IC Colloquium: Fairness in Algorithmic Decision Making


Event details

Date 01.11.2021 16:1517:15  
Category Conferences - Seminars
Event Language English
By: Sampath Kannan - University of Pennsylvania
Video of his talk

In this talk we take a theoretical computer science perspective on fairness of decisions made by algorithms, typically machine learning algorithms. We describe various ways of quantitatively formulating fairness, and systematic ways in which algorithms can fail to be fair. We survey models and techniques for achieving fairness in some scenarios and the challenges to doing so in others.

Sampath Kannan is the Henry Salvatori Professor in the Department of Computer and Information Science at the University of Pennsylvania. He obtained his Ph.D. from the University of California, Berkeley in 1989.

His research interests are in the areas of Algorithmic Fairness, Program Reliability, Streaming Computation, and Computational Biology. Sampath Kannan served as Associate Dean for Academics in the School of Engineering and Applied Science at Penn between 2006 and 2008 and as Division Director for the Computing and Communication Foundations Division at the National Science Foundation from 2008 to 2010. He was the Chair of the Computer and Information Science Department at Penn from 2014 to 2018. He is a Fellow of the ACM and the AAAS, and a recepient of the SIGACT Distinguished Service Award.

More information

Practical information

  • General public
  • Free


  • Host: Emmanuel Abbé