Title: On conditional parity as a notion of non-discrimination in machine learning,
Abstract: We identify conditional parity as a general notion of non-discrimination in
machine learning. In fact, several recently proposed notions of
non-discrimination, including a few counterfactual notions, are instances of
conditional parity. We show that conditional parity is amenable to statistical
analysis by studying randomization as a general mechanism for achieving
conditional parity and a kernel-based test of conditional parity.