标题： 我受到公平对待了吗？ 个人判断公平性的概念框架 显示英文标题

标题： Am I Being Treated Fairly? A Conceptual Framework for Individuals to Ascertain Fairness

摘要： 当前的公平性度量方法和缓解技术为从业者提供了评估自动决策（ADM）系统非歧视性的工具。但如果我作为一个面临ADM系统做出决策的个人，我想知道：我是否受到了公平对待？ 我们探讨了如何为用户提供询问ADM系统是否公平的能力。本文主张将公平性不仅视为ADM系统的属性，还视为个人获取影响自身决策信息的权利，以便在这些决策被证明具有歧视性时，能够质疑并寻求有效的补救措施。我们不仅考察了算法公平性领域的现有研究，还研究了可解释人工智能、问责制和争议性方面的关键概念。 通过整合这些领域的理念，我们提出了一种概念框架，结合不同的工具来确定ADM系统的公平性。我们的框架从面向从业者的解决方案转向使个人能够理解、挑战和验证决策公平性的机制，并为组织和政策制定者提供蓝图，弥合技术要求与实用、以用户为中心的问责制之间的差距。 显示英文摘要

摘要： Current fairness metrics and mitigation techniques provide tools for practitioners to asses how non-discriminatory Automatic Decision Making (ADM) systems are. What if I, as an individual facing a decision taken by an ADM system, would like to know: Am I being treated fairly? We explore how to create the affordance for users to be able to ask this question of ADM. In this paper, we argue for the reification of fairness not only as a property of ADM, but also as an epistemic right of an individual to acquire information about the decisions that affect them and use that information to contest and seek effective redress against those decisions, in case they are proven to be discriminatory. We examine key concepts from existing research not only in algorithmic fairness but also in explainable artificial intelligence, accountability, and contestability. Integrating notions from these domains, we propose a conceptual framework to ascertain fairness by combining different tools that empower the end-users of ADM systems. Our framework shifts the focus from technical solutions aimed at practitioners to mechanisms that enable individuals to understand, challenge, and verify the fairness of decisions, and also serves as a blueprint for organizations and policymakers, bridging the gap between technical requirements and practical, user-centered accountability.