Fairness in decision-making processes is often quantified using probabilistic metrics. However, these metrics may not fully capture the real-world consequences of unfairness. In this article, we adopt a utility-based approach to more accurately measure the real-world impacts of decision-making process. In particular, we show that if the concept of $\varepsilon$-fairness is employed, it can possibly lead to outcomes that are maximally unfair in the real-world context. Additionally, we address the common issue of unavailable data on false negatives by proposing a reduced setting that still captures essential fairness considerations. We illustrate our findings with two real-world examples: college admissions and credit risk assessment. Our analysis reveals that while traditional probability-based evaluations might suggest fairness, a utility-based approach uncovers the necessary actions to truly achieve equality. For instance, in the college admission case, we find that enhancing completion rates is crucial for ensuring fairness. Summarizing, this paper highlights the importance of considering the real-world context when evaluating fairness.

本文研究了决策过程中的公平性，并提出了基于效用的方法来更准确地评估决策过程的真实世界影响。通过两个实际案例研究，发现传统的概率评估可能无法全面捕捉公平性，而基于效用的方法则可以揭示实现平等的必要行动。总结来说，本文强调了在评估公平性时考虑真实世界背景的重要性。

ε-公平的不公平性