Difference between revisions of "Automated Resume Screening"
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| − | '''Automated Resume Screening''' refers to the use of [[Wikipedia: Machine Learning|machine learning]] [[Wikipedia: Algorithms|algorithms]] and [[Wikipedia: artificial intelligence|artificial intelligence (AI)]] to parse and extract information from applicant [[Wikipedia: Resume|resumes]]. Different algorithms are used to identify relevant skills and experience for the job from the applicant's resume using keywords in the job description and requirements. | + | '''Automated Resume Screening''' refers to the use of [[Wikipedia: Machine Learning|machine learning]] [[Wikipedia: Algorithms|algorithms]] and [[Wikipedia: artificial intelligence|artificial intelligence (AI)]] to parse and extract information from applicant [[Wikipedia: Resume|resumes]]. Different algorithms are used to identify relevant skills and experience for the job from the applicant's resume using keywords in the job description and requirements. Variations of algorithms can be used according to the company's hiring criteria. Certain companies may use algorithms that just do word matching between the job post and the resume, while some may place weights on certain past experiences and backgrounds. The use of automated resume screening then may stimulate bias against underprivileged applicants with lesser experience and relevant job backgrounds resulting in [[Wikipedia: gender bias|gender bias]], [[Wikipedia: racial bias|racial bias]], and circumstantial bias. |
==<big> Benefits for Companies </big>== | ==<big> Benefits for Companies </big>== | ||
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===Organized=== | ===Organized=== | ||
Most resume screening programs come as part of [[Wikipedia: applicant tracking system|applicant tracking system]]. These programs can store personal and contact information of different applicants categorized by their key skills and talents. If some candidate does not seem a good fit for some role at the current time, these programs keep their information in the system and can use it in future in case a relevant role opens that is a good fit for the candidate. This increases the pool of applicants and helps companies find a better fit for their roles. | Most resume screening programs come as part of [[Wikipedia: applicant tracking system|applicant tracking system]]. These programs can store personal and contact information of different applicants categorized by their key skills and talents. If some candidate does not seem a good fit for some role at the current time, these programs keep their information in the system and can use it in future in case a relevant role opens that is a good fit for the candidate. This increases the pool of applicants and helps companies find a better fit for their roles. | ||
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| + | ===Outreach=== | ||
| + | Outreach is a time-consuming part of the recruiting process. Companies aim to attract as many applicants as possible in order to find the most appropriate and beneficial fit for their role. | ||
==<big> Ethical Implications </big>== | ==<big> Ethical Implications </big>== | ||
Revision as of 15:51, 10 February 2022
Automated Resume Screening refers to the use of machine learning algorithms and artificial intelligence (AI) to parse and extract information from applicant resumes. Different algorithms are used to identify relevant skills and experience for the job from the applicant's resume using keywords in the job description and requirements. Variations of algorithms can be used according to the company's hiring criteria. Certain companies may use algorithms that just do word matching between the job post and the resume, while some may place weights on certain past experiences and backgrounds. The use of automated resume screening then may stimulate bias against underprivileged applicants with lesser experience and relevant job backgrounds resulting in gender bias, racial bias, and circumstantial bias.
Contents
Benefits for Companies
Time Efficient
Automating resume screening using AI algorithms saves companies time-to-hire. On average, a recruiter spends 6 seconds to manually scan a resume [1]. AI algorithms can process exponentially more applicants than humans in the same time and can also extract more meaningful information than a human can in the same time. This reduces the amount of applicants recruiters have to manually evaluate before hiring someone for a specific position reducing the time-to-hire.
Organized
Most resume screening programs come as part of applicant tracking system. These programs can store personal and contact information of different applicants categorized by their key skills and talents. If some candidate does not seem a good fit for some role at the current time, these programs keep their information in the system and can use it in future in case a relevant role opens that is a good fit for the candidate. This increases the pool of applicants and helps companies find a better fit for their roles.
Outreach
Outreach is a time-consuming part of the recruiting process. Companies aim to attract as many applicants as possible in order to find the most appropriate and beneficial fit for their role.
Ethical Implications
Gender Bias
Ethnic Bias
Circumstantial Bias
Reducing Bias
References
- ↑ Bart Turczynski. 2021 HR Statistics: Job Search, Hiring, Recruiting & Interviews. Zety. https://zety.com/blog/hr-statistics#resume-statistics
