Track Two

An Equality Opportunity: Combating Disability Discrimination in AI

Abstract

As the FAccT community continues its work on bias and discrimination in AI-based systems, we hope to add another dimension to these efforts: discriminatory impacts for people with disabilities. Disability raises several unique challenges for identifying, assessing, and mitigating bias, in addition to presenting significant intersectional challenges. In this interactive workshop session we will outline the particular challenges presented by auditing for disability discrimination. We will invite attendees to consider research questions such as: How do you test for and mitigate bias in the absence of data about a protected characteristic? Are there technical solutions for the classification challenges raised by the unique complexities of disability data, and for data reflecting the experience of people who are multiply marginalized? We will use structured breakout sessions to discuss these questions and consider directions for developing solutions for these challenges.