PIMS - IAM Distinguished Colloquium: Avrim Blum

There is growing concern about fairness in algorithmic decision making: Is it treating different groups fairly? How can we make it fairer? And what do we even mean by fair? In this talk I will discuss some of our work on this topic, focusing on the setting of online decision making. For instance, a classic result states that given a collection of predictors, one can adaptively combine them to perform nearly as well as the best in hindsight (achieve “no regret”) without any stochastic assumptions.