Inherent Trade-Offs in Algorithmic Fairness

  • Jon Kleinberg | Cornell University

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 selection problems that involve sets rather than just individuals. This talk is based on joint work with Sendhil Mullainathan, Manish Raghavan, and Maithra Raghu.

发言人详细信息

Jon Kleinberg is the Tisch University Professor in the Departments of Computer Science and Information Science at Cornell University. His research focuses on issues at the interface of algorithms, networks, and information, with an emphasis on the social and information networks that underpin the Web and other on-line media. 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 Nevanlinna Prize, the Newell Award, and the ACM Prize in Computing.

系列： MSR AI Distinguished Lectures and Fireside Chats