Krishna Gummadi is a tenured faculy member and head of the Networked Systems research group at the Max Planck Institute for Software Systems (MPI-SWS) in Germany. He received his Ph.D. degree in Computer Science and Engineering from the University of Washington, Seattle.
Algorithmic (data-driven) decision making is increasingly being used to assist or replace human decision making in a variety of domains ranging from banking (rating user credit) and recruiting (ranking applicants) to judiciary (profiling criminals) and journalism (recommending news-stories). Against this background, in this talk, I will pose and attempt to answer the following high-level questions:
(a) Can algorithmic decision making be discriminatory?(b) Can algorithmic discrimination be controlled? i.e., can algorithmic decision making be made more fair?(c) Can algorithmic decisions be used to detect and avoid implicit biases in human decisions?