Fair ML and Causal ML


These slides are a contribution to a class on future developments of artificial intelligence and machine learning. The first set of slides introduces the problem of fair decision-making in machine learning systems, and illustrates some sample solutions underlining ideas and flaws. The second set of slides discusses the problem of assessing causal relations in data, and points to solutions in the direction of causal graphical models.

Slides here