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44 Cardozo L. Rev. 145 (2022-2023)
Automating Discrimination: AI Hiring Practices and Gender Inequality

handle is hein.journals/cdozo44 and id is 155 raw text is: 











      AUTOMATING DISCRIMINATION: Al HIRING
           PRACTICES AND GENDER INEQUALITY


                     Lori Andrews   & Hannah   Buchert




     I think people underestimate the impact algorithms and recommendation
engines have on jobs, Derek Kan, Vice President of Product Management at Monster
says.l The way you present yourself is most likely read by thousands of machines and
servers first, before it even gets to a human eye.2


                            TABLE OF  CONTENTS


INTRODUCTION   ................................................................................................................147
I.  ARTIFICIAL INTELLIGENCE AND MACHINE  LEARNING  IN HIRING DECISIONS ....152
II. THE LAW  OF EMPLOYMENT   DISCRIMINATION  UNDER  TITLE VII .......................156
      A . D isparate Treatm ent .......................................................................... 158
      B . D isparate Im pact ................................................................................ 162
III. APPLICATION OF TITLE VII TO AI TECHNOLOGIES IN HIRING ............................168
      A.  Resume  Scanning................................................................................ 168
            1.  The Technological Underpinnings of Resume-Scanning, Its
                Current Uses, and Its Gendered Impacts................................. 168
            2.  The Potential Role of Existing Law in Response to Gender
                Discrimination in Resume Scanning ....................................... 171



   t Lori Andrews, J.D., Professor of Law, Chicago-Kent College of Law; Director, Institute for
Science, Law, and Technology, Illinois Institute of Technology and Hannah Bucher, J.D., Chicago-
Kent College of Law. The authors wish to thank Adrienne Finucane, Bora Ndregjoni, Kelby Roth,
and Andrew White for their research, editorial insights, creativity, and inspiration in connection
with this Article. They are also grateful for the insights of Anita Bernstein, Richard Gonzalez, Ruth
Kaufman, Ellen Mitchell, Clements Ripley, and Jim Stark.
    1 Sheridan Wall & Hilke Schellmann, LinkedIn's Job-Matching AI Was Biased. The Company's
Solution? More AL., MIT TECH. REv. (June 25, 2021), https://www.technologyreview.com/2021/06/
23/1026825/linkedin-ai-bias-ziprecruiter-monster-artificial-intelligence [https://perma.cc/45R2-
LMJJ].
   2 Id.


145

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