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61 St. Louis U. L.J. 17 (2016-2017)
People Analytics and the Regulation of Information under the Fair Credit Reporting Act

handle is hein.journals/stlulj61 and id is 29 raw text is: 










PEOPLE ANALYTICS AND THE REGULATION OF INFORMATION
             UNDER THE FAIR CREDIT REPORTING ACT



                PAULINE T. KIM* AND ERIKA HANSON**


                                INTRODUCTION

    People  analytics-the  use  of big data  and computer   algorithms to make
personnel   decisions-has been drawing increasing public and scholarly
scrutiny.' Software  is now  available for screening  applicants to identify the
most  promising  candidates, or searching  online profiles to find top prospects
for recruitment.2  Algorithms  claim  to predict  which  workers  will be  most
productive  or which employees  are most  likely to leave their jobs.3 These tools


* Daniel Noyes Kirby Professor of Law, Washington University School of Law, St. Louis,
Missouri.
** J.D., Washington University School of Law, St. Louis, Missouri.
     1. See, e.g., EXECUTIVE OFFICE OF THE PRESIDENT, BIG DATA: SEIZING OPPORTUNITIES,
PRESERVING  VALUES, 51-53 (May 2014), https://www.whitehouse.gov/sites/default/files/docs/
big-data privacy-report may_1_2014.pdf [http://perma.cc/HF2G-F2A2]; Danielle Keats Citron
&  Frank Pasquale, The Scored Society: Due Process for Automated Predictions, 89 WASH. L.
REV.  1 (2014); Kate Crawford & Jason Schultz, Big Data and Due Process: Toward a
Framework  to Redress Predictive Privacy Harms, 55 B.C. L. REV. 93 (2014); FEDERAL TRADE
COMMiSSION, BIG DATA: A TOOL FOR INCLUSION OR EXCLUSION? UNDERSTANDING THE ISSUES
(Jan. 2016), https://www.ftc.gov/system/files/documents/reports/big-data-tool-inclusion-or-exclu
sion-understanding-issues/1 60106big-data-rpt.pdf  [http://perma.cc/H636-LGLSI;  FRANK
PASQUALE, THE BLACK  Box SOCIETY (2015); Danah Boyd & Kate Crawford, Critical Questions
for Big Data, 15 INFO. COMM. & Soc'Y 662, 666-68 (2012); Solon Barocas & Andrew D. Selbst,
Big Data's Disparate Impact, 104 CALIF. L. REv. 671 (2016); Cynthia Dwork & Deirdre K.
Mulligan, It's Not Privacy, and It's Not Fair, 66 STAN. L. REV. ONLINE 35 (2013); Pauline T.
Kim, Data-Driven Discrimination at Work, 58 WM. & MARY L. REv. (forthcoming 2017); Alex
Rosenblat, et al., Data & Civil Rights: Employment Primer, DATA & CIVIL RIGHTS CONFERENCE
(Oct. 30, 2014), http://papers.ssrn.com/sol3/papers.cfn?abstract-id=2541512 [http://perma.cc/5H
C2-PP8U]; Matthew T. Bodie, et al., The Law and Policy of People Analytics, 88 U. COLO. L.
REV. (forthcoming 2017), http://papers.ssm.com/sol3/papers.cfm?abstract-id=2769980 [http://per
ma.cc/W6DX-GDV3].
     2. Josh Bersin, Big Data in Human Resources: Talent Analytics (People Analytics) Comes
 of Age, FORBES (Feb. 17, 2013), http://www.forbes.com/sites/joshbersin/2013/02/17/bigdata-in-
 human-resources-talent-analytics-comes-of-age [http://perma.cc/FD3U-7UTJ].
     3. George Anders, Who Should You Hire? LinkedIn Says: Try Our Algorithm, FORBES
 (Apr. 10, 2013), http://www.forbes.com/sites/georgeanders/2013/04/10/who-should-you-hire-
 linkedin-says-try-our-algorithm/#18ffecO42506 [http://perma.cc/UWD8-5WNL]; Claire Cain
 Miller, Can an Algorithm Hire Better Than a Human?,  N.Y. TIMES (June 25, 2015),


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