In this work, we present Fairness Aware Counterfactuals for Subgroups (FACTS), a framework for auditing subgroup fairness through counterfactual explanations. We start with revisiting (and generalizing) existing notions and introducing new, more refined notions of subgroup fairness. We aim to (a) formulate different aspects of the difficulty of individuals in certain subgroups to achieve recourse, i.e. receive the desired outcome, either at the micro level, considering members of the subgroup individually, or at the macro level, considering the subgroup as a whole, and (b) introduce notions of subgroup fairness that are robust, if not totally oblivious, to the cost of achieving recourse. We accompany these notions with an efficient, model-agnostic, highly parameterizable, and explainable framework for evaluating subgroup fairness. We demonstrate the advantages, the wide applicability, and the efficiency of our approach through a thorough experimental evaluation of different benchmark datasets.

翻译：本文提出面向子组的公平感知反事实框架（FACTS），一种通过反事实解释对子组公平性进行审计的框架。我们首先回顾（并泛化）现有概念，引入更精细的全新子组公平性定义。旨在：(a) 从微观层面（单独考虑子组成员）和宏观层面（将子组视为整体）刻画特定子组成员获得补救措施（即实现预期结果）的困难程度；(b) 引入对补救成本具有鲁棒性（若非完全无感）的子组公平性概念。我们为这些概念配套开发了一个高效、模型无关、高度可参数化且可解释的子组公平性评估框架。通过对不同基准数据集的全面实验评估，展示了本方法的优势、广泛适用性及高效性。