The Measure and Mismeasure of Fairness: A Critical Review of Fair Machine Learning

od · 14. prosinec 2019 · 216 zhlédnutí ·

NIPS 2019

The nascent field of fair machine learning aims to ensure that decisions guided by algorithms are equitable. Over the last few years, several formal definitions of fairness have gained prominence. But, in this talk, I'll argue that nearly all of these popular mathematical formalizations suffer from significant statistical limitations. In particular, when used as design objectives, these definitions, perversely, can harm the very groups they were intended to protect.