Ranking is a fundamental operation in information access systems, to filter information and direct user attention towards items deemed most relevant to them. Due to position bias, items of similar relevance may receive significantly different exposure, raising fairness concerns for item providers and motivating recent research into fair ranking. While the area has progressed dramatically over recent years, no study to date has investigated the potential problem posed by duplicated items. Duplicates and near-duplicates are common in several domains, including marketplaces and document collections available to search engines. In this work, we study the behaviour of different fair ranking policies in the presence of duplicates, quantifying the extra-exposure gained by redundant items. We find that fairness-aware ranking policies may conflict with diversity, due to their potential to incentivize duplication more than policies solely focused on relevance. This fact poses a problem for system owners who, as a result of this incentive, may have to deal with increased redundancy, which is at odds with user satisfaction. Finally, we argue that this aspect represents a blind spot in the normative reasoning underlying common fair ranking metrics, as rewarding providers who duplicate their items with increased exposure seems unfair for the remaining providers.
翻译:排名是信息存取系统的基本操作,可以过滤信息,并引导用户关注被认为与它们最相关的项目。由于定位偏差,具有类似相关性的项目可能会受到截然不同的曝光,引起对项目提供者的公平关注,并促使最近对公平排名的研究。虽然这一领域近年来进展显著,但迄今为止还没有研究重复项目的潜在问题。在包括可供搜索引擎使用的市场和文件收藏在内的若干领域,重复和近乎重复的现象是常见的。在这项工作中,我们研究了存在重复项目时不同公平排名政策的行为,对多余项目获得的额外接触进行了量化。我们发现,公平意识的排名政策可能与多样性发生冲突,因为它们有可能激发重复,而不是仅仅侧重于相关性的政策。这一事实给系统所有人造成了一个问题,由于这种激励,他们可能不得不处理更多的冗余,这与用户的满意程度不相符。最后,我们认为,这一方面在规范推理中是一个盲点,说明通用公平排名指标的基础,因为用增加的曝光量来奖励重复其物品的供应商,对其余供应商来说似乎是不公平的。