Penalizing Unfairness in Binary Classification

30 Jun 2017Yahav BechavodKatrina Ligett

We present a new approach for mitigating unfairness in learned classifiers. In particular, we focus on binary classification tasks over individuals from two populations, where, as our criterion for fairness, we wish to achieve similar false positive rates in both populations, and similar false negative rates in both populations... (read more)

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