Patrick LOISEAU

Abstract

Many machine learning algorithms are used to make decisions that affect the lives of humans (e.g., for hiring or criminal risk assessment). Yet in the past they have often been observed to discriminate against certain demographic groups. In this tutorial, we will introduce the problem of fairness in machine learning, with some examples from different learning tasks. We will then study the different methods to train fair learning algorithms, for the case of classification. We will do a hands-on example for the famous compas dataset.