This paper proposes a method for measuring fairness through equality of effort by applying algorithmic recourse through minimal interventions. Equality of effort is a property that can be quantified at both the individual and the group level. It answers the counterfactual question: what is the minimal cost for a protected individual or the average minimal cost for a protected group of individuals to reverse the outcome computed by an automated system? Algorithmic recourse increases the flexibility and applicability of the notion of equal effort: it overcomes its previous limitations by reconciling multiple treatment variables, introducing feasibility and plausibility constraints, and integrating the actual relative costs of interventions. We extend the existing definition of equality of effort and present an algorithm for its assessment via algorithmic recourse. We validate our approach both on synthetic data and on the German credit dataset.

翻译：本文提出一种通过最低限度干预应用算法手段衡量公平的方法,通过平等努力衡量公平性; 平等努力是一种可以在个人和群体一级量化的财产; 它回答了反事实问题:受保护的个人的最低费用是多少,还是受保护的个人群体扭转自动化系统计算的结果的平均最低费用? 使用比额手段增加了平等努力概念的灵活性和适用性:它克服了以往的局限性,调和了多种治疗变量,引入了可行性和合理性限制,并整合了干预的实际相对费用; 我们扩大了现有的平等努力定义,并提出了一种通过算法手段进行评估的算法; 我们验证了我们在合成数据和德国信用数据集方面的做法。