Video Summary

The paper studies the problem of training neural networks on data that is biased. The authors propose a method called "fair adversarial training" that can reduce bias in the learned model. They evaluate their method on a variety of datasets and tasks, and show that it can significantly reduce bias without sacrificing accuracy.