In research studying the fairness of machine learning algorithms and models, fairness often means that a metric is the same when computed for two different groups of people. For example, one might define fairness to mean that the false positive rate of a ...

Increasingly, software is making autonomous decisions in case of criminal sentencing, approving credit cards, hiring employees, and so on. Some of these decisions show bias and adversely affect certain social groups (e.g. those defined by sex, race, age,...

Machine learning software is increasingly being used to make decisions that affect people's lives. But sometimes, the core part of this software (the learned model), behaves in a biased manner that gives undue advantages to a specific group of people (...