论文标题
公平排名：批判性审查，挑战和未来的方向
Fair ranking: a critical review, challenges, and future directions
论文作者
论文摘要
排名，建议和检索系统被广泛用于在线平台和其他社会系统中，包括电子商务，媒体流程，录取，演出平台和招聘。在最近的过去，已经开发了一项大型的“公平排名”研究文献，使这些系统对正在排名的个人，提供商或内容公平。这些文献中的大多数都为单个检索实例定义了公平性，或者是随着时间的流逝的多个检索实例的简单添加概念。这项工作概述了这种文献，详细介绍了这种方法错过的经常特定于上下文的关注：高级排名和真正的提供商效用之间的差距，随着时间的流逝，溢出和复合效果，诱导的战略激励措施以及统计不确定性的效果。然后，我们为更全面和面临影响的公平排名研究议程提供了前进的途径，包括来自其他领域的方法论课，以及更广泛的利益相关者社区在克服数据瓶颈和设计有效的监管环境中的作用。
Ranking, recommendation, and retrieval systems are widely used in online platforms and other societal systems, including e-commerce, media-streaming, admissions, gig platforms, and hiring. In the recent past, a large "fair ranking" research literature has been developed around making these systems fair to the individuals, providers, or content that are being ranked. Most of this literature defines fairness for a single instance of retrieval, or as a simple additive notion for multiple instances of retrievals over time. This work provides a critical overview of this literature, detailing the often context-specific concerns that such an approach misses: the gap between high ranking placements and true provider utility, spillovers and compounding effects over time, induced strategic incentives, and the effect of statistical uncertainty. We then provide a path forward for a more holistic and impact-oriented fair ranking research agenda, including methodological lessons from other fields and the role of the broader stakeholder community in overcoming data bottlenecks and designing effective regulatory environments.
