UVic Mathematics of Ethical Decision Making Series: Sampath Kannan

Fairness in machine learning classification has been a topic of great interest given the increasing use of such classifiers in critical settings. There are many possible definitions of fairness and many potential sources of unfairness. Given this complex landscape, most research has focused on studying single classifiers in isolation.

In reality an individual is subjected to a network of classifiers: for example, one is classified at each stage of life (school, college, employment to name a few), and one may also be classified in parallel by many classifiers (such as when seeking college admissions). In addition, individuals may modify their behavior based on their knowledge of the classifier, leading to equilibrium phenomena. Another feedback effect is that the result of the classifier may affect the features of an individual (or of the next generation) for future classifications.

In this talk we present work that takes the first steps in exploring questions of fairness in networks of classifiers and in systems with feedback. Given the inherent complexity of the analysis, our models are very stylized, but it is our belief that some of the qualitative conclusions apply to real-world situations.

Speaker Biography: 

Sampath Kannan is the Henry Salvatori Professor in the Department of Computer and Information Science at the University of Pennsylvania. His research interests are in the areas of Algorithmic Fairness, Combinatorial Algorithms, 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 served as Associate Director for Theoretical Computer Science at the Simons Foundation from 2010 to 2013. He was the Chair of the Computer and Information Science Department at Penn between 2013 and 2018. He is a Fellow of the ACM, and the recipient of the ACM SIGACT Distinguished Service Award. He is also a Fellow of the American Association for the Advancement of Science.