Discrimination in Human vs. Algorithmic Decision Making

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?