Mitigating Bias in Algorithmic Employment Screening: Evaluating Claims and Practices

22 Pages Posted: 25 Jun 2019

See all articles by Manish Raghavan

Manish Raghavan

Cornell University - Department of Computer Science

Solon Barocas

Cornell University

Jon Kleinberg

Cornell University - Department of Computer Science

Karen Levy

Cornell University

Date Written: June 21, 2019

Abstract

There has been rapidly growing interest in the use of algorithms for employment assessment, especially as a means to address or mitigate bias in hiring. Yet, to date, little is known about how these methods are being used in practice. How are algorithmic assessments built, validated, and examined for bias? In this work, we document and assess the claims and practices of companies offering algorithms for employment assessment, using a methodology that can be applied to evaluate similar applications and issues of bias in other domains. In particular, we identify vendors of algorithmic pre-employment assessments (i.e., algorithms to screen candidates), document what they have disclosed about their development and validation procedures, and evaluate their techniques for detecting and mitigating bias. We find that companies' formulation of "bias" varies, as do their approaches to dealing with it. We also discuss the various choices vendors make regarding data collection and prediction targets, in light of the risks and trade-offs that these choices pose. We consider the implications of these choices and we raise a number of technical and legal considerations.

Keywords: algorithmic bias, employment screening

Suggested Citation

Raghavan, Manish and Barocas, Solon and Kleinberg, Jon and Levy, Karen, Mitigating Bias in Algorithmic Employment Screening: Evaluating Claims and Practices (June 21, 2019). Available at SSRN: https://ssrn.com/abstract=3408010 or http://dx.doi.org/10.2139/ssrn.3408010

Manish Raghavan (Contact Author)

Cornell University - Department of Computer Science ( email )

402 Bill & Melinda Gates Hall
Ithaca, NY 14853
United States

Solon Barocas

Cornell University ( email )

Ithaca, NY 14853
United States

Jon Kleinberg

Cornell University - Department of Computer Science ( email )

4130 Upson Hall
Ithaca, NY 14853-7501
United States

Karen Levy

Cornell University ( email )

Ithaca, NY 14853
United States

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