People Analytics and the Regulation of Information Under the Fair Credit Reporting Act

14 Pages Posted: 15 Jul 2016

See all articles by Pauline Kim

Pauline Kim

Washington University in St. Louis - School of Law

Erika Hanson

Washington University in Saint Louis - School of Law

Date Written: July 14, 2016

Abstract

People analytics — the use of big data and computer algorithms to make personnel decisions — has been drawing increasing public and scholarly scrutiny. Concerns have been raised that the data collection intrudes on individual privacy, and that algorithms can produce unfair or discriminatory results. This symposium contribution considers whether the Fair Credit Reporting Act’s regulation of consumer information used for employment purposes can respond these concerns. The FCRA establishes certain procedural requirements, and these can sometimes help individual workers challenge inaccurate information about them. However, the statute does little to curb intrusive data collection practices or to address the risks of unfair or discriminatory algorithms, revealing the limitations of a purely procedural approach to regulating the use of big data in employment.

Keywords: employment, privacy, discrimination, data analytics, people analytics, algorithms, big data, Fair Credit Reporting Act

Suggested Citation

Kim, Pauline and Hanson, Erika, People Analytics and the Regulation of Information Under the Fair Credit Reporting Act (July 14, 2016). St. Louis University Law Journal, Forthcoming; Washington University in St. Louis Legal Studies Research Paper No. 16-07-15. Available at SSRN: https://ssrn.com/abstract=2809910

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)

Erika Hanson

Washington University in Saint Louis - School of Law ( email )

Campus Box 1120
St. Louis, MO 63130
United States

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