Abstract: Using data efficiently is no longer our only burden. As automated decisions in socio-technical systems affect more lives than ever, it is imperative that we also use data responsibly. Being non-discriminatory and fair is one such responsibility. To date, explorations of fairness in intelligent decision systems have mostly ignored long-term influence on the underlying population. In this talk I give a first comprehensive perspective of this problem. Among the various insights I provide is quantifying both sides of the mismatch hypothesis: when can we hope that affirmative action is indeed beneficial to society?
Bio: Mesrob I. Ohannessian is a Research Assistant Professor at the Toyota Technological Institute at Chicago. He was previously a postdoc at UCSD, MSR-Inria, and Université Paris-Sud. He received his PhD in EECS from MIT. His research interests are in machine learning, statistics, information theory, and their applications, particularly to problems marked by data scarcity and to decisions that affect society.
