Inherent Trade-Offs in Algorithmic Fairness

Fri, Mar 29, 2019, 12:00 pm to 1:00 pm
Center for Statistics and Machine Learning
CSML & Program for Quantitative and Analytical Political Science

Recent discussion in the public sphere about classification by algorithms has involved tension between competing notions of what it means for such a classification to be fair to different groups. We consider several of the key fairness conditions that lie at the heart of these debates, and discuss recent research establishing inherent trade-offs between these conditions. We also consider a variety of methods for promoting fairness and related notions for classification and ranking problems that involve sets rather than just individuals. This talk is based on joint work with Sendhil Mullainathan and Manish Raghavan. 

Jon Kleinberg is the Tisch University Professor in the Departments of Computer Science and Information Science at Cornell University. His research focuses on the interaction of algorithms and networks, and the roles they play in large-scale social and information systems. He is a member of the National Academy of Sciences and the National Academy of Engineering, and the recipient of research fellowships from the MacArthur, Packard, Simons, and Sloan Foundations, as well as awards including the Harvey Prize, the Lanchester Prize, the Nevanlinna Prize, and the ACM Prize in Computing.