Understanding the Limitations of Fairness Surrogate Functions and Proposing Improved Approaches for Algorithmic Fairness

Fairness surrogate functions used in algorithmic fairness may exhibit a significant gap between the fairness definition and the surrogate, leading to unfair outcomes. Additionally, the use of unbounded surrogate functions can result in high instability. This paper proposes solutions, including a general sigmoid surrogate and a balanced surrogate approach, to address these issues and provide fairness and stability guarantees.