« The process of mathematically defining “fair” decision-making metrics also forces us to pin down tradeoffs between fairness and accuracy that must be faced and have sometimes been swept under the carpet by policy-makers. It makes us rethink what it really means to treat all groups equally—in some cases equal treatment may only be possible by learning different group-specific criteria.There is an entirely new field emerging at the intersection of computer science, law, and ethics. It will not only lead to fairer algorithms, but also to algorithms which track accountability, and make clear which factors contributed to a decision. There’s much reason to be hopeful! » – Jennifer T. Chayes.
Source : How Machine Learning Advances Will Improve the Fairness of Algorithms | HuffPost