By: Jonathan H. Walter
Employment is a priority for the class of 2020 right now, and today more applicants than ever are look for jobs online. In 2015, the Pew Research Center found 79 percent of applicants used online resources in their most recent job search, and over one third said those online resources were the most important tool available to them. This same report found more than half of U.S. adults looked for job information online and 45 percent applied online. However, when segmenting for Americans under the age of 49, 75 percent of applicants looked for jobs online and 68 percent applied online. This shows that the trend for younger Americans, and as such the future of job applications will be in the digital space.
While there is more known about issues of discrimination in employment advertising, little in known about internal recruiting tools or internal promotion tools utilized by companies. These internal recruiting algorithms make it more difficult to enforce current anti-discrimination laws within companies. Recently, Amazon shut down its internal recruitment AI after discovering it was discriminating against women. These algorithmic systems, if not audited or corrected for bias, are susceptible to producing self-perpetuating and arbitrary bias, and, if left unfettered, these algorithms could filter out many qualified individuals belonging to these marginalized groups.
Recent studies have found that over half of human resource managers said AI would be a regular part of their work within the next five years. The use of algorithms in the tracking, ranking and matching of candidates to positions will not be going anywhere any time soon. As the hiring process becomes more digitized, a need for oversight of these platforms has become abundantly clear.
*University of Richmond Journal of Law and Technology is not endorsed by, directly affiliated with, maintained, authorized, or sponsored by ZipRecruiter.com. All product and company names are the registered trademarks of their original owners.
 Aaron Smith, Searching for Work in the Digital Era, Pew Research Center (2015) http://www.pewinternet.org/2015/11/19/searching-for-work-in-the-digital-era/.
 Examples of job websites that use these kinds of tools are ZipRecruiter, LinkedIn, Indeed, and Monster.com.
 Figuring out how exactly these algorithms work can be incredibly difficult as algorithms are protected by trade secret. See Taylor Moore, Trade Secrets & Algorithms as Barriers to Social Justice, Center for Democracy and Technology (2017) https://cdt.org/files/2017/08/2017-07-31-Trade-Secret-Algorithms-as-Barriers-to-Social-Justice.pdf.
 23 Surprising Stats on Candidate Expereince – Infographic, Career Arc (2016) http://www.careerarc.com/blog/2016/06/candidate-experience-study-infographic/.
 See Department of Justice Statement of Interest, National Fair Housing Alliance et al., v. Facebook, Inc., Case 1:18-cv-02689-JGK (S.D.N.Y. 2018); Department of Justice Statement of Interest, Onuoha, et al., v. Facebook, 5:16-cv-06440 (N.D.C.A. 2018); Bradley et al., v. T-Mobile US, INC. et al., 5:17-cv-07232 (N.D.Cal. 2017); Jeffrey Dastin, Amazon Scraps AI Recruiting Tool That Showed Bias Against Women, Reuters (Oct. 9, 2018) https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G/; Julia Angwin and Terry Parris Jr., Facebook Lets Advertisers Exclude Users By Race, ProPublica (Oct. 28, 2016) https://www.propublica.org/article/facebook-lets-advertisers-exclude-users-by-race; Julia Angwin et al., Facebook (Still) Letting Housing Advertisers Exclude Users by Race, ProPublica (Nov. 21, 2017) https://www.propublica.org/article/facebook-advertising-discrimination-housing-race-sex-national-origin.
 See ACLU et al. Charge of Discrimination Against Facebook, https://www.aclu.org/sites/default/files/field_document/facebook_bill.pdf (citation omitted).
 AJ Wilcox, LinkedIn’s new Matched Audiences feature just blew Facebook Custom Audiences out of the water for B2B, Marketing Land (Apr. 24, 2017) https://marketingland.com/linkedins-new-matched-audiences-feature-just-blew-facebook-custom-audiences-water-b2b-212213; Matched Audiences, LinkedIn https://business.linkedin.com/marketing-solutions/ad-targeting/matched-audiences; About similar audiences on the Display Network, Google Ads Help https://support.google.com/google-ads/answer/2676774?hl=en.
 Jeff Kauflin, 12 Websites To Jump-Start Your Career In 2018, Forbes (Oct. 19, 2017) https://www.forbes.com/sites/jeffkauflin/2017/10/19/12-websites-to-jump-start-your-career-in-2018/#46b95fa919d8.
 Jeffrey Dastin, Amazon Scraps AI Recruiting Tool That Showed Bias Against Women, Reuters (Oct. 9, 2018) https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G/.
 Supra note 29 at 89; see also Solon Barocas and Anderw Selbst, Losing Out on Employment Because of Big Data Mining, New York Times (August 6, 2014) https://www.nytimes.com/roomfordebate/2014/08/06/is-big-data-spreading-inequality/losing-out-on-employment-because-of-big-data-mining.
 Supra note 42.