*POSTPONED* Artificial Intelligence, Big Data, and Proxy Discrimination in Insurance and Beyond
COVID-19 Update
Your health and wellbeing, and that of the community, are of the utmost importance to the University of Minnesota. The University is following the recommendation of the State of Minnesota, until further notice. Effective immediately, the Law School will be postponing this event to Spring 2021. An email will be sent to all registered attendees.
Big Data and Artificial Intelligence are revolutionizing the ways in which firms, governments, and employers classify individuals. One particularly important, but oft-misunderstood, danger created by these technologies is the risk of “proxy discrimination.” Proxy discrimination is a pernicious sub-type of disparate impact that arises when the usefulness to a discriminator of a facially-neutral practice derives, at least in part, from the very fact that the practice produces a disparate impact. Historically, this occurred when a firm intentionally used a proxy for a protected characteristic, as in the case of “redlining.” But Big Data and Artificial Intelligence create a fundamentally new risk of unintentional proxy discrimination.
This lecture will explore this risk in detail, with a focus on the insurance setting, where it is particularly prominent.
A brief reception will follow Professor Schwarcz's lecture until 6 p.m. in Auerbach Commons. Complimentary refreshments will be provided.
Registration is required.