Understanding Fairness Surrogate Functions in Algorithmic Fairness

arXiv:2310.11211v4 Announce Type: replace
Abstract: It has been observed that machine learning algorithms exhibit biased predictions against certain population groups. To mitigate such bias while achieving comparable accuracy, a promising approach is to introduce surrogate functions of the concerned fairness definition and solve a constrained optimization problem. However, it is intriguing in previous work that such fairness surrogate functions may yield unfair results and high instability. In this work, in order to deeply understand them, taking a widely used fairness …

abstract accuracy algorithmic fairness algorithms arxiv bias cs.ai cs.lg definition fairness functions however machine machine learning machine learning algorithms optimization population predictions solve type understanding