FALE: Fairness-Aware ALE Plots for Auditing Bias in Subgroups

arXiv:2404.18685v1 Announce Type: new
Abstract: Fairness is steadily becoming a crucial requirement of Machine Learning (ML) systems. A particularly important notion is subgroup fairness, i.e., fairness in subgroups of individuals that are defined by more than one attributes. Identifying bias in subgroups can become both computationally challenging, as well as problematic with respect to comprehensibility and intuitiveness of the finding to end users. In this work we focus on the latter aspects; we propose an explainability method tailored to identifying …

abstract ale arxiv become bias cs.lg fairness machine machine learning notion plots subgroups systems type