.net]]<br />
Brawl Stars is considered a third-person hero shooter game.<ref>Hero Shooter https://en.wikipedia.org/wiki/Hero_shooter</ref> Each character, also known as a brawler, has unique abilities, thus making it a hero shooter game. Even though Brawl Stars is a mobile game, it has quite a few game modes. Maps rotate occasionally for each game mode. Other special events are included periodically. <br />
*<b>Hot Zone</b>: Two teams compete to control several zones on the map. Matches are three minutes long and the team that controls the most zones when the timer ends wins. <ref>https://brawlify.com/gamemodes/detail/Hot-Zone</ref><br />
*<b>Gem Grab</b>: Two teams compete to obtain 10 gems, which spawn at the middle of the map. A team wins when they obtain 10 gems and manages to keep the gems safe for 15 seconds.<ref>https://brawlify.com/gamemodes/detail/Gem-Grab</ref><br />
*<b>Solo Showdown</b>: Free-for-all among 10 players. Last player standing is crowned the winner.<ref>https://brawlify.com/gamemodes/detail/Showdown</ref><br />
*<b>Duo Showdown</b>: Similar to solo showdown, except players have a teammate to battle with. The last pair standing is crowned the winner.<ref>https://brawlify.com/gamemodes/detail/Duo-Showdown</ref><br />
*<b>Heist</b>: Two teams compete to protect their safe. The first team to destroy the opponent's safe is the winner.<ref>https://brawlify.com/gamemodes/detail/Heist</ref><br />
*<b>Bounty</b>: Two teams compete to obtain the most stars within two minutes. Stars are obtained by eliminating opponent players. The team with the most stars after the timer ends is the winner.<ref>https://brawlify.com/gamemodes/detail/Bounty</ref><br />
*<b>Brawl Ball</b>: Two teams compete to score goals, similar to soccer. The team that scores two goals first wins.<ref>https://brawlify.com/gamemodes/detail/Brawl-Ball</ref><br />
*<b>Siege</b>: Two teams compete to destroy the opposing team's turret(a tower that can attack the opposing team within a certain range). The team that does so first is the winner. <ref>https://brawlify.com/gamemodes/detail/Siege</ref><br />
*<b>Big Game</b>: Five players battle one player, who is a bigger brawler. The objective of the bigger brawler is to survive and the goal of the five players is to eliminate the bigger brawler. The bigger brawler wins if they stay alive for two minutes, and the five players win if they destroy him before the time runs out. <ref>https://brawlify.com/gamemodes/detail/Big-Game</ref><br />
<br />
== '''Brawlers''' ==<br />
Through 5 seasons, the game has gone from its original 15 brawlers to 45 brawlers<ref>https://brawlify.com/brawlers/</ref>. While each brawler has its own unique abilities, they all fall into certain class types. The different class types are Sharpshooter, Thrower, Support, Heavyweight, Fighter, and Assassin. All of these classes have their own strengths and weaknesses. Because most game modes are played in teams, the different classes of brawlers allow players to combine different traits to find a beneficial group synergy. <br />
[[File:Brawlermenu.jpg|thumbnail|right|Example menu of brawler selection screen]]<br />
<br />
===Sharpshooter===<br />
Sharpshooters are essentially the snipers of Brawl Stars. All Sharpshooters have incredibly long range, but have a below-average amount of health points. Sharpshooters also have one of the highest damage outputs of all the class types.<ref name = "brawlers">https://owwya.com/brawl-stars-brawler-list-all-characters-list-stats/</ref><br />
<br />
===Thrower===<br />
Throwers are brawlers that throw projectiles. Similar to Sharpshooters, they have great range, but have very few health points. What sets Throwers apart from Sharpshooters is their ability to throw projectiles over walls. This makes throwers very versatile and playable on almost any map. <ref name = "brawlers"></ref><br />
<br />
===Support===<br />
This class type has the most variety in terms of unique skills. Some Support brawlers can heal their teammates while one brawler can create a sandstorm and make his teammates invisible within a certain area. Support brawlers compliment any other type of teammate, but they typically lack in their attack power. <ref name = "brawlers"></ref><br />
<br />
===Heavyweight===<br />
The Heavyweight brawlers all have a considerable amount of health points but have an extremely short range. Most can only hit a smaller range in front of them. They are great for soaking up damage on a team. Because of this, Heavyweights heavily rely on hiding in bushes and sneaking up on the opposing team. <ref name = "brawlers"></ref><br />
<br />
===Fighter===<br />
Fighters are the all-around class type. Most Fighters have above-average health points and are above average in terms of damage output or attack range. While a Sharpshooter fighting a Heavyweight would heavily favor the Sharpshooter because of their superior range, a Fighter has no matchups where they clearly lose when in melee range. A Fighter is always a reliable class type to strengthen your team. <ref name = "brawlers"></ref><br />
<br />
===Assassin===<br />
Assassins are high mobility brawlers that generally focus on jumping onto valuable targets. Assassins typically have medium to low health and good damage, but make up for it with their ability to engage and disengage in fights at important times with fast burst damage, as their time between shots is often lower than other brawlers. <ref name = "brawlers"></ref><br />
<br />
== '''Transactions''' ==<br />
== Currency ==<br />
There are 3 different types of currency in the game: gems, coins, and star points. All types of currency are obtainable through the game without the need for in-app purchases. However, players may purchase gems with money for their account. These gems can be used to buy things like vanity, coins, and loot boxes. Coins and loot boxes can be used to upgrade brawlers and give paying gamers an advantage over those who do not. Brawl Stars also includes a seasonal free pass which players can upgrade to a premium version with gems. This premium version gives more and bigger loot boxes to players as well as guaranteed vanity gear, coins, brawlers, etc. assuming the player plays enough to unlock all the possible rewards.<br />
== Purchases == <br />
Since Supercell games are rated G or PG, there is generally no age limit to their games including Brawl Stars. Any in-app purchases made through the game are non-refundable. Supercell games like Brawl Stars do not offer any method for parents to restrict spending like disabling in-app purchases. <br />
<ref> “Parent's Guide × Supercell.” Supercell, supercell.com/en/parents/. </ref><br />
<br />
== '''Ethical Concerns''' ==<br />
===Business Model===<br />
Like Supercell’s previous hit games, Brawl Stars follows the freemium game model <ref> Li, Keyan Kelly. “Why Freemium Games Are Ethnical Problematic.” Medium, Medium, 29 Jan. 2017, medium.com/@haishili0105/why-freemium-games-are-ethnical-problematic-8582ffff77b4. </ref>. The word freemium is a combination of the word “free” and “premium.” These games are free to begin playing with in-app purchases as you play the game. These in-app purchases revolve around purchasing in-game items or currency that gives the user an advantage over users who do not buy in-app purchases. <br />
<br />
====Exploitation of User====<br />
At first glance, the freemium model seems mutually beneficial for both the consumers and the creators. Consumers can still play the game free of charge but can purchase items to make the game more fun. However, there are hidden motives behind this business model. Freemium games rely on microtransactions, which is another word for in-app purchases. Since the player is not paying for the game, the creators of the game earn revenue through microtransactions. Recently, Brawl Stars has accumulated over $1 billion in lifetime revenue and around $526 million in revenue from 2020 alone. <ref> Ahmed, W. (2021, January 30). Brawl stars surpasses $1 billion in revenue. Retrieved from https://dotesports.com/mobile/news/brawl-stars-surpasses-1-billion-in-lifetime-revenue </ref> <br />
<br />
If the creators of the game have the sole intention of monetizing as much as they can from these microtransactions to increase revenue, it becomes likely that the user may get exploited monetarily by the company. Supercell has released many top-selling mobile games in the past. On Jan 1, 2014, Supercell released Clash of Clans which has generated over $7 billion today. The company has also released other popular mobile games which have combined for total revenue of over $5.2 billion. <ref> Strategist, Craig Chapple Mobile Insights. “Clash Royale Crosses $3 Billion in Lifetime Player Spending.” Sensor Tower Blog, sensortower.com/blog/clash-royale-revenue-three-billion. </ref> One item that many freemium games have, including Brawl Stars, is the loot box. These boxes contain a collection of random items that the user receives upon purchase. Loot boxes contain inherent ethical issues with them. <ref> Neely, Eric L. “Come for the Game, Stay for the Cash Grab: The Ethics of Loot Boxes, Microtransactions, and Freemium Games.” </ref> An issue relating to these loot boxes is the algorithm used to determine what item the player receives and how transparent the company is with the algorithm to the user. There is a great deal of transparency in this aspect as the percentages of what tier item the user will receive is listed in the app. <ref> Brawler (and items) drop RATE (2019 Updated): Brawl Stars up! (2021, January 26). Retrieved from https://brawlstarsup.com/brawler-drop-rate/ </ref> Game monetization practices are now coming under scrutiny like the ethics of attracting players to spend money on in-game items. <ref> Earp, Jeffrey, and Francesca Pozzi. “Ethical Issues in Gaming: A Literature Review.” Academia.edu, www.academia.edu/37733245/Ethical_Issues_in_Gaming_A_Literature_Review. </ref><br />
<br />
=====Gambling Addiction=====<br />
Even when percentages are explicitly listed, loot boxes can be very easily compared to slot machines as they offer a random prize to the user of varying worth. With slot machines, the outcome is a range of money values while in Brawl Stars the outcome is a range of items with the corresponding value in virtual currency. Then, the concern of gambling addiction is raised. Gambling addiction, also called problem gambling, is "the urge to gamble continuously despite negative consequences or a desire to stop." Gambling addiction occurs because the actions "activate the same reward circuits in the brain as drugs and the clinical characteristics of gambling disorder are the same as those of drug addictions or alcoholism"<ref> Chóliz, M. (2018, January 31). Ethical gambling: A necessary new point of view of gambling in public health policies. Retrieved March, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5797763/ </ref> Over 50% of the top 100 mobile games offer in-app purchases for loot boxes. Out of that portion of mobile games, less than 10% allow a cash-out option to convert in-game items back into currency. <br />
<br />
===Video Game Addiction===<br />
Similar to gambling addiction, video game addiction is prominent in games such as Brawl Stars. Video game addiction can result in significant impairment to an individual's ability to function in various life domains over a prolonged period of time. The app follows a design that allows for constant play. The matches are quite short(under five minutes) and constant upgrades to the users' brawlers are available the more you play. Additionally, the user can make microtransactions, as specified above, to further gain progress in their game or account. This encourages playing the game for longer, potentially leading to video game addiction. Video game addiction can lead to a sedentary lifestyle, lack of social engagement, problems with concentration and attention, avoidance of developmental tasks, and increased aggression or violence. <ref> Edited by Meredith Watkins, M. (2021, February 08). Video game addiction symptoms and treatment. Retrieved from https://americanaddictioncenters.org/video-gaming-addiction </ref><br />
<br />
== '''References''' ==<br />
</references></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brawl_Stars&diff=98720Brawl Stars2021-03-25T17:54:46Z<p>Ptse: </p>
<hr />
<div>Brawl Stars is a multiplayer mobile game created by Supercell.<ref>Supercell https://supercell.com/en/our-story/</ref> Supercell has made many successful mobile games in the past, such as Clash of Clans<ref>https://supercell.com/en/games/clashofclans/</ref>, Clash Royale<ref> https://supercell.com/en/games/clashroyale/ </ref>, Hay Day<ref>https://supercell.com/en/games/hayday/</ref>, and Boom Beach<ref>https://supercell.com/en/games/boombeach/</ref>. Brawl Stars had its beta release on June 14, 2017 and was released worldwide over a year later on December 12, 2018.<ref> Asarch, S. (2018, November 20). 'Brawl Stars' Game Lead Talks Lessons Learned After 522-day Soft Launch. Retrieved from https://www.newsweek.com/brawl-stars-interview-release-game-director-spike-supercell-mobile-1224546 </ref> It is Supercell's most recent release and has been met with overwhelming success. In the four months after its release, the game amassed over 87 million players and 200 million dollars in revenue.<ref> Valdes G. (2019, April 16). Sensor Tower: Supercell’s Brawl Stars earns $200 million in its first four months. Retrieved from https://venturebeat.com/2019/04/16/sensor-tower-supercells-brawl-stars-earns-200-million-in-its-first-four-months/#:~:text=So%20far%2C%20Brawl%20Stars%20has,South%20Korea%20(%2438%20million) </ref>. By the end of December 2020, two years after its worldwide release, Brawl Stars earned a lifetime gross revenue of over $1 billion<ref>https://sensortower.com/blog/brawl-stars-revenue-one-billion</ref>. <br />
<br />
== '''Gameplay''' ==<br />
[[File:Gem grab.jpg|thumbnail|right|Picture from gamewith.net]]<br />
Brawl Stars is considered a third-person hero shooter game.<ref>Hero Shooter https://en.wikipedia.org/wiki/Hero_shooter</ref> Each character, also known as a brawler, has unique abilities, thus making it a hero shooter game. Even though Brawl Stars is a mobile game, it has quite a few game modes. Maps rotate occasionally for each game mode. Other special events are included periodically. <br />
*<b>Hot Zone</b>: Two teams compete to control several zones on the map. Matches are three minutes long and the team that controls the most zones when the timer ends wins. <ref>https://brawlify.com/gamemodes/detail/Hot-Zone</ref><br />
*<b>Gem Grab</b>: Two teams compete to obtain 10 gems, which spawn at the middle of the map. A team wins when they obtain 10 gems and manages to keep the gems safe for 15 seconds.<ref>https://brawlify.com/gamemodes/detail/Gem-Grab</ref><br />
*<b>Solo Showdown</b>: Free-for-all among 10 players. Last player standing is crowned the winner.<ref>https://brawlify.com/gamemodes/detail/Showdown</ref><br />
*<b>Duo Showdown</b>: Similar to solo showdown, except players have a teammate to battle with. The last pair standing is crowned the winner.<ref>https://brawlify.com/gamemodes/detail/Duo-Showdown</ref><br />
*<b>Heist</b>: Two teams compete to protect their safe. The first team to destroy the opponent's safe is the winner.<ref>https://brawlify.com/gamemodes/detail/Heist</ref><br />
*<b>Bounty</b>: Two teams compete to obtain the most stars within two minutes. Stars are obtained by eliminating opponent players. The team with the most stars after the timer ends is the winner.<ref>https://brawlify.com/gamemodes/detail/Bounty</ref><br />
*<b>Brawl Ball</b>: Two teams compete to score goals, similar to soccer. The team that scores two goals first wins.<ref>https://brawlify.com/gamemodes/detail/Brawl-Ball</ref><br />
*<b>Siege</b>: Two teams compete to destroy the opposing team's turret(a tower that can attack the opposing team within a certain range). The team that does so first is the winner. <ref>https://brawlify.com/gamemodes/detail/Siege</ref><br />
*<b>Big Game</b>: Five players battle one player, who is a bigger brawler. The objective of the bigger brawler is to survive and the goal of the five players is to eliminate the bigger brawler. The bigger brawler wins if they stay alive for two minutes, and the five players win if they destroy him before the time runs out. <ref>https://brawlify.com/gamemodes/detail/Big-Game</ref><br />
<br />
== '''Brawlers''' ==<br />
Through 5 seasons, the game has gone from its original 15 brawlers to 45 brawlers<ref>https://brawlify.com/brawlers/</ref>. While each brawler has its own unique abilities, they all fall into certain class types. The different class types are Sharpshooter, Thrower, Support, Heavyweight, Fighter, and Assassin. All of these classes have their own strengths and weaknesses. Because most game modes are played in teams, the different classes of brawlers allow players to combine different traits to find a beneficial group synergy. <br />
[[File:Brawlermenu.jpg|thumbnail|right|Example menu of brawler selection screen]]<br />
<br />
===Sharpshooter===<br />
Sharpshooters are essentially the snipers of Brawl Stars. All Sharpshooters have incredibly long range, but have a below-average amount of health points. Sharpshooters also have one of the highest damage outputs of all the class types.<ref name = "brawlers">https://owwya.com/brawl-stars-brawler-list-all-characters-list-stats/</ref><br />
<br />
===Thrower===<br />
Throwers are brawlers that throw projectiles. Similar to Sharpshooters, they have great range, but have very few health points. What sets Throwers apart from Sharpshooters is their ability to throw projectiles over walls. This makes throwers very versatile and playable on almost any map. <ref name = "brawlers"></ref><br />
<br />
===Support===<br />
This class type has the most variety in terms of unique skills. Some Support brawlers can heal their teammates while one brawler can create a sandstorm and make his teammates invisible within a certain area. Support brawlers compliment any other type of teammate, but they typically lack in their attack power. <ref name = "brawlers"></ref><br />
<br />
===Heavyweight===<br />
The Heavyweight brawlers all have a considerable amount of health points but have an extremely short range. Most can only hit a smaller range in front of them. They are great for soaking up damage on a team. Because of this, Heavyweights heavily rely on hiding in bushes and sneaking up on the opposing team. <ref name = "brawlers"></ref><br />
<br />
===Fighter===<br />
Fighters are the all-around class type. Most Fighters have above-average health points and are above average in terms of damage output or attack range. While a Sharpshooter fighting a Heavyweight would heavily favor the Sharpshooter because of their superior range, a Fighter has no matchups where they clearly lose when in melee range. A Fighter is always a reliable class type to strengthen your team. <ref name = "brawlers"></ref><br />
<br />
===Assassin===<br />
Assassins are high mobility brawlers that generally focus on jumping onto valuable targets. Assassins typically have medium to low health and good damage, but make up for it with their ability to engage and disengage in fights at important times with fast burst damage, as their time between shots is often lower than other brawlers. <ref name = "brawlers"></ref><br />
<br />
== '''Transactions''' ==<br />
== Currency ==<br />
There are 3 different types of currency in the game: gems, coins, and star points. All types of currency are obtainable through the game without the need for in-app purchases. However, players may purchase gems with money for their account. These gems can be used to buy things like vanity, coins, and loot boxes. Coins and loot boxes can be used to upgrade brawlers and give paying gamers an advantage over those who do not. Brawl Stars also includes a seasonal free pass which players can upgrade to a premium version with gems. This premium version gives more and bigger loot boxes to players as well as guaranteed vanity gear, coins, brawlers, etc. assuming the player plays enough to unlock all the possible rewards.<br />
== Purchases == <br />
Since Supercell games are rated G or PG, there is generally no age limit to their games including Brawl Stars. Any in-app purchases made through the game are non-refundable. Supercell games like Brawl Stars do not offer any method for parents to restrict spending like disabling in-app purchases. <br />
<ref> “Parent's Guide × Supercell.” Supercell, supercell.com/en/parents/. </ref><br />
<br />
== '''Ethical Concerns''' ==<br />
===Business Model===<br />
Like Supercell’s previous hit games, Brawl Stars follows the freemium game model <ref> Li, Keyan Kelly. “Why Freemium Games Are Ethnical Problematic.” Medium, Medium, 29 Jan. 2017, medium.com/@haishili0105/why-freemium-games-are-ethnical-problematic-8582ffff77b4. </ref>. The word freemium is a combination of the word “free” and “premium.” These games are free to begin playing with in-app purchases as you play the game. These in-app purchases revolve around purchasing in-game items or currency that gives the user an advantage over users who do not buy in-app purchases. In Brawl Stars, an in-app purchase can be used to obtain one of the three in-game currencies, gems. Using gems, a player can exchange for gold, buy loot boxes, or even buy a new brawler. <br />
<br />
At first glance, the freemium model seems mutually beneficial for both the consumers and the creators. Consumers can still play the game free of charge but can purchase items to make the game more fun. However, the hidden motives behind this business model are what makes it dangerous. Freemium games rely on microtransactions, which is another word for in-app purchases. Since the player is not paying for the game, the creators of the game earn revenue through microtransactions. Recently, Brawl Stars has accumulated over $1 billion in lifetime revenue and around $526 million in revenue from 2020 alone. <ref> Ahmed, W. (2021, January 30). Brawl stars surpasses $1 billion in revenue. Retrieved from https://dotesports.com/mobile/news/brawl-stars-surpasses-1-billion-in-lifetime-revenue </ref> <br />
<br />
====Exploitation of User====<br />
If the creators of the game have the sole intention of monetizing as much as they can from these microtransactions to increase revenue, it becomes likely that the user may get exploited monetarily by the company. Supercell has released many top-selling mobile games in the past. On Jan 1, 2014, Supercell released Clash of Clans which has not generated over $7 billion today. The company has also released other popular mobile game titles like Clash Royale, Hay Day, and Boom Beach which have combined total revenue of over $5.2 billion. <ref> Strategist, Craig Chapple Mobile Insights. “Clash Royale Crosses $3 Billion in Lifetime Player Spending.” Sensor Tower Blog, sensortower.com/blog/clash-royale-revenue-three-billion. </ref> One item that many freemium games have, including Brawl Stars, is the loot box. These boxes contain a collection of items and the user receives random items from the collection upon purchasing it. Loot boxes contain inherent ethical issues with them. <ref> Neely, Eric L. “Come for the Game, Stay for the Cash Grab: The Ethics of Loot Boxes, Microtransactions, and Freemium Games.” </ref> An issue relating to these loot boxes is the algorithm used to determine what item the player receives and how transparent the company is with the algorithm to the user. There is a great deal of transparency in this aspect as the percentages of what tier item the user will receive is listed in the app. <ref> Brawler (and items) drop RATE (2019 Updated): Brawl Stars up! (2021, January 26). Retrieved from https://brawlstarsup.com/brawler-drop-rate/ </ref> Game monetization practices are now coming under scrutiny like the ethics of attracting players to spend money on in-game items. <ref> Earp, Jeffrey, and Francesca Pozzi. “Ethical Issues in Gaming: A Literature Review.” Academia.edu, www.academia.edu/37733245/Ethical_Issues_in_Gaming_A_Literature_Review. </ref><br />
<br />
=====Gambling Addiction=====<br />
Even when percentages are explicitly listed, loot boxes can be very easily compared to slot machines as they offer a random prize to the user of varying worth. With slot machines, the outcome is a range of money values while in Brawl Stars the outcome is a range of items with the corresponding value in virtual currency. Then, the concern of gambling addiction is raised. Gambling addiction, also called problem gambling, is "the urge to gamble continuously despite negative consequences or a desire to stop". Gambling addiction occurs because the actions "activate the same reward circuits in the brain as drugs and the clinical characteristics of gambling disorder are the same as those of drug addictions or alcoholism"<ref> Chóliz, M. (2018, January 31). Ethical gambling: A necessary new point of view of gambling in public health policies. Retrieved March, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5797763/ </ref> Over 50% of the top 100 mobile games offer in-app purchases for loot boxes. Out of that portion of mobile games, less than 10% allow a cash-out option to convert in-game items back into currency. Although this is not gambling in the traditional sense, studies show that adults that made bets on esports or video games have also made bets with money. <ref> Khonych, Alena (2019). "Ethical and Legal Dimensions of Microtransactions in Videogames" </ref><br />
<br />
===Video Game Addiction===<br />
Similar to gambling addiction, Video game addiction, or problematic, compulsive use of video games that results in significant impairment to an individual's ability to function in various life domains over a prolonged period of time, is prominent in apps such as Brawl Stars. The app follows a design that allows for constant play as there are short matches(under five minutes) and constant upgrades to the users' brawlers and account as a whole. Additionally, the user can make microtransactions, as specified above, to further gain progress in their game or account. This encourages playing the game for longer, potentially leading to video game addiction. Video game addiction can lead to a sedentary lifestyle, lack of social engagement, problems with concentration and attention, avoidance of developmental tasks, and increased aggression or violence. <ref> Edited by Meredith Watkins, M. (2021, February 08). Video game addiction symptoms and treatment. Retrieved from https://americanaddictioncenters.org/video-gaming-addiction </ref><br />
<br />
== '''References''' ==<br />
</references></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brawl_Stars&diff=98690Brawl Stars2021-03-25T17:42:51Z<p>Ptse: </p>
<hr />
<div>Brawl Stars is a multiplayer mobile game created by Supercell.<ref>Supercell https://supercell.com/en/our-story/</ref> Supercell has made many successful mobile games in the past, such as Clash of Clans<ref>https://supercell.com/en/games/clashofclans/</ref>, Clash Royale<ref> https://supercell.com/en/games/clashroyale/ </ref>, Hay Day<ref>https://supercell.com/en/games/hayday/</ref>, and Boom Beach<ref>https://supercell.com/en/games/boombeach/</ref>. Brawl Stars had its beta release on June 14, 2017 and was released worldwide over a year later on December 12, 2018.<ref> Asarch, S. (2018, November 20). 'Brawl Stars' Game Lead Talks Lessons Learned After 522-day Soft Launch. Retrieved from https://www.newsweek.com/brawl-stars-interview-release-game-director-spike-supercell-mobile-1224546 </ref> It is Supercell's most recent release and has been met with overwhelming success. In the four months after its release, the game amassed over 87 million players and 200 million dollars in revenue.<ref> Valdes G. (2019, April 16). Sensor Tower: Supercell’s Brawl Stars earns $200 million in its first four months. Retrieved from https://venturebeat.com/2019/04/16/sensor-tower-supercells-brawl-stars-earns-200-million-in-its-first-four-months/#:~:text=So%20far%2C%20Brawl%20Stars%20has,South%20Korea%20(%2438%20million) </ref>. By the end of December 2020, two years after its worldwide release, Brawl Stars earned a lifetime gross revenue of over $1 billion<ref>https://sensortower.com/blog/brawl-stars-revenue-one-billion</ref>. <br />
<br />
== '''Gameplay''' ==<br />
[[File:Gem grab.jpg|thumbnail|right|Picture from gamewith.net]]<br />
Brawl Stars is considered a third person hero shooter game.<ref>Hero Shooter https://en.wikipedia.org/wiki/Hero_shooter</ref> Each character, also known as a brawler, has unique abilities, thus making it a hero shooter game. Even though Brawl Stars is a mobile game, it has quite a few game modes. Maps rotate occasionally for each game mode. Other special events are included periodically. <br />
*<b>Hot Zone</b>: Two teams compete to control several zones on the map. Matches are three minutes long and the team that controls the most zones when the timer ends wins. <ref>https://brawlify.com/gamemodes/detail/Hot-Zone</ref><br />
*<b>Gem Grab</b>: Two teams compete to obtain 10 gems, which spawn at the middle of the map. A team wins when they obtain 10 gems and manages to keep the gems safe for 15 seconds.<ref>https://brawlify.com/gamemodes/detail/Gem-Grab</ref><br />
*<b>Solo Showdown</b>: Free-for-all among 10 players. Last player standing is crowned the winner.<ref>https://brawlify.com/gamemodes/detail/Showdown</ref><br />
*<b>Duo Showdown</b>: Similar to solo showdown, except players have a teammate to battle with. Last pair standing is crowned the winner.<ref>https://brawlify.com/gamemodes/detail/Duo-Showdown</ref><br />
*<b>Heist</b>: Two teams compete to protect their safe. The first team to destroy the opponent's safe is the winner.<ref>https://brawlify.com/gamemodes/detail/Heist</ref><br />
*<b>Bounty</b>: Two teams compete to obtain the most stars within two minutes. Stars are obtained by eliminating opponent players. The team with the most stars after the timer ends is the winner.<ref>https://brawlify.com/gamemodes/detail/Bounty</ref><br />
*<b>Brawl Ball</b>: Two teams compete to score goals, similar to soccer. The team that scores two goals first wins.<ref>https://brawlify.com/gamemodes/detail/Brawl-Ball</ref><br />
*<b>Siege</b>: Two teams compete to destroy the opposing team's turret. The team that does so first is the winner. <ref>https://brawlify.com/gamemodes/detail/Siege</ref><br />
*<b>Big Game</b>: Five players battle one player, who is a bigger brawler. The objective of the bigger brawler is to survive and the goal of the five players is to eliminate the bigger brawler. The single player wins if they stay alive for two minutes, and the five players win if they destroy him before the time runs out. <ref>https://brawlify.com/gamemodes/detail/Big-Game</ref><br />
<br />
== '''Brawlers''' ==<br />
Through 5 seasons, the game has gone from its original 15 brawlers to 45 brawlers<ref>https://brawlify.com/brawlers/</ref>. While each brawler has their own unique abilities, they all fall into certain class types. The different class types are: sharpshooter, thrower, support, heavyweight, fighter, and assassin. All of these classes have their own strengths and weaknesses. Because most game modes are played in teams, the different classes of brawlers allows players to combine different traits to find a beneficial group synergy. <br />
[[File:Brawlermenu.jpg|thumbnail|right|Example menu of brawler selection screen]]<br />
<br />
===Sharpshooter===<br />
Sharpshooters are essentially the snipers of Brawl Stars. All Sharpshooters have incredibly long range, but have a below average amount of health points. Sharpshooters also have one of the highest damage output of all the class types.<ref name = "brawlers">https://owwya.com/brawl-stars-brawler-list-all-characters-list-stats/</ref><br />
<br />
===Thrower===<br />
Throwers are brawlers that throw projectiles. Similar to Sharpshooters, they have great range, but have very little health points. What sets Throwers apart from Sharpshooters is their ability to throw projectiles over walls. This makes throwers very versatile and playable on almost any map. <ref name = "brawlers"></ref><br />
<br />
===Support===<br />
This class type has the most variety in terms of unique skills. Some Support brawlers can heal their teammates while one brawler can create a sandstorm and make his teammates invisible within a certain area. Support brawlers compliment any other type of teammate, but they typically lack in their attack power. <br />
<br />
===Heavyweight===<br />
The Heavyweight brawlers all have a considerable amount of health points, but have extremely short range. Most can only hit a smaller range in front of them. They are great for soaking up damage on a team. Because of this, Heavyweights heavily rely on hiding in bushes and sneaking up on the opposing team. <br />
<br />
===Fighter===<br />
Fighters are the all-around class type. Most Fighters have above average health points and are above average in terms of damage output or attack range. While a Sharpshooter fighting a Heavyweight would heavily favor the Sharpshooter because of their superior range, a Fighter has no matchups where they clearly lose when in melee range. A Fighter is always a reliable class type to strengthen your team.<br />
<br />
===Assassin===<br />
Assassins are high mobility brawlers that generally focus on jumping onto valuable targets. Assassins typically have medium to low health and good damage, but make up for it with their ability to engage and disengage in fights at important times with fast burst damage, as their time between shots is often lower than other brawlers.<br />
<br />
== '''Transactions''' ==<br />
== Currency ==<br />
There are 3 different types of currency in the game: gems, coins, and star points. All types of currency are obtainable through the game without the need for in-app purchases. However, players may purchase gems with money for their account. These gems can be used to buy things like vanity, coins, and loot boxes. Coins and loot boxes can be used to upgrade brawlers and give paying gamers an advantage over those who don’t. Consumers can also support their favorite Brawl Stars content creators only when making in-app purchases. Brawl Stars also includes a seasonal free pass which players can upgrade to a premium version with gems. This premium version gives more and bigger loot boxes to players as well as guaranteed vanity gear, coins, brawlers, etc. assuming the player plays enough to unlock all the possible rewards.<br />
== Purchases == <br />
Since Supercell games are rated G or PG, there is generally no age limit to their games including Brawl Stars. Any in-app purchases made through the game are non-refundable. Supercell games like Brawl Stars do not offer any method for parents to restrict spending like disabling in-app purchases. <br />
<ref> “Parent's Guide × Supercell.” Supercell, supercell.com/en/parents/. </ref><br />
<br />
== '''Ethical Concerns''' ==<br />
===Business Model===<br />
Like Supercell’s previous hit games, Brawl Stars follows the freemium game model <ref> Li, Keyan Kelly. “Why Freemium Games Are Ethnical Problematic.” Medium, Medium, 29 Jan. 2017, medium.com/@haishili0105/why-freemium-games-are-ethnical-problematic-8582ffff77b4. </ref>. The word freemium is a combination of the word “free” and “premium.” These games are free to begin playing with in-app purchases as you play the game. These in-app purchases revolve around purchasing in-game items or currency that gives the user an advantage over users who do not buy in-app purchases. In Brawl Stars, an in-app purchase can be used to obtain one of the three in-game currencies, gems. Using gems, a player can exchange for gold, buy loot boxes, or even buy a new brawler. <br />
<br />
At first glance, the freemium model seems mutually beneficial for both the consumers and the creators. Consumers can still play the game free of charge but can purchase items to make the game more fun. However, the hidden motives behind this business model are what makes it dangerous. Freemium games rely on microtransactions, which is another word for in-app purchases. Since the player is not paying for the game, the creators of the game earn revenue through microtransactions. Recently, Brawl Stars has accumulated over $1 billion in lifetime revenue and around $526 million in revenue from 2020 alone. <ref> Ahmed, W. (2021, January 30). Brawl stars surpasses $1 billion in revenue. Retrieved from https://dotesports.com/mobile/news/brawl-stars-surpasses-1-billion-in-lifetime-revenue </ref> <br />
<br />
====Exploitation of User====<br />
If the creators of the game have the sole intention of monetizing as much as they can from these microtransactions to increase revenue, it becomes likely that the user may get exploited monetarily by the company. Supercell has released many top-selling mobile games in the past. On Jan 1, 2014, Supercell released Clash of Clans which has not generated over $7 billion today. The company has also released other popular mobile game titles like Clash Royale, Hay Day, and Boom Beach which have combined total revenue of over $5.2 billion. <ref> Strategist, Craig Chapple Mobile Insights. “Clash Royale Crosses $3 Billion in Lifetime Player Spending.” Sensor Tower Blog, sensortower.com/blog/clash-royale-revenue-three-billion. </ref> One item that many freemium games have, including Brawl Stars, is the loot box. These boxes contain a collection of items and the user receives random items from the collection upon purchasing it. Loot boxes contain inherent ethical issues with them. <ref> Neely, Eric L. “Come for the Game, Stay for the Cash Grab: The Ethics of Loot Boxes, Microtransactions, and Freemium Games.” </ref> An issue relating to these loot boxes is the algorithm used to determine what item the player receives and how transparent the company is with the algorithm to the user. There is a great deal of transparency in this aspect as the percentages of what tier item the user will receive is listed in the app. <ref> Brawler (and items) drop RATE (2019 Updated): Brawl Stars up! (2021, January 26). Retrieved from https://brawlstarsup.com/brawler-drop-rate/ </ref> Game monetization practices are now coming under scrutiny like the ethics of attracting players to spend money on in-game items. <ref> Earp, Jeffrey, and Francesca Pozzi. “Ethical Issues in Gaming: A Literature Review.” Academia.edu, www.academia.edu/37733245/Ethical_Issues_in_Gaming_A_Literature_Review. </ref><br />
<br />
=====Gambling Addiction=====<br />
Even when percentages are explicitly listed, loot boxes can be very easily compared to slot machines as they offer a random prize to the user of varying worth. With slot machines, the outcome is a range of money values while in Brawl Stars the outcome is a range of items with the corresponding value in virtual currency. Then, the concern of gambling addiction is raised. Gambling addiction, also called problem gambling, is "the urge to gamble continuously despite negative consequences or a desire to stop". Gambling addiction occurs because the actions "activate the same reward circuits in the brain as drugs and the clinical characteristics of gambling disorder are the same as those of drug addictions or alcoholism"<ref> Chóliz, M. (2018, January 31). Ethical gambling: A necessary new point of view of gambling in public health policies. Retrieved March, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5797763/ </ref> Over 50% of the top 100 mobile games offer in-app purchases for loot boxes. Out of that portion of mobile games, less than 10% allow a cash-out option to convert in-game items back into currency. Although this is not gambling in the traditional sense, studies show that adults that made bets on esports or video games have also made bets with money. <ref> Khonych, Alena (2019). "Ethical and Legal Dimensions of Microtransactions in Videogames" </ref><br />
<br />
===Video Game Addiction===<br />
Similar to gambling addiction, Video game addiction, or problematic, compulsive use of video games that results in significant impairment to an individual's ability to function in various life domains over a prolonged period of time, is prominent in apps such as Brawl Stars. The app follows a design that allows for constant play as there are short matches(under five minutes) and constant upgrades to the users' brawlers and account as a whole. Additionally, the user can make microtransactions, as specified above, to further gain progress in their game or account. This encourages playing the game for longer, potentially leading to video game addiction. Video game addiction can lead to a sedentary lifestyle, lack of social engagement, problems with concentration and attention, avoidance of developmental tasks, and increased aggression or violence. <ref> Edited by Meredith Watkins, M. (2021, February 08). Video game addiction symptoms and treatment. Retrieved from https://americanaddictioncenters.org/video-gaming-addiction </ref><br />
<br />
== '''References''' ==<br />
</references></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brawl_Stars&diff=98687Brawl Stars2021-03-25T17:41:47Z<p>Ptse: </p>
<hr />
<div>Brawl Stars is a multiplayer mobile game created by Supercell.<ref>Supercell https://supercell.com/en/our-story/</ref> Supercell has made many successful mobile games in the past, such as Clash of Clans<ref>https://supercell.com/en/games/clashofclans/</ref>, Clash Royale<ref> https://supercell.com/en/games/clashroyale/ </ref>, Hay Day<ref>https://supercell.com/en/games/hayday/</ref>, and Boom Beach<ref>https://supercell.com/en/games/boombeach/</ref>. Brawl Stars had its beta release on June 14, 2017 and was released worldwide over a year later on December 12, 2018.<ref> Asarch, S. (2018, November 20). 'Brawl Stars' Game Lead Talks Lessons Learned After 522-day Soft Launch. Retrieved from https://www.newsweek.com/brawl-stars-interview-release-game-director-spike-supercell-mobile-1224546 </ref> It is Supercell's most recent release and has been met with overwhelming success. In the four months after its release, the game amassed over 87 million players and 200 million dollars in revenue.<ref> Valdes G. (2019, April 16). Sensor Tower: Supercell’s Brawl Stars earns $200 million in its first four months. Retrieved from https://venturebeat.com/2019/04/16/sensor-tower-supercells-brawl-stars-earns-200-million-in-its-first-four-months/#:~:text=So%20far%2C%20Brawl%20Stars%20has,South%20Korea%20(%2438%20million) </ref>. By the end of December 2020, two years after its worldwide release, Brawl Stars earned a lifetime gross revenue of over $1 billion<ref>https://sensortower.com/blog/brawl-stars-revenue-one-billion</ref>. <br />
<br />
== '''Gameplay''' ==<br />
[[File:Gem grab.jpg|thumbnail|right|Picture from gamewith.net]]<br />
Brawl Stars is considered a third person hero shooter game.<ref>Hero Shooter https://en.wikipedia.org/wiki/Hero_shooter</ref> Each character, also known as a brawler, has unique abilities, thus making it a hero shooter game. Even though Brawl Stars is a mobile game, it has quite a few game modes. Maps rotate occasionally for each game mode. Other special events are included periodically. <br />
*<b>Hot Zone</b>: Two teams compete to control several zones on the map. Matches are three minutes long and the team that controls the most zones when the timer ends wins. <ref>https://brawlify.com/gamemodes/detail/Hot-Zone</ref><br />
*<b>Gem Grab</b>: Two teams compete to obtain 10 gems, which spawn at the middle of the map. A team wins when they obtain 10 gems and manages to keep the gems safe for 15 seconds.<ref>https://brawlify.com/gamemodes/detail/Gem-Grab</ref><br />
*<b>Solo Showdown</b>: Free-for-all among 10 players. Last player standing is crowned the winner.<ref>https://brawlify.com/gamemodes/detail/Showdown</ref><br />
*<b>Duo Showdown</b>: Similar to solo showdown, except players have a teammate to battle with. Last pair standing is crowned the winner.<ref>https://brawlify.com/gamemodes/detail/Duo-Showdown</ref><br />
*<b>Heist</b>: Two teams compete to protect their safe. The first team to destroy the opponent's safe is the winner.<ref>https://brawlify.com/gamemodes/detail/Heist</ref><br />
*<b>Bounty</b>: Two teams compete to obtain the most stars within two minutes. Stars are obtained by eliminating opponent players. The team with the most stars after the timer ends is the winner.<ref>https://brawlify.com/gamemodes/detail/Bounty</ref><br />
*<b>Brawl Ball</b>: Two teams compete to score goals, similar to soccer. The team that scores two goals first wins.<ref>https://brawlify.com/gamemodes/detail/Brawl-Ball</ref><br />
*<b>Siege</b>: Two teams compete to destroy the opposing team's turret. The team that does so first is the winner. <ref>https://brawlify.com/gamemodes/detail/Siege</ref><br />
*<b>Big Game</b>: Five players battle one player, who is a bigger brawler. The objective of the bigger brawler is to survive and the goal of the five players is to eliminate the bigger brawler. The single player wins if they stay alive for two minutes, and the five players win if they destroy him before the time runs out. <ref>https://brawlify.com/gamemodes/detail/Big-Game</ref><br />
<br />
== '''Brawlers''' ==<br />
Through 5 seasons, the game has gone from its original 15 brawlers to 45 brawlers<ref>https://brawlify.com/brawlers/</ref>. While each brawler has their own unique abilities, they all fall into certain class types. The different class types are: sharpshooter, thrower, support, heavyweight, fighter, and assassin. All of these classes have their own strengths and weaknesses. Because most game modes are played in teams, the different classes of brawlers allows players to combine different traits to find a beneficial group synergy. <br />
[[File:Brawlermenu.jpg|thumbnail|right|Example menu of brawler selection screen]]<br />
<br />
===Sharpshooter===<br />
Sharpshooters are essentially the snipers of Brawl Stars. All Sharpshooters have incredibly long range, but have a below average amount of health points. Sharpshooters also have one of the highest damage output of all the class types.<ref = "brawlers">https://owwya.com/brawl-stars-brawler-list-all-characters-list-stats/</ref><br />
<br />
===Thrower===<br />
Throwers are brawlers that throw projectiles. Similar to Sharpshooters, they have great range, but have very little health points. What sets Throwers apart from Sharpshooters is their ability to throw projectiles over walls. This makes throwers very versatile and playable on almost any map. <ref = "brawlers"></ref><br />
<br />
===Support===<br />
This class type has the most variety in terms of unique skills. Some Support brawlers can heal their teammates while one brawler can create a sandstorm and make his teammates invisible within a certain area. Support brawlers compliment any other type of teammate, but they typically lack in their attack power. <br />
<br />
===Heavyweight===<br />
The Heavyweight brawlers all have a considerable amount of health points, but have extremely short range. Most can only hit a smaller range in front of them. They are great for soaking up damage on a team. Because of this, Heavyweights heavily rely on hiding in bushes and sneaking up on the opposing team. <br />
<br />
===Fighter===<br />
Fighters are the all-around class type. Most Fighters have above average health points and are above average in terms of damage output or attack range. While a Sharpshooter fighting a Heavyweight would heavily favor the Sharpshooter because of their superior range, a Fighter has no matchups where they clearly lose when in melee range. A Fighter is always a reliable class type to strengthen your team.<br />
<br />
===Assassin===<br />
Assassins are high mobility brawlers that generally focus on jumping onto valuable targets. Assassins typically have medium to low health and good damage, but make up for it with their ability to engage and disengage in fights at important times with fast burst damage, as their time between shots is often lower than other brawlers.<br />
<br />
== '''Transactions''' ==<br />
== Currency ==<br />
There are 3 different types of currency in the game: gems, coins, and star points. All types of currency are obtainable through the game without the need for in-app purchases. However, players may purchase gems with money for their account. These gems can be used to buy things like vanity, coins, and loot boxes. Coins and loot boxes can be used to upgrade brawlers and give paying gamers an advantage over those who don’t. Consumers can also support their favorite Brawl Stars content creators only when making in-app purchases. Brawl Stars also includes a seasonal free pass which players can upgrade to a premium version with gems. This premium version gives more and bigger loot boxes to players as well as guaranteed vanity gear, coins, brawlers, etc. assuming the player plays enough to unlock all the possible rewards.<br />
== Purchases == <br />
Since Supercell games are rated G or PG, there is generally no age limit to their games including Brawl Stars. Any in-app purchases made through the game are non-refundable. Supercell games like Brawl Stars do not offer any method for parents to restrict spending like disabling in-app purchases. <br />
<ref> “Parent's Guide × Supercell.” Supercell, supercell.com/en/parents/. </ref><br />
<br />
== '''Ethical Concerns''' ==<br />
===Business Model===<br />
Like Supercell’s previous hit games, Brawl Stars follows the freemium game model <ref> Li, Keyan Kelly. “Why Freemium Games Are Ethnical Problematic.” Medium, Medium, 29 Jan. 2017, medium.com/@haishili0105/why-freemium-games-are-ethnical-problematic-8582ffff77b4. </ref>. The word freemium is a combination of the word “free” and “premium.” These games are free to begin playing with in-app purchases as you play the game. These in-app purchases revolve around purchasing in-game items or currency that gives the user an advantage over users who do not buy in-app purchases. In Brawl Stars, an in-app purchase can be used to obtain one of the three in-game currencies, gems. Using gems, a player can exchange for gold, buy loot boxes, or even buy a new brawler. <br />
<br />
At first glance, the freemium model seems mutually beneficial for both the consumers and the creators. Consumers can still play the game free of charge but can purchase items to make the game more fun. However, the hidden motives behind this business model are what makes it dangerous. Freemium games rely on microtransactions, which is another word for in-app purchases. Since the player is not paying for the game, the creators of the game earn revenue through microtransactions. Recently, Brawl Stars has accumulated over $1 billion in lifetime revenue and around $526 million in revenue from 2020 alone. <ref> Ahmed, W. (2021, January 30). Brawl stars surpasses $1 billion in revenue. Retrieved from https://dotesports.com/mobile/news/brawl-stars-surpasses-1-billion-in-lifetime-revenue </ref> <br />
<br />
====Exploitation of User====<br />
If the creators of the game have the sole intention of monetizing as much as they can from these microtransactions to increase revenue, it becomes likely that the user may get exploited monetarily by the company. Supercell has released many top-selling mobile games in the past. On Jan 1, 2014, Supercell released Clash of Clans which has not generated over $7 billion today. The company has also released other popular mobile game titles like Clash Royale, Hay Day, and Boom Beach which have combined total revenue of over $5.2 billion. <ref> Strategist, Craig Chapple Mobile Insights. “Clash Royale Crosses $3 Billion in Lifetime Player Spending.” Sensor Tower Blog, sensortower.com/blog/clash-royale-revenue-three-billion. </ref> One item that many freemium games have, including Brawl Stars, is the loot box. These boxes contain a collection of items and the user receives random items from the collection upon purchasing it. Loot boxes contain inherent ethical issues with them. <ref> Neely, Eric L. “Come for the Game, Stay for the Cash Grab: The Ethics of Loot Boxes, Microtransactions, and Freemium Games.” </ref> An issue relating to these loot boxes is the algorithm used to determine what item the player receives and how transparent the company is with the algorithm to the user. There is a great deal of transparency in this aspect as the percentages of what tier item the user will receive is listed in the app. <ref> Brawler (and items) drop RATE (2019 Updated): Brawl Stars up! (2021, January 26). Retrieved from https://brawlstarsup.com/brawler-drop-rate/ </ref> Game monetization practices are now coming under scrutiny like the ethics of attracting players to spend money on in-game items. <ref> Earp, Jeffrey, and Francesca Pozzi. “Ethical Issues in Gaming: A Literature Review.” Academia.edu, www.academia.edu/37733245/Ethical_Issues_in_Gaming_A_Literature_Review. </ref><br />
<br />
=====Gambling Addiction=====<br />
Even when percentages are explicitly listed, loot boxes can be very easily compared to slot machines as they offer a random prize to the user of varying worth. With slot machines, the outcome is a range of money values while in Brawl Stars the outcome is a range of items with the corresponding value in virtual currency. Then, the concern of gambling addiction is raised. Gambling addiction, also called problem gambling, is "the urge to gamble continuously despite negative consequences or a desire to stop". Gambling addiction occurs because the actions "activate the same reward circuits in the brain as drugs and the clinical characteristics of gambling disorder are the same as those of drug addictions or alcoholism"<ref> Chóliz, M. (2018, January 31). Ethical gambling: A necessary new point of view of gambling in public health policies. Retrieved March, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5797763/ </ref> Over 50% of the top 100 mobile games offer in-app purchases for loot boxes. Out of that portion of mobile games, less than 10% allow a cash-out option to convert in-game items back into currency. Although this is not gambling in the traditional sense, studies show that adults that made bets on esports or video games have also made bets with money. <ref> Khonych, Alena (2019). "Ethical and Legal Dimensions of Microtransactions in Videogames" </ref><br />
<br />
===Video Game Addiction===<br />
Similar to gambling addiction, Video game addiction, or problematic, compulsive use of video games that results in significant impairment to an individual's ability to function in various life domains over a prolonged period of time, is prominent in apps such as Brawl Stars. The app follows a design that allows for constant play as there are short matches(under five minutes) and constant upgrades to the users' brawlers and account as a whole. Additionally, the user can make microtransactions, as specified above, to further gain progress in their game or account. This encourages playing the game for longer, potentially leading to video game addiction. Video game addiction can lead to a sedentary lifestyle, lack of social engagement, problems with concentration and attention, avoidance of developmental tasks, and increased aggression or violence. <ref> Edited by Meredith Watkins, M. (2021, February 08). Video game addiction symptoms and treatment. Retrieved from https://americanaddictioncenters.org/video-gaming-addiction </ref><br />
<br />
== '''References''' ==<br />
</references></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brawl_Stars&diff=98686Brawl Stars2021-03-25T17:41:21Z<p>Ptse: </p>
<hr />
<div>Brawl Stars is a multiplayer mobile game created by Supercell.<ref>Supercell https://supercell.com/en/our-story/</ref> Supercell has made many successful mobile games in the past, such as Clash of Clans<ref>https://supercell.com/en/games/clashofclans/</ref>, Clash Royale<ref> https://supercell.com/en/games/clashroyale/ </ref>, Hay Day<ref>https://supercell.com/en/games/hayday/</ref>, and Boom Beach<ref>https://supercell.com/en/games/boombeach/</ref>. Brawl Stars had its beta release on June 14, 2017 and was released worldwide over a year later on December 12, 2018.<ref> Asarch, S. (2018, November 20). 'Brawl Stars' Game Lead Talks Lessons Learned After 522-day Soft Launch. Retrieved from https://www.newsweek.com/brawl-stars-interview-release-game-director-spike-supercell-mobile-1224546 </ref> It is Supercell's most recent release and has been met with overwhelming success. In the four months after its release, the game amassed over 87 million players and 200 million dollars in revenue.<ref> Valdes G. (2019, April 16). Sensor Tower: Supercell’s Brawl Stars earns $200 million in its first four months. Retrieved from https://venturebeat.com/2019/04/16/sensor-tower-supercells-brawl-stars-earns-200-million-in-its-first-four-months/#:~:text=So%20far%2C%20Brawl%20Stars%20has,South%20Korea%20(%2438%20million) </ref>. By the end of December 2020, two years after its worldwide release, Brawl Stars earned a lifetime gross revenue of over $1 billion<ref>https://sensortower.com/blog/brawl-stars-revenue-one-billion</ref>. <br />
<br />
== '''Gameplay''' ==<br />
[[File:Gem grab.jpg|thumbnail|right|Picture from gamewith.net]]<br />
Brawl Stars is considered a third person hero shooter game.<ref>Hero Shooter https://en.wikipedia.org/wiki/Hero_shooter</ref> Each character, also known as a brawler, has unique abilities, thus making it a hero shooter game. Even though Brawl Stars is a mobile game, it has quite a few game modes. Maps rotate occasionally for each game mode. Other special events are included periodically. <br />
*<b>Hot Zone</b>: Two teams compete to control several zones on the map. Matches are three minutes long and the team that controls the most zones when the timer ends wins. <ref>https://brawlify.com/gamemodes/detail/Hot-Zone</ref><br />
*<b>Gem Grab</b>: Two teams compete to obtain 10 gems, which spawn at the middle of the map. A team wins when they obtain 10 gems and manages to keep the gems safe for 15 seconds.<ref>https://brawlify.com/gamemodes/detail/Gem-Grab</ref><br />
*<b>Solo Showdown</b>: Free-for-all among 10 players. Last player standing is crowned the winner.<ref>https://brawlify.com/gamemodes/detail/Showdown</ref><br />
*<b>Duo Showdown</b>: Similar to solo showdown, except players have a teammate to battle with. Last pair standing is crowned the winner.<ref>https://brawlify.com/gamemodes/detail/Duo-Showdown</ref><br />
*<b>Heist</b>: Two teams compete to protect their safe. The first team to destroy the opponent's safe is the winner.<ref>https://brawlify.com/gamemodes/detail/Heist</ref><br />
*<b>Bounty</b>: Two teams compete to obtain the most stars within two minutes. Stars are obtained by eliminating opponent players. The team with the most stars after the timer ends is the winner.<ref>https://brawlify.com/gamemodes/detail/Bounty</ref><br />
*<b>Brawl Ball</b>: Two teams compete to score goals, similar to soccer. The team that scores two goals first wins.<ref>https://brawlify.com/gamemodes/detail/Brawl-Ball</ref><br />
*<b>Siege</b>: Two teams compete to destroy the opposing team's turret. The team that does so first is the winner. <ref>https://brawlify.com/gamemodes/detail/Siege</ref><br />
*<b>Big Game</b>: Five players battle one player, who is a bigger brawler. The objective of the bigger brawler is to survive and the goal of the five players is to eliminate the bigger brawler. The single player wins if they stay alive for two minutes, and the five players win if they destroy him before the time runs out. <ref>https://brawlify.com/gamemodes/detail/Big-Game</ref><br />
<br />
== '''Brawlers''' ==<br />
Through 5 seasons, the game has gone from its original 15 brawlers to 45 brawlers<ref>https://brawlify.com/brawlers/</ref>. While each brawler has their own unique abilities, they all fall into certain class types. The different class types are: sharpshooter, thrower, support, heavyweight, fighter, and assassin. All of these classes have their own strengths and weaknesses. Because most game modes are played in teams, the different classes of brawlers allows players to combine different traits to find a beneficial group synergy. <br />
[[File:Brawlermenu.jpg|thumbnail|right|Example menu of brawler selection screen]]<br />
<br />
===Sharpshooter===<br />
Sharpshooters are essentially the snipers of Brawl Stars. All Sharpshooters have incredibly long range, but have a below average amount of health points. Sharpshooters also have one of the highest damage output of all the class types.<ref = "brawlers">https://owwya.com/brawl-stars-brawler-list-all-characters-list-stats/</ref><br />
<br />
===Thrower===<br />
Throwers are brawlers that throw projectiles. Similar to Sharpshooters, they have great range, but have very little health points. What sets Throwers apart from Sharpshooters is their ability to throw projectiles over walls. This makes throwers very versatile and playable on almost any map. <ref = "brawlers"><br />
<br />
===Support===<br />
This class type has the most variety in terms of unique skills. Some Support brawlers can heal their teammates while one brawler can create a sandstorm and make his teammates invisible within a certain area. Support brawlers compliment any other type of teammate, but they typically lack in their attack power. <br />
<br />
===Heavyweight===<br />
The Heavyweight brawlers all have a considerable amount of health points, but have extremely short range. Most can only hit a smaller range in front of them. They are great for soaking up damage on a team. Because of this, Heavyweights heavily rely on hiding in bushes and sneaking up on the opposing team. <br />
<br />
===Fighter===<br />
Fighters are the all-around class type. Most Fighters have above average health points and are above average in terms of damage output or attack range. While a Sharpshooter fighting a Heavyweight would heavily favor the Sharpshooter because of their superior range, a Fighter has no matchups where they clearly lose when in melee range. A Fighter is always a reliable class type to strengthen your team.<br />
<br />
===Assassin===<br />
Assassins are high mobility brawlers that generally focus on jumping onto valuable targets. Assassins typically have medium to low health and good damage, but make up for it with their ability to engage and disengage in fights at important times with fast burst damage, as their time between shots is often lower than other brawlers.<br />
<br />
== '''Transactions''' ==<br />
== Currency ==<br />
There are 3 different types of currency in the game: gems, coins, and star points. All types of currency are obtainable through the game without the need for in-app purchases. However, players may purchase gems with money for their account. These gems can be used to buy things like vanity, coins, and loot boxes. Coins and loot boxes can be used to upgrade brawlers and give paying gamers an advantage over those who don’t. Consumers can also support their favorite Brawl Stars content creators only when making in-app purchases. Brawl Stars also includes a seasonal free pass which players can upgrade to a premium version with gems. This premium version gives more and bigger loot boxes to players as well as guaranteed vanity gear, coins, brawlers, etc. assuming the player plays enough to unlock all the possible rewards.<br />
== Purchases == <br />
Since Supercell games are rated G or PG, there is generally no age limit to their games including Brawl Stars. Any in-app purchases made through the game are non-refundable. Supercell games like Brawl Stars do not offer any method for parents to restrict spending like disabling in-app purchases. <br />
<ref> “Parent's Guide × Supercell.” Supercell, supercell.com/en/parents/. </ref><br />
<br />
== '''Ethical Concerns''' ==<br />
===Business Model===<br />
Like Supercell’s previous hit games, Brawl Stars follows the freemium game model <ref> Li, Keyan Kelly. “Why Freemium Games Are Ethnical Problematic.” Medium, Medium, 29 Jan. 2017, medium.com/@haishili0105/why-freemium-games-are-ethnical-problematic-8582ffff77b4. </ref>. The word freemium is a combination of the word “free” and “premium.” These games are free to begin playing with in-app purchases as you play the game. These in-app purchases revolve around purchasing in-game items or currency that gives the user an advantage over users who do not buy in-app purchases. In Brawl Stars, an in-app purchase can be used to obtain one of the three in-game currencies, gems. Using gems, a player can exchange for gold, buy loot boxes, or even buy a new brawler. <br />
<br />
At first glance, the freemium model seems mutually beneficial for both the consumers and the creators. Consumers can still play the game free of charge but can purchase items to make the game more fun. However, the hidden motives behind this business model are what makes it dangerous. Freemium games rely on microtransactions, which is another word for in-app purchases. Since the player is not paying for the game, the creators of the game earn revenue through microtransactions. Recently, Brawl Stars has accumulated over $1 billion in lifetime revenue and around $526 million in revenue from 2020 alone. <ref> Ahmed, W. (2021, January 30). Brawl stars surpasses $1 billion in revenue. Retrieved from https://dotesports.com/mobile/news/brawl-stars-surpasses-1-billion-in-lifetime-revenue </ref> <br />
<br />
====Exploitation of User====<br />
If the creators of the game have the sole intention of monetizing as much as they can from these microtransactions to increase revenue, it becomes likely that the user may get exploited monetarily by the company. Supercell has released many top-selling mobile games in the past. On Jan 1, 2014, Supercell released Clash of Clans which has not generated over $7 billion today. The company has also released other popular mobile game titles like Clash Royale, Hay Day, and Boom Beach which have combined total revenue of over $5.2 billion. <ref> Strategist, Craig Chapple Mobile Insights. “Clash Royale Crosses $3 Billion in Lifetime Player Spending.” Sensor Tower Blog, sensortower.com/blog/clash-royale-revenue-three-billion. </ref> One item that many freemium games have, including Brawl Stars, is the loot box. These boxes contain a collection of items and the user receives random items from the collection upon purchasing it. Loot boxes contain inherent ethical issues with them. <ref> Neely, Eric L. “Come for the Game, Stay for the Cash Grab: The Ethics of Loot Boxes, Microtransactions, and Freemium Games.” </ref> An issue relating to these loot boxes is the algorithm used to determine what item the player receives and how transparent the company is with the algorithm to the user. There is a great deal of transparency in this aspect as the percentages of what tier item the user will receive is listed in the app. <ref> Brawler (and items) drop RATE (2019 Updated): Brawl Stars up! (2021, January 26). Retrieved from https://brawlstarsup.com/brawler-drop-rate/ </ref> Game monetization practices are now coming under scrutiny like the ethics of attracting players to spend money on in-game items. <ref> Earp, Jeffrey, and Francesca Pozzi. “Ethical Issues in Gaming: A Literature Review.” Academia.edu, www.academia.edu/37733245/Ethical_Issues_in_Gaming_A_Literature_Review. </ref><br />
<br />
=====Gambling Addiction=====<br />
Even when percentages are explicitly listed, loot boxes can be very easily compared to slot machines as they offer a random prize to the user of varying worth. With slot machines, the outcome is a range of money values while in Brawl Stars the outcome is a range of items with the corresponding value in virtual currency. Then, the concern of gambling addiction is raised. Gambling addiction, also called problem gambling, is "the urge to gamble continuously despite negative consequences or a desire to stop". Gambling addiction occurs because the actions "activate the same reward circuits in the brain as drugs and the clinical characteristics of gambling disorder are the same as those of drug addictions or alcoholism"<ref> Chóliz, M. (2018, January 31). Ethical gambling: A necessary new point of view of gambling in public health policies. Retrieved March, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5797763/ </ref> Over 50% of the top 100 mobile games offer in-app purchases for loot boxes. Out of that portion of mobile games, less than 10% allow a cash-out option to convert in-game items back into currency. Although this is not gambling in the traditional sense, studies show that adults that made bets on esports or video games have also made bets with money. <ref> Khonych, Alena (2019). "Ethical and Legal Dimensions of Microtransactions in Videogames" </ref><br />
<br />
===Video Game Addiction===<br />
Similar to gambling addiction, Video game addiction, or problematic, compulsive use of video games that results in significant impairment to an individual's ability to function in various life domains over a prolonged period of time, is prominent in apps such as Brawl Stars. The app follows a design that allows for constant play as there are short matches(under five minutes) and constant upgrades to the users' brawlers and account as a whole. Additionally, the user can make microtransactions, as specified above, to further gain progress in their game or account. This encourages playing the game for longer, potentially leading to video game addiction. Video game addiction can lead to a sedentary lifestyle, lack of social engagement, problems with concentration and attention, avoidance of developmental tasks, and increased aggression or violence. <ref> Edited by Meredith Watkins, M. (2021, February 08). Video game addiction symptoms and treatment. Retrieved from https://americanaddictioncenters.org/video-gaming-addiction </ref><br />
<br />
== '''References''' ==<br />
</references></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brawl_Stars&diff=98617Brawl Stars2021-03-25T17:13:05Z<p>Ptse: </p>
<hr />
<div>Brawl Stars is a multiplayer mobile game created by Supercell.<ref>Supercell https://supercell.com/en/our-story/</ref> Supercell has made many successful mobile games in the past, such as Clash of Clans<ref>https://supercell.com/en/games/clashofclans/</ref>, Clash Royale<ref> https://supercell.com/en/games/clashroyale/ </ref>, Hay Day<ref>https://supercell.com/en/games/hayday/</ref>, and Boom Beach<ref>https://supercell.com/en/games/boombeach/</ref>. Brawl Stars had its beta release on June 14, 2017 and was released worldwide over a year later on December 12, 2018.<ref> Asarch, S. (2018, November 20). 'Brawl Stars' Game Lead Talks Lessons Learned After 522-day Soft Launch. Retrieved from https://www.newsweek.com/brawl-stars-interview-release-game-director-spike-supercell-mobile-1224546 </ref> It is Supercell's most recent release and has been met with overwhelming success. In the four months after its release, the game amassed over 87 million players and 200 million dollars in revenue.<ref> Valdes G. (2019, April 16). Sensor Tower: Supercell’s Brawl Stars earns $200 million in its first four months. Retrieved from https://venturebeat.com/2019/04/16/sensor-tower-supercells-brawl-stars-earns-200-million-in-its-first-four-months/#:~:text=So%20far%2C%20Brawl%20Stars%20has,South%20Korea%20(%2438%20million) </ref>. By the end of December 2020, two years after its worldwide release, Brawl Stars earned a lifetime gross revenue of over $1 billion<ref>https://sensortower.com/blog/brawl-stars-revenue-one-billion</ref>. <br />
<br />
== '''Gameplay''' ==<br />
[[File:Gem grab.jpg|thumbnail|right|Picture from gamewith.net]]<br />
Brawl Stars is considered a third person hero shooter game.<ref>Hero Shooter https://en.wikipedia.org/wiki/Hero_shooter</ref> Each character, also known as a brawler, has unique abilities, thus making it a hero shooter game. Even though Brawl Stars is a mobile game, it has quite a few game modes. Maps rotate occasionally for each game mode. Other special events are included periodically. <br />
*<b>Hot Zone</b>: Two teams compete to control several zones of the map. Matches are three minutes long and the team that controls the most zones when the timer ends wins.<br />
*<b>Gem Grab</b>: Two teams compete to obtain 10 gems, which spawn at the middle of the map. A team wins when they obtain 10 gems and manages to keep the gems safe for 15 seconds.<br />
*<b>Solo Showdown</b>: Free-for-all among 10 players. Last player standing is crowned the winner.<br />
*<b>Duo Showdown</b>: Similar to solo showdown, except players have a teammate to battle with. Last pair standing is crowned the winner.<br />
*<b>Heist</b>: Two teams compete to protect their safe. The first team to destroy the opponent's safe is the winner.<br />
*<b>Bounty</b>: Two teams compete to obtain the most stars within two minutes. Stars are obtained by eliminating opponent players. The team with the most stars after the timer ends is the winner.<br />
*<b>Brawl Ball</b>: Two teams compete to score goals. The team that scores two goals first wins.<br />
*<b>Siege</b>: Two teams compete to destroy the opposing team's turret. The team that does so first is the winner.<br />
*<b>Big Game</b>: Five players battle one player, who is a bigger brawler. The objective of the bigger brawler is to survive and the goal of the five players is to eliminate the bigger brawler. The single player wins if they stay alive for two minutes, and the five players win if they destroy him before the time runs out.<br />
*<b>Robo Rumble</b>: Three players battle against waves of robot enemies. The objective is to protect a safe in the center of the map for two minutes. There are four robots: melee, ranged, mini, and big. Melee robots have high health but low range, ranged robots have high range but low health, mini robots have medium health and high movement speed. The Big robot is only sent out once, and serves as a boss. It is has very high health and a combination of melee and ranged attacks.<br />
*<b>Boss Fight</b>: Three players battle against one Boss Robot. The Boss Robot and the robots that spawn to aide it progressively get stronger as time continues, and the players must eliminate the Boss Robot without having all three players die within a similar time frame. The Boss Robot has many stages of difficulties that are unlocked by beating the previous difficulty.<br />
*<b>Super City Rampage</b>: Similar to Boss Fight, three players battle against one Mega Monster. The Mega Monster attacks the surrounding terrain (the city), and only periodically turns to attack the players. The goal is to reduce the Mega Monster's health to zero before the it destroys the entire city.<br />
*<b>Present Plunder</b>: A season event where two teams of three compete in a Capture-The-Flag type game where each team attempts to reach their opponent's side of the map, take the present, and return it to their own side.<br />
*<b>Championship Challenge</b>: A season event teams compete in a tournament style in a 16 team bracket to become the winner.<br />
<br />
== '''Brawlers''' ==<br />
Through 5 seasons, the game has gone from its original 15 brawlers to 45 brawlers<ref>https://brawlify.com/brawlers/</ref>. While each brawler has their own unique abilities, they all fall into certain class types. The different class types are: sharpshooter, thrower, support, heavyweight, fighter, and assassin. All of these classes have their own strengths and weaknesses. Because most game modes are played in teams, the different classes of brawlers allows players to combine different traits to find a beneficial group synergy. <br />
[[File:Brawlermenu.jpg|thumbnail|right|Example menu of brawler selection screen]]<br />
<br />
===Sharpshooter===<br />
Sharpshooters are essentially the snipers of Brawl Stars. All Sharpshooters have incredibly long range, but have a below average amount of health points. Sharpshooters also have one of the highest damage output of all the class types. While the game is quite balanced, never count out a Sharpshooter to change the flow of the game.<br />
<br />
===Thrower===<br />
Throwers are brawlers that throw projectiles. Similar to Sharpshooters, they have great range, but have very little health points. What sets Throwers apart from Sharpshooters is their ability to throw projectiles over walls. This makes throwers very versatile and playable on almost any map. <br />
<br />
===Support===<br />
This class type has the most variety in terms of unique skills. Some Support brawlers can heal their teammates while one brawler can create a sandstorm and make his teammates invisible within a certain area. Support brawlers compliment any other type of teammate, but they typically lack in their attack power. <br />
<br />
===Heavyweight===<br />
The Heavyweight brawlers all have a considerable amount of health points, but have extremely short range. Most can only hit a smaller range in front of them. They are great for soaking up damage on a team. Because of this, Heavyweights heavily rely on hiding in bushes and sneaking up on the opposing team. <br />
<br />
===Fighter===<br />
Fighters are the all-around class type. Most Fighters have above average health points and are above average in terms of damage output or attack range. While a Sharpshooter fighting a Heavyweight would heavily favor the Sharpshooter because of their superior range, a Fighter has no matchups where they clearly lose when in melee range. A Fighter is always a reliable class type to strengthen your team.<br />
<br />
===Assassin===<br />
Assassins are high mobility brawlers that generally focus on jumping onto valuable targets. Assassins typically have medium to low health and good damage, but make up for it with their ability to engage and disengage in fights at important times with fast burst damage, as their time between shots is often lower than other brawlers.<br />
<br />
== '''Transactions''' ==<br />
== Currency ==<br />
There are 3 different types of currency in the game: gems, coins, and star points. All types of currency are obtainable through the game without the need for in-app purchases. However, players may purchase gems with money for their account. These gems can be used to buy things like vanity, coins, and loot boxes. Coins and loot boxes can be used to upgrade brawlers and give paying gamers an advantage over those who don’t. Consumers can also support their favorite Brawl Stars content creators only when making in-app purchases. Brawl Stars also includes a seasonal free pass which players can upgrade to a premium version with gems. This premium version gives more and bigger loot boxes to players as well as guaranteed vanity gear, coins, brawlers, etc. assuming the player plays enough to unlock all the possible rewards.<br />
== Purchases == <br />
Since Supercell games are rated G or PG, there is generally no age limit to their games including Brawl Stars. Any in-app purchases made through the game are non-refundable. Supercell games like Brawl Stars do not offer any method for parents to restrict spending like disabling in-app purchases. <br />
<ref> “Parent's Guide × Supercell.” Supercell, supercell.com/en/parents/. </ref><br />
<br />
== '''Ethical Concerns''' ==<br />
===Business Model===<br />
Like Supercell’s previous hit games, Brawl Stars follows the freemium game model <ref> Li, Keyan Kelly. “Why Freemium Games Are Ethnical Problematic.” Medium, Medium, 29 Jan. 2017, medium.com/@haishili0105/why-freemium-games-are-ethnical-problematic-8582ffff77b4. </ref>. The word freemium is a combination of the word “free” and “premium.” These games are free to begin playing with in-app purchases as you play the game. These in-app purchases revolve around purchasing in-game items or currency that gives the user an advantage over users who do not buy in-app purchases. In Brawl Stars, an in-app purchase can be used to obtain one of the three in-game currencies, gems. Using gems, a player can exchange for gold, buy loot boxes, or even buy a new brawler. <br />
<br />
At first glance, the freemium model seems mutually beneficial for both the consumers and the creators. Consumers can still play the game free of charge but can purchase items to make the game more fun. However, the hidden motives behind this business model are what makes it dangerous. Freemium games rely on microtransactions, which is another word for in-app purchases. Since the player is not paying for the game, the creators of the game earn revenue through microtransactions. Recently, Brawl Stars has accumulated over $1 billion in lifetime revenue and around $526 million in revenue from 2020 alone. <ref> Ahmed, W. (2021, January 30). Brawl stars surpasses $1 billion in revenue. Retrieved from https://dotesports.com/mobile/news/brawl-stars-surpasses-1-billion-in-lifetime-revenue </ref> <br />
<br />
====Exploitation of User====<br />
If the creators of the game have the sole intention of monetizing as much as they can from these microtransactions to increase revenue, it becomes likely that the user may get exploited monetarily by the company. Supercell has released many top-selling mobile games in the past. On Jan 1, 2014, Supercell released Clash of Clans which has not generated over $7 billion today. The company has also released other popular mobile game titles like Clash Royale, Hay Day, and Boom Beach which have combined total revenue of over $5.2 billion. <ref> Strategist, Craig Chapple Mobile Insights. “Clash Royale Crosses $3 Billion in Lifetime Player Spending.” Sensor Tower Blog, sensortower.com/blog/clash-royale-revenue-three-billion. </ref> One item that many freemium games have, including Brawl Stars, is the loot box. These boxes contain a collection of items and the user receives random items from the collection upon purchasing it. Loot boxes contain inherent ethical issues with them. <ref> Neely, Eric L. “Come for the Game, Stay for the Cash Grab: The Ethics of Loot Boxes, Microtransactions, and Freemium Games.” </ref> An issue relating to these loot boxes is the algorithm used to determine what item the player receives and how transparent the company is with the algorithm to the user. There is a great deal of transparency in this aspect as the percentages of what tier item the user will receive is listed in the app. <ref> Brawler (and items) drop RATE (2019 Updated): Brawl Stars up! (2021, January 26). Retrieved from https://brawlstarsup.com/brawler-drop-rate/ </ref> Game monetization practices are now coming under scrutiny like the ethics of attracting players to spend money on in-game items. <ref> Earp, Jeffrey, and Francesca Pozzi. “Ethical Issues in Gaming: A Literature Review.” Academia.edu, www.academia.edu/37733245/Ethical_Issues_in_Gaming_A_Literature_Review. </ref><br />
<br />
=====Gambling Addiction=====<br />
Even when percentages are explicitly listed, loot boxes can be very easily compared to slot machines as they offer a random prize to the user of varying worth. With slot machines, the outcome is a range of money values while in Brawl Stars the outcome is a range of items with the corresponding value in virtual currency. Then, the concern of gambling addiction is raised. Gambling addiction, also called problem gambling, is "the urge to gamble continuously despite negative consequences or a desire to stop". Gambling addiction occurs because the actions "activate the same reward circuits in the brain as drugs and the clinical characteristics of gambling disorder are the same as those of drug addictions or alcoholism"<ref> Chóliz, M. (2018, January 31). Ethical gambling: A necessary new point of view of gambling in public health policies. Retrieved March, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5797763/ </ref> Over 50% of the top 100 mobile games offer in-app purchases for loot boxes. Out of that portion of mobile games, less than 10% allow a cash-out option to convert in-game items back into currency. Although this is not gambling in the traditional sense, studies show that adults that made bets on esports or video games have also made bets with money. <ref> Khonych, Alena (2019). "Ethical and Legal Dimensions of Microtransactions in Videogames" </ref><br />
<br />
===Video Game Addiction===<br />
Similar to gambling addiction, Video game addiction, or problematic, compulsive use of video games that results in significant impairment to an individual's ability to function in various life domains over a prolonged period of time, is prominent in apps such as Brawl Stars. The app follows a design that allows for constant play as there are short matches(under five minutes) and constant upgrades to the users' brawlers and account as a whole. Additionally, the user can make microtransactions, as specified above, to further gain progress in their game or account. This encourages playing the game for longer, potentially leading to video game addiction. Video game addiction can lead to a sedentary lifestyle, lack of social engagement, problems with concentration and attention, avoidance of developmental tasks, and increased aggression or violence. <ref> Edited by Meredith Watkins, M. (2021, February 08). Video game addiction symptoms and treatment. Retrieved from https://americanaddictioncenters.org/video-gaming-addiction </ref><br />
<br />
== '''References''' ==<br />
</references></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Online_Poker&diff=98535Online Poker2021-03-25T15:18:30Z<p>Ptse: </p>
<hr />
<div>==Beginnings==<br />
The rise of online poker has been evident in the last two decades, much of which is due to Chris Moneymaker. In 2003, Moneymaker entered an $86 buy-in tournament on Pokerstars and came in first place with the reward being a spot in the $10,000 buy-in World Series of Poker(WSOP) main event. He eventually won this tournament and $2.5 million in winnings. This led to a boom in the online poker industry as by 2006, the field for the WSOP main event increased ten-fold and there were more than 38 million tournaments hosted by Pokerstars.<ref> Vardi, N. (2020, January 25). The Incredible Rise Of PokerStars Cofounder Isai Scheinberg—And His Surrender To Federal Agents. Retrieved March 12, 2021, from https://www.forbes.com/sites/nathanvardi/2020/01/24/the-incredible-rise-of-pokerstars-cofounder-isai-scheinbergand-his-surrender-to-federal-agents/?sh=45d6c0ed4fb0 </ref><br />
<br />
However, in 2006 President George W. Bush introduced the Unlawful Internet Gambling Enforcement Act (UIGEA), <ref name="gambling_insider"> Insider, G. (2020, July 24). Online poker: A great comeback story. Retrieved from https://www.gamblinginsider.com/in-depth/9636/online-poker-a-great-comeback-story </ref>, which led to the illegalization of online poker in the United States. In 2011, Pokerstars was taken to court in United States vs Scheinberg, the founder of Pokerstars, for a multi-million dollar internet gambling business in violation of UIGEA. <ref> USAO - New York, Southern, Department of Justice. (2020, March 25). PokerStars Founder Pleads Guilty [Press release]. Retrieved from https://www.justice.gov/usao-sdny/pr/pokerstars-founder-pleads-guilty </ref> This resulted in Europe being the powerhouse in online poker, evident still today.<br />
<br />
==Current Day==<br />
There are numerous big-name sites that command thousands of players daily, such as PokerStars, Partypoker, and Americas Cardroom. This is a huge increase from the previous decade. There are cash games of stakes from $.01/$.02 up to $100/$200. Tournaments often have prize pools of over $1 million. Additionally, the emergence of Covid-19 in 2020 significantly hurt casinos but was extremely beneficial for online gaming. The Stars Group, the owner of Pokerstars, reported sizable growth in their first quarter 2020 trading update, with the increased usage of their poker software as a major reason. The group's revenue of $735m for the quarter was a rise of 27% year-on-year.<ref name="gambling_insider"> </ref><br />
<br />
Regulations in the online poker industry have also become looser as time has passed. Most recently, Gretchen Whitmer passed the Lawful Gaming Act <ref> LAWFUL INTERNET GAMING ACT, MI, §§ Act 152 of 2019-432.301-432.322. </ref> which legalized online gaming, such as online poker, in the state of Michigan. The effects of this were recently realized, with Pokerstars being the first site available in Michigan and their MCOOP(Michigan Championship of Online Poker) series have already awarded over $2 million to users.<ref> PokerStars launches in Michigan. (2021, January 29). Retrieved March 12, 2021, from https://www.pokerstars.com/en/news/pokerstars-launches-in-michigan/69124/ </ref> This is signaling that the current trajectory for online poker usage is only going upwards for the near future.<br />
<br />
==Ethics in Online Poker==<br />
===Collusion===<br />
A major issue within the online poker industry is collusion. This is when two players are sitting at the same table and give each other information about what hole cards they had in their hand, or other information that is unfair to the opposing players at the table. This is a very common technique and can be difficult to address. At Pokerstars and many other online poker companies, they can restrict two players from the same IP from sitting down at the same table. <ref> P. (Director). (2014, November 25). Inside PokerStars 4: How does POKERSTARS protect the game? | POKERSTARS [Video file]. Retrieved from https://www.youtube.com/watch?v=d5upxYyeoQ8&amp;t=220s </ref> This, however, is only a small blockade for players attempting to collude. Players can play from different locations and still give each other an unfair advantage against the rest of the players at the table. This issue is not much of a problem for live poker in comparison to online poker as there are fundamental computer science problems that are very difficult to solve relating to discovering the collusion. <ref name="research_gate"> Smed, J., &amp; Knuutila, T. (2006). Can We Prevent Collusion in Multiplayer Online Games? (Unpublished master's thesis). Conference: Proceedings of the Ninth Scandinavian Conference on Artificial Intelligence (SCAI 2006), Espoo, Finland. </ref><br />
<br />
===Bots===<br />
[[File:poker_bots.png|thumbnail|right|Representation of bots from https://www.cardschat.com/poker-bots.php]]<br />
"Bots" are the term in the poker industry for a player who is sitting at your table who is actually not a real person, but rather a computer program. This computer program can be programmed to play the most optimal <ref> M. (2020, November 08). Learn about Poker: What Is Gto (game theory OPTIMAL)? - 2021. Retrieved from https://www.masterclass.com/articles/learn-about-poker-what-is-gto-game-theory-optimal#gto-poker-and-mixed-strategy </ref> poker possible, making it virtually impossible to beat them. In 2019, an AI named "Pluribus" decisively defeated six of the best players in the world over a long duration of hands played. <ref> Carnegie Mellon University, C. (2019, July 11). AI beats professionals in Six-player poker. Retrieved from https://www.sciencedaily.com/releases/2019/07/190711141343.htm#:~:text=The%20AI%2C%20called%20Pluribus%2C%20defeated,against%20five%20copies%20of%20Pluribus </ref> While the bots played against aren't this computationally advanced, they are only increasing in term of ability as technology improves and are still far better than the average individual.<br />
<br />
===Gambling Addiction===<br />
One of the psychological issues related to online poker is the idea of gambling addiction, or the uncontrollable, compulsive urge to keep gambling despite the negative impacts that result from it. Gambling addiction occurs because the actions "activate the same reward circuits in the brain as drugs and the clinical characteristics of gambling disorder are the same as those of drug addictions or alcoholism"<ref> Chóliz, M. (2018, January 31). Ethical gambling: A necessary new point of view of gambling in public health policies. Retrieved March, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5797763/ </ref>. While this is a major issue related to gambling in general, it is compounded by the accessibility and improvements of the online gaming industry. Playing poker has never been easier as all it requires is to sign up online and make a deposit, a task that takes no more than five minutes. This increases the urge to compulsively gamble as there are virtually no barriers to stop someone from doing so. Additionally, it is hard for friends and family to know that someone has a gambling addiction when they are doing it online as it is not as evident. This results in the downsides of a gambling addiction to potentially be much worse than if they had to gamble in person.<br />
<br />
Gambling addictions in online poker have been proved to be caused by certain psychological factors. One of these causes is “tilt,” which is also very common among gaming communities. Tilt is typically classified by the loss of rational decision-making during a game. The frequency of tilt episodes in an individual has been found to be one of the leading indicators of gambling addictions.<ref>Moreau A., Chauchard E., Sevigny S., Giroux I. (2020, July 13). Tilt in Online Poker: Loss of Control and Gambling Disorder. Retrieved from https://www-ncbi-nlm-nih-gov.proxy.lib.umich.edu/pmc/articles/PMC7400001/?tool=pmcentrez</ref> Another one of these causes is something known as “chasing losses.” Chasing losses is the result of trying to win back the money that was lost in previous rounds. As a result, people who chase losses will end up playing more than they originally intended to, and will even bet more money per round in hopes to win back their lost money faster. While poker is a game that involves strategy, many people justify chasing losses with a sort of false sense that the odds will eventually swing in their favor.<ref>Gainsbury S., Suhonen N., Saastamoinen J. (2014) Chasing losses in online poker and casino games: Characteristics and game play of Internet gamblers at risk of disordered gambling. Retrieved from https://core.ac.uk/download/pdf/20322462.pdf</ref> These factors that contribute to online gambling addictions could also be due to the demographic of players. A study done in Portugal showed that the average age for those who played online poker was almost ten years younger than the average age of those who played offline.<ref>Hubert P., Griffiths M. (2017, November 29). A Comparison of Online Versus Offline Gambling Harm in Portuguese Pathological Gamblers: An Empirical Study. Retrieved from https://link-springer-com.proxy.lib.umich.edu/article/10.1007%2Fs11469-017-9846-8</ref> Players who are younger may be more immature and lack the emotional control that is needed for playing poker. This can make them more susceptible to tilt and chasing losses. As mentioned earlier, the accessibility of online poker is also a dangerous factor, especially coupled with these other psychological factors. The mental effects of gambling addictions are also not very pretty. One study showed that those with gambling addictions suffered from anxiety and depression as well.<ref>Barrault S., Bonnaire C., Herrmann F. (2017, January 19) Anxiety, Depression and Emotion Regulation Among Regular Online Poker Players. Retrieved from https://link-springer-com.proxy.lib.umich.edu/article/10.1007%2Fs10899-017-9669-3</ref> This can create a vicious cycle for online poker players. Keeping a cool head to make smart decisions is very important, but having anxiety and depression can lead to having negative emotions and lead players to make rash decisions. The rash decisions could then lead them to tilt or start chasing losses.<br />
<br />
===Future of Online Poker Ethics===<br />
The future of online poker ethics relies on creating better algorithms to detect collusion. This is evidenced through the current software's inability to detect collusion at a relevant rate. There have been creations of bots who collude together where the poker software was unable to detect that they were colluding. <ref> Langner, T., Locher, T., Dr., &amp; Wattenhofer, R., Prof. Dr. (2012). Collusion in Online Poker Pays Off (Unpublished master's thesis). </ref> Similarly, the software was unable to detect that they were computer programs and not real people. It is possible to solve these problems through the means of either prevention or detection.<ref name="research_gate"> </ref> Advancements in these security aspects would catastrophically reduce the amount of cheating in online poker. Additionally, the effects of gambling addiction are prominent and as the current upwards trend for new online poker users continues, the likelihood of gambling addiction increases.<br />
<br />
==References==</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Online_Poker&diff=98532Online Poker2021-03-25T15:05:32Z<p>Ptse: added to gambling addictions</p>
<hr />
<div>==Beginnings==<br />
The rise of online poker has been evident in the last two decades, much of which is due to Chris Moneymaker. In 2003, Moneymaker entered an $86 buy-in tournament on Pokerstars and came in first place with the reward being a spot in the $10,000 buy-in World Series of Poker(WSOP) main event. He eventually won this tournament and $2.5 million in winnings. This led to a boom in the online poker industry as by 2006, the field for the WSOP main event increased ten-fold and there were more than 38 million tournaments hosted by Pokerstars.<ref> Vardi, N. (2020, January 25). The Incredible Rise Of PokerStars Cofounder Isai Scheinberg—And His Surrender To Federal Agents. Retrieved March 12, 2021, from https://www.forbes.com/sites/nathanvardi/2020/01/24/the-incredible-rise-of-pokerstars-cofounder-isai-scheinbergand-his-surrender-to-federal-agents/?sh=45d6c0ed4fb0 </ref><br />
<br />
However, in 2006 President George W. Bush introduced the Unlawful Internet Gambling Enforcement Act (UIGEA), <ref name="gambling_insider"> Insider, G. (2020, July 24). Online poker: A great comeback story. Retrieved from https://www.gamblinginsider.com/in-depth/9636/online-poker-a-great-comeback-story </ref>, which led to the illegalization of online poker in the United States. In 2011, Pokerstars was taken to court in United States vs Scheinberg, the founder of Pokerstars, for a multi-million dollar internet gambling business in violation of UIGEA. <ref> USAO - New York, Southern, Department of Justice. (2020, March 25). PokerStars Founder Pleads Guilty [Press release]. Retrieved from https://www.justice.gov/usao-sdny/pr/pokerstars-founder-pleads-guilty </ref> This resulted in Europe being the powerhouse in online poker, evident still today.<br />
<br />
==Current Day==<br />
There are numerous big name sites that command thousands of players daily, such as PokerStars, Partypoker, and Americas Cardroom. This is a huge increase from the previous decade. There are cash games of stakes from $.01/$.02 up to $100/$200 and often tournaments with prize pools of over $1 million. Additionally, the emergence of Covid-19 in 2020 significantly hurt casinos but was extremely beneficial for online gaming. The Stars Group, owner of Pokerstars, reported sizable growth in their first quarter 2020 trading update, with the increased usage of their poker software as a major reason. The group's revenue of $735m for the quarter was a rise of 27% year-on-year.<ref name="gambling_insider"> </ref><br />
<br />
Regulations in the online poker industry have also become looser as time has passed. Most recently, Gretchen Whitmer passed the Lawful Gaming Act <ref> LAWFUL INTERNET GAMING ACT, MI, §§ Act 152 of 2019-432.301-432.322. </ref> which legalized online gaming, such as online poker, in the state of Michigan. The effects of this were recently realized, with Pokerstars being the first site available in Michigan and their MCOOP(Michigan Championship of Online Poker) series have already awarded over $2 million to users.<ref> PokerStars launches in Michigan. (2021, January 29). Retrieved March 12, 2021, from https://www.pokerstars.com/en/news/pokerstars-launches-in-michigan/69124/ </ref> This is signaling that the current trajectory for online poker usage is only upwards for the near future.<br />
<br />
==Ethics in Online Poker==<br />
===Collusion===<br />
A major issue within the online poker industry is collusion. This is when two players are sitting at the same table and give each other information about what hole cards they had in their hand, or other information that is unfair to the opposing players at the table. This is a very common technique and can be difficult to address. At Pokerstars and many other online poker companies, they can restrict two players from the same IP from sitting down at the same table. <ref> P. (Director). (2014, November 25). Inside PokerStars 4: How does POKERSTARS protect the game? | POKERSTARS [Video file]. Retrieved from https://www.youtube.com/watch?v=d5upxYyeoQ8&amp;t=220s </ref> This, however, is only a small blockade for players attempting to collude. Players can play from different locations and still give each other and unfair advantage against the rest of the players at the table. This issue is not much of a problem for live poker in comparison to online poker as there are fundamental computer science problems that are very difficult to solve relating to discovering the collusion. <ref name="research_gate"> Smed, J., &amp; Knuutila, T. (2006). Can We Prevent Collusion in Multiplayer Online Games? (Unpublished master's thesis). Conference: Proceedings of the Ninth Scandinavian Conference on Artificial Intelligence (SCAI 2006), Espoo, Finland. </ref><br />
<br />
===Bots===<br />
[[File:poker_bots.png|thumbnail|right|Representation of bots from https://www.cardschat.com/poker-bots.php]]<br />
"Bots" are the term in the poker industry for a player who is sitting at your table who is actually not a real person, but rather a computer program. This computer program can be programmed to play the most optimal <ref> M. (2020, November 08). Learn about Poker: What Is Gto (game theory OPTIMAL)? - 2021. Retrieved from https://www.masterclass.com/articles/learn-about-poker-what-is-gto-game-theory-optimal#gto-poker-and-mixed-strategy </ref> poker possible, making it virtually impossible to beat them. In 2019, an AI named "Pluribus" decisively defeated six of the best players in the world over a long duration of hands played. <ref> Carnegie Mellon University, C. (2019, July 11). AI beats professionals in Six-player poker. Retrieved from https://www.sciencedaily.com/releases/2019/07/190711141343.htm#:~:text=The%20AI%2C%20called%20Pluribus%2C%20defeated,against%20five%20copies%20of%20Pluribus </ref> While the bots played against aren't this computationally advanced, they are only increasing in ability as technology improves and are still far better than the average individual.<br />
<br />
===Gambling Addiction===<br />
One of the psychological issues related to online poker is the idea of gambling addiction, or the uncontrollable, compulsive urge to keep gambling despite the negative impacts that result from it. Gambling addiction occurs because the actions "activate the same reward circuits in the brain as drugs and the clinical characteristics of gambling disorder are the same as those of drug addictions or alcoholism"<ref> Chóliz, M. (2018, January 31). Ethical gambling: A necessary new point of view of gambling in public health policies. Retrieved March, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5797763/ </ref>. While this is a major issue related to gambling in general, it is compounded with the accessibility and improvements of the online gaming industry. Playing poker has never been easier as all it requires is to sign up online and make a deposit, a task that takes no more than five minutes. This increases the urge to compulsively gamble as there are virtually no barriers from stopping someone from doing so. Additionally, it is hard for friends and family to know that someone has a gambling addiction when they are doing it online as it is not as evident. This results in the downsides of a gambling addiction to potentially be much worse than if they had to gamble in person.<br />
<br />
Gambling addictions in online poker have been proved to be caused by certain psychological factors. One of these causes is “tilt,” which is also very common among gaming communities. Tilt is typically classified by the loss of rational decision-making during a game. The frequency of tilt episodes in an individual has been found to be one of the leading indicators of gambling addictions.<ref>Moreau A., Chauchard E., Sevigny S., Giroux I. (2020, July 13). Tilt in Online Poker: Loss of Control and Gambling Disorder. Retrieved from https://www-ncbi-nlm-nih-gov.proxy.lib.umich.edu/pmc/articles/PMC7400001/?tool=pmcentrez</ref> Another one of these causes is something known as “chasing losses.” Chasing losses is the result of trying to win back the money that was lost in previous rounds. As a result, people who chase losses will end up playing more than they originally intended to, and will even bet more money per round in hopes to win back their lost money faster. While poker is a game that involves strategy, many people justify chasing losses with a sort of false sense that the odds will eventually swing in their favor.<ref>Gainsbury S., Suhonen N., Saastamoinen J. (2014) Chasing losses in online poker and casino games: Characteristics and game play of Internet gamblers at risk of disordered gambling. Retrieved from https://core.ac.uk/download/pdf/20322462.pdf</ref> These factors that contribute to online gambling addictions could also be due to the demographic of players. A study done in Portugal showed that the average age for those who played online poker was almost ten years younger than the average age of those who played offline.<ref>Hubert P., Griffiths M. (2017, November 29). A Comparison of Online Versus Offline Gambling Harm in Portuguese Pathological Gamblers: An Empirical Study. Retrieved from https://link-springer-com.proxy.lib.umich.edu/article/10.1007%2Fs11469-017-9846-8</ref> Players who are younger may be more immature and lack the emotional control that is needed for playing poker. This can make them more susceptible to tilt and chasing losses. As mentioned earlier, the accessibility of online poker is also a dangerous factor, especially coupled with these other psychological factors. The mental effects of gambling addictions are also not very pretty. One study showed that those with gambling addictions suffered from anxiety and depression as well.<ref>Barrault S., Bonnaire C., Herrmann F. (2017, January 19) Anxiety, Depression and Emotion Regulation Among Regular Online Poker Players. Retrieved from https://link-springer-com.proxy.lib.umich.edu/article/10.1007%2Fs10899-017-9669-3</ref> This can create a vicious cycle for online poker players. Keeping a cool head to make smart decisions is very important, but having anxiety and depression can lead to having negative emotions and lead players to make rash decisions. The rash decisions could then lead them to tilt or start chasing losses.<br />
<br />
===Future of Online Poker Ethics===<br />
The future of online poker ethics relies on creating better algorithms to detect collusion. This is evidenced through the current software's inability to detect collusion at a relevant rate. There have been creations of bots who collude together where the poker software was unable to detect that they were colluding. <ref> Langner, T., Locher, T., Dr., &amp; Wattenhofer, R., Prof. Dr. (2012). Collusion in Online Poker Pays Off (Unpublished master's thesis). </ref> Similarly, the software was unable to detect that they were computer programs and not real people. It is possible to solve these problems through the means of either prevention or detection.<ref name="research_gate"> </ref> Advancements in these security aspects would catastrophically reduce the amount of cheating in online poker. Additionally, the effects of gambling addiction are prominent and as the current upwards trend for new online poker users continues, the likelihood of gambling addiction increases.<br />
<br />
==References==</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Misinformation_on_WeChat&diff=97845Misinformation on WeChat2021-03-18T18:49:54Z<p>Ptse: </p>
<hr />
<div>[http://si410wiki.sites.uofmhosting.net/index.php/WeChat WeChat] is an ethnic media hotspot, delivering media produced by and for a specific ethnic group. In this case, Chinese Americans, many of whom are first-generation immigrants who downloaded the app with the intention of using it to keep in touch with relatives abroad. Just like social media applications in America, WeChat faces similar problems. Parallel to the spread of misinformation targeting older adults on Facebook, a similar phenomenon is occurring through WeChat. This is possible in part due to the curation method of the app that leads to asymmetric polarization. <ref name = "Columbia">“WeChatting American Politics: Misinformation, Polarization, and Immigrant Chinese Media” (15 May 2018. Retrieved on 9 March 2021.), [https://academiccommons.columbia.edu/doi/10.7916/D8FB6KCR]</ref><br />
<br />
==Background==<br />
Due to China’s Great Firewall, most mainstream social media platforms are unavailable in China without the use of a VPN. Because of this, WeChat is one of the main social media platforms in China. Not only that, but it is one of the few applications that can be used in China and outside of China. However, WeChat is much more than just a social media platform. WeChat is also capable of handling monetary transactions between users, similar to Venmo. In addition, it also provides resources for those with language barriers. These two are just some of the functions that WeChat has. Essentially, WeChat is a “super app” that has functions that span many different applications that are used in America.<ref name = "WeChat Ban">"The Logic of a US WeChat Ban" (September 2020. Retrieved on 17 March 2021), [https://search-proquest-com.proxy.lib.umich.edu/docview/1846452974?pq-origsite=summon]</ref><br />
<br />
==Causes==<br />
===Partisan Outlets===<br />
The presence of partisan news outlets on WeChat helps contribute to the asymmetrical polarization. Right-wing outlets produce more articles per month and draw significantly more views than left-wing outlets. Since these are ethnic media outlets, news that is reported specifically is of interest to Chinese Americans. Misinformation becomes easily spread when popular topics in WeChat don’t align with topics on mainstream English or Chinese speaking media. Some of these topics include affirmative action, undocumented immigration, and Muslims/Islam. This happens because when there is no prominent or mainstream reporting of especially salient topics on WeChat, there is a lack of counternarratives and fact-checking.<ref name = "Columbia"/> <br />
[[File:Issuesalience.png|500px|thumb|center|Issue Salience Among Left vs Right Outlets on WeChat<ref name = "Columbia"/> ]]<br />
===Curation===<br />
Another contributor to WeChat’s misinformation problem is its relatively algorithm-less design. Users encounter content by either subscribing directly to news accounts, a chronologically sorted news feed where content is shared by friends, and circulated in invite-only groups. This type of curation makes information flow very socially driven, as information is shared by organically created, trusted networks and not suggested to the user. Out of both personally and socially curated content, social curation plays a larger role in information exposure. In a study conducted by the Tow Center for Digital Journalism at Columbia, 87% of respondents who are WeChat users read articles posted by friends, 79% read articles from private groups, and 57% actively read from their subscribed news accounts.<ref name = "Columbia"/> These private groups can range from tight-knit group chats to a form more like Facebook groups, where large groups are typically driven or members loosely have something in common. The larger groups are constantly evolving and splitting to form narrower and narrower echo chambers, where misinformation easily spreads unchecked. This decentralized format in combination with the attention economy allows for clickbait headlines, emotional hysteria, editorializing, and lack of source checking to run rampant.<ref name = "Columbia"/> On top of this, Wechat is entirely dependent on individual users to report false information, providing ideal conditions for misinformation to breed.<br />
<br />
===Censorship===<br />
Unlike social media in the United States, WeChat is heavily regulated by the Chinese government. One of the methods that they use for censoring content on WeChat is the use of keywords.<ref>"It’s crucial to understand how misinformation flows through diaspora communities" (11 December 2020. Retrieved on 17 March 2021), [https://firstdraftnews.org/latest/misinfo-chinese-diaspora/]</ref> Any article, post, or message posted on WeChat can be censored through the searching of keywords.<ref name = "WeChat Ban"/> In addition, any individual or group that speaks out against the Chinese government on WeChat can also face consequences.<ref>"On Tech: WeChat unites and divides in America" (6 October 2020. Retrieved on 17 March 2021), [https://www-proquest-com.proxy.lib.umich.edu/docview/2448649581/3C6C89B069CE4D93PQ/1?accountid=14667]</ref> They do not experience the same type of free speech rights that we do in the United States.<br />
<br />
Another form of censorship on WeChat that the Chinese government has used is stopping the media from exposing misinformation. Cracking down on the media originally started because of the propaganda being put out by the Communist Party and President Xi Jinping. Many people were suspicious of the propaganda being put out and the media took it upon themselves to reveal the truth. Despite their efforts, there is not much the media in China can do in terms of exposing misinformation because of the Chinese government.<ref>"Fake News Is Rampant Even Under Tight Chinese Filters; Crackdown on professional media erodes those outlets' role as public watchdogs" (7 December 2016. Retrieved on 17 March 2021), [https://search-proquest-com.proxy.lib.umich.edu/docview/1846452974?pq-origsite=summon]</ref><br />
<br />
<br />
==Affected Users==<br />
The sharing of misinformation disproportionately targets older Asian Americans. There has been a recent rise in conservatism among first-generation Chinese immigrants. 35% of Chinese Americans supported Trump in 2016, with this statistic being higher with first-generation immigrants.<ref>“2016 Post-Election National Asian American Survey” (16 May 2017. Retrieved on 11 March 2021.), [http://naasurvey.com/wp-content/uploads/2017/05/NAAS16-post-election-report.pdf]</ref><br />
<br />
==Recent Examples of Misinformation==<br />
- Nearing the 2020 presidential election, a flyer was being spread around claiming that the U.S. Department of Homeland Security was dispatching the National Guard and military to control riots on election day.<ref name = "propublica">“Misinformation Image on WeChat Attempts to Frighten Chinese Americans Out of Voting” (2 November 2020. Retrieved on 9 March 2021.), [https://www.propublica.org/article/misinformation-image-on-wechat-attempts-to-frighten-chinese-americans-out-of-voting]</ref><br />
<br />
- Information about a mainstream media coverup of Joe Biden and his son Hunter Biden was also circulated, they were allegedly being investigated for racketeering and charges.<ref name = "propublica"/><br />
<br />
==Efforts to Combat Misinformation==<br />
Some groups such as the [https://en.wikipedia.org/wiki/Chinese_Progressive_Association_(San_Francisco) Chinese Progressive Association] and NoMelonGroup are attempting to debunk some of the false stories spread on WeChat with posts containing official sources and combat sensationalized stories with counter-narratives. However, these efforts remain overshadowed by the misinformation itself and are not viewed nearly as much as the original article. Faced with the asymmetric polarization of the app along with the social curation method of content sharing, this information is at a disadvantage in being spread as widely and quickly as more provocative misinformation.<ref name = "Columbia"/><ref name = "propublica"/><br />
[[File:flyer.png|300px|thumb|center|A flyer created by the Chinese Progressive Association to Debunk Riot Rumors<ref name = "propublica"/>]]<br />
<br />
==White House Response, Potential Ethical Implications==<br />
In response to not only the glut of misinformation, but also concerns about censorship and data collection on the app, the former presidential administration had spearheaded banning the app. Those opposed to the ban cited First Amendment rights as a reason why the action would be ethically ambiguous.<ref name = "wapo">“Chinese censorship invades the U.S. via WeChat” (7 January 2021. Retrieved on 10 March 2021.), [https://academiccommons.columbia.edu/doi/10.7916/D8FB6KCR]</ref> Users of the app are on it to stay connected with relatives and friends in China, where multiple Western social media outlets are banned. George Shen, a technology executive in the Boston area, argues that the free existence of WeChat is a threat to the First Amendment itself, as the extent of the false information muffles free speech and discourse.<ref name = "wapo"/> The question of whether the existence of echo chambers dug within WeChat spreading misinformation swings more towards a right of free speech or an abuse of it remains central to the debate.<br />
<br />
==References==</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Misinformation_on_WeChat&diff=97843Misinformation on WeChat2021-03-18T18:42:28Z<p>Ptse: </p>
<hr />
<div>[http://si410wiki.sites.uofmhosting.net/index.php/WeChat WeChat] is an ethnic media hotspot, delivering media produced by and for a specific ethnic group. In this case, Chinese Americans, many of whom are first generation immigrants who downloaded the app with the intention of using it to keep in touch with relatives abroad. Parallel to the spread of misinformation targeting older adults on Facebook, a similar phenomenon is occurring through WeChat. This is possible in part due to the curation method of the app that leads to asymmetric polarization. <ref name = "Columbia">“WeChatting American Politics: Misinformation, Polarization, and Immigrant Chinese Media” (15 May 2018. Retrieved on 9 March 2021.), [https://academiccommons.columbia.edu/doi/10.7916/D8FB6KCR]</ref><br />
<br />
==Background==<br />
Due to China’s Great Firewall, most mainstream social media platforms are unavailable in China without the use of a VPN. Because of this, WeChat is one of the main social media platforms in China. Not only that, but it is one of the few applications that can be used in China and outside of China. However, WeChat is much more than just a social media platform. WeChat is also capable of handling monetary transactions between users, similar to Venmo. In addition, it also provides resources for those with language barriers. These two are just some of the functions that WeChat has. Essentially, WeChat is a “super app” that has functions that span many different applications that are used in America.<ref name = "WeChat Ban">"The Logic of a US WeChat Ban" (September 2020. Retrieved on 17 March 2021), [https://search-proquest-com.proxy.lib.umich.edu/docview/1846452974?pq-origsite=summon]</ref><br />
<br />
==Causes==<br />
===Partisan Outlets===<br />
The presence of partisan news outlets on WeChat helps contribute to the asymmetrical polarization, with right-wing outlets producing more articles per month and drawing significantly more views than left-wing outlets. Since these are ethnic media outlets, news that is reported specifically is of interest to Chinese Americans. Misinformation becomes easily spread when popular topics in WeChat don’t align with topics on mainstream English or Chinese speaking media. Some of these topics include affirmative action, undocumented immigration, and Muslims/Islam. This happens because when there is no prominent or mainstream reporting of especially salient topics on WeChat, there is a lack of counternarratives and fact-checking.<ref name = "Columbia"/> <br />
[[File:Issuesalience.png|500px|thumb|center|Issue Salience Among Left vs Right Outlets on WeChat<ref name = "Columbia"/> ]]<br />
===Curation===<br />
Another contributor to WeChat’s misinformation problem is due to its relatively algorithm-less design. Users encounter content by either subscribing directly to news accounts, a chronologically sorted news feed where content is shared by friends, and circulated in invite-only groups. This type of curation makes information flow very socially driven, as information is shared by organically created, trusted networks and not suggested to the user. Out of both personally and socially curated content, social curation plays a larger role in information exposure. In a study conducted by the Tow Center for Digital Journalism at Columbia, 87% of respondents who are WeChat users read articles posted by friends, 79% read articles from private groups, and 57% actively read from their subscribed news accounts.<ref name = "Columbia"/> These private groups can range from tight-knit group chats to a form more like Facebook groups, where large groups are topically driven or members loosely have something in common. The larger groups are constantly evolving and splitting to form narrower and narrower echo chambers, where misinformation easily spreads unchecked. This decentralized format in combination with the attention economy allows for clickbait headlines, emotional hysteria, editorializing, and lack of source checking to run rampant.<ref name = "Columbia"/> On top of this, Wechat is entirely dependent on individual users to report false information, providing ideal conditions for misinformation to breed.<br />
<br />
===Censorship===<br />
Unlike social media in the United States, WeChat is heavily regulated by the Chinese government. One of the methods that they use for censoring content on WeChat is the use of keywords.<ref>"It’s crucial to understand how misinformation flows through diaspora communities" (11 December 2020. Retrieved on 17 March 2021), [https://firstdraftnews.org/latest/misinfo-chinese-diaspora/]</ref> Any article, post, or message posted on WeChat can be censored through the searching of keywords.<ref name = "WeChat Ban"/> In addition, any individual or group that speaks out against the Chinese government on WeChat can also face consequences.<ref>"On Tech: WeChat unites and divides in America" (6 October 2020. Retrieved on 17 March 2021), [https://www-proquest-com.proxy.lib.umich.edu/docview/2448649581/3C6C89B069CE4D93PQ/1?accountid=14667]</ref> They do not experience the same type of free speech rights that we do in the United States.<br />
<br />
Another form of censorship on WeChat that the Chinese government has used is stopping the media from exposing misinformation. Cracking down on the media originally started because of the propaganda being put out by the Communist party and President Xi Jinping. Many people were suspicious of the propaganda being put out and the media took it upon themselves to reveal the truth. Despite their efforts, there is not much the media in China can do in terms of exposing misinformation because of the Chinese government.<ref>"Fake News Is Rampant Even Under Tight Chinese Filters; Crackdown on professional media erodes those outlets' role as public watchdogs" (7 December 2016. Retrieved on 17 March 2021), [https://search-proquest-com.proxy.lib.umich.edu/docview/1846452974?pq-origsite=summon]</ref><br />
<br />
<br />
==Affected Users==<br />
The sharing of misinformation disproportionately targets older Asian Americans. There has been a recent rise of conservatism among first generation Chinese immigrants. 35% of Chinese Americans supported Trump in 2016, with this statistic being higher with first generation immigrants.<ref>“2016 Post-Election National Asian American Survey” (16 May 2017. Retrieved on 11 March 2021.), [http://naasurvey.com/wp-content/uploads/2017/05/NAAS16-post-election-report.pdf]</ref><br />
<br />
==Recent Examples of Misinformation==<br />
- Nearing the 2020 presidential election, a flyer was being spread around claiming that the U.S. Department of Homeland Security was dispatching the National Guard and military to control riots on election day.<ref name = "propublica">“Misinformation Image on WeChat Attempts to Frighten Chinese Americans Out of Voting” (2 November 2020. Retrieved on 9 March 2021.), [https://www.propublica.org/article/misinformation-image-on-wechat-attempts-to-frighten-chinese-americans-out-of-voting]</ref><br />
<br />
- Information about a mainstream media coverup of Joe Biden and his son Hunter Biden was also circulated, they were allegedly being investigated for racketeering and charges.<ref name = "propublica"/><br />
<br />
==Efforts to Combat Misinformation==<br />
Some groups such as the [https://en.wikipedia.org/wiki/Chinese_Progressive_Association_(San_Francisco) Chinese Progressive Association] and NoMelonGroup are attempting to debunk some of the false stories spread on WeChat with posts containing official sources and combat sensationalized stories with counter-narratives. However, these efforts remain overshadowed by the misinformation itself and are not viewed nearly as much as the original article. Faced with the asymmetric polarization of the app along with the social curation method of content sharing, this information is at a disadvantage in being spread as widely and quickly as more provocative misinformation.<ref name = "Columbia"/><ref name = "propublica"/><br />
[[File:flyer.png|300px|thumb|center|A flyer created by the Chinese Progressive Association to Debunk Riot Rumors<ref name = "propublica"/>]]<br />
<br />
==White House Response, Potential Ethical Implications==<br />
In response to not only the glut of misinformation, but also concerns about censorship and data collection on the app, the former presidential administration had spearheaded banning the app. Those opposed to the ban cited First Amendment rights as a reason why the action would be ethically ambiguous.<ref name = "wapo">“Chinese censorship invades the U.S. via WeChat” (7 January 2021. Retrieved on 10 March 2021.), [https://academiccommons.columbia.edu/doi/10.7916/D8FB6KCR]</ref> Users of the app are on it to stay connected with relatives and friends in China, where multiple Western social media outlets are banned. George Shen, a technology executive in the Boston area, argues that the free existence of WeChat is a threat to the First Amendment itself, as the extent of the false information muffles free speech and discourse.<ref name = "wapo"/> The question of whether the existence of echo chambers dug within WeChat spreading misinformation swings more towards a right of free speech or an abuse of it remains central to the debate.<br />
<br />
==References==</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brawl_Stars&diff=96583Brawl Stars2021-03-12T14:36:22Z<p>Ptse: </p>
<hr />
<div>Brawl Stars is a multiplayer mobile game created by Supercell. Supercell has made many successful mobile games in the past, such as Clash of Clans and Clash Royale. Brawl Stars was released in 2017 and is their most recent release. While Brawl Stars has been just as fun as Supercell’s past games, there are some ethical concerns regarding its business model. <br />
<br />
== '''Gameplay''' ==<br />
[[File:Gem grab.jpg|thumbnail|right|Picture from gamewith.net]]<br />
Brawl Stars is considered a third person hero shooter game. Each character, also known as a brawler, has unique abilities, thus making it a hero shooter game. Even though Brawl Stars is a mobile game, it has quite a few game modes. The main game mode is called Gem Grab. This game mode is played with two teams of three. The objective is to collect the gems in the middle of the map. The first team to hold 10 gems wins the game. The other popular game modes are Brawl Ball, Bounty, and Showdown. Brawl Ball and Bounty are also played in teams of three while Showdown can be played individually or in pairs. <br />
<br />
== '''Brawlers''' ==<br />
Through 5 seasons, the game has gone from its original 15 brawlers to 44 brawlers. While each brawler has their own unique abilities, they all fall into certain class types. The different class types are: sharpshooter, thrower, support, heavyweight, and fighter. All of these classes have their own strengths and weaknesses. Because most game modes are played in teams, having brawlers from class types that compliment each other well is very important. <br />
<br />
===Sharpshooter===<br />
Sharpshooters are essentially the snipers of Brawl Stars. All Sharpshooters have incredibly long range, but have a below average amount of health points. Sharpshooters also have one of the highest damage output of all the class types. While the game is quite balanced, never count out a Sharpshooter to change the flow of the game.<br />
<br />
===Thrower===<br />
Throwers are brawlers that throw projectiles. Similar to Sharpshooters, they have great range, but have very little health points. What sets Throwers apart from Sharpshooters is their ability to throw projectiles over walls. This makes throwers very versatile and playable on almost any map. <br />
<br />
===Support===<br />
This class type has the most variety in terms of unique skills. Some Support brawlers can heal their teammates while one brawler can create a sandstorm and make his teammates invisible within a certain area. Support brawlers compliment any other type of teammate, but they typically lack in their attack power. <br />
<br />
===Heavyweight===<br />
The Heavyweight brawlers all have a considerable amount of health points, but have extremely short range. Most can only hit a smaller range in front of them. Because of this, Heavyweights heavily rely on hiding in bushes and sneaking up on the opposing team. <br />
<br />
===Fighter===<br />
Fighters are the all-around class type. Most Fighters have above average health points and are above average in terms of damage output or attack range. While a Sharpshooter fighting a Heavyweight would heavily favor the Sharpshooter because of their superior range, a Fighter has no matchups where they clearly lose. A Fighter is always a reliable class type to strengthen your team. <br />
<br />
== '''Ethical Concerns with Business Model''' ==<br />
<br />
===Business Model===<br />
Like Supercell’s previous hit games, Brawl Stars follows the freemium game model. The word freemium is a combination of the word “free” and “premium.” These games are free to begin playing with in-app purchases as you play the game. These in-app purchases are usually for certain items or an exchange for in-game currency that can give you some sort of advantage. In Brawl Stars, an in-app purchase can be used to obtain one of the three in-game currencies, gems. Using gems, a player can exchange for gold, buy loot boxes, or even buy a new brawler. <br />
<br />
===Ethical Concerns===<br />
At first glance, the freemium model seems mutually beneficial for both the consumers and the creators. Consumers can still play the game free of charge, but can purchase items to make the game more fun. However, the hidden motives behind this business model is what makes it dangerous. Freemium games benefit off of “microtransactions.” Microtransaction is another word for in-app purchases for freemium games. Since the player is not paying for the game, they are making microtransactions for in-game items. If the creators of the game have the sole intention of monetizing as much as they can from these microtransactions then there is an ethical issue. One item that many freemium games have is the loot box. These boxes contain random items that are unknown to the user before purchasing it. Generally, the ethical issue around loot boxes is the underlying motive behind them. Games in the past did not include the percentages/likelihood of certain items appearing from a loot box. Intentional or not, this leads players to continuously purchase loot boxes in hopes to obtain certain items. Loot boxes in this context are clearly not ethical as they create a sort of gambling effect when opening boxes. Brawl Star’s version of loot boxes are called Brawl Boxes. Unlike other games Brawl Stars provides the likelihoods of certain items appearing from Brawl Boxes. This informs the player on their decision to spend real money on Brawl Boxes.<br />
<br />
== '''References''' ==<br />
Li, Keyan Kelly. “Why Freemium Games Are Ethnical Problematic.” Medium, Medium, 29 Jan. 2017, medium.com/@haishili0105/why-freemium-games-are-ethnical-problematic-8582ffff77b4. <br />
<br />
Neely, Eric L. “Come for the Game, Stay for the Cash Grab: The Ethics of Loot Boxes, Microtransactions, and Freemium Games.” <br />
<br />
Peck, Dave. “The Murky Ethics of Freemium Games.” Dave Peck, 2 July 2012, davepeck.org/2012/07/02/the-murky-ethics-of-freemium-games/.</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brawl_Stars&diff=96582Brawl Stars2021-03-12T14:36:04Z<p>Ptse: </p>
<hr />
<div>Brawl Stars is a multiplayer mobile game created by Supercell. Supercell has made many successful mobile games in the past, such as Clash of Clans and Clash Royale. Brawl Stars was released in 2017 and is their most recent release. While Brawl Stars has been just as fun as Supercell’s past games, there are some ethical concerns regarding its business model. <br />
<br />
== '''Gameplay''' ==<br />
[[File:Gem grab.jpg|thumbnail|right|Picture from gamewith.net]]<br />
Brawl Stars is considered a third person hero shooter game. Each character, also known as a brawler, has unique abilities, thus making it a hero shooter game. Even though Brawl Stars is a mobile game, it has quite a few game modes. The main game mode is called Gem Grab. This game mode is played with two teams of three. The objective is to collect the gems in the middle of the map. The first team to hold 10 gems wins the game. The other popular game modes are Brawl Ball, Bounty, and Showdown. Brawl Ball and Bounty are also played in teams of three while Showdown can be played individually or in pairs. <br />
<br />
== '''Brawlers''' ==<br />
Through 5 seasons, the game has gone from its original 15 brawlers to 44 brawlers. While each brawler has their own unique abilities, they all fall into certain class types. The different class types are: sharpshooter, thrower, support, heavyweight, and fighter. All of these classes have their own strengths and weaknesses. Because most game modes are played in teams, having brawlers from class types that compliment each other well is very important. <br />
<br />
===Sharpshooter===<br />
Sharpshooters are essentially the snipers of Brawl Stars. All Sharpshooters have incredibly long range, but have a below average amount of health points. Sharpshooters also have one of the highest damage output of all the class types. While the game is quite balanced, never count out a Sharpshooter to change the flow of the game.<br />
<br />
===Thrower===<br />
Throwers are brawlers that throw projectiles. Similar to Sharpshooters, they have great range, but have very little health points. What sets Throwers apart from Sharpshooters is their ability to throw projectiles over walls. This makes throwers very versatile and playable on almost any map. <br />
<br />
===Support===<br />
This class type has the most variety in terms of unique skills. Some Support brawlers can heal their teammates while one brawler can create a sandstorm and make his teammates invisible within a certain area. Support brawlers compliment any other type of teammate, but they typically lack in their attack power. <br />
<br />
===Heavyweight===<br />
The Heavyweight brawlers all have a considerable amount of health points, but have extremely short range. Most can only hit a smaller range in front of them. Because of this, Heavyweights heavily rely on hiding in bushes and sneaking up on the opposing team. <br />
<br />
===Fighter===<br />
Fighters are the all-around class type. Most Fighters have above average health points and are above average in terms of damage output or attack range. While a Sharpshooter fighting a Heavyweight would heavily favor the Sharpshooter because of their superior range, a Fighter has no matchups where they clearly lose. A Fighter is always a reliable class type to strengthen your team. <br />
<br />
== '''Ethical Concerns with Business Model''' ==<br />
<br />
===Business Model===<br />
Like Supercell’s previous hit games, Brawl Stars follows the freemium game model. The word freemium is a combination of the word “free” and “premium.” These games are free to begin playing with in-app purchases as you play the game. These in-app purchases are usually for certain items or an exchange for in-game currency that can give you some sort of advantage. In Brawl Stars, an in-app purchase can be used to obtain one of the three in-game currencies, gems. Using gems, a player can exchange for gold, buy loot boxes, or even buy a new brawler. <br />
<br />
===Ethical Concerns===<br />
At first glance, the freemium model seems mutually beneficial for both the consumers and the creators. Consumers can still play the game free of charge, but can purchase items to make the game more fun. However, the hidden motives behind this business model is what makes it dangerous. Freemium games benefit off of “microtransactions.” Microtransaction is another word for in-app purchases for freemium games. Since the player is not paying for the game, they are making microtransactions for in-game items. If the creators of the game have the sole intention of monetizing as much as they can from these microtransactions then there is an ethical issue. One item that many freemium games have is the loot box. These boxes contain random items that are unknown to the user before purchasing it. Generally, the ethical issue around loot boxes is the underlying motive behind them. Games in the past did not include the percentages/likelihood of certain items appearing from a loot box. Intentional or not, this leads players to continuously purchase loot boxes in hopes to obtain certain items. Loot boxes in this context are clearly not ethical as they create a sort of gambling effect when opening boxes. Brawl Star’s version of loot boxes are called Brawl Boxes. Unlike other games Brawl Stars provides the likelihoods of certain items appearing from Brawl Boxes. This informs the player on their decision to spend real money on Brawl Boxes.<br />
<br />
== '''References''' ==<br />
Li, Keyan Kelly. “Why Freemium Games Are Ethnical Problematic.” Medium, Medium, 29 Jan. 2017, medium.com/@haishili0105/why-freemium-games-are-ethnical-problematic-8582ffff77b4. <br />
Neely, Eric L. “Come for the Game, Stay for the Cash Grab: The Ethics of Loot Boxes, Microtransactions, and Freemium Games.” <br />
Peck, Dave. “The Murky Ethics of Freemium Games.” Dave Peck, 2 July 2012, davepeck.org/2012/07/02/the-murky-ethics-of-freemium-games/.</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brawl_Stars&diff=96563Brawl Stars2021-03-12T14:28:46Z<p>Ptse: </p>
<hr />
<div>Brawl Stars is a multiplayer mobile game created by Supercell. Supercell has made many successful mobile games in the past, such as Clash of Clans and Clash Royale. Brawl Stars was released in 2017 and is their most recent release. While Brawl Stars has been just as fun as Supercell’s past games, there are some ethical concerns regarding its business model. <br />
<br />
== '''Gameplay''' ==<br />
[[File:Gem grab.jpg|thumbnail|right|Picture from gamewith.net]]<br />
Brawl Stars is considered a third person hero shooter game. Each character, also known as a brawler, has unique abilities, thus making it a hero shooter game. Even though Brawl Stars is a mobile game, it has quite a few game modes. The main game mode is called Gem Grab. This game mode is played with two teams of three. The objective is to collect the gems in the middle of the map. The first team to hold 10 gems wins the game. The other popular game modes are Brawl Ball, Bounty, and Showdown. Brawl Ball and Bounty are also played in teams of three while Showdown can be played individually or in pairs. <br />
<br />
== '''Brawlers''' ==<br />
Through 5 seasons, the game has gone from its original 15 brawlers to 44 brawlers. While each brawler has their own unique abilities, they all fall into certain class types. The different class types are: sharpshooter, thrower, support, heavyweight, and fighter. All of these classes have their own strengths and weaknesses. Because most game modes are played in teams, having brawlers from class types that compliment each other well is very important. <br />
<br />
===Sharpshooter===<br />
Sharpshooters are essentially the snipers of Brawl Stars. All Sharpshooters have incredibly long range, but have a below average amount of health points. Sharpshooters also have one of the highest damage output of all the class types. While the game is quite balanced, never count out a Sharpshooter to change the flow of the game.<br />
<br />
===Thrower===<br />
Throwers are brawlers that throw projectiles. Similar to Sharpshooters, they have great range, but have very little health points. What sets Throwers apart from Sharpshooters is their ability to throw projectiles over walls. This makes throwers very versatile and playable on almost any map. <br />
<br />
===Support===<br />
This class type has the most variety in terms of unique skills. Some Support brawlers can heal their teammates while one brawler can create a sandstorm and make his teammates invisible within a certain area. Support brawlers compliment any other type of teammate, but they typically lack in their attack power. <br />
<br />
===Heavyweight===<br />
The Heavyweight brawlers all have a considerable amount of health points, but have extremely short range. Most can only hit a smaller range in front of them. Because of this, Heavyweights heavily rely on hiding in bushes and sneaking up on the opposing team. <br />
<br />
===Fighter===<br />
Fighters are the all-around class type. Most Fighters have above average health points and are above average in terms of damage output or attack range. While a Sharpshooter fighting a Heavyweight would heavily favor the Sharpshooter because of their superior range, a Fighter has no matchups where they clearly lose. A Fighter is always a reliable class type to strengthen your team. <br />
<br />
== '''Ethical Concerns with Business Model''' ==<br />
<br />
===Business Model===<br />
Like Supercell’s previous hit games, Brawl Stars follows the freemium game model. The word freemium is a combination of the word “free” and “premium.” These games are free to begin playing with in-app purchases as you play the game. These in-app purchases are usually for certain items or an exchange for in-game currency that can give you some sort of advantage. In Brawl Stars, an in-app purchase can be used to obtain one of the three in-game currencies, gems. Using gems, a player can exchange for gold, buy loot boxes, or even buy a new brawler. <br />
<br />
===Ethical Concerns===<br />
At first glance, the freemium model seems mutually beneficial for both the consumers and the creators. Consumers can still play the game free of charge, but can purchase items to make the game more fun. However, the hidden motives behind this business model is what makes it dangerous. Freemium games benefit off of “microtransactions.” Microtransaction is another word for in-app purchases for freemium games. Since the player is not paying for the game, they are making microtransactions for in-game items. If the creators of the game have the sole intention of monetizing as much as they can from these microtransactions then there is an ethical issue. One item that many freemium games have is the loot box. These boxes contain random items that are unknown to the user before purchasing it. Generally, the ethical issue around loot boxes is the underlying motive behind them. Games in the past did not include the percentages/likelihood of certain items appearing from a loot box. Intentional or not, this leads players to continuously purchase loot boxes in hopes to obtain certain items. Loot boxes in this context are clearly not ethical as they create a sort of gambling effect when opening boxes. Brawl Star’s version of loot boxes are called Brawl Boxes. Unlike other games Brawl Stars provides the likelihoods of certain items appearing from Brawl Boxes. This informs the player on their decision to spend real money on Brawl Boxes.</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=File:Gem_grab.jpg&diff=96561File:Gem grab.jpg2021-03-12T14:27:04Z<p>Ptse: </p>
<hr />
<div></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brawl_Stars&diff=96549Brawl Stars2021-03-12T14:20:46Z<p>Ptse: Created page with "Brawl Stars is a multiplayer mobile game created by Supercell. Supercell has made many successful mobile games in the past, such as Clash of Clans and Clash Royale. Brawl Star..."</p>
<hr />
<div>Brawl Stars is a multiplayer mobile game created by Supercell. Supercell has made many successful mobile games in the past, such as Clash of Clans and Clash Royale. Brawl Stars was released in 2017 and is their most recent release. While Brawl Stars has been just as fun as Supercell’s past games, there are some ethical concerns regarding its business model. <br />
<br />
== '''Gameplay''' ==<br />
Brawl Stars is considered a third person hero shooter game. Each character, also known as a brawler, has unique abilities, thus making it a hero shooter game. Even though Brawl Stars is a mobile game, it has quite a few game modes. The main game mode is called Gem Grab. This game mode is played with two teams of three. The objective is to collect the gems in the middle of the map. The first team to hold 10 gems wins the game. The other popular game modes are Brawl Ball, Bounty, and Showdown. Brawl Ball and Bounty are also played in teams of three while Showdown can be played individually or in pairs. <br />
<br />
== '''Brawlers''' ==<br />
Through 5 seasons, the game has gone from its original 15 brawlers to 44 brawlers. While each brawler has their own unique abilities, they all fall into certain class types. The different class types are: sharpshooter, thrower, support, heavyweight, and fighter. All of these classes have their own strengths and weaknesses. Because most game modes are played in teams, having brawlers from class types that compliment each other well is very important. <br />
<br />
===Sharpshooter===<br />
Sharpshooters are essentially the snipers of Brawl Stars. All Sharpshooters have incredibly long range, but have a below average amount of health points. Sharpshooters also have one of the highest damage output of all the class types. While the game is quite balanced, never count out a Sharpshooter to change the flow of the game.<br />
<br />
===Thrower===<br />
Throwers are brawlers that throw projectiles. Similar to Sharpshooters, they have great range, but have very little health points. What sets Throwers apart from Sharpshooters is their ability to throw projectiles over walls. This makes throwers very versatile and playable on almost any map. <br />
<br />
===Support===<br />
This class type has the most variety in terms of unique skills. Some Support brawlers can heal their teammates while one brawler can create a sandstorm and make his teammates invisible within a certain area. Support brawlers compliment any other type of teammate, but they typically lack in their attack power. <br />
<br />
===Heavyweight===<br />
The Heavyweight brawlers all have a considerable amount of health points, but have extremely short range. Most can only hit a smaller range in front of them. Because of this, Heavyweights heavily rely on hiding in bushes and sneaking up on the opposing team. <br />
<br />
===Fighter===<br />
Fighters are the all-around class type. Most Fighters have above average health points and are above average in terms of damage output or attack range. While a Sharpshooter fighting a Heavyweight would heavily favor the Sharpshooter because of their superior range, a Fighter has no matchups where they clearly lose. A Fighter is always a reliable class type to strengthen your team. <br />
<br />
== '''Ethical Concerns with Business Model''' ==<br />
<br />
===Business Model===<br />
Like Supercell’s previous hit games, Brawl Stars follows the freemium game model. The word freemium is a combination of the word “free” and “premium.” These games are free to begin playing with in-app purchases as you play the game. These in-app purchases are usually for certain items or an exchange for in-game currency that can give you some sort of advantage. In Brawl Stars, an in-app purchase can be used to obtain one of the three in-game currencies, gems. Using gems, a player can exchange for gold, buy loot boxes, or even buy a new brawler. <br />
<br />
===Ethical Concerns===<br />
At first glance, the freemium model seems mutually beneficial for both the consumers and the creators. Consumers can still play the game free of charge, but can purchase items to make the game more fun. However, the hidden motives behind this business model is what makes it dangerous. Freemium games benefit off of “microtransactions.” Microtransaction is another word for in-app purchases for freemium games. Since the player is not paying for the game, they are making microtransactions for in-game items. If the creators of the game have the sole intention of monetizing as much as they can from these microtransactions then there is an ethical issue. One item that many freemium games have is the loot box. These boxes contain random items that are unknown to the user before purchasing it. Generally, the ethical issue around loot boxes is the underlying motive behind them. Games in the past did not include the percentages/likelihood of certain items appearing from a loot box. Intentional or not, this leads players to continuously purchase loot boxes in hopes to obtain certain items. Loot boxes in this context are clearly not ethical as they create a sort of gambling effect when opening boxes. Brawl Star’s version of loot boxes are called Brawl Boxes. Unlike other games Brawl Stars provides the likelihoods of certain items appearing from Brawl Boxes. This informs the player on their decision to spend real money on Brawl Boxes.</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Topics&diff=96532Topics2021-03-12T14:17:17Z<p>Ptse: /* B */</p>
<hr />
<div>http://si410ethics11.projects.si.umich.edu/images/topics.png<br />
<br />
''Please add your newly created pages to this list in alphabetical order, and remember to surround with the appropriate MediaWiki syntax (i.e.:'' <nowiki>*[[your page]]</nowiki>'').''<br />
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== Blue Star Articles ==<br />
<br/><br />
*[[:Category:BlueStar2019|Blue Star Articles (2019)]]<br />
*[[:Category:BlueStar2018|Blue Star Articles (2018)]]<br />
*[[:Category:Blue Star|Blue Star Articles (2017)]]<br />
*[[:Category:GoldStar|Gold Star Articles (2010-2016)]]<br />
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== List of New Articles in 2020 ==<br />
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[[:Category:2020New|New Articles 2020]]<br />
*[[:Category:2020Concept|Concept]]<br />
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== New Articles in 2019 ==<br />
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[[:Category:2019New|New Articles 2019]]<br />
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== John Walsh Thesis Revision ==<br />
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*[[John Walsh Thesis Revision]]<br />
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*[[:Portal:Life on Digital Worlds|Life on Digital Worlds]]<br />
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<br><br />
{| style="width:400px;"<br />
! width="250"|Category<br />
! style="width:150px;text-align:center"|Number of Pages<br />
|-<br />
|[[:Category:Action Needed|Action Needed]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Action Needed}}<br />
|-<br />
|[[:Category:Censorship|Censorship]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Censorship}}<br />
|-<br />
|[[:Category:Citations Needed|Citations Needed]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Citations Needed}}<br />
|-<br />
|[[:Category:Computer Simulation|Computer Simulation]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Computer Simulation}}<br />
|-<br />
|[[:Category:Concepts|Concepts]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Concepts}}<br />
|-<br />
|[[:Category:Corporations|Corporations]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Corporations}}<br />
|-<br />
|[[:Category:Cyberpunk (genre)|Cyberpunk]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Cyberpunk (genre)}}<br />
|-<br />
|[[:Category:Hardware|Hardware]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Hardware}}<br />
|-<br />
|[[:Category:Information Ethics|Information Ethics]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Information Ethics}}<br />
|-<br />
|[[:Category:Internet slang|Internet Slang]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Internet slang}}<br />
|-<br />
|[[:Category:Malware|Malware]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Malware}}<br />
|-<br />
|[[:Category:Media Content|Media Content]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Media Content}}<br />
|-<br />
|[[:Category:Missing Information|Missing Information]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Missing Information}}<br />
|-<br />
|[[:Category:Music|Music]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Music}}<br />
|-<br />
|[[:Category:Open Source Projects|Open Source Projects]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Open Source Projects}}<br />
|-<br />
|[[:Category:Organizations|Organizations]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Organizations}}<br />
|-<br />
|[[:Category:Out of Date|Out of Date]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Out of Date}}<br />
|-<br />
|[[:Category:People|People]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:People}}<br />
|-<br />
|[[:Category:Piracy|Piracy]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Piracy}}<br />
|-<br />
|[[:Category:Politics|Politics]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Politics}}<br />
|-<br />
|[[:Category:Portals|Portals]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Portals}}<br />
|-<br />
|[[:Category:Privacy|Privacy]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Privacy}}<br />
|-<br />
|[[:Category:Services|Services]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Services}}<br />
|-<br />
|[[:Category:Social Networking|Social Networking]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Social Networking}}<br />
|-<br />
|[[:Category:Software|Software]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Software}}<br />
|-<br />
|[[:Category:Sports|Sports]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Sports}}<br />
|-<br />
|[[:Category:Video Games|Video Games]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Video Games}}<br />
|-<br />
|[[:Category:Virtual Environments, Concerns, & Issues|Virtual Environments]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Virtual Environments, Concerns, & Issues}}<br />
|-<br />
|[[:Category:Websites|Websites]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Websites}}<br />
|}<br />
<br><br />
<br />
== Topics ==<br />
<br><br />
{{Section-Menu}}<br />
{{Section|||1}}<br />
=== # ===<br />
----<br />
*[[3D printing]]<br />
*[[4chan]]<br />
*[[4shared]]<br />
*[[8tracks]]<br />
*[[9GAG]]<br />
<br />
=== A ===<br />
----<br />
*[[Aaron Swartz]]<br />
*[[Accelerationism]]<br />
*[[Adblocking]]<br />
*[[Adobe Inc.]]<br />
*[[AdverGaming]]<br />
*[[Advertising ethics online]]<br />
*[[Aging In Place Technology]]<br />
*[[Airbnb]]<br />
*[[Alex Jones]]<br />
*[[Algorithmic Justice League]]<br />
*[[Algorithmic Audits]]<br />
*[[Algorithms]]<br />
*[[Amazon Alexa (Amazon Echo)]]<br />
*[[Amazon.com]]<br />
*[[Ancestry data]]<br />
*''the'' [[The Amy Boyer Case|Amy Boyer Case]]<br />
*[[Android]]<br />
*[[Angry Birds]]<br />
*''Anonymous''<br />
**[[Anonymous Behavior in Virtual Environments|Behavior in Virtual Environment]]<br />
**[[Anonymous (group)|Group]]<br />
*[[Apex Legends (game)]]<br />
*[[Applicant tracking systems]]<br />
*[[Artificial Agents]]<br />
*[[Artificial Intelligence and Technology]]<br />
*[[Artificial Intelligence in China]]<br />
*[[Artificial Intelligence in the Music Industry]]<br />
*[[Artificial SuperIntelligence]]<br />
*[[Ashley Madison (website)]]<br />
*[[Ask.fm]]<br />
*[[Assassin's Creed (Main Series)]]<br />
*[[Athletes and burner accounts]]<br />
*[[Augmented Reality]]<br />
*[[Automatic gender recognition]]<br />
*[[Automated Decision Making in Child Protection]]<br />
*[[Automation of Artistic Output]]<br />
*[[Autonomous Systems]]<br />
*[[Autonomous Vehicles]]<br />
*[[Avatar]]<br />
<br />
=== B ===<br />
----<br />
*[[Baidu]]<br />
*[[Banality of Simulated Evil]]<br />
*[[Bandcamp]]<br />
*[[Bartle Test]]<br />
*[[Battlestar Galactica (2004 TV Series)]]<br />
*[[Behavioral biometrics]]<br />
*[[Bias in Information]]<br />
*[[Biem App]]<br />
*[[Big Data analytics for personalized medicine]]<br />
*[[The Big Four]]<br />
*[[Binge Watching]]<br />
*[[Biobanking]]<br />
*[[BioShock]]<br />
*[[BioWare]]<br />
*[[Bitcoins]]<br />
*[[Bitmoji]]<br />
*[[BitTorrent]]<br />
*[[Black Mirror]]<br />
*[[Black Twitter]]<br />
*[[Bliss]]<br />
*[[Blizzard Entertainment]]<br />
*[[Blockchain]]<br />
*[[Borderlands (video game series)]]<br />
*[[Brain-Machine Interface]]<br />
*[[Brain-to-Brain Interface]]<br />
*[[Brave Browser]]<br />
*[[Brawl Stars]]<br />
*[[Bumble]]<br />
*[[BuzzFeed]]<br />
<br />
=== C ===<br />
----<br />
*[[Call of Duty]]<br />
*[[Cambridge Analytica]]<br />
*[[Cancel Culture]]<br />
*[[Canvas]]<br />
*[[Carrier IQ]]<br />
*[[CD Projekt]]<br />
*[[CEIU Thesis]]<br />
*[[Censorship]]<br />
*[[Censorship in China]]<br />
*[[Censorship in Turkey]]<br />
*[[CGI Influencers]]<br />
*[[Chamath Palihapitiya]]<br />
*[[Chatroulette]]<br />
*[[Cheating]]<br />
*[[Cheating in eSports]]<br />
*[[Cheating Technologies]]<br />
*[[Children's Online Privacy Protection Act (COPPA)]]<br />
*[[Circuit of Culture]]<br />
*[[Circumventing Internet Censorship]]<br />
*[[Citizendium]]<br />
*[[Civilization]]<br />
*[[Clash of Clans]]<br />
*[[Clearview AI]]<br />
*[[Click fraud]]<br />
*[[Clickbait]]<br />
*''Cloud''<br />
**[[Cloud Computing|Computing]]<br />
**[[Cloud Security|Security]]<br />
*[[Clubhouse]]<br />
*[[Clueful Chatting]]<br />
*[[Cookies]]<br />
*[[Complex]]<br />
*[[Computer Vision]]<br />
*[[Confidentiality of Online Data]]<br />
*[[Content moderation]]<br />
*[[Content moderation in Twitter]]<br />
*[[Content moderation in Reddit]]<br />
*[[Counter-Strike: Global Offensive (video game)]]<br />
*[[COVID-19 Data Privacy]]<br />
*[[Craigslist]]<br />
*[[Creative Commons]]<br />
*[[Criminal sentencing software]]<br />
*[[Crowdsourcing]]<br />
*[[Cryptocurrency]]<br />
*''Cyber (overlaps with Online)''{{Relation||Internet|#Internet}} {{Relation||Virtual|#Virtual}}<br />
**[[Cyberbullying|Bullying]] {{Relation|cases of|David Thorne|#D}}<br />
**[[Cybercurrency|Currency]]<br />
**[[Cyberlaw|Law]]<br />
**[[Cyberpunk 2077 (videogame)]]<br />
**[[Cybersex|Sex]]<br />
***''Sex in'' [[Online Dating#Sex|Online Dating]]<br />
**[[Cybersecurity]]<br />
**[[Cyberstalking|Stalking]] {{Relation|use of crowdsourcing|Human Flesh Search|#H}} {{Relation||Tiayna.cn|#T}} {{Relation|cases of|Amy Boyer|#A}}<br />
**[[Cyberwarfare|Warfare]]<br />
*[[Cybersecurity in Banking]]<br />
<br />
=== D ===<br />
----<br />
*[[Daily Fantasy Sports]]<br />
*[[Dark Patterns]]<br />
*[[Dark Web]]<br />
*''Data (overlaps with Information)''<br />
**[[Data Aggregation Online|Aggregation Online]]<br />
**[[Data Mining|Mining]]<br />
*[[Deontology]] <br />
*[[Data brokers]]<br />
*[[Datafication of Children]]<br />
*[[Dating Apps]]<br />
*[[Digital Marketing]]<br />
*[[David Thorne]]<br />
*[[Da Vinci Surgical System]]<br />
*[[Deepfake]]<br />
*[[Deepfake Detectors]]<br />
*[[Defcon (video game)]]<br />
*[[Depop]]<br />
*[[Detroit: Become Human]]<br />
*[[Deus Ex (Series)]]<br />
**[[Deus Ex: Human Revolution]]<br />
*[[Device implant]]<br />
*[[Diablo (Franchise)]]<br />
**[[Diablo II]]<br />
**[[Diablo III]]<br />
*[[Diaspora]]<br />
*''Digital''<br />
**[[Digital Property|Property]]<br />
*[[Digital_divide]]<br />
**[[Digital DJing|DJing]]<br />
**[[Digital Piracy|Piracy]]<br />
**[[Digital Rights Management|Rights Management]]<br />
*[[Disclosive Ethics]]<br />
*[[Disinformation of the COVID-19 Pandemic]]<br />
*[[DoorDash]]<br />
*[[DNA Testing]]<br />
*[[Domain Name System]]<br />
*[[Downloadable Content in Video Games]]<br />
*[[Dragonfly]]<br />
*[[Drones]]<br />
*[[Dropbox]]<br />
*[[Drupal]]<br />
*[[Duke F*** List]]<br />
<br />
=== E ===<br />
----<br />
*[[eBay]]<br />
*[[Echo Chambers]]<br />
*[[Edward Castronova]]<br />
*[[Edward H. Spence]]<br />
*[[Edward Snowden]]<br />
*[[Effective Altruism]]<br />
*[[Elder Scrolls]]<br />
*[[Electronic Arts]]<br />
*[[Electric Sheep]]<br />
*[[Electronic voting systems]]<br />
*''Electronic''<br />
**[[Electronic Health Records|Health Records]]<br />
**[[Electronic Sports|Sports]]<br />
*[[Elizabeth Holmes]]<br />
*[[Elon Musk]]<br />
*[[Empathy in Gaming]]<br />
*[[Emoji]]<br />
*[[Employers and Online Privacy]]<br />
*[[The Entire History of You]]<br />
*''Ethics''<br />
**''and'' [[Data Equity]]<br />
**''in'' [[Ethics in Computer & Video Games|Computer & Video Games]]<br />
**''in'' [[Ethics in Hacking|Hacking]]<br />
**''of'' [[Information Ethics|Information]]<br />
**''of'' [[Ethics of Advertising to Children & Teens|Advertising to Children & Teens]]<br />
**''of'' [[Ethics of Drone Warfare|Drone Warfare]]<br />
<br />
*[[Ethical game design]]<br />
*[[Etsy]]<br />
*[[Ex Machina (2014)]]<br />
*[[Experience Project]]<br />
<br />
=== F ===<br />
----<br />
*''Facebook''<br />
**[[Advertising on Facebook]]<br />
**[[Facebook|Company]]<br />
**[[Facebook Messenger]]<br />
**[[Facebook newsfeed curation]]<br />
**[[Facebook Privacy Policy|Privacy Policy]]<br />
**[[Data Mining and Manipulation]]<br />
**[[Facebook in Africa]]<br />
*[[FaceTime]]<br />
*[[Face recognition]]<br />
*[[Face recognition in law enforcement]]<br />
*[[Fake News]]<br />
*[[Fallout 76]]<br />
*[[Fan fiction]]<br />
*[[Fast Fashion]]<br />
*[[Find My Friends]]<br />
*[[File Sharing]]<br />
*[[Filter Bubble]]<br />
*[[Final Fantasy XIV]]<br />
*[[Fitness Influencers]]<br />
*[[Fitness Game]]<br />
*[[First Person Shooters]]<br />
*[[Flaming]]<br />
*[[Flash]]<br />
*[[Free Basics]]<br />
*[[Freedom of Expression]]<br />
*[[Freemium model]]<br />
<br />
=== G ===<br />
----<br />
*[[Galaxy S3]]<br />
*[[Game Addiction]]<br />
*[[Gamergate]]<br />
*[[Gattaca]]<br />
*[[Gender bias in the Online Job Search]]<br />
*[[Gender bias in Wikipedia]]<br />
*[[Gender in Video Games]]<br />
*[[Genealogy platforms]]<br />
*[[General Data Protection Regulation]]<br />
*[[Genetically Modified Food]]<br />
*[[Gene Editing]]<br />
*[[Genomics]]<br />
*[[Genovese Syndrome]]<br />
*[[Genshin Impact]]<br />
*[[Geographic Information Systems]]<br />
*[[George Hotz]]<br />
*[[Ghost Writing Online]]<br />
*[[Girls Around Me]]<br />
*[[GLANSER]]<br />
*[[GoFundMe]]<br />
*''Google''<br />
**[[Google|Company]]<br />
**[[Google Books|Books]]<br />
**[[Google Glass| Google Glass]]<br />
**[[Google Home]]<br />
**[[Google Clips]]<br />
**[[Google Street View|Street View]]<br />
**[[Google Photos]]<br />
*[[Grand Theft Auto IV]]<br />
*[[Grand Theft Auto V]]<br />
*[[Griefing]]<br />
*[[Grindr]]<br />
*[[GroupMe]]<br />
<br />
=== H ===<br />
----<br />
*[[Hackers]]<br />
*[[Hacking the 2016 US Presidential Election]]<br />
*[[Healthcare Data Monetization]]<br />
*[[Health Informatics]]<br />
*[[Her (film) (2013)]]<br />
*[[Her Interactive]]<br />
*[[Herman Tavani]]<br />
*[[High Frequency Trading]]<br />
*[[Hinge]]<br />
*[[Hulu]]<br />
*[[Human Flesh Search]] {{Relation|related to|Tianya.cn|#T}}<br />
*[[Human Microchipping]]<br />
*[["Human out of the Loop" Military Systems]]<br />
*[[Human Trafficking]]<br />
*[[Humans (British TV Series)]]<br />
<br />
=== I ===<br />
----<br />
*[[iCloud]]<br />
*[[id Software]]<br />
*[[Illegal/Unauthorized Streaming]]<br />
*[[Illegal Sports Streams]]<br />
*[[Imgur]]<br />
*[[In-app purchases]]<br />
*[[Infamous (series)]]<br />
*[[Influencer Marketing]]<br />
*[[Infoglut]]<br />
*[[Informatics]]<br />
*''Information'' {{Relation|overlaps with|Data|#Data}}<br />
**[[Information Ethics|Ethics]]<br />
**[[Information Freedom|Freedom]]<br />
**[[Freedom_of_Information_policies|Freedom of Information Policy]] <br />
**[[Information Overload|Overload]]<br />
**[[Information Reliability|Reliability]]<br />
**[[Information Security|Security]]<br />
**[[Information Transparency|Transparency]]<br />
**[[Information Vandalism|Vandalism]]<br />
*[[Informational Friction]]<br />
*[[Infosphere]]<br />
*[[Instagram]]<br />
*[[Instagram Ads]]<br />
*[[Intellectual Property]]<br />
*[[Internet of things]]<br />
*''Internet'' {{Relation|overlaps with|Cyber|#Cyber}} {{Relation||Online|#Online}} {{Relation||Virtual|#Virtual}}<br />
**[[Internet Archive|Archive]]<br />
**[[Internet Censorship in Hong Kong|Censorship in Hong Kong]]<br />
**[[Internet Censorship in South Korea|Censorship in South Korea]]<br />
**[[Internet Censorship in the United Kingdom|Censorship in the United Kingdom]]<br />
**[[Cybersecurity Law in Vietnam|Censorship in Vietnam]]<br />
**''in'' [[Circumventing Internet Censorship|Circumventing Censorship]]<br />
**[[Internet Control|Control]]<br />
**[[Internet meme|Meme]]<br />
*[[Iris Recognition]]<br />
<br />
=== J ===<br />
----<br />
*[[Jack Dorsey]]<br />
*[[Jailbreaking]]<br />
*[[James H. Moor]]<br />
*[[Jeremy Bentham]]<br />
*[[John Weckert]]<br />
*[[Julian Dibbell]]<br />
*[[Jurassic Park (1993)]]<br />
*[[Just another mediawiki page]]<br />
<br />
=== K ===<br />
----<br />
*[[Kathleen Wallace]]<br />
*[[Kay Mathiesen]]<br />
*[[Kim Dotcom]]<br />
*[[Kickstarter]]<br />
*[[Kind of Bloop]]<br />
*[[Klarna]]<br />
<br />
=== L ===<br />
----<br />
*[[LambdaMOO]]<br />
*[[Larry Ellison]]<br />
*[[Lawrence Lessig]]<br />
*[[League of Legends]]<br />
*[[The League (Dating App)]]<br />
*[[Libraries and Ethical Information Technology]]<br />
*[[LikeALittle]]<br />
*[[Limewire]]<br />
*[[Line (Application)]]<br />
*[[LinkedIn]]<br />
*[[Linus Torvalds]]<br />
*[[Live Video]]<br />
*[[Location targeted advertising]]<br />
*[[Lookbook.nu]]<br />
*[[Loot Box]]<br />
*[[Love Plus]]<br />
*[[Low Orbit Ion Cannon]]<br />
*[[Luciano Floridi]]<br />
*[[Lyft]]<br />
<br />
=== M ===<br />
----<br />
*[[Machine learning in healthcare]]<br />
*[[macOS]]<br />
*[[MagicBands]]<br />
*[[Major League Baseball]]<br />
*[[Manhunt]]<br />
*[[MapleStory]]<br />
*[[Mark Zuckerberg]]<br />
*[[Mashup]]<br />
*[[Mass Effect]]<br />
*''the'' [[The Matrix|Matrix]]<br />
*[[Internet meme|Meme]]<br />
*[[Mechanical Turk]]<br />
*[[Megaupload]]<br />
*[[Metadata]]<br />
*[[Metal Gear Solid]]<br />
*[[Mia Consalvo]]<br />
*[[Michael Kearns]]<br />
*[[Microsoft]]<br />
*[[Microsoft chatbots]]<br />
*[[Microtransactions]]<br />
*[[Miguel Sicart]]<br />
*[[Military Entertainment Complex]]<br />
*[[Minecraft]]<br />
*[[Mirai Botnet]]<br />
*[[Misinformation]]<br />
*[[MMORPGs]]<br />
*[[Mods]]<br />
*[[MOOC (Massive Open Online Courses)]]<br />
*[[Moore's Law]]<br />
*[[Morris Worm]]<br />
*[[Mortal Kombat]]<br />
*[[Mr. Robot]]<br />
*[[Music piracy]]<br />
*[[MuslimPro]]<br />
*[[Myanmar Social Media Blackout]]<br />
*[[Myspace]]<br />
<br />
=== N ===<br />
----<br />
*[[Naughty Dog]]<br />
*[[Napster]]<br />
*[[National Security Agency]]<br />
*[[NBA Top Shot]]<br />
*[[NSA Cryptography]]<br />
*[[NCAA Football (Video Game Series)]]<br />
*[[Need For Speed (Video Game Series)]]<br />
*[[Nest Thermostat]]<br />
*[[Net neutrality]]<br />
*[[Netflix]]<br />
*[[Nextdoor]]<br />
*[[NFT Art]]<br />
*[[Norbert Wiener]]<br />
*[[Nosedive, Black Mirror]]<br />
*[[Nymwars]]<br />
<br />
=== O ===<br />
----<br />
*[[OK The Pirate Bay]]<br />
*[[Omegle]]<br />
*[[One America News Network (OANN)]]<br />
*''Online'' {{Relation|overlaps with|Cyber|#Cyber}} {{Relation||Internet|#Internet}} {{Relation||Virtual|#Virtual}}<br />
**[[Cyberbullying|Bullying]] ''in Cyberspace''<br />
**[[Online Cheating|Cheating]]<br />
**[[Online Dating|Dating]]<br />
***[[Online Dating - Catfishing Edition|Catfishing]]<br />
**[[Online Gambling|Gambling]]<br />
**[[Online Identity|Identity]]<br />
**[[Online Identity Theft|Identity Theft]]<br />
**[[Libel Online|Libel]]<br />
**[[Online Poker]]<br />
**[[Online Reputation Systems|Reputation Systems]]<br />
**''Sex in'' [[Online Dating#Sex|Online Dating]]<br />
**[[Online shopping|Shopping]]<br />
**[[Cyberstalking|Stalking]] ''in CyberSpace''<br />
*[[Old School Runescape]]<br />
*[[The Open Internet|Open Internet]]<br />
*[[Onavo]]<br />
*[[OnlyFans]]<br />
*[[OnStar]]<br />
*[[OpenAi]]<br />
*[[Orwell (Video Game)]]<br />
*[[Overwatch]]<br />
*[[Open Source Software]]<br />
<br />
=== P ===<br />
----<br />
*[[Palantir Technologies]]<br />
*[[Pandora]]<br />
*[[Parasocial Relationship]]<br />
*[[PARO Therapeutic Robot]]<br />
*[[Parody]]<br />
*[[Parler]]<br />
*[[Patents]]<br />
*[[PayDay 2]]<br />
*[[PayPal]]<br />
*[[Periscope]]<br />
*[[Peter Thiel]]<br />
*[[Philip Brey]]<br />
*''Photo'' {{Relation|issues of|Digital Photography|#D}}<br />
**[[Photo Editing|Editing]]<br />
**[[Phototruth|Truth]]<br />
*[[Pinterest]]<br />
*[[The Pirate Bay|Pirate Bay]]<br />
*[[Plagiarism]]<br />
*[[PlayerUnknown's Battlegrounds]]<br />
*[[PlayStation Party Recording]]<br />
*[[Pokémon Go]]<br />
*[[PokerStars]]<br />
*[[Pornography]]<br />
*[[Portal 2]]<br />
*[[Postal 2]]<br />
*[[Prank YouTubers]]<br />
*[[Predictive Policing]]<br />
*''Privacy''<br />
**[[Facebook Privacy Policy|Facebook Policy]]<br />
**''in'' [[Privacy in the China|China]]<br />
**''in'' [[Privacy in the Online Environment|Online Enviornment]]<br />
**''in'' [[Privacy in Social Networking|Social Networking]]<br />
**''in'' [[Privacy in public]]<br />
**[[Privacy Policies at Apple Inc.|Apple Policy]]<br />
*[[Privacy in Venmo]]<br />
*[[Privacy in the China]]<br />
*[[Pro-Ana Forums]]<br />
*[[Protect IP Act]]<br />
*[[Proxy Culture]]<br />
*[[Public Morality]]<br />
*[[The Punisher]]<br />
*[[Punishments in Virtual Environments]]<br />
<br />
===Q ===<br />
-----<br />
*[[QR Codes]]<br />
*[[Quora]]<br />
*[[Quantified Self Movement]]<br />
*[[Quantum Computing]]<br />
=== R ===<br />
----<br />
*[[Racial Algorithmic Bias]]<br />
*[[Racism in Video Games]]<br />
*[[Radio-frequency Identification]]<br />
*[[Ransomware]]<br />
*[[Raph Koster]]<br />
*[[Rapsodo]]<br />
*[[Ray Kurzweil]]<br />
*[[Real Fake Page]]<br />
*[[Real Money Trade]]<br />
*[[Recommender Systems]]<br />
*[[Reddit]]<br />
**[[/r/AmITheAsshole]]<br />
**[[/r/wallstreetbets]]<br />
**[[/r/2meirl4meirl]]<br />
*[[Reid Hoffman]]<br />
*[[Remote Access]]<br />
*[[Renren]]<br />
*[[Revenge Porn]]<br />
*[[Richard Stallman]]<br />
*[[Right to be Forgotten]]<br />
*[[RIP Trolling]]<br />
*[[Rockmelt]]<br />
*[[Role of Parents in Internet Censorship]]<br />
*[[Rumble Fighter]]<br />
<br />
=== S ===<br />
------<br />
*[[Sampling (hip hop)]]<br />
*[[Self Driving Cars]]<br />
*[[Sergey Aleynikov]]<br />
*[[Serious Games]]<br />
*[[Senior Citizens]]<br />
*[[Sexting]]<br />
*[[Sharing Subscription Services]]<br />
*''Sims''<br />
**[[The Sims 3|The Sims 3]]<br />
**[[The Sims Online|The Sims Online]]<br />
**[[The Sims 4|The Sims 4]]<br />
*[[SingularityNet]]<br />
*[[Slack (Application)]]<br />
*[[Smart Doorbell]]<br />
*[[Smart Home]]<br />
*[[Smartphones (Location Services)]]<br />
*[[SNAP and Other Federal Nutrition Programs]]<br />
*[[Soccer & FIFA]]<br />
*[[Social Credit System]]<br />
*''Social''<br />
**[[Social Media in Sports|Media in Sports]]<br />
**[[Social media in national elections (2016)]]<br />
**[[Social Networking|Networking]]<br />
**[[Social Networking Services|Networking Services]] {{Relation|for sites|Facebook|Facebook}} {{Relation||Tianya.cn|Tianya.cn}} {{Relation||Twitter|Twitter}} {{Relation||Tumblr|Tumblr}}<br />
**[[Social Media (Meta)|Media (Meta)]]<br />
*[[Social Media and Depression]]<br />
*[[Social media and the 2020 US presidential election]]<br />
*[[Social Media Websites in Investigations]]<br />
*[[Solar Winds Hack]]<br />
* [[Sousveillance]]<br />
*[[Snapchat]]<br />
*[[Spam]]<br />
*[[Spoof]]<br />
*[[Spotify]]<br />
*[[Spycams in South Korea]]<br />
*[[Starcraft II]]<br />
*[[Statistical Modeling]]<br />
*[[Steam]]<br />
*[[Steve Jobs]]<br />
*[[Stop Online Piracy Act]]<br />
*[[Student-Athlete Social Media Monitoring]]<br />
*[[StumbleUpon]]<br />
*[[Stuxnet Trojan]] {{Relation|type of|Worm|#W}} {{Relation|utilizes|Rootkit|#R}}<br />
*[[Suits]]<br />
*[[Super Smash Bros. Ultimate]]<br />
*[[Surveillance Capitalism]]<br />
*[[Surveillance in China]]<br />
*[[Surveillance Technologies]]<br />
*[[Sword Art Online]]<br />
<br />
=== T ===<br />
------<br />
*[[Targeted Advertising (Online)]]<br />
*[[Team Fortress 2]]<br />
*[[Technological Determinism]]<br />
*[[Technological Singularity]]<br />
*[[Telepresence]]<br />
*[[Tencent]]<br />
*[[Tesla, Inc.]]<br />
*[[Testimonials]]<br />
*[[The Truman Show]]<br />
*[[The Internet's Footprint]]<br />
*[[Thomas M. Powers]]<br />
*[[Tianya.cn]]<br />
*[[TikTok]]<br />
*[[TikTok Subcultures]]<br />
*[[Tim Berners-Lee]]<br />
*[[Tinder]]<br />
*[[Tor]]<br />
*[[Touch ID]]<br />
*[[Transhumanism]]<br />
*[[Transparency in software development]]<br />
*[[Tristan Harris]]<br />
*[[Trustworthiness of information]]<br />
*[[Troll]]<br />
*[[Tumblr]]<br />
*[[Twitter]]<br />
*[[Twitch.tv]]<br />
<br />
=== U ===<br />
----<br />
*[[Uber]]<br />
*[[Ubiquitous Computing]]<br />
*[[Unabomber Manifesto]]<br />
*[[Uniqueness Debate]]<br />
*[[Undertale]]<br />
*[[Utilitarian Philosophy]]<br />
<br />
=== V ===<br />
----<br />
*[[Valorant]]<br />
*[[Valve]]<br />
*[[Value Sensitive Design]]<br />
*[[Venmo]]<br />
*''Virtual'' {{Relation|overlaps with|Cyber|#Cyber}} {{Relation||Internet|#Internet}} {{Relation||Online|#Online}}<br />
**[[Virtual Assistants]]<br />
**''Bullying in'' [[Cyberbullying|Cyberspace]]<br />
**[[Virtual Child Pornography|Child Pornography]]<br />
**[[Virtual Community|Community]]<br />
**[[Virtual Crimes and Punishments|Crimes and Punishments]]<br />
** ''Dating ''[[Online Dating#Virtual_Dating|Online]]<br />
**[[Virtual Dating Simulations|Dating Simulations]]<br />
**[[Virtual Environment|Environment]]<br />
**[[Punishments in Virtual Environments|Punishment]]<br />
**[[Virtual Private Network|Private Network]]<br />
**[[Virtual Rape|Rape]]<br />
**''Sex in'' [[Cybersex|Cyberspace]]<br />
**''Stalking in'' [[Cyberstalking|Cyberspace]]<br />
*[[Virtual sweatshops]]<br />
*[[Violence and video games]]<br />
*[[Violence in Video Games]]<br />
*[[Virtual Magic Kingdom]]<br />
*[[Virtual Private Network (VPN)]]<br />
*[[Virtual Reality and Computer Simulations]]<br />
*[[Virtual Reality in Prison]]<br />
*[[Video Surveillance]]<br />
*[[Voice imitation algorithms]]<br />
*[[Vlogging]]<br />
*[[Vuze]]<br />
<br />
=== W ===<br />
----<br />
*[[Warcraft III]]<br />
*[[Watch Dogs]]<br />
*[[Watson (computer)]]<br />
*[[Wattpad]]<br />
*[[Waze]]<br />
*[[Wearable health tech]]<br />
*[[Web 2.0]]<br />
*[[Webcams]]<br />
*[[Webtoon App]]<br />
*[[WeChat]]<br />
**[[Misinformation on WeChat]]<br />
*[[Weibo]]<br />
*[[Westworld and AI]]<br />
*[[WhatsApp]]<br />
*[[Whisper]]<br />
*[[Wii U]]<br />
*[[WikiLeaks]]<br />
*[[Wikipedia]]<br />
**[[Wikipedia Bots|Bots]]<br />
**[[Gender bias in Wikipedia]]<br />
*[[Witcher 3: Wild Hunt]]<br />
*[[Women in Gaming]]<br />
*[[World of Warcraft]]<br />
<br />
=== X ===<br />
----<br />
*[[The X-Files]]<br />
*[[Xkcd]]<br />
<br />
<br />
=== Y ===<br />
----<br />
*[[Yelp Reviewing]]<br />
*[[Yik Yak]]<br />
*''YouTube''<br />
**[[YouTube|YouTube (Website)]]<br />
**[[YouTube Beauty Community|Beauty Community]]<br />
**[[YouTube recommendation algorithm]]<br />
<br />
=== Z ===<br />
----<br />
*[[Zoom]]<br />
*[[Zynga]]</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brawlstars&diff=96529Brawlstars2021-03-12T14:16:51Z<p>Ptse: </p>
<hr />
<div>Brawl Stars is a multiplayer mobile game created by Supercell. Supercell has made many successful mobile games in the past, such as Clash of Clans and Clash Royale. Brawl Stars was released in 2017 and is their most recent release. While Brawl Stars has been just as fun as Supercell’s past games, there are some ethical concerns regarding its business model.</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Patrick_Tse&diff=94553Patrick Tse2021-03-04T22:50:56Z<p>Ptse: </p>
<hr />
<div><br />
== '''Introduction''' ==<br />
<br />
Personally, I find the Internet somewhat scary because of how easy it is for people to access information through the Internet. Because of this, most of my social media accounts are private and I also am not very active on my social media. I do play a few video games, mobile and console. These games collect data for their benefit as well. However, most of the information is only the data from my gameplay and not any of my personal information. Overall, I believe my data identity accurately represents a small part of my whole identity.<br />
<br />
== '''Google Search''' ==<br />
[[File:Old patrick.png|thumbnail|right|Google Search for Patrick Tse]]<br />
Aside from having private social media accounts, there is a bigger problem when you google “Patrick Tse.” The first person who shows up is an actor, producer, screenwriter, and director in Hong Kong cinema. It makes sense that a university student does not show up compared to this Hong Kong celebrity. He takes up almost the first four pages when searched up. To try to narrow down the search, I tried typing my name with my middle name as well. To my surprise, there were still no results near what I was looking for. The Hong Kong celebrity showed up again… Since even typing in my full name did not yield any results I wanted to see how specific the searches had to be for anything about me to show up. After searching my name attached with something that could potentially be related to me, I finally got something! When I searched “patrick tse california,” California is where I am from, my LinkedIn account was the first result that showed up. I realized this was because my LinkedIn account has information I inputted about where I went to high school in California. When I searched up “patrick tse michigan” my LinkedIn is also the first result because it has information about me attending the University of Michigan. All my other social media accounts do not have any information about where I am from, so it would make sense why they did not show up. I attempted to search for my Facebook and Instagram as well. However, for Facebook there were quite a few other Patrick Tses. After scrolling through for a while I still could not find myself. Although searching for my Facebook was unsuccessful, I was able to find my Instagram. I had to search up my username for it to be found. Even though I was able to find it, my account is private.<br />
<br />
One thing I realized while searching for information on myself is that social media has become a political piece of technology. In Winner’s, Do Artifacts Have Politics?, he discusses the idea of certain pieces of technology being inherently political. This means that the piece of technology needs some sort of political structure of control to make sure it is not used in the wrong context. However, social media has created its own sort of politics around it. The popularity of people and their appearance on their social media have become extremely important. For example, my LinkedIn showing up in a simple google search matters because employers can see my profile. My LinkedIn has information about me that hopefully represents a side of me that has qualities that are desirable to an employer. My past job experiences, education, etc. are all on my LinkedIn. Given the pretext that LinkedIn is more of a professional social media platform, it would make sense for a user to only put information that would be appropriate in a workplace. For that reason, my LinkedIn account by no means represents all of me, but it is the main thing that shows up when my name is googled. It was a political decision by me to keep my other social media accounts more private and to have my LinkedIn more exposed. If someone were to find me online, their first impression of me hopefully would be someone who is professional and well put together. <br />
<br />
To conclude, basing the search solely on Google, the search has to be quite specific to get any sort of meaningful result. This is mostly because I enjoy my privacy from others on the web who I do not know. Although there seems to be a minimal amount of information from a basic google search, there is a lot of my information out there. From making accounts for games to putting my email on a mailing list, I have no idea how many accounts I have created for a variety of things.<br />
<br />
== '''App/Account Data''' ==<br />
<br />
Whether it’s a new game on my phone or creating an account to get free shipping, my information is all over the place. The main pieces of data that all these services ask for are name, phone number, and email. Personally, I do not find giving such basic information a problem. I do not think giving my phone number or email does much harm. While they have my contact information, it is my decision to engage or ignore whoever contacts me. However, there are certain things that I have signed up for that require quite sensitive information. For example, the app Webull, a stock trading platform, required that I input my social security number. In this case, I know that Webull is a reliable app because I personally know people who have used this app and have had no problems with it. While I know that the app is most likely reliable, I always feel as if you should still be weary when giving such private information. A couple of years ago, I had an incident where a college I had applied to informed me that they had been hacked and that some of the information about applicants and students had been stolen. Thankfully nothing happened to me personally, but it shows that systems that seem to be safe may not always be safe. <br />
<br />
===Game Data===<br />
[[File:Brawlstars.PNG|thumbnail|right|screenshot of the game Brawlstars]]<br />
One of the things that intrigues me is the data that is gathered on mobile and video games. In many of the games I play, especially mobile, there are in-app purchases. There are typically two types of currencies: one that is more easily acquired and one that is harder to acquire but money in real life can be used to purchase more of this currency. The one that can be bought with money typically can help you gain materials that will make the game easier or more fun. One of the mobile games that I currently play, Brawlstars, has this same sort of model. Without getting into too much detail about the game itself, the main points about the game that I want to discuss is how currency is acquired and how materials are bought. In the game, there are two currencies: coins and gems. Coins are the more easily attained currency and gems are the currency that can be bought through in-app purchase. One important thing to note is that coins can also be bought in exchange for gems. When buying materials to upgrade your characters, sometimes the exact materials needed to upgrade a character will show up. The catch is that many times it will end up costing a hefty amount to get those materials. Since the materials in the shop change daily, it incentivizes users to spend real money to get those materials. The fact that this situation consistently happens lets me know that the game is clearly monitoring my progress and trying to get me to spend money, which is most likely part of the business model. While this data is only contained within the game and does not have any effect on my life, I find it interesting how the data is used. Just in the way that some sites have targeted ads, some games use the users’ data to gain an advantage on them.<br />
<br />
== '''Conclusion''' ==<br />
<br />
Searching the Internet for myself was quite interesting. I knew from the start that it would not be easy to find myself online due to my social media accounts being private. Because LinkedIn was the only social media platform I could find on myself, I believe my data identity does not well represent me as a whole. My LinkedIn profile is strictly my professional identity. It does not include anything about my hobbies or any of my private information. While my data identity does not fully represent me, that is actually more of a relief to me. If my data identity was a very accurate representation of myself, that would mean that there is a considerable amount of information about me that is public. Since that is not the case, that means that I am keeping my digital footprint to a minimum which is exactly what I want!</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Patrick_Tse&diff=94548Patrick Tse2021-03-04T22:45:50Z<p>Ptse: </p>
<hr />
<div><br />
== '''Introduction''' ==<br />
<br />
Personally, I find the Internet somewhat scary because of how easy it is for people to access information through the Internet. Because of this, most of my social media accounts are private and I also am not very active on my social media. I do play a few video games, mobile and console. These games also collect data for their benefit as well. However, most of the information is only the data from my game and not my personal information. Overall, I believe that my data identity accurately represents only a part of my whole identity.<br />
<br />
== '''Google Search''' ==<br />
[[File:Old patrick.png|thumbnail|right|Google Search for Patrick Tse]]<br />
Aside from having private social media accounts, there is a bigger problem when you google “Patrick Tse.” The first person who shows up is an actor, producer, screenwriter, and director in Hong Kong cinema. It makes sense that a university student does not show up compared to this Hong Kong celebrity. He takes up almost the first four pages when searched up. To try to narrow down the search, I tried typing my name with my middle name as well. To my surprise, there were still no results near what I was looking for. The Hong Kong celebrity showed up again… Since even typing in my full name did not yield any results I wanted to see how specific the searches had to be for anything about me to show up. After searching my name attached with something that could potentially be related to me, I finally got something! When I searched “patrick tse california,” California is where I am from, my LinkedIn account was the first result that showed up. I realized this was because my LinkedIn account has information I inputted about where I went to high school in California. When I searched up “patrick tse michigan” my LinkedIn is also the first result because it has information about me attending the University of Michigan. All my other social media accounts do not have any information about where I am from, so it would make sense why they did not show up. I attempted to search for my Facebook and Instagram as well. However, for Facebook there were quite a few other Patrick Tses. After scrolling through for a while I still could not find myself. Although searching for my Facebook was unsuccessful, I was able to find my Instagram. I had to search up my username for it to be found. Even though I was able to find it, my account is private.<br />
<br />
One thing I realized while searching for information on myself is that social media has become a political piece of technology. In Winner’s, Do Artifacts Have Politics?, he discusses the idea of certain pieces of technology being inherently political. This means that the piece of technology needs some sort of political structure of control to make sure it is not used in the wrong context. However, social media has created its own sort of politics around it. The popularity of people and their appearance on their social media have become extremely important. For example, my LinkedIn showing up in a simple google search matters because employers can see my profile. My LinkedIn has information about me that hopefully represents a side of me that has qualities that are desirable to an employer. My past job experiences, education, etc. are all on my LinkedIn. Given the pretext that LinkedIn is more of a professional social media platform, it would make sense for a user to only put information that would be appropriate in a workplace. For that reason, my LinkedIn account by no means represents all of me, but it is the main thing that shows up when my name is googled. It was a political decision by me to keep my other social media accounts more private and to have my LinkedIn more exposed. If someone were to find me online, their first impression of me hopefully would be someone who is professional and well put together. <br />
<br />
To conclude, basing the search solely on Google, the search has to be quite specific to get any sort of meaningful result. This is mostly because I enjoy my privacy from others on the web who I do not know. Although there seems to be a minimal amount of information from a basic google search, there is a lot of my information out there. From making accounts for games to putting my email on a mailing list, I have no idea how many accounts I have created for a variety of things.<br />
<br />
== '''App/Account Data''' ==<br />
<br />
Whether it’s a new game on my phone or creating an account to get free shipping, my information is all over the place. The main pieces of data that all these services ask for are name, phone number, and email. Personally, I do not find giving such basic information a problem. I do not think giving my phone number or email does much harm. While they have my contact information, it is my decision to engage or ignore whoever contacts me. However, there are certain things that I have signed up for that require quite sensitive information. For example, the app Webull, a stock trading platform, required that I input my social security number. In this case, I know that Webull is a reliable app because I personally know people who have used this app and have had no problems with it. While I know that the app is most likely reliable, I always feel as if you should still be weary when giving such private information. A couple of years ago, I had an incident where a college I had applied to informed me that they had been hacked and that some of the information about applicants and students had been stolen. Thankfully nothing happened to me personally, but it shows that systems that seem to be safe may not always be safe. <br />
<br />
===Game Data===<br />
[[File:Brawlstars.PNG|thumbnail|right|screenshot of the game Brawlstars]]<br />
One of the things that intrigues me is the data that is gathered on mobile and video games. In many of the games I play, especially mobile, there are in-app purchases. There are typically two types of currencies: one that is more easily acquired and one that is harder to acquire but money in real life can be used to purchase more of this currency. The one that can be bought with money typically can help you gain materials that will make the game easier or more fun. One of the mobile games that I currently play, Brawlstars, has this same sort of model. Without getting into too much detail about the game itself, the main points about the game that I want to discuss is how currency is acquired and how materials are bought. In the game, there are two currencies: coins and gems. Coins are the more easily attained currency and gems are the currency that can be bought through in-app purchase. One important thing to note is that coins can also be bought in exchange for gems. When buying materials to upgrade your characters, sometimes the exact materials needed to upgrade a character will show up. The catch is that many times it will end up costing a hefty amount to get those materials. Since the materials in the shop change daily, it incentivizes users to spend real money to get those materials. The fact that this situation consistently happens lets me know that the game is clearly monitoring my progress and trying to get me to spend money, which is most likely part of the business model. While this data is only contained within the game and does not have any effect on my life, I find it interesting how the data is used. Just in the way that some sites have targeted ads, some games use the users’ data to gain an advantage on them.<br />
<br />
== '''Conclusion''' ==<br />
<br />
Searching the Internet for myself was quite interesting. I knew from the start that it would not be easy to find myself online due to my social media accounts being private. Because LinkedIn was the only social media platform I could find on myself, I believe my data identity does not well represent me as a whole. My LinkedIn profile is strictly my professional identity. It does not include anything about my hobbies or any of my private information. While my data identity does not fully represent me, that is actually more of a relief to me. If my data identity was a very accurate representation of myself, that would mean that there is a considerable amount of information about me that is public. Since that is not the case, that means that I am keeping my digital footprint to a minimum which is exactly what I want!</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Brawlstars&diff=94204Brawlstars2021-02-25T14:29:28Z<p>Ptse: Created page with "Brawlstars is a game made by the company Supercell."</p>
<hr />
<div>Brawlstars is a game made by the company Supercell.</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Topics&diff=94203Topics2021-02-25T14:29:07Z<p>Ptse: /* B */</p>
<hr />
<div>http://si410ethics11.projects.si.umich.edu/images/topics.png<br />
<br />
''Please add your newly created pages to this list in alphabetical order, and remember to surround with the appropriate MediaWiki syntax (i.e.:'' <nowiki>*[[your page]]</nowiki>'').''<br />
<br />
<br />
__NOTOC__<br />
<br />
<br />
== Blue Star Articles ==<br />
<br/><br />
*[[:Category:BlueStar2019|Blue Star Articles (2019)]]<br />
*[[:Category:BlueStar2018|Blue Star Articles (2018)]]<br />
*[[:Category:Blue Star|Blue Star Articles (2017)]]<br />
*[[:Category:GoldStar|Gold Star Articles (2010-2016)]]<br />
<br><br />
<br />
== List of New Articles in 2020 ==<br />
<br><br />
[[:Category:2020New|New Articles 2020]]<br />
*[[:Category:2020Concept|Concept]]<br />
*[[:Category:2020Person|Person]]<br />
*[[:Category:2020Object|Object]]<br />
<br><br />
<br />
== New Articles in 2019 ==<br />
<br><br />
[[:Category:2019New|New Articles 2019]]<br />
<br><br />
<br />
== John Walsh Thesis Revision ==<br />
<br/><br />
*[[John Walsh Thesis Revision]]<br />
<br />
== Portals and Class Writing Exercises ==<br />
<br><br />
*[[:Portal:Life on Digital Worlds|Life on Digital Worlds]]<br />
<br/><br />
<br />
== Categories ==<br />
<br><br />
{| style="width:400px;"<br />
! width="250"|Category<br />
! style="width:150px;text-align:center"|Number of Pages<br />
|-<br />
|[[:Category:Action Needed|Action Needed]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Action Needed}}<br />
|-<br />
|[[:Category:Censorship|Censorship]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Censorship}}<br />
|-<br />
|[[:Category:Citations Needed|Citations Needed]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Citations Needed}}<br />
|-<br />
|[[:Category:Computer Simulation|Computer Simulation]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Computer Simulation}}<br />
|-<br />
|[[:Category:Concepts|Concepts]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Concepts}}<br />
|-<br />
|[[:Category:Corporations|Corporations]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Corporations}}<br />
|-<br />
|[[:Category:Cyberpunk (genre)|Cyberpunk]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Cyberpunk (genre)}}<br />
|-<br />
|[[:Category:Hardware|Hardware]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Hardware}}<br />
|-<br />
|[[:Category:Information Ethics|Information Ethics]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Information Ethics}}<br />
|-<br />
|[[:Category:Internet slang|Internet Slang]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Internet slang}}<br />
|-<br />
|[[:Category:Malware|Malware]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Malware}}<br />
|-<br />
|[[:Category:Media Content|Media Content]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Media Content}}<br />
|-<br />
|[[:Category:Missing Information|Missing Information]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Missing Information}}<br />
|-<br />
|[[:Category:Music|Music]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Music}}<br />
|-<br />
|[[:Category:Open Source Projects|Open Source Projects]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Open Source Projects}}<br />
|-<br />
|[[:Category:Organizations|Organizations]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Organizations}}<br />
|-<br />
|[[:Category:Out of Date|Out of Date]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Out of Date}}<br />
|-<br />
|[[:Category:People|People]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:People}}<br />
|-<br />
|[[:Category:Piracy|Piracy]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Piracy}}<br />
|-<br />
|[[:Category:Politics|Politics]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Politics}}<br />
|-<br />
|[[:Category:Portals|Portals]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Portals}}<br />
|-<br />
|[[:Category:Privacy|Privacy]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Privacy}}<br />
|-<br />
|[[:Category:Services|Services]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Services}}<br />
|-<br />
|[[:Category:Social Networking|Social Networking]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Social Networking}}<br />
|-<br />
|[[:Category:Software|Software]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Software}}<br />
|-<br />
|[[:Category:Sports|Sports]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Sports}}<br />
|-<br />
|[[:Category:Video Games|Video Games]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Video Games}}<br />
|-<br />
|[[:Category:Virtual Environments, Concerns, & Issues|Virtual Environments]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Virtual Environments, Concerns, & Issues}}<br />
|-<br />
|[[:Category:Websites|Websites]]<br />
|style="text-align:center"| {{PAGESINCATEGORY:Websites}}<br />
|}<br />
<br><br />
<br />
== Topics ==<br />
<br><br />
{{Section-Menu}}<br />
{{Section|||1}}<br />
=== # ===<br />
----<br />
*[[3D printing]]<br />
*[[4chan]]<br />
*[[4shared]]<br />
*[[8tracks]]<br />
*[[9GAG]]<br />
<br />
=== A ===<br />
----<br />
*[[Aaron Swartz]]<br />
*[[Adblocking]]<br />
*[[Adobe Inc.]]<br />
*[[AdverGaming]]<br />
*[[Advertising ethics online]]<br />
*[[Aging In Place Technology]]<br />
*[[Airbnb]]<br />
*[[Alex Jones]]<br />
*[[Algorithmic Justice League]]<br />
*[[Algorithms]]<br />
*[[Amazon Alexa (Amazon Echo)]]<br />
*[[Amazon.com]]<br />
*[[Ancestry data]]<br />
*''the'' [[The Amy Boyer Case|Amy Boyer Case]]<br />
*[[Android]]<br />
*[[Angry Birds]]<br />
*''Anonymous''<br />
**[[Anonymous Behavior in Virtual Environments|Behavior in Virtual Environment]]<br />
**[[Anonymous (group)|Group]]<br />
*[[Apex Legends (game)]]<br />
*[[Applicant tracking systems]]<br />
*[[Artificial Agents]]<br />
*[[Artificial Intelligence and Technology]]<br />
*[[Artificial Intelligence in China]]<br />
*[[Artificial Intelligence in the Music Industry]]<br />
*[[Artificial SuperIntelligence]]<br />
*[[Ashley Madison (website)]]<br />
*[[Ask.fm]]<br />
*[[Assassin's Creed (Main Series)]]<br />
*[[Athletes and burner accounts]]<br />
*[[Augmented Reality]]<br />
*[[Automatic gender recognition]]<br />
*[[Automation]]<br />
*[[Autonomous Systems]]<br />
*[[Autonomous Vehicles]]<br />
*[[Avatar]]<br />
<br />
=== B ===<br />
----<br />
*[[Banality of Simulated Evil]]<br />
*[[Bandcamp]]<br />
*[[Bartle Test]]<br />
*[[Battlestar Galactica (2004 TV Series)]]<br />
*[[Behavioral biometrics]]<br />
*[[Bias in Information]]<br />
*[[Biem App]]<br />
*[[Big Data analytics for personalized medicine]]<br />
*[[The Big Four]]<br />
*[[Binge Watching]]<br />
*[[Biobanking]]<br />
*[[BioShock]]<br />
*[[BioWare]]<br />
*[[Bitcoins]]<br />
*[[Bitmoji]]<br />
*[[BitTorrent]]<br />
*[[Black Mirror]]<br />
*[[Black Twitter]]<br />
*[[Bliss]]<br />
*[[Blizzard Entertainment]]<br />
*[[Blockchain]]<br />
*[[Borderlands (video game series)]]<br />
*[[Brain-Machine Interface]]<br />
*[[Brave Browser]]<br />
*[[Brawlstars]]<br />
*[[Bumble]]<br />
*[[BuzzFeed]]<br />
<br />
=== C ===<br />
----<br />
*[[Call of Duty]]<br />
*[[Cambridge Analytica]]<br />
*[[Cancel Culture]]<br />
*[[Canvas]]<br />
*[[Carrier IQ]]<br />
*[[CD Projekt]]<br />
*[[CEIU Thesis]]<br />
*[[Censorship]]<br />
*[[Censorship in China]]<br />
*[[Chamath Palihapitiya]]<br />
*[[Chatroulette]]<br />
*[[Cheating]]<br />
*[[Cheating in eSports]]<br />
*[[Cheating Technologies]]<br />
*[[Circumventing Internet Censorship]]<br />
*[[Citizendium]]<br />
*[[Civilization]]<br />
*[[Clash of Clans]]<br />
*[[Clearview AI]]<br />
*[[Click fraud]]<br />
*[[Clickbait]]<br />
*''Cloud''<br />
**[[Cloud Computing|Computing]]<br />
**[[Cloud Security|Security]]<br />
*[[Clubhouse]]<br />
*[[Clueful Chatting]]<br />
*[[Cookies]]<br />
*[[Complex]]<br />
*[[Confidentiality of Online Data]]<br />
*[[Content moderation]]<br />
*[[Content moderation in Twitter]]<br />
*[[Content moderation in Reddit]]<br />
*[[Counter-Strike: Global Offensive (video game)]]<br />
*[[Craigslist]]<br />
*[[Creative Commons]]<br />
*[[Criminal sentencing software]]<br />
*[[Crowdsourcing]]<br />
*[[Cryptocurrency]]<br />
*''Cyber (overlaps with Online)''{{Relation||Internet|#Internet}} {{Relation||Virtual|#Virtual}}<br />
**[[Cyberbullying|Bullying]] {{Relation|cases of|David Thorne|#D}}<br />
**[[Cybercurrency|Currency]]<br />
**[[Cyberlaw|Law]]<br />
**[[Cyberpunk 2077 (videogame)]]<br />
**[[Cybersex|Sex]]<br />
***''Sex in'' [[Online Dating#Sex|Online Dating]]<br />
**[[Cybersecurity]]<br />
**[[Cyberstalking|Stalking]] {{Relation|use of crowdsourcing|Human Flesh Search|#H}} {{Relation||Tiayna.cn|#T}} {{Relation|cases of|Amy Boyer|#A}}<br />
**[[Cyberwarfare|Warfare]]<br />
*[[Cybersecurity in Banking]]<br />
<br />
=== D ===<br />
----<br />
*[[Daily Fantasy Sports]]<br />
*[[Dark Patterns]]<br />
*[[Dark Web]]<br />
*''Data (overlaps with Information)''<br />
**[[Data Aggregation Online|Aggregation Online]]<br />
**[[Data Mining|Mining]]<br />
*[[Deontology]] <br />
*[[Data brokers]]<br />
*[[Datafication of Children]]<br />
*[[Dating Apps]]<br />
*[[Digital Marketing]]<br />
*[[David Thorne]]<br />
*[[Da Vinci Surgical System]]<br />
*[[Deepfake]]<br />
*[[Defcon (video game)]]<br />
*[[Depop]]<br />
*[[Detroit: Become Human]]<br />
*[[Deus Ex (Series)]]<br />
**[[Deus Ex: Human Revolution]]<br />
*[[Device implant]]<br />
*[[Diablo (Franchise)]]<br />
**[[Diablo II]]<br />
**[[Diablo III]]<br />
*[[Diaspora]]<br />
*''Digital''<br />
**[[Digital Property|Property]]<br />
*[[Digital_divide]]<br />
**[[Digital DJing|DJing]]<br />
**[[Digital Piracy|Piracy]]<br />
**[[Digital Rights Management|Rights Management]]<br />
*[[Dipsea]]<br />
*[[Disclosive Ethics]]<br />
*[[DoorDash]]<br />
*[[DNA Testing]]<br />
*[[Domain Name System]]<br />
*[[Downloadable Content in Video Games]]<br />
*[[Dragonfly]]<br />
*[[Drones]]<br />
*[[Dropbox]]<br />
*[[Drupal]]<br />
*[[Duke F*** List]]<br />
<br />
=== E ===<br />
----<br />
*[[eBay]]<br />
*[[Echo Chambers]]<br />
*[[Edward Castronova]]<br />
*[[Edward H. Spence]]<br />
*[[Edward Snowden]]<br />
*[[Effective Altruism]]<br />
*[[Elder Scrolls]]<br />
*[[Electronic Arts]]<br />
*[[Electric Sheep]]<br />
*[[Electronic voting systems]]<br />
*''Electronic''<br />
**[[Electronic Health Records|Health Records]]<br />
**[[Electronic Sports|Sports]]<br />
*[[Elizabeth Holmes]]<br />
*[[Elon Musk]]<br />
*[[Empathy in Gaming]]<br />
*[[Emoji]]<br />
*[[Employers and Online Privacy]]<br />
*[[The Entire History of You]]<br />
*''Ethics''<br />
**''and'' [[Data Equity]]<br />
**''in'' [[Ethics in Computer & Video Games|Computer & Video Games]]<br />
**''in'' [[Ethics in Hacking|Hacking]]<br />
**''of'' [[Information Ethics|Information]]<br />
**''of'' [[Ethics of Advertising to Children & Teens|Advertising to Children & Teens]]<br />
*[[Ethical game design]]<br />
*[[Etsy]]<br />
*[[Ex Machina (2014)]]<br />
*[[Experience Project]]<br />
<br />
=== F ===<br />
----<br />
*''Facebook''<br />
**[[Advertising on Facebook]]<br />
**[[Facebook|Company]]<br />
**[[Facebook Messenger]]<br />
**[[Facebook newsfeed curation]]<br />
**[[Facebook Privacy Policy|Privacy Policy]]<br />
**[[Data Mining and Manipulation]]<br />
**[[Facebook in Africa]]<br />
*[[FaceTime]]<br />
*[[Face recognition]]<br />
*[[Face recognition in law enforcement]]<br />
*[[Fake News]]<br />
*[[Fan fiction]]<br />
*[[Fast Fashion]]<br />
*[[Find My Friends]]<br />
*[[File Sharing]]<br />
*[[Filter Bubble]]<br />
*[[Final Fantasy XIV]]<br />
*[[Fitness and Nutrition Influencers and Misinformation]]<br />
*[[Fitness Game]]<br />
*[[First Person Shooters]]<br />
*[[Flaming]]<br />
*[[Flash]]<br />
*[[Free Basics]]<br />
*[[Freedom of Expression]]<br />
*[[Freemium model]]<br />
<br />
=== G ===<br />
----<br />
*[[Galaxy S3]]<br />
*[[Game Addiction]]<br />
*[[Gamergate]]<br />
*[[Gattaca]]<br />
*[[Gender bias in the Online Job Search]]<br />
*[[Gender bias in Wikipedia]]<br />
*[[Gender in Video Games]]<br />
*[[Genealogy platforms]]<br />
*[[General Data Protection Regulation]]<br />
*[[Genetically Modified Food]]<br />
*[[Gene Editing]]<br />
*[[Genomics]]<br />
*[[Genovese Syndrome]]<br />
*[[Genshin Impact]]<br />
*[[Geographic Information Systems]]<br />
*[[George Hotz]]<br />
*[[Ghost Writing Online]]<br />
*[[Girls Around Me]]<br />
*[[GLANSER]]<br />
*''Google''<br />
**[[Google|Company]]<br />
**[[Google Books|Books]]<br />
**[[Google Glass| Google Glass]]<br />
**[[Google Home]]<br />
**[[Google Clips]]<br />
**[[Google Street View|Street View]]<br />
**[[Google Photos]]<br />
*[[Grand Theft Auto IV]]<br />
*[[Grand Theft Auto V]]<br />
*[[Griefing]]<br />
*[[Grindr]]<br />
*[[GroupMe]]<br />
<br />
=== H ===<br />
----<br />
*[[Hackers]]<br />
*[[Hacking the 2016 US Presidential Election]]<br />
*[[Healthcare Data Monetization]]<br />
*[[Health Informatics]]<br />
*[[Her (film) (2013)]]<br />
*[[Her Interactive]]<br />
*[[Herman Tavani]]<br />
*[[High Frequency Trading]]<br />
*[[Hinge]]<br />
*[[Hulu]]<br />
*[[Human Flesh Search]] {{Relation|related to|Tianya.cn|#T}}<br />
*[[Human Microchipping]]<br />
*[["Human out of the Loop" Military Systems]]<br />
*[[Human Trafficking]]<br />
*[[Humans (British TV Series)]]<br />
<br />
=== I ===<br />
----<br />
*[[iCloud]]<br />
*[[id Software]]<br />
*[[Imgur]]<br />
*[[Infamous (series)]]<br />
*[[Influencer Marketing]]<br />
*[[Infoglut]]<br />
*[[Informatics]]<br />
*''Information'' {{Relation|overlaps with|Data|#Data}}<br />
**[[Information Ethics|Ethics]]<br />
**[[Information Freedom|Freedom]]<br />
**[[Freedom_of_Information_policies|Freedom of Information Policy]] <br />
**[[Information Overload|Overload]]<br />
**[[Information Reliability|Reliability]]<br />
**[[Information Security|Security]]<br />
**[[Information Transparency|Transparency]]<br />
**[[Information Vandalism|Vandalism]]<br />
*[[Informational Friction]]<br />
*[[Infosphere]]<br />
*[[Instagram]]<br />
*[[Instagram Ads]]<br />
*[[Intellectual Property]]<br />
*[[Internet of things]]<br />
*''Internet'' {{Relation|overlaps with|Cyber|#Cyber}} {{Relation||Online|#Online}} {{Relation||Virtual|#Virtual}}<br />
**[[Internet Archive|Archive]]<br />
**[[Internet Censorship in Hong Kong|Censorship in Hong Kong]]<br />
**[[Internet Censorship in South Korea|Censorship in South Korea]]<br />
**[[Internet Censorship in the United Kingdom|Censorship in the United Kingdom]]<br />
**[[Cybersecurity Law in Vietnam|Censorship in Vietnam]]<br />
**''in'' [[Circumventing Internet Censorship|Circumventing Censorship]]<br />
**[[Internet Control|Control]]<br />
**[[Internet meme|Meme]]<br />
*[[Iris Recognition]]<br />
<br />
=== J ===<br />
----<br />
*[[Jack Dorsey]]<br />
*[[Jailbreaking]]<br />
*[[James H. Moor]]<br />
*[[Jeremy Bentham]]<br />
*[[John Weckert]]<br />
*[[Julian Dibbell]]<br />
*[[Jurassic Park (1993)]]<br />
*[[Just another mediawiki page]]<br />
<br />
=== K ===<br />
----<br />
*[[Kathleen Wallace]]<br />
*[[Kay Mathiesen]]<br />
*[[Kim Dotcom]]<br />
*[[Kickstarter]]<br />
*[[Kind of Bloop]]<br />
<br />
=== L ===<br />
----<br />
*[[LambdaMOO]]<br />
*[[Larry Ellison]]<br />
*[[Lawrence Lessig]]<br />
*[[League of Legends]]<br />
*[[The League (Dating App)]]<br />
*[[Libraries and Ethical Information Technology]]<br />
*[[LikeALittle]]<br />
*[[Limewire]]<br />
*[[Line (Application)]]<br />
*[[LinkedIn]]<br />
*[[Linus Torvalds]]<br />
*[[Live Video]]<br />
*[[Location targeted advertising]]<br />
*[[Lookbook.nu]]<br />
*[[Loot Box]]<br />
*[[Love Plus]]<br />
*[[Low Orbit Ion Cannon]]<br />
*[[Luciano Floridi]]<br />
*[[Lyft]]<br />
<br />
=== M ===<br />
----<br />
*[[Machine learning in healthcare]]<br />
*[[macOS]]<br />
*[[Magic Bands]]<br />
*[[Major League Baseball]]<br />
*[[Manhunt]]<br />
*[[MapleStory]]<br />
*[[Mark Zuckerberg]]<br />
*[[Mashup]]<br />
*[[Mass Effect]]<br />
*''the'' [[The Matrix|Matrix]]<br />
*[[Internet meme|Meme]]<br />
*[[Mechanical Turk]]<br />
*[[Megaupload]]<br />
*[[Metadata]]<br />
*[[Mia Consalvo]]<br />
*[[Michael Kearns]]<br />
*[[Microsoft chatbots]]<br />
*[[Microtransactions]]<br />
*[[Miguel Sicart]]<br />
*[[Military Entertainment Complex]]<br />
*[[Minecraft]]<br />
*[[Mirai Botnet]]<br />
*[[Misinformation]]<br />
*[[MMORPGs]]<br />
*[[Mods]]<br />
*[[MOOC (Massive Open Online Courses)]]<br />
*[[Moore's Law]]<br />
*[[Morris Worm]]<br />
*[[Mortal Kombat]]<br />
*[[Mr. Robot]]<br />
*[[Music piracy]]<br />
*[[Myspace]]<br />
<br />
=== N ===<br />
----<br />
*[[Napster]]<br />
*[[National Security Agency]]<br />
*[[NBA Top Shot]]<br />
*[[NSA Cryptography]]<br />
*[[NCAA Football (Video Game Series)]]<br />
*[[Need For Speed (Video Game Series)]]<br />
*[[Nerve]]<br />
*[[Nest Thermostat]]<br />
*[[Net neutrality]]<br />
*[[Netflix]]<br />
*[[Nextdoor]]<br />
*[[NFT Art]]<br />
*[[Norbert Wiener]]<br />
*[[Nosedive, Black Mirror]]<br />
*[[Nymwars]]<br />
<br />
=== O ===<br />
----<br />
*[[OK The Pirate Bay]]<br />
*[[Omegle]]<br />
*''Online'' {{Relation|overlaps with|Cyber|#Cyber}} {{Relation||Internet|#Internet}} {{Relation||Virtual|#Virtual}}<br />
**[[Cyberbullying|Bullying]] ''in Cyberspace''<br />
**[[Online Cheating|Cheating]]<br />
**[[Online Dating|Dating]]<br />
**[[Online Data Disadvantages in Latin America]]<br />
**[[Online Gambling|Gambling]]<br />
**[[Online Identity|Identity]]<br />
**[[Online Identity Theft|Identity Theft]]<br />
**[[Libel Online|Libel]]<br />
**[[Online Poker in reference to Live Poker]]<br />
**[[Online Reputation Systems|Reputation Systems]]<br />
**''Sex in'' [[Online Dating#Sex|Online Dating]]<br />
**[[Online shopping|Shopping]]<br />
**[[Cyberstalking|Stalking]] ''in CyberSpace''<br />
*[[Old School Runescape]]<br />
*[[The Open Internet|Open Internet]]<br />
*[[Onavo]]<br />
*[[OnlyFans]]<br />
*[[OnStar]]<br />
*[[OpenAi]]<br />
*[[Orwell (Video Game)]]<br />
*[[Overwatch]]<br />
*[[Open Source Software]]<br />
<br />
=== P ===<br />
----<br />
*[[Palantir Technologies]]<br />
*[[Pandora]]<br />
*[[Parasocial Relationship]]<br />
*[[PARO Therapeutic Robot]]<br />
*[[Parody]]<br />
*[[Patents]]<br />
*[[PayPal]]<br />
*[[Periscope]]<br />
*[[Peter Thiel]]<br />
*[[Philip Brey]]<br />
*''Photo'' {{Relation|issues of|Digital Photography|#D}}<br />
**[[Photo Editing|Editing]]<br />
**[[Phototruth|Truth]]<br />
*[[Pinterest]]<br />
*[[The Pirate Bay|Pirate Bay]]<br />
*[[Plagiarism]]<br />
*[[PlayerUnknown's Battlegrounds]]<br />
*[[Pokémon Go]]<br />
*[[PokerStars]]<br />
*[[Pornography]]<br />
*[[Portal 2]]<br />
*[[Postal 2]]<br />
*[[Prank YouTubers]]<br />
*[[Predictive Policing]]<br />
*''Privacy''<br />
**[[Facebook Privacy Policy|Facebook Policy]]<br />
**''in'' [[Privacy in the China|China]]<br />
**''in'' [[Privacy in the Online Environment|Online Enviornment]]<br />
**''in'' [[Privacy in Social Networking|Social Networking]]<br />
**''in'' [[Privacy in public]]<br />
**[[Privacy Policies at Apple Inc.|Apple Policy]]<br />
*[[Privacy in Venmo]]<br />
*[[Privacy in the China]]<br />
*[[Pro-Ana Forums]]<br />
*[[Protect IP Act]]<br />
*[[Proxy Culture]]<br />
*[[Public Morality]]<br />
*[[The Punisher]]<br />
*[[Punishments in Virtual Environments]]<br />
<br />
===Q ===<br />
-----<br />
*[[QR Codes]]<br />
*[[Quora]]<br />
*[[Quantified Self]]<br />
*[[Quantum Computing]]<br />
=== R ===<br />
----<br />
*[[Racial Algorithmic Bias]]<br />
*[[Racism in Video Games]]<br />
*[[Radio-frequency Identification]]<br />
*[[Ransomware]]<br />
*[[Raph Koster]]<br />
*[[Ray Kurzweil]]<br />
*[[Real Fake Page]]<br />
*[[Real Money Trade]]<br />
*[[Recommender Systems]]<br />
*[[Reddit]]<br />
**[[/r/AmITheAsshole]]<br />
**[[/r/wallstreetbets]]<br />
**[[/r/2meirl4meirl]]<br />
*[[Reid Hoffman]]<br />
*[[Remote Access]]<br />
*[[Renren]]<br />
*[[Revenge Porn]]<br />
*[[Richard Stallman]]<br />
*[[Right to be Forgotten]]<br />
*[[RIP Trolling]]<br />
*[[Rockmelt]]<br />
*[[Rumble Fighter]]<br />
<br />
=== S ===<br />
------<br />
*[[Sampling (hip hop)]]<br />
*[[Self Driving Cars]]<br />
*[[Sergey Aleynikov]]<br />
*[[Serious Games]]<br />
*[[Sexting]]<br />
*[[Sharing Subscription Services]]<br />
*''Sims''<br />
**[[The Sims 3|The Sims 3]]<br />
**[[The Sims Online|The Sims Online]]<br />
**[[The Sims 4|The Sims 4]]<br />
*[[SingularityNet]]<br />
*[[Slack (Application)]]<br />
*[[Smart Doorbell]]<br />
*[[Smart Home]]<br />
*[[Smartphones (Location Services)]]<br />
*[[SNAP Program]]<br />
*[[Soccer & FIFA]]<br />
*[[Social Credit System]]<br />
*''Social''<br />
**[[Social Media in Sports|Media in Sports]]<br />
**[[Social media in national elections (2016)]]<br />
**[[Social Networking|Networking]]<br />
**[[Social Networking Services|Networking Services]] {{Relation|for sites|Facebook|Facebook}} {{Relation||Tianya.cn|Tianya.cn}} {{Relation||Twitter|Twitter}} {{Relation||Tumblr|Tumblr}}<br />
**[[Social Media (Meta)|Media (Meta)]]<br />
*[[Social Media and Depression]]<br />
*[[Social media and the 2020 US presidential election]]<br />
*[[Social Media Websites in Investigations]]<br />
* [[Sousveillance]]<br />
*[[Snapchat]]<br />
*[[Spam]]<br />
*[[Spoof]]<br />
*[[Spotify]]<br />
*[[Spycams in South Korea]]<br />
*[[Starcraft II]]<br />
*[[Statistical Modeling]]<br />
*[[Steam]]<br />
*[[Steve Jobs]]<br />
*[[Stop Online Piracy Act]]<br />
*[[Student-Athlete Social Media Monitoring]]<br />
*[[StumbleUpon]]<br />
*[[Stuxnet Trojan]] {{Relation|type of|Worm|#W}} {{Relation|utilizes|Rootkit|#R}}<br />
*[[Suits]]<br />
*[[Super Smash Bros. Ultimate]]<br />
*[[Surveillance Capitalism]]<br />
*[[Surveillance in China]]<br />
*[[Surveillance Technologies]]<br />
*[[Sword Art Online]]<br />
<br />
=== T ===<br />
------<br />
*[[Targeted Advertising (Online)]]<br />
*[[Team Fortress 2]]<br />
*[[Technological Determinism]]<br />
*[[Technological Singularity]]<br />
*[[Telepresence]]<br />
*[[Tencent]]<br />
*[[Tesla, Inc.]]<br />
*[[Testimonials]]<br />
*[[The Truman Show]]<br />
*[[The Internet and Food]]<br />
*[[Thomas M. Powers]]<br />
*[[Tianya.cn]]<br />
*[[TikTok]]<br />
*[[TikTok Subcategory Radicalization]]<br />
*[[Tim Berners-Lee]]<br />
*[[Tinder]]<br />
*[[Tor]]<br />
*[[Transhumanism]]<br />
*[[Transparency in software development]]<br />
*[[Transparency in Social Media Participation]]<br />
*[[Trustworthiness of information]]<br />
*[[Troll]]<br />
*[[Tumblr]]<br />
*[[Twitter]]<br />
*[[Twitch.tv]]<br />
<br />
=== U ===<br />
----<br />
*[[Uber]]<br />
*[[Ubiquitous Computing]]<br />
*[[Unabomber Manifesto]]<br />
*[[Uniqueness Debate]]<br />
*[[Undertale]]<br />
*[[Utilitarian Philosophy]]<br />
<br />
=== V ===<br />
----<br />
*[[Valorant]]<br />
*[[Valve]]<br />
*[[Value Sensitive Design]]<br />
*[[Venmo]]<br />
*''Virtual'' {{Relation|overlaps with|Cyber|#Cyber}} {{Relation||Internet|#Internet}} {{Relation||Online|#Online}}<br />
**[[Virtual Assistants]]<br />
**''Bullying in'' [[Cyberbullying|Cyberspace]]<br />
**[[Virtual Child Pornography|Child Pornography]]<br />
**[[Virtual Community|Community]]<br />
**[[Virtual Crimes and Punishments|Crimes and Punishments]]<br />
** ''Dating ''[[Online Dating#Virtual_Dating|Online]]<br />
**[[Virtual Dating Simulations|Dating Simulations]]<br />
**[[Virtual Environment|Environment]]<br />
**[[Punishments in Virtual Environments|Punishment]]<br />
**[[Virtual Private Network|Private Network]]<br />
**[[Virtual Rape|Rape]]<br />
**''Sex in'' [[Cybersex|Cyberspace]]<br />
**''Stalking in'' [[Cyberstalking|Cyberspace]]<br />
*[[Virtual sweatshops]]<br />
*[[Violence and video games]]<br />
*[[Violence in Video Games]]<br />
*[[Virtual Magic Kingdom]]<br />
*[[Virtual Reality and Computer Simulations]]<br />
*[[Virtual Reality in Prison]]<br />
*[[Video Surveillance]]<br />
*[[Voice imitation algorithms]]<br />
*[[Vlogging]]<br />
*[[Vuze]]<br />
<br />
=== W ===<br />
----<br />
*[[Warcraft III]]<br />
*[[Watch Dogs]]<br />
*[[Watson (computer)]]<br />
*[[Wattpad]]<br />
*[[Waze]]<br />
*[[Wearable health tech]]<br />
*[[Web 2.0]]<br />
*[[Webcams]]<br />
*[[Webtoon App]]<br />
*[[WeChat]]<br />
**[[Misinformation on WeChat]]<br />
*[[Weibo]]<br />
*[[Westworld and AI]]<br />
*[[WhatsApp]]<br />
*[[Whisper]]<br />
*[[Wii U]]<br />
*[[WikiLeaks]]<br />
*[[Wikipedia]]<br />
**[[Wikipedia Bots|Bots]]<br />
**[[Gender bias in Wikipedia]]<br />
*[[Witcher 3: Wild Hunt]]<br />
*[[Women in Gaming]]<br />
*[[World of Warcraft]]<br />
<br />
=== X ===<br />
----<br />
*[[The X-Files]]<br />
*[[Xkcd]]<br />
<br />
<br />
=== Y ===<br />
----<br />
*[[Yelp Reviewing]]<br />
*[[Yik Yak]]<br />
*''YouTube''<br />
**[[YouTube|YouTube (Website)]]<br />
**[[YouTube Beauty Community|Beauty Community]]<br />
**[[YouTube recommendation algorithm]]<br />
<br />
=== Z ===<br />
----<br />
*[[Zoom]]<br />
*[[Zynga]]</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Talk:Soumya_Tejam&diff=94015Talk:Soumya Tejam2021-02-24T22:33:07Z<p>Ptse: Created page with "Comment by Patrick Tse: Hi Soumya! I really enjoyed reading your Wiki page! I really liked the use of bold words when you wanted the statement you were making to stand out. My..."</p>
<hr />
<div>Comment by Patrick Tse: Hi Soumya! I really enjoyed reading your Wiki page! I really liked the use of bold words when you wanted the statement you were making to stand out. My favorite one is when you said "my online identity isn't created by me, it is created for me." I feel like that statement really epitomizes the point of this assignment. Another part I liked was the section on the different types of identities. It was great that you made that distinction because one's data identity may be part of the whole identity, but not the whole thing.<br />
<br />
The only thing that I would recommend you revise is the lack of capitalization on some words. For companies like Facebook and Instagram, their names should definitely be capitalized.</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Talk:Alex_Wang&diff=93986Talk:Alex Wang2021-02-24T17:56:45Z<p>Ptse: </p>
<hr />
<div>Comment from Patrick Tse: Hi Alex! I really liked reading your Wiki page! <br />
<br />
I really like that you used many subheadings under each section. It made it really easy to follow along when you changed topics and it feels more like a real Wiki page as well! Your claim, in the beginning, was very clear and was well supported by your information about your Google searches along with your preferences about social media. <br />
<br />
There are some spots that I think could make your page even better with a few edits. First, there are a few typos throughout your Wiki page. A quick re-read should do the trick. Second, I feel like the subheadings about your data identity being incomplete and unauthentic could be put into one subheading. While there is a slight difference between the two, I feel like they are similar enough to put together. The last thing that I would like to suggest is adding more to the subsection labeled Privacy Concerns. The idea discussed in that paragraph could easily be related to some class readings. Other than that, I think your Wiki page looks great!</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Talk:Alex_Wang&diff=93985Talk:Alex Wang2021-02-24T17:56:07Z<p>Ptse: Created page with "Hi Alex! I really liked reading your Wiki page! I really like that you used many subheadings under each section. It made it really easy to follow along when you changed top..."</p>
<hr />
<div>Hi Alex! I really liked reading your Wiki page! <br />
<br />
I really like that you used many subheadings under each section. It made it really easy to follow along when you changed topics and it feels more like a real Wiki page as well! Your claim, in the beginning, was very clear and was well supported by your information about your Google searches along with your preferences about social media. <br />
<br />
There are some spots that I think could make your page even better with a few edits. First, there are a few typos throughout your Wiki page. A quick re-read should do the trick. Second, I feel like the subheadings about your data identity being incomplete and unauthentic could be put into one subheading. While there is a slight difference between the two, I feel like they are similar enough to put together. The last thing that I would like to suggest is adding more to the subsection labeled Privacy Concerns. The idea discussed in that paragraph could easily be related to some class readings. Other than that, I think your Wiki page looks great!</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Patrick_Tse&diff=93473Patrick Tse2021-02-19T16:17:58Z<p>Ptse: adding picture</p>
<hr />
<div><br />
== '''Introduction''' ==<br />
<br />
Personally, I find the Internet somewhat scary because of how easy it is for people to access information through the Internet. Because of this, most of my social media accounts are private and I also am not very active on my social media. Due to my lack of a presence online, I believe that my data identity accurately represents only a part of my whole identity.<br />
<br />
== '''Google Search''' ==<br />
[[File:Old patrick.png|thumbnail|right|Google Search for Patrick Tse]]<br />
Aside from having private social media accounts, there is a bigger problem when you google “Patrick Tse.” The first person who shows up is an actor, producer, screenwriter, and director in Hong Kong cinema. It makes sense that a university student does not show up compared to this Hong Kong celebrity. He takes up almost the first four pages when searched up. To try to narrow down the search, I tried typing my name with my middle name as well. To my surprise, there were still no results near what I was looking for. The Hong Kong celebrity showed up again… Since even typing in my full name did not yield any results I wanted to see how specific the searches had to be for anything about me to show up. After searching my name attached with something that could potentially be related to me, I finally got something! When I searched “patrick tse california,” California is where I am from, my LinkedIn account was the first result that showed up. I realized this was because my LinkedIn account has information I inputted about where I went to high school in California. When I searched up “patrick tse michigan” my LinkedIn is also the first result because it has information about me attending the University of Michigan. All my other social media accounts do not have any information about where I am from, so it would make sense why they did not show up. I attempted to search for my Facebook and Instagram as well. However, for Facebook there were quite a few other Patrick Tses. After scrolling through for a while I still could not find myself. Although searching for my Facebook was unsuccessful, I was able to find my Instagram. I had to search up my username for it to be found. Even though I was able to find it, my account is private.<br />
<br />
One thing I realized while searching for information on myself is that social media has become a political piece of technology. In Winner’s, Do Artifacts Have Politics?, he discusses the idea of certain pieces of technology being inherently political. This means that the piece of technology needs some sort of political structure of control to make sure it is not used in the wrong context. However, social media has created its own sort of politics around it. The popularity of people and their appearance on their social media have become extremely important. For example, my LinkedIn showing up in a simple google search matters because employers can see my profile. My LinkedIn has information about me that hopefully represents a side of me that has qualities that are desirable to an employer. My past job experiences, education, etc. are all on my LinkedIn. Given the pretext that LinkedIn is more of a professional social media platform, it would make sense for a user to only put information that would be appropriate in a workplace. For that reason, my LinkedIn account by no means represents all of me, but it is the main thing that shows up when my name is googled. It was a very political decision by me to keep my other social media accounts more private and to have my LinkedIn more exposed. My LinkedIn has much more information about me so potential employers can get a sense of what type of person I am. I would not want my personal social media accounts showing up alongside my LinkedIn. <br />
<br />
To conclude, basing the search solely on Google, the search has to be quite specific to get any sort of meaningful result. This is mostly because I enjoy my privacy from others on the web who I do not know. Although there seems to be a minimal amount of information from a basic google search, there is a lot of my information out there. From making accounts for games to putting my email on a mailing list, I have no idea how many accounts I have created for a variety of things.<br />
<br />
== '''App/Account Data''' ==<br />
<br />
Whether it’s a new game on my phone or creating an account to get free shipping, my information is all over the place. The main pieces of data that all these services ask for are name, phone number, and email. Personally, I do not find giving such basic information a problem. I do not think giving my phone number or email does much harm. While they have my contact information, it is my decision to engage or ignore whoever contacts me. However, there are certain things that I have signed up for that require quite sensitive information. For example, the app Webull, a stock trading platform, required that I input my social security number. In this case, I know that Webull is a reliable app because I personally know people who have used this app and have had no problems with it. While I know that the app is most likely reliable, I always feel as if you should still be weary when giving such private information. A couple of years ago, I had an incident where a college I had applied to informed me that they had been hacked and that some of the information about applicants and students had been stolen. Thankfully nothing happened to me personally, but it shows that systems that seem to be safe may not always be safe. <br />
<br />
===Game Data===<br />
[[File:Brawlstars.PNG|thumbnail|right|screenshot of the game Brawlstars]]<br />
One of the things that intrigues me is the data that is gathered on mobile and video games. In many of the games I play, especially mobile, there are in-app purchases. There are typically two types of currencies: one that is more easily acquired and one that is harder to acquire but money in real life can be used to purchase more of this currency. The one that can be bought with money typically can help you gain materials that will make the game easier or more fun. One of the mobile games that I currently play, Brawlstars, has this same sort of model. Without getting into too much detail about the game itself, the main points about the game that I want to discuss is how currency is acquired and how materials are bought. In the game, there are two currencies: coins and gems. Coins are the more easily attained currency and gems are the currency that can be bought through in-app purchase. One important thing to note is that coins can also be bought in exchange for gems. When buying materials to upgrade your characters, sometimes the exact materials needed to upgrade a character will show up. The catch is that many times it will end up costing a hefty amount to get those materials. Since the materials in the shop change daily, it incentivizes users to spend real money to get those materials. The fact that this situation consistently happens lets me know that the game is clearly monitoring my progress and trying to get me to spend money, which is most likely part of the business model. While this data is only contained within the game and does not have any affect on my life, I find it interesting how the data is used. Just in the way that some sites have targeted ads, some games use the users’ data to gain an advantage on them.<br />
<br />
== '''Conclusion''' ==<br />
<br />
Searching the Internet for myself was quite interesting. I knew from the start that it would not be easy to find myself online due to my social media accounts being private. Because LinkedIn was the only social media platform I could find on myself, I believe my data identity does not well represent me as a whole. My LinkedIn profile is strictly my professional identity. It does not include anything about my hobbies or any of my private information. While my data identity does not fully represent me, that is actually more of a relief to me. If my data identity was a very accurate representation of myself, that would mean that there is a considerable amount of information about me that is public. Since that is not the case, that means that I am keeping my digital footprint to a minimum which is exactly what I want!</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=File:Old_patrick.png&diff=93464File:Old patrick.png2021-02-19T16:17:01Z<p>Ptse: </p>
<hr />
<div></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Patrick_Tse&diff=93442Patrick Tse2021-02-19T16:14:36Z<p>Ptse: adding picture</p>
<hr />
<div><br />
== '''Introduction''' ==<br />
<br />
Personally, I find the Internet somewhat scary because of how easy it is for people to access information through the Internet. Because of this, most of my social media accounts are private and I also am not very active on my social media. Due to my lack of a presence online, I believe that my data identity accurately represents only a part of my whole identity.<br />
<br />
== '''Google Search''' ==<br />
[[File:Patricktse.png|thumbnail|right|Picture of "other" Patrick Tse]]<br />
Aside from having private social media accounts, there is a bigger problem when you google “Patrick Tse.” The first person who shows up is an actor, producer, screenwriter, and director in Hong Kong cinema. It makes sense that a university student does not show up compared to this Hong Kong celebrity. He takes up almost the first four pages when searched up. To try to narrow down the search, I tried typing my name with my middle name as well. To my surprise, there were still no results near what I was looking for. The Hong Kong celebrity showed up again… Since even typing in my full name did not yield any results I wanted to see how specific the searches had to be for anything about me to show up. After searching my name attached with something that could potentially be related to me, I finally got something! When I searched “patrick tse california,” California is where I am from, my LinkedIn account was the first result that showed up. I realized this was because my LinkedIn account has information I inputted about where I went to high school in California. When I searched up “patrick tse michigan” my LinkedIn is also the first result because it has information about me attending the University of Michigan. All my other social media accounts do not have any information about where I am from, so it would make sense why they did not show up. I attempted to search for my Facebook and Instagram as well. However, for Facebook there were quite a few other Patrick Tses. After scrolling through for a while I still could not find myself. Although searching for my Facebook was unsuccessful, I was able to find my Instagram. I had to search up my username for it to be found. Even though I was able to find it, my account is private.<br />
<br />
One thing I realized while searching for information on myself is that social media has become a political piece of technology. In Winner’s, Do Artifacts Have Politics?, he discusses the idea of certain pieces of technology being inherently political. This means that the piece of technology needs some sort of political structure of control to make sure it is not used in the wrong context. However, social media has created its own sort of politics around it. The popularity of people and their appearance on their social media have become extremely important. For example, my LinkedIn showing up in a simple google search matters because employers can see my profile. My LinkedIn has information about me that hopefully represents a side of me that has qualities that are desirable to an employer. My past job experiences, education, etc. are all on my LinkedIn. Given the pretext that LinkedIn is more of a professional social media platform, it would make sense for a user to only put information that would be appropriate in a workplace. For that reason, my LinkedIn account by no means represents all of me, but it is the main thing that shows up when my name is googled. It was a very political decision by me to keep my other social media accounts more private and to have my LinkedIn more exposed. My LinkedIn has much more information about me so potential employers can get a sense of what type of person I am. I would not want my personal social media accounts showing up alongside my LinkedIn. <br />
<br />
To conclude, basing the search solely on Google, the search has to be quite specific to get any sort of meaningful result. This is mostly because I enjoy my privacy from others on the web who I do not know. Although there seems to be a minimal amount of information from a basic google search, there is a lot of my information out there. From making accounts for games to putting my email on a mailing list, I have no idea how many accounts I have created for a variety of things.<br />
<br />
== '''App/Account Data''' ==<br />
<br />
Whether it’s a new game on my phone or creating an account to get free shipping, my information is all over the place. The main pieces of data that all these services ask for are name, phone number, and email. Personally, I do not find giving such basic information a problem. I do not think giving my phone number or email does much harm. While they have my contact information, it is my decision to engage or ignore whoever contacts me. However, there are certain things that I have signed up for that require quite sensitive information. For example, the app Webull, a stock trading platform, required that I input my social security number. In this case, I know that Webull is a reliable app because I personally know people who have used this app and have had no problems with it. While I know that the app is most likely reliable, I always feel as if you should still be weary when giving such private information. A couple of years ago, I had an incident where a college I had applied to informed me that they had been hacked and that some of the information about applicants and students had been stolen. Thankfully nothing happened to me personally, but it shows that systems that seem to be safe may not always be safe. <br />
<br />
===Game Data===<br />
[[File:Brawlstars.PNG|thumbnail|right|screenshot of the game Brawlstars]]<br />
One of the things that intrigues me is the data that is gathered on mobile and video games. In many of the games I play, especially mobile, there are in-app purchases. There are typically two types of currencies: one that is more easily acquired and one that is harder to acquire but money in real life can be used to purchase more of this currency. The one that can be bought with money typically can help you gain materials that will make the game easier or more fun. One of the mobile games that I currently play, Brawlstars, has this same sort of model. Without getting into too much detail about the game itself, the main points about the game that I want to discuss is how currency is acquired and how materials are bought. In the game, there are two currencies: coins and gems. Coins are the more easily attained currency and gems are the currency that can be bought through in-app purchase. One important thing to note is that coins can also be bought in exchange for gems. When buying materials to upgrade your characters, sometimes the exact materials needed to upgrade a character will show up. The catch is that many times it will end up costing a hefty amount to get those materials. Since the materials in the shop change daily, it incentivizes users to spend real money to get those materials. The fact that this situation consistently happens lets me know that the game is clearly monitoring my progress and trying to get me to spend money, which is most likely part of the business model. While this data is only contained within the game and does not have any affect on my life, I find it interesting how the data is used. Just in the way that some sites have targeted ads, some games use the users’ data to gain an advantage on them.<br />
<br />
== '''Conclusion''' ==<br />
<br />
Searching the Internet for myself was quite interesting. I knew from the start that it would not be easy to find myself online due to my social media accounts being private. Because LinkedIn was the only social media platform I could find on myself, I believe my data identity does not well represent me as a whole. My LinkedIn profile is strictly my professional identity. It does not include anything about my hobbies or any of my private information. While my data identity does not fully represent me, that is actually more of a relief to me. If my data identity was a very accurate representation of myself, that would mean that there is a considerable amount of information about me that is public. Since that is not the case, that means that I am keeping my digital footprint to a minimum which is exactly what I want!</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Patrick_Tse&diff=93427Patrick Tse2021-02-19T16:13:28Z<p>Ptse: adding picture</p>
<hr />
<div><br />
== '''Introduction''' ==<br />
<br />
Personally, I find the Internet somewhat scary because of how easy it is for people to access information through the Internet. Because of this, most of my social media accounts are private and I also am not very active on my social media. Due to my lack of a presence online, I believe that my data identity accurately represents only a part of my whole identity.<br />
<br />
== '''Google Search''' ==<br />
[[File:Patrick.png|thumbnail|right|Picture of Patrick Tse]]<br />
Aside from having private social media accounts, there is a bigger problem when you google “Patrick Tse.” The first person who shows up is an actor, producer, screenwriter, and director in Hong Kong cinema. It makes sense that a university student does not show up compared to this Hong Kong celebrity. He takes up almost the first four pages when searched up. To try to narrow down the search, I tried typing my name with my middle name as well. To my surprise, there were still no results near what I was looking for. The Hong Kong celebrity showed up again… Since even typing in my full name did not yield any results I wanted to see how specific the searches had to be for anything about me to show up. After searching my name attached with something that could potentially be related to me, I finally got something! When I searched “patrick tse california,” California is where I am from, my LinkedIn account was the first result that showed up. I realized this was because my LinkedIn account has information I inputted about where I went to high school in California. When I searched up “patrick tse michigan” my LinkedIn is also the first result because it has information about me attending the University of Michigan. All my other social media accounts do not have any information about where I am from, so it would make sense why they did not show up. I attempted to search for my Facebook and Instagram as well. However, for Facebook there were quite a few other Patrick Tses. After scrolling through for a while I still could not find myself. Although searching for my Facebook was unsuccessful, I was able to find my Instagram. I had to search up my username for it to be found. Even though I was able to find it, my account is private.<br />
<br />
One thing I realized while searching for information on myself is that social media has become a political piece of technology. In Winner’s, Do Artifacts Have Politics?, he discusses the idea of certain pieces of technology being inherently political. This means that the piece of technology needs some sort of political structure of control to make sure it is not used in the wrong context. However, social media has created its own sort of politics around it. The popularity of people and their appearance on their social media have become extremely important. For example, my LinkedIn showing up in a simple google search matters because employers can see my profile. My LinkedIn has information about me that hopefully represents a side of me that has qualities that are desirable to an employer. My past job experiences, education, etc. are all on my LinkedIn. Given the pretext that LinkedIn is more of a professional social media platform, it would make sense for a user to only put information that would be appropriate in a workplace. For that reason, my LinkedIn account by no means represents all of me, but it is the main thing that shows up when my name is googled. It was a very political decision by me to keep my other social media accounts more private and to have my LinkedIn more exposed. My LinkedIn has much more information about me so potential employers can get a sense of what type of person I am. I would not want my personal social media accounts showing up alongside my LinkedIn. <br />
<br />
To conclude, basing the search solely on Google, the search has to be quite specific to get any sort of meaningful result. This is mostly because I enjoy my privacy from others on the web who I do not know. Although there seems to be a minimal amount of information from a basic google search, there is a lot of my information out there. From making accounts for games to putting my email on a mailing list, I have no idea how many accounts I have created for a variety of things.<br />
<br />
== '''App/Account Data''' ==<br />
<br />
Whether it’s a new game on my phone or creating an account to get free shipping, my information is all over the place. The main pieces of data that all these services ask for are name, phone number, and email. Personally, I do not find giving such basic information a problem. I do not think giving my phone number or email does much harm. While they have my contact information, it is my decision to engage or ignore whoever contacts me. However, there are certain things that I have signed up for that require quite sensitive information. For example, the app Webull, a stock trading platform, required that I input my social security number. In this case, I know that Webull is a reliable app because I personally know people who have used this app and have had no problems with it. While I know that the app is most likely reliable, I always feel as if you should still be weary when giving such private information. A couple of years ago, I had an incident where a college I had applied to informed me that they had been hacked and that some of the information about applicants and students had been stolen. Thankfully nothing happened to me personally, but it shows that systems that seem to be safe may not always be safe. <br />
<br />
===Game Data===<br />
[[File:Brawlstars.PNG|thumbnail|right|screenshot of the game Brawlstars]]<br />
One of the things that intrigues me is the data that is gathered on mobile and video games. In many of the games I play, especially mobile, there are in-app purchases. There are typically two types of currencies: one that is more easily acquired and one that is harder to acquire but money in real life can be used to purchase more of this currency. The one that can be bought with money typically can help you gain materials that will make the game easier or more fun. One of the mobile games that I currently play, Brawlstars, has this same sort of model. Without getting into too much detail about the game itself, the main points about the game that I want to discuss is how currency is acquired and how materials are bought. In the game, there are two currencies: coins and gems. Coins are the more easily attained currency and gems are the currency that can be bought through in-app purchase. One important thing to note is that coins can also be bought in exchange for gems. When buying materials to upgrade your characters, sometimes the exact materials needed to upgrade a character will show up. The catch is that many times it will end up costing a hefty amount to get those materials. Since the materials in the shop change daily, it incentivizes users to spend real money to get those materials. The fact that this situation consistently happens lets me know that the game is clearly monitoring my progress and trying to get me to spend money, which is most likely part of the business model. While this data is only contained within the game and does not have any affect on my life, I find it interesting how the data is used. Just in the way that some sites have targeted ads, some games use the users’ data to gain an advantage on them.<br />
<br />
== '''Conclusion''' ==<br />
<br />
Searching the Internet for myself was quite interesting. I knew from the start that it would not be easy to find myself online due to my social media accounts being private. Because LinkedIn was the only social media platform I could find on myself, I believe my data identity does not well represent me as a whole. My LinkedIn profile is strictly my professional identity. It does not include anything about my hobbies or any of my private information. While my data identity does not fully represent me, that is actually more of a relief to me. If my data identity was a very accurate representation of myself, that would mean that there is a considerable amount of information about me that is public. Since that is not the case, that means that I am keeping my digital footprint to a minimum which is exactly what I want!</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Patrick_Tse&diff=93414Patrick Tse2021-02-19T16:11:48Z<p>Ptse: adding picture</p>
<hr />
<div><br />
== '''Introduction''' ==<br />
<br />
Personally, I find the Internet somewhat scary because of how easy it is for people to access information through the Internet. Because of this, most of my social media accounts are private and I also am not very active on my social media. Due to my lack of a presence online, I believe that my data identity accurately represents only a part of my whole identity.<br />
<br />
== '''Google Search''' ==<br />
<br />
Aside from having private social media accounts, there is a bigger problem when you google “Patrick Tse.” The first person who shows up is an actor, producer, screenwriter, and director in Hong Kong cinema. It makes sense that a university student does not show up compared to this Hong Kong celebrity. He takes up almost the first four pages when searched up. To try to narrow down the search, I tried typing my name with my middle name as well. To my surprise, there were still no results near what I was looking for. The Hong Kong celebrity showed up again… Since even typing in my full name did not yield any results I wanted to see how specific the searches had to be for anything about me to show up. After searching my name attached with something that could potentially be related to me, I finally got something! When I searched “patrick tse california,” California is where I am from, my LinkedIn account was the first result that showed up. I realized this was because my LinkedIn account has information I inputted about where I went to high school in California. When I searched up “patrick tse michigan” my LinkedIn is also the first result because it has information about me attending the University of Michigan. All my other social media accounts do not have any information about where I am from, so it would make sense why they did not show up. I attempted to search for my Facebook and Instagram as well. However, for Facebook there were quite a few other Patrick Tses. After scrolling through for a while I still could not find myself. Although searching for my Facebook was unsuccessful, I was able to find my Instagram. I had to search up my username for it to be found. Even though I was able to find it, my account is private.<br />
[[File:Old patrick.png|thumbnail|right|Picture of Patrick Tse]]<br />
One thing I realized while searching for information on myself is that social media has become a political piece of technology. In Winner’s, Do Artifacts Have Politics?, he discusses the idea of certain pieces of technology being inherently political. This means that the piece of technology needs some sort of political structure of control to make sure it is not used in the wrong context. However, social media has created its own sort of politics around it. The popularity of people and their appearance on their social media have become extremely important. For example, my LinkedIn showing up in a simple google search matters because employers can see my profile. My LinkedIn has information about me that hopefully represents a side of me that has qualities that are desirable to an employer. My past job experiences, education, etc. are all on my LinkedIn. Given the pretext that LinkedIn is more of a professional social media platform, it would make sense for a user to only put information that would be appropriate in a workplace. For that reason, my LinkedIn account by no means represents all of me, but it is the main thing that shows up when my name is googled. It was a very political decision by me to keep my other social media accounts more private and to have my LinkedIn more exposed. My LinkedIn has much more information about me so potential employers can get a sense of what type of person I am. I would not want my personal social media accounts showing up alongside my LinkedIn. <br />
<br />
To conclude, basing the search solely on Google, the search has to be quite specific to get any sort of meaningful result. This is mostly because I enjoy my privacy from others on the web who I do not know. Although there seems to be a minimal amount of information from a basic google search, there is a lot of my information out there. From making accounts for games to putting my email on a mailing list, I have no idea how many accounts I have created for a variety of things.<br />
<br />
== '''App/Account Data''' ==<br />
<br />
Whether it’s a new game on my phone or creating an account to get free shipping, my information is all over the place. The main pieces of data that all these services ask for are name, phone number, and email. Personally, I do not find giving such basic information a problem. I do not think giving my phone number or email does much harm. While they have my contact information, it is my decision to engage or ignore whoever contacts me. However, there are certain things that I have signed up for that require quite sensitive information. For example, the app Webull, a stock trading platform, required that I input my social security number. In this case, I know that Webull is a reliable app because I personally know people who have used this app and have had no problems with it. While I know that the app is most likely reliable, I always feel as if you should still be weary when giving such private information. A couple of years ago, I had an incident where a college I had applied to informed me that they had been hacked and that some of the information about applicants and students had been stolen. Thankfully nothing happened to me personally, but it shows that systems that seem to be safe may not always be safe. <br />
<br />
===Game Data===<br />
[[File:Brawlstars.PNG|thumbnail|right|screenshot of the game Brawlstars]]<br />
One of the things that intrigues me is the data that is gathered on mobile and video games. In many of the games I play, especially mobile, there are in-app purchases. There are typically two types of currencies: one that is more easily acquired and one that is harder to acquire but money in real life can be used to purchase more of this currency. The one that can be bought with money typically can help you gain materials that will make the game easier or more fun. One of the mobile games that I currently play, Brawlstars, has this same sort of model. Without getting into too much detail about the game itself, the main points about the game that I want to discuss is how currency is acquired and how materials are bought. In the game, there are two currencies: coins and gems. Coins are the more easily attained currency and gems are the currency that can be bought through in-app purchase. One important thing to note is that coins can also be bought in exchange for gems. When buying materials to upgrade your characters, sometimes the exact materials needed to upgrade a character will show up. The catch is that many times it will end up costing a hefty amount to get those materials. Since the materials in the shop change daily, it incentivizes users to spend real money to get those materials. The fact that this situation consistently happens lets me know that the game is clearly monitoring my progress and trying to get me to spend money, which is most likely part of the business model. While this data is only contained within the game and does not have any affect on my life, I find it interesting how the data is used. Just in the way that some sites have targeted ads, some games use the users’ data to gain an advantage on them.<br />
<br />
== '''Conclusion''' ==<br />
<br />
Searching the Internet for myself was quite interesting. I knew from the start that it would not be easy to find myself online due to my social media accounts being private. Because LinkedIn was the only social media platform I could find on myself, I believe my data identity does not well represent me as a whole. My LinkedIn profile is strictly my professional identity. It does not include anything about my hobbies or any of my private information. While my data identity does not fully represent me, that is actually more of a relief to me. If my data identity was a very accurate representation of myself, that would mean that there is a considerable amount of information about me that is public. Since that is not the case, that means that I am keeping my digital footprint to a minimum which is exactly what I want!</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=File:Brawlstars.PNG&diff=93405File:Brawlstars.PNG2021-02-19T16:10:38Z<p>Ptse: </p>
<hr />
<div></div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Patrick_Tse&diff=93398Patrick Tse2021-02-19T16:09:57Z<p>Ptse: picture</p>
<hr />
<div><br />
== '''Introduction''' ==<br />
<br />
Personally, I find the Internet somewhat scary because of how easy it is for people to access information through the Internet. Because of this, most of my social media accounts are private and I also am not very active on my social media. Due to my lack of a presence online, I believe that my data identity accurately represents only a part of my whole identity.<br />
<br />
== '''Google Search''' ==<br />
<br />
Aside from having private social media accounts, there is a bigger problem when you google “Patrick Tse.” The first person who shows up is an actor, producer, screenwriter, and director in Hong Kong cinema. It makes sense that a university student does not show up compared to this Hong Kong celebrity. He takes up almost the first four pages when searched up. To try to narrow down the search, I tried typing my name with my middle name as well. To my surprise, there were still no results near what I was looking for. The Hong Kong celebrity showed up again… Since even typing in my full name did not yield any results I wanted to see how specific the searches had to be for anything about me to show up. After searching my name attached with something that could potentially be related to me, I finally got something! When I searched “patrick tse california,” California is where I am from, my LinkedIn account was the first result that showed up. I realized this was because my LinkedIn account has information I inputted about where I went to high school in California. When I searched up “patrick tse michigan” my LinkedIn is also the first result because it has information about me attending the University of Michigan. All my other social media accounts do not have any information about where I am from, so it would make sense why they did not show up. I attempted to search for my Facebook and Instagram as well. However, for Facebook there were quite a few other Patrick Tses. After scrolling through for a while I still could not find myself. Although searching for my Facebook was unsuccessful, I was able to find my Instagram. I had to search up my username for it to be found. Even though I was able to find it, my account is private.<br />
<br />
One thing I realized while searching for information on myself is that social media has become a political piece of technology. In Winner’s, Do Artifacts Have Politics?, he discusses the idea of certain pieces of technology being inherently political. This means that the piece of technology needs some sort of political structure of control to make sure it is not used in the wrong context. However, social media has created its own sort of politics around it. The popularity of people and their appearance on their social media have become extremely important. For example, my LinkedIn showing up in a simple google search matters because employers can see my profile. My LinkedIn has information about me that hopefully represents a side of me that has qualities that are desirable to an employer. My past job experiences, education, etc. are all on my LinkedIn. Given the pretext that LinkedIn is more of a professional social media platform, it would make sense for a user to only put information that would be appropriate in a workplace. For that reason, my LinkedIn account by no means represents all of me, but it is the main thing that shows up when my name is googled. It was a very political decision by me to keep my other social media accounts more private and to have my LinkedIn more exposed. My LinkedIn has much more information about me so potential employers can get a sense of what type of person I am. I would not want my personal social media accounts showing up alongside my LinkedIn. <br />
<br />
To conclude, basing the search solely on Google, the search has to be quite specific to get any sort of meaningful result. This is mostly because I enjoy my privacy from others on the web who I do not know. Although there seems to be a minimal amount of information from a basic google search, there is a lot of my information out there. From making accounts for games to putting my email on a mailing list, I have no idea how many accounts I have created for a variety of things.<br />
<br />
== '''App/Account Data''' ==<br />
<br />
Whether it’s a new game on my phone or creating an account to get free shipping, my information is all over the place. The main pieces of data that all these services ask for are name, phone number, and email. Personally, I do not find giving such basic information a problem. I do not think giving my phone number or email does much harm. While they have my contact information, it is my decision to engage or ignore whoever contacts me. However, there are certain things that I have signed up for that require quite sensitive information. For example, the app Webull, a stock trading platform, required that I input my social security number. In this case, I know that Webull is a reliable app because I personally know people who have used this app and have had no problems with it. While I know that the app is most likely reliable, I always feel as if you should still be weary when giving such private information. A couple of years ago, I had an incident where a college I had applied to informed me that they had been hacked and that some of the information about applicants and students had been stolen. Thankfully nothing happened to me personally, but it shows that systems that seem to be safe may not always be safe. <br />
<br />
===Game Data===<br />
[[File:Brawlstars.PNG|thumbnail|right|screenshot of the game Brawlstars]]<br />
One of the things that intrigues me is the data that is gathered on mobile and video games. In many of the games I play, especially mobile, there are in-app purchases. There are typically two types of currencies: one that is more easily acquired and one that is harder to acquire but money in real life can be used to purchase more of this currency. The one that can be bought with money typically can help you gain materials that will make the game easier or more fun. One of the mobile games that I currently play, Brawlstars, has this same sort of model. Without getting into too much detail about the game itself, the main points about the game that I want to discuss is how currency is acquired and how materials are bought. In the game, there are two currencies: coins and gems. Coins are the more easily attained currency and gems are the currency that can be bought through in-app purchase. One important thing to note is that coins can also be bought in exchange for gems. When buying materials to upgrade your characters, sometimes the exact materials needed to upgrade a character will show up. The catch is that many times it will end up costing a hefty amount to get those materials. Since the materials in the shop change daily, it incentivizes users to spend real money to get those materials. The fact that this situation consistently happens lets me know that the game is clearly monitoring my progress and trying to get me to spend money, which is most likely part of the business model. While this data is only contained within the game and does not have any affect on my life, I find it interesting how the data is used. Just in the way that some sites have targeted ads, some games use the users’ data to gain an advantage on them.<br />
<br />
== '''Conclusion''' ==<br />
<br />
Searching the Internet for myself was quite interesting. I knew from the start that it would not be easy to find myself online due to my social media accounts being private. Because LinkedIn was the only social media platform I could find on myself, I believe my data identity does not well represent me as a whole. My LinkedIn profile is strictly my professional identity. It does not include anything about my hobbies or any of my private information. While my data identity does not fully represent me, that is actually more of a relief to me. If my data identity was a very accurate representation of myself, that would mean that there is a considerable amount of information about me that is public. Since that is not the case, that means that I am keeping my digital footprint to a minimum which is exactly what I want!</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Patrick_Tse&diff=93385Patrick Tse2021-02-19T16:07:02Z<p>Ptse: adding picture</p>
<hr />
<div><br />
== '''Introduction''' ==<br />
<br />
Personally, I find the Internet somewhat scary because of how easy it is for people to access information through the Internet. Because of this, most of my social media accounts are private and I also am not very active on my social media. Due to my lack of a presence online, I believe that my data identity accurately represents only a part of my whole identity.<br />
<br />
== '''Google Search''' ==<br />
<br />
Aside from having private social media accounts, there is a bigger problem when you google “Patrick Tse.” The first person who shows up is an actor, producer, screenwriter, and director in Hong Kong cinema. It makes sense that a university student does not show up compared to this Hong Kong celebrity. He takes up almost the first four pages when searched up. To try to narrow down the search, I tried typing my name with my middle name as well. To my surprise, there were still no results near what I was looking for. The Hong Kong celebrity showed up again… Since even typing in my full name did not yield any results I wanted to see how specific the searches had to be for anything about me to show up. After searching my name attached with something that could potentially be related to me, I finally got something! When I searched “patrick tse california,” California is where I am from, my LinkedIn account was the first result that showed up. I realized this was because my LinkedIn account has information I inputted about where I went to high school in California. When I searched up “patrick tse michigan” my LinkedIn is also the first result because it has information about me attending the University of Michigan. All my other social media accounts do not have any information about where I am from, so it would make sense why they did not show up. I attempted to search for my Facebook and Instagram as well. However, for Facebook there were quite a few other Patrick Tses. After scrolling through for a while I still could not find myself. Although searching for my Facebook was unsuccessful, I was able to find my Instagram. I had to search up my username for it to be found. Even though I was able to find it, my account is private.<br />
<br />
One thing I realized while searching for information on myself is that social media has become a political piece of technology. In Winner’s, Do Artifacts Have Politics?, he discusses the idea of certain pieces of technology being inherently political. This means that the piece of technology needs some sort of political structure of control to make sure it is not used in the wrong context. However, social media has created its own sort of politics around it. The popularity of people and their appearance on their social media have become extremely important. For example, my LinkedIn showing up in a simple google search matters because employers can see my profile. My LinkedIn has information about me that hopefully represents a side of me that has qualities that are desirable to an employer. My past job experiences, education, etc. are all on my LinkedIn. Given the pretext that LinkedIn is more of a professional social media platform, it would make sense for a user to only put information that would be appropriate in a workplace. For that reason, my LinkedIn account by no means represents all of me, but it is the main thing that shows up when my name is googled. It was a very political decision by me to keep my other social media accounts more private and to have my LinkedIn more exposed. My LinkedIn has much more information about me so potential employers can get a sense of what type of person I am. I would not want my personal social media accounts showing up alongside my LinkedIn. <br />
<br />
To conclude, basing the search solely on Google, the search has to be quite specific to get any sort of meaningful result. This is mostly because I enjoy my privacy from others on the web who I do not know. Although there seems to be a minimal amount of information from a basic google search, there is a lot of my information out there. From making accounts for games to putting my email on a mailing list, I have no idea how many accounts I have created for a variety of things.<br />
<br />
== '''App/Account Data''' ==<br />
<br />
Whether it’s a new game on my phone or creating an account to get free shipping, my information is all over the place. The main pieces of data that all these services ask for are name, phone number, and email. Personally, I do not find giving such basic information a problem. I do not think giving my phone number or email does much harm. While they have my contact information, it is my decision to engage or ignore whoever contacts me. However, there are certain things that I have signed up for that require quite sensitive information. For example, the app Webull, a stock trading platform, required that I input my social security number. In this case, I know that Webull is a reliable app because I personally know people who have used this app and have had no problems with it. While I know that the app is most likely reliable, I always feel as if you should still be weary when giving such private information. A couple of years ago, I had an incident where a college I had applied to informed me that they had been hacked and that some of the information about applicants and students had been stolen. Thankfully nothing happened to me personally, but it shows that systems that seem to be safe may not always be safe. <br />
<br />
===Game Data===<br />
[[File:IMG 4475.PNG|thumbnail|screenshot of the game Brawlstars]]<br />
One of the things that intrigues me is the data that is gathered on mobile and video games. In many of the games I play, especially mobile, there are in-app purchases. There are typically two types of currencies: one that is more easily acquired and one that is harder to acquire but money in real life can be used to purchase more of this currency. The one that can be bought with money typically can help you gain materials that will make the game easier or more fun. One of the mobile games that I currently play, Brawlstars, has this same sort of model. Without getting into too much detail about the game itself, the main points about the game that I want to discuss is how currency is acquired and how materials are bought. In the game, there are two currencies: coins and gems. Coins are the more easily attained currency and gems are the currency that can be bought through in-app purchase. One important thing to note is that coins can also be bought in exchange for gems. When buying materials to upgrade your characters, sometimes the exact materials needed to upgrade a character will show up. The catch is that many times it will end up costing a hefty amount to get those materials. Since the materials in the shop change daily, it incentivizes users to spend real money to get those materials. The fact that this situation consistently happens lets me know that the game is clearly monitoring my progress and trying to get me to spend money, which is most likely part of the business model. While this data is only contained within the game and does not have any affect on my life, I find it interesting how the data is used. Just in the way that some sites have targeted ads, some games use the users’ data to gain an advantage on them.<br />
<br />
== '''Conclusion''' ==<br />
<br />
Searching the Internet for myself was quite interesting. I knew from the start that it would not be easy to find myself online due to my social media accounts being private. Because LinkedIn was the only social media platform I could find on myself, I believe my data identity does not well represent me as a whole. My LinkedIn profile is strictly my professional identity. It does not include anything about my hobbies or any of my private information. While my data identity does not fully represent me, that is actually more of a relief to me. If my data identity was a very accurate representation of myself, that would mean that there is a considerable amount of information about me that is public. Since that is not the case, that means that I am keeping my digital footprint to a minimum which is exactly what I want!</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Patrick_Tse&diff=92515Patrick Tse2021-02-19T04:33:34Z<p>Ptse: edit</p>
<hr />
<div>== '''Introduction''' ==<br />
<br />
Personally, I find the Internet somewhat scary because of how easy it is for people to access information through the Internet. Because of this, most of my social media accounts are private and I also am not very active on my social media. Due to my lack of a presence online, I believe that my data identity accurately represents only a part of my whole identity.<br />
<br />
== '''Google Search''' ==<br />
<br />
Aside from having private social media accounts, there is a bigger problem when you google “Patrick Tse.” The first person who shows up is an actor, producer, screenwriter, and director in Hong Kong cinema. It makes sense that a university student does not show up compared to this Hong Kong celebrity. He takes up almost the first four pages when searched up. To try to narrow down the search, I tried typing my name with my middle name as well. To my surprise, there were still no results near what I was looking for. The Hong Kong celebrity showed up again… Since even typing in my full name did not yield any results I wanted to see how specific the searches had to be for anything about me to show up. After searching my name attached with something that could potentially be related to me, I finally got something! When I searched “patrick tse california,” California is where I am from, my LinkedIn account was the first result that showed up. I realized this was because my LinkedIn account has information I inputted about where I went to high school in California. When I searched up “patrick tse michigan” my LinkedIn is also the first result because it has information about me attending the University of Michigan. All my other social media accounts do not have any information about where I am from, so it would make sense why they did not show up. I attempted to search for my Facebook and Instagram as well. However, for Facebook there were quite a few other Patrick Tses. After scrolling through for a while I still could not find myself. Although searching for my Facebook was unsuccessful, I was able to find my Instagram. I had to search up my username for it to be found. Even though I was able to find it, my account is private.<br />
<br />
One thing I realized while searching for information on myself is that social media has become a political piece of technology. In Winner’s, Do Artifacts Have Politics?, he discusses the idea of certain pieces of technology being inherently political. This means that the piece of technology needs some sort of political structure of control to make sure it is not used in the wrong context. However, social media has created its own sort of politics around it. The popularity of people and their appearance on their social media have become extremely important. For example, my LinkedIn showing up in a simple google search matters because employers can see my profile. My LinkedIn has information about me that hopefully represents a side of me that has qualities that are desirable to an employer. My past job experiences, education, etc. are all on my LinkedIn. Given the pretext that LinkedIn is more of a professional social media platform, it would make sense for a user to only put information that would be appropriate in a workplace. For that reason, my LinkedIn account by no means represents all of me, but it is the main thing that shows up when my name is googled. It was a very political decision by me to keep my other social media accounts more private and to have my LinkedIn more exposed. My LinkedIn has much more information about me so potential employers can get a sense of what type of person I am. I would not want my personal social media accounts showing up alongside my LinkedIn. <br />
<br />
To conclude, basing the search solely on Google, the search has to be quite specific to get any sort of meaningful result. This is mostly because I enjoy my privacy from others on the web who I do not know. Although there seems to be a minimal amount of information from a basic google search, there is a lot of my information out there. From making accounts for games to putting my email on a mailing list, I have no idea how many accounts I have created for a variety of things.<br />
<br />
== '''App/Account Data''' ==<br />
<br />
Whether it’s a new game on my phone or creating an account to get free shipping, my information is all over the place. The main pieces of data that all these services ask for are name, phone number, and email. Personally, I do not find giving such basic information a problem. I do not think giving my phone number or email does much harm. While they have my contact information, it is my decision to engage or ignore whoever contacts me. However, there are certain things that I have signed up for that require quite sensitive information. For example, the app Webull, a stock trading platform, required that I input my social security number. In this case, I know that Webull is a reliable app because I personally know people who have used this app and have had no problems with it. While I know that the app is most likely reliable, I always feel as if you should still be weary when giving such private information. A couple of years ago, I had an incident where a college I had applied to informed me that they had been hacked and that some of the information about applicants and students had been stolen. Thankfully nothing happened to me personally, but it shows that systems that seem to be safe may not always be safe. <br />
<br />
===Game Data===<br />
<br />
One of the things that intrigues me is the data that is gathered on mobile and video games. In many of the games I play, especially mobile, there are in-app purchases. There are typically two types of currencies: one that is more easily acquired and one that is harder to acquire but money in real life can be used to purchase more of this currency. The one that can be bought with money typically can help you gain materials that will make the game easier or more fun. One of the mobile games that I currently play, Brawlstars, has this same sort of model. Without getting into too much detail about the game itself, the main points about the game that I want to discuss is how currency is acquired and how materials are bought. In the game, there are two currencies: coins and gems. Coins are the more easily attained currency and gems are the currency that can be bought through in-app purchase. One important thing to note is that coins can also be bought in exchange for gems. When buying materials to upgrade your characters, sometimes the exact materials needed to upgrade a character will show up. The catch is that many times it will end up costing a hefty amount to get those materials. Since the materials in the shop change daily, it incentivizes users to spend real money to get those materials. The fact that this situation consistently happens lets me know that the game is clearly monitoring my progress and trying to get me to spend money, which is most likely part of the business model. While this data is only contained within the game and does not have any affect on my life, I find it interesting how the data is used. Just in the way that some sites have targeted ads, some games use the users’ data to gain an advantage on them.<br />
<br />
== '''Conclusion''' ==<br />
<br />
Searching the Internet for myself was quite interesting. I knew from the start that it would not be easy to find myself online due to my social media accounts being private. Because LinkedIn was the only social media platform I could find on myself, I believe my data identity does not well represent me as a whole. My LinkedIn profile is strictly my professional identity. It does not include anything about my hobbies or any of my private information. While my data identity does not fully represent me, that is actually more of a relief to me. If my data identity was a very accurate representation of myself, that would mean that there is a considerable amount of information about me that is public. Since that is not the case, that means that I am keeping my digital footprint to a minimum which is exactly what I want!</div>Ptsehttp://si410wiki.sites.uofmhosting.net/index.php?title=Patrick_Tse&diff=92514Patrick Tse2021-02-19T04:32:35Z<p>Ptse: data identity</p>
<hr />
<div>== '''Introduction''' ==<br />
<br />
Personally, I find the Internet somewhat scary because of how easy it is for people to access information through the Internet. Because of this, most of my social media accounts are private and I also am not very active on my social media. Due to my lack of a presence online, I believe that my data identity accurately represents only a part of my whole identity.<br />
<br />
== '''Google Search''' ==<br />
<br />
Aside from having private social media accounts, there is a bigger problem when you google “Patrick Tse.” The first person who shows up is an actor, producer, screenwriter, and director in Hong Kong cinema. It makes sense that a university student does not show up compared to this Hong Kong celebrity. He takes up almost the first four pages when searched up. To try to narrow down the search, I tried typing my name with my middle name as well. To my surprise, there were still no results near what I was looking for. The Hong Kong celebrity showed up again… Since even typing in my full name did not yield any results I wanted to see how specific the searches had to be for anything about me to show up. After searching my name attached with something that could potentially be related to me, I finally got something! When I searched “patrick tse california,” California is where I am from, my LinkedIn account was the first result that showed up. I realized this was because my LinkedIn account has information I inputted about where I went to high school in California. When I searched up “patrick tse michigan” my LinkedIn is also the first result because it has information about me attending the University of Michigan. All my other social media accounts do not have any information about where I am from, so it would make sense why they did not show up. I attempted to search for my Facebook and Instagram as well. However, for Facebook there were quite a few other Patrick Tses. After scrolling through for a while I still could not find myself. Although searching for my Facebook was unsuccessful, I was able to find my Instagram. I had to search up my username for it to be found. Even though I was able to find it, my account is private.<br />
<br />
One thing I realized while searching for information on myself is that social media has become a political piece of technology. In Winner’s, Do Artifacts Have Politics?, he discusses the idea of certain pieces of technology being inherently political. This means that the piece of technology needs some sort of political structure of control to make sure it is not used in the wrong context. However, social media has created its own sort of politics around it. The popularity of people and their appearance on their social media have become extremely important. For example, my LinkedIn showing up in a simple google search matters because employers can see my profile. My LinkedIn has information about me that hopefully represents a side of me that has qualities that are desirable to an employer. My past job experiences, education, etc. are all on my LinkedIn. Given the pretext that LinkedIn is more of a professional social media platform, it would make sense for a user to only put information that would be appropriate in a workplace. For that reason, my LinkedIn account by no means represents all of me, but it is the main thing that shows up when my name is googled. It was a very political decision by me to keep my other social media accounts more private and to have my LinkedIn more exposed. My LinkedIn has much more information about me so potential employers can get a sense of what type of person I am. I would not want my personal social media accounts showing up alongside my LinkedIn. <br />
<br />
To conclude, basing the search solely on Google, the search has to be quite specific to get any sort of meaningful result. This is mostly because I enjoy my privacy from others on the web who I do not know. Although there seems to be a minimal amount of information from a basic google search, there is a lot of my information out there. From making accounts for games to putting my email on a mailing list, I have no idea how many accounts I have created for a variety of things.<br />
<br />
== '''App/Account Data''' ==<br />
<br />
Whether it’s a new game on my phone or creating an account to get free shipping, my information is all over the place. The main pieces of data that all these services ask for are name, phone number, and email. Personally, I do not find giving such basic information a problem. I do not think giving my phone number or email does much harm. While they have my contact information, it is my decision to engage or ignore whoever contacts me. However, there are certain things that I have signed up for that require quite sensitive information. For example, the app Webull, a stock trading platform, required that I input my social security number. In this case, I know that Webull is a reliable app because I personally know people who have used this app and have had no problems with it. While I know that the app is most likely reliable, I always feel as if you should still be weary when giving such private information. A couple of years ago, I had an incident where a college I had applied to informed me that they had been hacked and that some of the information about applicants and students had been stolen. Thankfully nothing happened to me personally, but it shows that systems that seem to be safe may not always be safe. <br />
<br />
Game Data(subheading)<br />
<br />
One of the things that intrigues me is the data that is gathered on mobile and video games. In many of the games I play, especially mobile, there are in-app purchases. There are typically two types of currencies: one that is more easily acquired and one that is harder to acquire but money in real life can be used to purchase more of this currency. The one that can be bought with money typically can help you gain materials that will make the game easier or more fun. One of the mobile games that I currently play, Brawlstars, has this same sort of model. Without getting into too much detail about the game itself, the main points about the game that I want to discuss is how currency is acquired and how materials are bought. In the game, there are two currencies: coins and gems. Coins are the more easily attained currency and gems are the currency that can be bought through in-app purchase. One important thing to note is that coins can also be bought in exchange for gems. When buying materials to upgrade your characters, sometimes the exact materials needed to upgrade a character will show up. The catch is that many times it will end up costing a hefty amount to get those materials. Since the materials in the shop change daily, it incentivizes users to spend real money to get those materials. The fact that this situation consistently happens lets me know that the game is clearly monitoring my progress and trying to get me to spend money, which is most likely part of the business model. While this data is only contained within the game and does not have any affect on my life, I find it interesting how the data is used. Just in the way that some sites have targeted ads, some games use the users’ data to gain an advantage on them.<br />
<br />
== '''Conclusion''' ==<br />
<br />
Searching the Internet for myself was quite interesting. I knew from the start that it would not be easy to find myself online due to my social media accounts being private. Because LinkedIn was the only social media platform I could find on myself, I believe my data identity does not well represent me as a whole. My LinkedIn profile is strictly my professional identity. It does not include anything about my hobbies or any of my private information. While my data identity does not fully represent me, that is actually more of a relief to me. If my data identity was a very accurate representation of myself, that would mean that there is a considerable amount of information about me that is public. Since that is not the case, that means that I am keeping my digital footprint to a minimum which is exactly what I want!</div>Ptse