Learning Fair Representations

2 code implementations • International Conference on Machine Learning 2013 • Rich Zemel, Yu Wu, Kevin Swersky, Toni Pitassi, Cynthia Dwork

We propose a learning algorithm for fair classification that achieves both group fairness (the proportion of members in a protected group receiving positive classification is identical to the proportion in the population as a whole), and individual fairness (similar individuals should be treated similarly).

Classification Fairness +1