Difference between revisions of "Infoglut"
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| − | '''Infoglut''' refers to | + | An '''Infoglut''' (or information glut) -- otherwise know as “information overload”, “infobesity”, or “information anxiety” -- refers to excessive amounts of disorganized information that continuously accumulate. As Luciano Floridi states, "Infoglut means that at a certain point the whole system does not absorb anything". Because of the sheer amount of information, largely composed of distracting and meaningless clutter, organizing infospheres and gathering relevant information to form coherent conclusions is extremely difficult.<ref>“What Is Infoglut? Definition and Meaning.” BusinessDictionary.com, www.businessdictionary.com/definition/infoglut.html.</ref><ref name = "Zeldes">Zeldes, Nathan. “Infoglut.” IEEE Spectrum, vol. 46, no. 10, 2009, pp. 30–55., doi:10.1109/mspec.2009.5267994.</ref> |
| − | It is generally associated with | + | It is generally associated with being overwhelmed and hopelessly confused by the massses of information being presented -- which are more often than not devoid of any meaning, patterns, or content. Therefore, it is closely related to the concepts of [https://en.wikipedia.org/wiki/Information_overload Information Overload] and Information Anxiety. Infoglut is classified by some, notably by [https://en.wikipedia.org/wiki/Luciano_Floridi Luciano Floridi] as an Epistemological problem, which is a broader philosophical concept dealing with the theory of knowledge and perception. <ref>Floridi, Luciano. “‘Infoglut’ - Q&A.” YouTube, YouTube, 20 Dec. 2016, www.youtube.com/watch?v=2UHTPkeByLM.</ref> |
| − | + | ||
| − | + | ||
| − | + | The growth of the technology field, the rapid increase in the ability to distribute and access information, and the growing shift in focus towards "Big Data" all continue to be determinants of today's information overload. Consequently, the effect of being rendered unable to absorb information due to the sheer mass of availability has grown into a large ethical issue that stems from technological and informational advances. | |
| − | |||
| − | |||
| − | == | + | == Origin and Evolution == |
| − | The | + | The taxonomy of the term is very telling: Infoglut derived from the words “Information”, referring to facts and data, and “Glut”, referencing “Gluttony”. Gluttony suggests a dangerous abundance and excessiveness. Having appeared in several published works since its creation, the term was recently publicized in 2013 by Marc Andrejevic's book "Infoglut: How Too Much Information Is Changing the Way We Think And Know". |
| + | In his book, Andrejevic discusses the concept of information overload and different strategies to tame infoglut in society. | ||
| − | + | The origins of the word date as far back as the early-mid 1990s, where it has been mentioned in several articles and books. Thomas John's book "Managing the Infoglut: Information Filtering Using Neural Networks" and Michael Marien's article "Infoglut and competing problems: Key barriers suggesting a new strategy for sustainability" <ref>“Infoglut and Competing Problems: Key Barriers Suggesting a New Strategy for Sustainability.” Futures, Pergamon, 26 Apr. 2002, www.sciencedirect.com/science/article/pii/0016328794901139.</ref> were both published in 1994 and indicate the widespread use and research surrounding the term. In addition to introducing the term, they also normalized it. | |
| − | The Information Age (also known as The Computer Age, The Digital Age, The New Media Age), started in the 1970s and is still | + | The Information Age (also known as The Computer Age, The Digital Age, The New Media Age), started in the 1970s and is still developing today. It follows trend from the Industrial Age that preceded it and has its title due to the rapid transition from the global economy's focus on industrialization to informational technology. In this era, the computing power, storage and memory capacity, as well as speed of computers, have risen exponentially, facilitating the abundance of information that now exists. Since the onset of the Information Age, the rise in information and computation has led to a rise in innovations and data analysis and has paved the way for further job creation and economic globalization. The full effect on the economy is not yet fully understood and is still largely debated. |
== Research and Publications == | == Research and Publications == | ||
=== Books === | === Books === | ||
| − | Since the 1990s, there | + | Since the 1990s, there have been extensive discussions about Infoglut and its effects. [[File:Infoglut.jpg|thumbnail|Marc Andrejevic's Book On Infoglut, 2013]] Numerous books have been published about the dangers and merits of infoglut, and more importantly, how to deal with it in the current information landscape. "Managing the Infoglut : Information Filtering Using Neural Networks" by Thomas John exemplifies the kind of work that existed ahead of its time regarding both Infoglut and Neural Networks, terms that have come to light in the 21st century with the rise of Artificial Intelligence. The book discusses the dangers of too much information at once and the speed with which data can accumulate, and how to maintain the ability to efficiently retrieve information from within the data, through the use of an "electronic superhighway."<ref>John, Thomas. “Managing the Infoglut: Information Filtering Using Neural Networks.” SpringerLink, Springer, Boston, MA, 1 Jan. 1994, link.springer.com/chapter/10.1007/978-1-4615-2734-3_16.</ref> Marc Andrejevic's "Infoglut : How Too Much Information Is Changing the Way We Think And Know" is the latest book on Infoglut that caused a major wave, and is a cornerstone for the subject, expanding on the various strategies to deal with information overload and "big data," and how these strategies are connected and the new forms of control they enable.<ref>Andrejevic, Mark. “Infoglut | How Too Much Information Is Changing the Way We Think and Know.” Taylor & Francis, Taylor & Francis, 26 June 2013, www.taylorfrancis.com/books/9781135119522.</ref> |
=== Articles === | === Articles === | ||
| − | Articles on the subject include “Turning an Info-Glut into A Library” by Robert Pool<ref>Pool, R. “Turning an Info-Glut into a Library.” Science, 7 Oct. 1994, go.galegroup.com/ps/anonymous?id=GALE%7CA15827725&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=00368075&p=AONE&sw=w.</ref>, written in 1994, that discusses converting the overload of | + | Articles on the subject include “Turning an Info-Glut into A Library” by Robert Pool<ref>Pool, R. “Turning an Info-Glut into a Library.” Science, 7 Oct. 1994, go.galegroup.com/ps/anonymous?id=GALE%7CA15827725&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=00368075&p=AONE&sw=w.</ref>, written in 1994, that discusses converting the overload of information caused by infoglut into a positive and usable source of data . In 1997, David Shenk wrote an article called "Data Smog : Surviving the Info Glut"<ref>Shenk, and David. “Data Smog: Surviving the Info Glut.” Technology Review, 30 Nov. 1996, eric.ed.gov/?id=EJ544699.</ref> which similarly highlights the dangers and drawbacks of the Information Age and how it leads to Information Anxiety . In 1998, The Harvard Journal of Law and Technology published a paper called “Internet Infoglut and Invisible Ink: Spamdexing Search Engines with Meta Tags” <ref>Nathenson, Ira S. “Internet Infoglut and Invisible Ink: Spamdexing Search Engines with Meta Tags .” HeinOnline, heinonline.org/HOL/LandingPage?handle=hein.journals%2Fhjlt12&div=8&id=&page=.</ref> by Ira S Nathenson, which drew upon the works of Shenk, amongst others . There have been articles throughout the 2000s including "The Profession of IT - Infoglut" by Peter J. Denning in 2006 and "Infoglut" by Nathan Zeldes in 2009. |
==Parsing Through Infoglut== | ==Parsing Through Infoglut== | ||
| − | Due to the excessive amount of information that people are being | + | Due to the excessive amount of information that people are being exposed to each day, it is helpful to have a method of parsing through this immense amount of information in order to be able to easily digest it without getting confused or overwhelmed. Data mining helps to extract this information and transform it into a more digestible structure for easy user consumption using methods that stem from computer science and statistics. [https://en.wikipedia.org/wiki/Data_mining Data Miners] help people combat information overload in a way that the common eye would not recognize <ref>Andrejevic, M. (2013). Infoglut: How too much information is changing the way we think and know. Infoglut: How Too Much Information is Changing the Way we Think and Know. 1-202. 10.4324/9780203075319.</ref>. |
| + | |||
| + | Another way in which people can parse through excessive amounts of information is by purchasing technology that is tuned to combating infoglut. An example of this is the technology that protects users from exposure to unnecessary information, such as unwanted phone calls and email spam. Installing filters on search engines and media feeds is another way to prioritize favorable information and sift out the insignificant matter. However, even filters have trouble refining results due to the infoglut, so nowadays filters do a better job at "filtering forward" information and with-holding the rest temporarily, though this data will still come up once you get through what the algorithm decided was most prevalent. This does not eliminate useless data, it only delays it. Another drawback to filters is that they may limit choices that would have educated the individual on information from what they wouldn't normally view. This promotes the "echo chamber" effect of surrounding the reader with information that coincides with what they normally view and agree with, instead of informing them on multiple perspectives to create a well-rounded understanding and individual. This tendency of filters to put forth information that reinforces previously established opinions can often create extremists who are not exposed to the critical information outside of their comfort zone. Infoglut is a rapidly increasing phenomenon, and it is up to the users to be proactive and take steps to cut down on the amount of information to which they are exposed to create healthy, knowledgable information citizens. <ref>Zeldes, Nathan. “How to Beat Information Overload.” IEEE Spectrum: Technology, Engineering, and Science News, IEEE Spectrum, 30 Sept. 2009, spectrum.ieee.org/computing/it/how-to-beat-information-overload.</ref>. | ||
== Ethical Issues == | == Ethical Issues == | ||
| − | The rise in Information has also seen a host of related ethical issues surface along with it. Primarily, Infoglut hampers people's decision-making abilities by offering too many details and information, the surplus of which leads to high levels of indecisiveness a long loop of searching. This has led to a various attention deficit issues within people. There is also a rising conflict between information and privacy, as many people do not believe that | + | The rise in Information overload has also seen a host of related ethical issues surface along with it. Primarily, Infoglut hampers people's decision-making abilities by offering too many details and information, the surplus of which leads to high levels of indecisiveness and a long loop of searching. Much like the "Too many choices" paradox<ref>Tugend, Alina. “The Paralyzing Problem of Too Many Choices.” The New York Times, The New York Times, 26 Feb. 2010, www.nytimes.com/2010/02/27/your-money/27shortcuts.html.</ref>, which dictates that an over abundance of choices can make it much harder to actually make a decision, infoglut affects searching information in the same way. Like a sponge absorbing too much water, once too much information is gathered, its usefulness diminishes. This results in an inefficiency of sorts because people are spending more time sorting thorough information than they are actually processing it. This has led to a various attention deficit issues within people. There is also a rising conflict between information and privacy, as many people do not believe that it is possible to protect individual privacy to the extent that it was before. It has also raised environmental concerns, corporations have increased their usage of paper, given the high volume of information needed to be documented tangibly. |
| − | === | + | === Epistemological Issues === |
| − | Luciano Floridi has repeatedly considered Infoglut to be a larger | + | Luciano Floridi has repeatedly considered Infoglut to be a larger epistemological problem (e.g. what knowledge is valid, who it belongs to, and the distinctions between belief and opinion). He pointed out specific ethical problems that arise with big data mostly centered around privacy. In a lecture delivered at Oxford University, Floridi asked the splitting question "Does respect for individual's privacy require respect for privacy of the group to which the individual belongs to?"<ref>“Big Data, Small Patterns, and Huge Ethical Issues.” Oxford Internet Institute, www.oii.ox.ac.uk/videos/big-data-small-patterns-and-huge-ethical-issues/.</ref>. He believes that there are a plethora of ethical questions and dilemmas that arise with growing data and that the matters of group privacy and individual privacy have several points of intersection that can be potential grey areas or problem points moving forward. Floridi also points out about infoglut that beyond a certain point, a system is not able to comprehend or absorb any more due to the sheer mass of information it is being fed. He says that at a point, while it might be possible to discern that the data is half right and half wrong, it might be impossible to state which half is which. |
=== Information Entropy === | === Information Entropy === | ||
| − | Information entropy is the destruction, pollution, and depletion of information objects. The concept of Informational Entropy was coined by American Mathematician Claude Shannon. It is the measure of uncertainty within an event or topic. Generally, the lower the amount of information that exists within the scope of the event or matter, the higher the certainty. However, due to constantly growing rates of accumulating information, the level of information across subjects has increased vastly, leading to higher entropy and uncertainty. | + | Information entropy is the destruction, pollution, and depletion of information objects. The concept of Informational Entropy was coined by American Mathematician Claude Shannon. It is the measure of uncertainty within an event or topic. Generally, the lower the amount of information that exists within the scope of the event or matter, the higher the certainty. However, due to constantly growing rates of accumulating information, the level of information across subjects has increased vastly, leading to higher entropy and uncertainty. The uncertainty is in what information is valuable and urgent while it is diluted by the unreasonable amount of insignificant data circulating the infosphere. The infoglut makes it difficult for individuals to decipher what should be read and prioritized versus what should be ignored. If you have to sift through too much useless information to reach the important matter, it is discouraging and time-wasting, and the important information won't be absorbed. |
| − | There has also been an increase in individual entropy caused by the discrepancy between the speed at which digital information is being computed and transferred and people's personal rate of processing information. | + | There has also been an increase in individual entropy caused by the discrepancy between the speed at which digital information is being computed and then transferred and people's personal rate of processing information. Economist Herbert A. Simon has been quoted stating along similar lines that a “wealth of information creates a poverty of attention” and “an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients.” <ref>Schweller, Randall L. “The Age of Entropy.” Foreign Affairs, Foreign Affairs Magazine, 17 June 2014, www.foreignaffairs.com/articles/united-states/2014-06-16/age-entropy.</ref> Therefore, as the wealth of information grows with technology, people's attention to information diminishes. |
| − | Economist Herbert A. Simon has been quoted stating along similar lines that a “wealth of information creates a poverty of | + | |
=== Information Fatigue Syndrome === | === Information Fatigue Syndrome === | ||
| Line 50: | Line 48: | ||
<u>A list of symptoms include:</u><ref name="nguyen"/> | <u>A list of symptoms include:</u><ref name="nguyen"/> | ||
| − | + | * Poor concentration | |
| − | + | * Multitasking resulting in diminished productivity | |
| − | + | * Hurry Sickness | |
| − | + | * Heightened irritability or rage | |
| − | + | * Over simulation resulting in a mental trance like state | |
| − | + | * Compulsion related to checking online media and messaging sources | |
| − | + | * Stress and lowered immune responses<ref>Chard, P. (2002). Information overload: Are we technology's masters...or servants? WorldAtWork | |
Journal 11(3).</ref> | Journal 11(3).</ref> | ||
| + | === Data As A Commodity === | ||
| + | The increase in the sheer volume of information available to any given person has led to multiple large scale cases of privacy invasion. Within these infringements, personal data has become a commodity available for trade to augment greater consumer information. The more data pertaining to the common user that is gathered, the more accurately and successfully large corporations can target their intended consumers, the more successful they will be in turning a profit and growing their business. [https://en.wikipedia.org/wiki/Facebook–Cambridge_Analytica_data_scandal Facebook Cambridge Analytica Scandal ] of 2018 was a shocking event for millions of users. Their personal information was harvested from Facebook profiles without their consent and used for political purposes. The privacy of millions of people was compromised in favor of data collection. This led to concerns that this case was just scratching the surface of deeper and more questionable informational transactions. The event marked a critical shift in the perception of data, not as a resource but as a tradable commodity that could be used for profit. There arose a greater fear that people's individual privacy was being handed over to companies that treated it as tradable in exchange for monetary value. | ||
=== Aggregation === | === Aggregation === | ||
| − | Aggregation acts as a way to manage the constantly accumulating disorganized data. Aggregation brings together information that has been gathered from several sources into one single data structure <ref>Mooradian, Norman. 14 July 2009. The Importance of Privacy Revisited. Springer Science+Business Media. </ref> Data aggregation can have many different purposes, including statistical analysis, eliminating duplicate or irrelevant information, or summarizing data for quick consumption. A classic example of data aggregation would be | + | Aggregation acts as a way to manage the constantly accumulating disorganized data. Aggregation brings together information that has been gathered from several sources into one single data structure. <ref>Mooradian, Norman. 14 July 2009. The Importance of Privacy Revisited. Springer Science+Business Media. </ref> Data aggregation can have many different purposes, including statistical analysis, eliminating duplicate or irrelevant information, or summarizing data for quick consumption. A classic example of data aggregation would be Google searching someone's name and finding a few personal details about that individual. There is a dispute about whether a more in-depth data aggregation could be construed as an invasion of privacy. For example, a more intrusive example of data aggregation would be a data broker report that can be bought online that would include even more personal facts about an individual than a Google search could yield. There is an increasing amount of commercial data that is aggregated by companies in order to inform their marketing and advertising strategies. <ref>Mooradian, Norman. 14 July 2009. The Importance of Privacy Revisited. Springer Science+Business Media. </ref>. There can be challenges to this, as the data that is collected is highly unstructured and not always accurate. |
== See Also == | == See Also == | ||
| Line 82: | Line 82: | ||
| − | [[Category:2019New]] | + | [[Category:2019New]][[Category:Information Ethics]] |
| + | [[Category:BlueStar2019]] | ||
Latest revision as of 07:14, 29 April 2019
An Infoglut (or information glut) -- otherwise know as “information overload”, “infobesity”, or “information anxiety” -- refers to excessive amounts of disorganized information that continuously accumulate. As Luciano Floridi states, "Infoglut means that at a certain point the whole system does not absorb anything". Because of the sheer amount of information, largely composed of distracting and meaningless clutter, organizing infospheres and gathering relevant information to form coherent conclusions is extremely difficult.[1][2] It is generally associated with being overwhelmed and hopelessly confused by the massses of information being presented -- which are more often than not devoid of any meaning, patterns, or content. Therefore, it is closely related to the concepts of Information Overload and Information Anxiety. Infoglut is classified by some, notably by Luciano Floridi as an Epistemological problem, which is a broader philosophical concept dealing with the theory of knowledge and perception. [3]
The growth of the technology field, the rapid increase in the ability to distribute and access information, and the growing shift in focus towards "Big Data" all continue to be determinants of today's information overload. Consequently, the effect of being rendered unable to absorb information due to the sheer mass of availability has grown into a large ethical issue that stems from technological and informational advances.
Contents
Origin and Evolution
The taxonomy of the term is very telling: Infoglut derived from the words “Information”, referring to facts and data, and “Glut”, referencing “Gluttony”. Gluttony suggests a dangerous abundance and excessiveness. Having appeared in several published works since its creation, the term was recently publicized in 2013 by Marc Andrejevic's book "Infoglut: How Too Much Information Is Changing the Way We Think And Know". In his book, Andrejevic discusses the concept of information overload and different strategies to tame infoglut in society.
The origins of the word date as far back as the early-mid 1990s, where it has been mentioned in several articles and books. Thomas John's book "Managing the Infoglut: Information Filtering Using Neural Networks" and Michael Marien's article "Infoglut and competing problems: Key barriers suggesting a new strategy for sustainability" [4] were both published in 1994 and indicate the widespread use and research surrounding the term. In addition to introducing the term, they also normalized it.
The Information Age (also known as The Computer Age, The Digital Age, The New Media Age), started in the 1970s and is still developing today. It follows trend from the Industrial Age that preceded it and has its title due to the rapid transition from the global economy's focus on industrialization to informational technology. In this era, the computing power, storage and memory capacity, as well as speed of computers, have risen exponentially, facilitating the abundance of information that now exists. Since the onset of the Information Age, the rise in information and computation has led to a rise in innovations and data analysis and has paved the way for further job creation and economic globalization. The full effect on the economy is not yet fully understood and is still largely debated.
Research and Publications
Books
Since the 1990s, there have been extensive discussions about Infoglut and its effects. Numerous books have been published about the dangers and merits of infoglut, and more importantly, how to deal with it in the current information landscape. "Managing the Infoglut : Information Filtering Using Neural Networks" by Thomas John exemplifies the kind of work that existed ahead of its time regarding both Infoglut and Neural Networks, terms that have come to light in the 21st century with the rise of Artificial Intelligence. The book discusses the dangers of too much information at once and the speed with which data can accumulate, and how to maintain the ability to efficiently retrieve information from within the data, through the use of an "electronic superhighway."[5] Marc Andrejevic's "Infoglut : How Too Much Information Is Changing the Way We Think And Know" is the latest book on Infoglut that caused a major wave, and is a cornerstone for the subject, expanding on the various strategies to deal with information overload and "big data," and how these strategies are connected and the new forms of control they enable.[6]
Articles
Articles on the subject include “Turning an Info-Glut into A Library” by Robert Pool[7], written in 1994, that discusses converting the overload of information caused by infoglut into a positive and usable source of data . In 1997, David Shenk wrote an article called "Data Smog : Surviving the Info Glut"[8] which similarly highlights the dangers and drawbacks of the Information Age and how it leads to Information Anxiety . In 1998, The Harvard Journal of Law and Technology published a paper called “Internet Infoglut and Invisible Ink: Spamdexing Search Engines with Meta Tags” [9] by Ira S Nathenson, which drew upon the works of Shenk, amongst others . There have been articles throughout the 2000s including "The Profession of IT - Infoglut" by Peter J. Denning in 2006 and "Infoglut" by Nathan Zeldes in 2009.
Parsing Through Infoglut
Due to the excessive amount of information that people are being exposed to each day, it is helpful to have a method of parsing through this immense amount of information in order to be able to easily digest it without getting confused or overwhelmed. Data mining helps to extract this information and transform it into a more digestible structure for easy user consumption using methods that stem from computer science and statistics. Data Miners help people combat information overload in a way that the common eye would not recognize [10].
Another way in which people can parse through excessive amounts of information is by purchasing technology that is tuned to combating infoglut. An example of this is the technology that protects users from exposure to unnecessary information, such as unwanted phone calls and email spam. Installing filters on search engines and media feeds is another way to prioritize favorable information and sift out the insignificant matter. However, even filters have trouble refining results due to the infoglut, so nowadays filters do a better job at "filtering forward" information and with-holding the rest temporarily, though this data will still come up once you get through what the algorithm decided was most prevalent. This does not eliminate useless data, it only delays it. Another drawback to filters is that they may limit choices that would have educated the individual on information from what they wouldn't normally view. This promotes the "echo chamber" effect of surrounding the reader with information that coincides with what they normally view and agree with, instead of informing them on multiple perspectives to create a well-rounded understanding and individual. This tendency of filters to put forth information that reinforces previously established opinions can often create extremists who are not exposed to the critical information outside of their comfort zone. Infoglut is a rapidly increasing phenomenon, and it is up to the users to be proactive and take steps to cut down on the amount of information to which they are exposed to create healthy, knowledgable information citizens. [11].
Ethical Issues
The rise in Information overload has also seen a host of related ethical issues surface along with it. Primarily, Infoglut hampers people's decision-making abilities by offering too many details and information, the surplus of which leads to high levels of indecisiveness and a long loop of searching. Much like the "Too many choices" paradox[12], which dictates that an over abundance of choices can make it much harder to actually make a decision, infoglut affects searching information in the same way. Like a sponge absorbing too much water, once too much information is gathered, its usefulness diminishes. This results in an inefficiency of sorts because people are spending more time sorting thorough information than they are actually processing it. This has led to a various attention deficit issues within people. There is also a rising conflict between information and privacy, as many people do not believe that it is possible to protect individual privacy to the extent that it was before. It has also raised environmental concerns, corporations have increased their usage of paper, given the high volume of information needed to be documented tangibly.
Epistemological Issues
Luciano Floridi has repeatedly considered Infoglut to be a larger epistemological problem (e.g. what knowledge is valid, who it belongs to, and the distinctions between belief and opinion). He pointed out specific ethical problems that arise with big data mostly centered around privacy. In a lecture delivered at Oxford University, Floridi asked the splitting question "Does respect for individual's privacy require respect for privacy of the group to which the individual belongs to?"[13]. He believes that there are a plethora of ethical questions and dilemmas that arise with growing data and that the matters of group privacy and individual privacy have several points of intersection that can be potential grey areas or problem points moving forward. Floridi also points out about infoglut that beyond a certain point, a system is not able to comprehend or absorb any more due to the sheer mass of information it is being fed. He says that at a point, while it might be possible to discern that the data is half right and half wrong, it might be impossible to state which half is which.
Information Entropy
Information entropy is the destruction, pollution, and depletion of information objects. The concept of Informational Entropy was coined by American Mathematician Claude Shannon. It is the measure of uncertainty within an event or topic. Generally, the lower the amount of information that exists within the scope of the event or matter, the higher the certainty. However, due to constantly growing rates of accumulating information, the level of information across subjects has increased vastly, leading to higher entropy and uncertainty. The uncertainty is in what information is valuable and urgent while it is diluted by the unreasonable amount of insignificant data circulating the infosphere. The infoglut makes it difficult for individuals to decipher what should be read and prioritized versus what should be ignored. If you have to sift through too much useless information to reach the important matter, it is discouraging and time-wasting, and the important information won't be absorbed.
There has also been an increase in individual entropy caused by the discrepancy between the speed at which digital information is being computed and then transferred and people's personal rate of processing information. Economist Herbert A. Simon has been quoted stating along similar lines that a “wealth of information creates a poverty of attention” and “an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients.” [14] Therefore, as the wealth of information grows with technology, people's attention to information diminishes.
Information Fatigue Syndrome
Information Fatigue Syndrome was coined in an article titled “Information Overload: Causes, Symptoms and Solutions,” for the Harvard Graduate School of Education’s Learning Innovations Laboratory (LILA), by Joseph Ruff. Information Fatigue Syndrome is a direct result of the decreased effectiveness in decision making process caused by the excessive increase of information pertaining to the possible outcomes of decision being made. In the article, the dearth of attention created by an abundance of information is treated as a clinical illness, and it suggests its symptoms while offering its cures and proactive measures against it. [15]
A list of symptoms include:[15]
- Poor concentration
- Multitasking resulting in diminished productivity
- Hurry Sickness
- Heightened irritability or rage
- Over simulation resulting in a mental trance like state
- Compulsion related to checking online media and messaging sources
- Stress and lowered immune responses[16]
Data As A Commodity
The increase in the sheer volume of information available to any given person has led to multiple large scale cases of privacy invasion. Within these infringements, personal data has become a commodity available for trade to augment greater consumer information. The more data pertaining to the common user that is gathered, the more accurately and successfully large corporations can target their intended consumers, the more successful they will be in turning a profit and growing their business. Facebook Cambridge Analytica Scandal of 2018 was a shocking event for millions of users. Their personal information was harvested from Facebook profiles without their consent and used for political purposes. The privacy of millions of people was compromised in favor of data collection. This led to concerns that this case was just scratching the surface of deeper and more questionable informational transactions. The event marked a critical shift in the perception of data, not as a resource but as a tradable commodity that could be used for profit. There arose a greater fear that people's individual privacy was being handed over to companies that treated it as tradable in exchange for monetary value.
Aggregation
Aggregation acts as a way to manage the constantly accumulating disorganized data. Aggregation brings together information that has been gathered from several sources into one single data structure. [17] Data aggregation can have many different purposes, including statistical analysis, eliminating duplicate or irrelevant information, or summarizing data for quick consumption. A classic example of data aggregation would be Google searching someone's name and finding a few personal details about that individual. There is a dispute about whether a more in-depth data aggregation could be construed as an invasion of privacy. For example, a more intrusive example of data aggregation would be a data broker report that can be bought online that would include even more personal facts about an individual than a Google search could yield. There is an increasing amount of commercial data that is aggregated by companies in order to inform their marketing and advertising strategies. [18]. There can be challenges to this, as the data that is collected is highly unstructured and not always accurate.
See Also
References
- ↑ “What Is Infoglut? Definition and Meaning.” BusinessDictionary.com, www.businessdictionary.com/definition/infoglut.html.
- ↑ Zeldes, Nathan. “Infoglut.” IEEE Spectrum, vol. 46, no. 10, 2009, pp. 30–55., doi:10.1109/mspec.2009.5267994.
- ↑ Floridi, Luciano. “‘Infoglut’ - Q&A.” YouTube, YouTube, 20 Dec. 2016, www.youtube.com/watch?v=2UHTPkeByLM.
- ↑ “Infoglut and Competing Problems: Key Barriers Suggesting a New Strategy for Sustainability.” Futures, Pergamon, 26 Apr. 2002, www.sciencedirect.com/science/article/pii/0016328794901139.
- ↑ John, Thomas. “Managing the Infoglut: Information Filtering Using Neural Networks.” SpringerLink, Springer, Boston, MA, 1 Jan. 1994, link.springer.com/chapter/10.1007/978-1-4615-2734-3_16.
- ↑ Andrejevic, Mark. “Infoglut | How Too Much Information Is Changing the Way We Think and Know.” Taylor & Francis, Taylor & Francis, 26 June 2013, www.taylorfrancis.com/books/9781135119522.
- ↑ Pool, R. “Turning an Info-Glut into a Library.” Science, 7 Oct. 1994, go.galegroup.com/ps/anonymous?id=GALE%7CA15827725&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=00368075&p=AONE&sw=w.
- ↑ Shenk, and David. “Data Smog: Surviving the Info Glut.” Technology Review, 30 Nov. 1996, eric.ed.gov/?id=EJ544699.
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- ↑ Andrejevic, M. (2013). Infoglut: How too much information is changing the way we think and know. Infoglut: How Too Much Information is Changing the Way we Think and Know. 1-202. 10.4324/9780203075319.
- ↑ Zeldes, Nathan. “How to Beat Information Overload.” IEEE Spectrum: Technology, Engineering, and Science News, IEEE Spectrum, 30 Sept. 2009, spectrum.ieee.org/computing/it/how-to-beat-information-overload.
- ↑ Tugend, Alina. “The Paralyzing Problem of Too Many Choices.” The New York Times, The New York Times, 26 Feb. 2010, www.nytimes.com/2010/02/27/your-money/27shortcuts.html.
- ↑ “Big Data, Small Patterns, and Huge Ethical Issues.” Oxford Internet Institute, www.oii.ox.ac.uk/videos/big-data-small-patterns-and-huge-ethical-issues/.
- ↑ Schweller, Randall L. “The Age of Entropy.” Foreign Affairs, Foreign Affairs Magazine, 17 June 2014, www.foreignaffairs.com/articles/united-states/2014-06-16/age-entropy.
- ↑ 15.0 15.1 Nguyen, Steve. “Information Overload-When Information Becomes Noise.” Workplace Psychology, 23 Nov. 2014, workplacepsychology.net/2011/05/18/information-overload-when-information-becomes-noise/.
- ↑ Chard, P. (2002). Information overload: Are we technology's masters...or servants? WorldAtWork Journal 11(3).
- ↑ Mooradian, Norman. 14 July 2009. The Importance of Privacy Revisited. Springer Science+Business Media.
- ↑ Mooradian, Norman. 14 July 2009. The Importance of Privacy Revisited. Springer Science+Business Media.
