Sessions Information

  • January 4, 2019
    8:30 am - 10:15 am
    Session Type: Section Programs
    Session Capacity: N/A


    Employers across our economy are increasingly using new, technologically sophisticated tools to make decisions about which employees to hire, promote, and fire, as well as decisions about performance evaluation and pay. Some of these tools draw on unusual data sources; others use new “big data” methods to mine data for relevant correlations and inferences. How are legal actors—employers, employees, judges—supposed to decide whether the actions employers take with the help of these new tools constitute discrimination? Employment discrimination law is only beginning to come to grips with this question, which raises fascinating questions of its own about how best to apply theories such as disparate treatment and disparate impact to these novel decision-making methods. This panel will bring together many of the leading scholars in this rapidly-emerging field from both inside and outside the legal academy to evaluate these questions.

    Business meeting at program conclusion.

Date & Time
Speakers
Ifeoma Ajunwa, Cornell Law School

Stephanie Bornstein, University of Florida Fredric G. Levin College of Law

Joseph R. Fishkin, The University of Texas School of Law

Pauline T. Kim, Washington University in St. Louis School of Law

Mr. Andrew Selbst, Data & Society Research Institute

Charles A. Sullivan, Seton Hall University School of Law

Ms. Kelly Trindel, Ph.D., Pymetrics

Session Fees
  • [4150] Employment Discrimination Law, Co-Sponsored by Labor Relations and Employment Law and Internet Computer Law - Automatic Discrimination: Algorithms, Big Data, and the Law of Employment Decisions: $0.00
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