Sessions Information

  • January 3, 2020
    1:30 pm - 3:15 pm
    Session Type: Section Programs
    Session Capacity: N/A


    This program will explore the manner in which machine-learning technologies contribute to the formation of algorithmic knowledge in a variety of legal fields, including criminal justice, evidence, and litigation. The data assumptions underlying such predictive analytics are often problematic–whether for encoding human bias, or for being shielded from review by intellectual property protections. The failure of artificial intelligence technologies to account for informational asymmetries thus poses unique threats to our democratic institutions and justice system. However, artificial intelligence technologies have also shown great promise to promote equality, efficiency, and access to justice in law. This program will thus examine possible responses by lawyers and legal institutions to the challenges posed by machine-learning.
     
    Business meeting at program conclusion. 

Date & Time
Speakers
David F. Engstrom, Stanford Law School

Christine Chambers Goodman, Pepperdine University, Rick J. Caruso School of Law

Nicholson Price, The University of Michigan Law School

Arti K. Rai, Duke University School of Law

Andrea Roth, University of California, Berkeley School of Law

Session Fees
  • [4410] Evidence and Biolaw Joint Program, Co-Sponsored by Law & the Social Sciences and Litigation - Algorithmic Knowledge: Law, Science and Democracy: $0.00
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