Mitigating Bias in Algorithmic Hiring: Evaluating Claims and Practices

24 Pages Posted: 25 Jun 2019 Last revised: 15 Sep 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 in hiring, especially as a means to address or mitigate bias. Yet, to date, little is known about how these methods are used in practice. How are algorithmic assessments built, validated, and examined for bias? In this work, we document and analyze the claims and practices of companies offering algorithms for employment assessment. 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 practices, focusing particularly on efforts to detect and mitigate bias. Our analysis considers both technical and legal perspectives. Technically, we consider the various choices vendors make regarding data collection and prediction targets, and explore the risks and trade-offs that these choices pose. We also discuss how algorithmic de-biasing techniques interface with, and create challenges for, antidiscrimination law.

Keywords: algorithmic bias, employment screening

Suggested Citation

Raghavan, Manish and Barocas, Solon and Kleinberg, Jon and Levy, Karen, Mitigating Bias in Algorithmic Hiring: 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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