Manipulating Opportunity

70 Pages Posted: 16 Oct 2019 Last revised: 24 Jul 2020

See all articles by Pauline Kim

Pauline Kim

Washington University in St. Louis - School of Law

Date Written: October 9, 2019


Concerns about online manipulation have centered on fears about undermining the autonomy of consumers and citizens. What has been overlooked is the risk that the same techniques of personalizing information online can also threaten equality. When predictive algorithms are used to allocate information about opportunities like employment, housing, and credit, they can reproduce past patterns of discrimination and exclusion in these markets. This Article explores these issues by focusing on the labor market, which is increasingly dominated by tech intermediaries. These platforms rely on predictive algorithms to distribute information about job openings, match job seekers with hiring firms, or recruit passive candidates. Because algorithms are built by analyzing data about past behavior, their predictions about who will make a good match for which jobs will likely reflect existing occupational segregation and inequality. When tech intermediaries cause discriminatory effects, they may be liable under Title VII, and Section 230 of the Communications Decency Act should not bar such actions. However, because of the practical challenges that litigants face in identifying and proving liability retrospectively, a more effective approach to preventing discriminatory effects should focus on regulatory oversight to ensure the fairness of algorithmic systems.

Keywords: discrimination, bias, algorithms, AI, automated decision-making, occupational segregation, equality, employment

Suggested Citation

Kim, Pauline, Manipulating Opportunity (October 9, 2019). Washington University in St. Louis Legal Studies Research Paper No. 19-10-12, 106 Va. L. Rev. 867 (2020), Available at SSRN:

Pauline Kim (Contact Author)

Washington University in St. Louis - School of Law ( email )

Campus Box 1120
St. Louis, MO 63130
United States
314-935-8570 (Phone)
314-935-5356 (Fax)

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