Pairwise Fairness in Ranking as a Dissatisfaction Measure

Fairness and equity have become central to ranking problems in information access systems, such as search engines, recommender systems, or marketplaces. To date, several types of fair ranking measures have been proposed, including diversity, exposure, and pairwise fairness measures. Out of those, pairwise fairness is a family of metrics whose normative grounding has not been clearly explicated, leading to uncertainty with respect to the construct that is being measured and how it relates to stakeholders' desiderata. In this paper, we develop a normative and behavioral grounding for pairwise fairness in ranking. Leveraging measurement theory and user browsing models, we derive an interpretation of pairwise fairness centered on the construct of producer dissatisfaction, tying pairwise fairness to perceptions of ranking quality. Highlighting the key limitations of prior pairwise measures, we introduce a set of reformulations that allow us to capture behavioral and practical aspects of ranking systems. These reformulations form the basis for a novel pairwise metric of producer dissatisfaction. Our analytical and empirical study demonstrates the relationship between dissatisfaction, pairwise, and exposure-based fairness metrics, enabling informed adoption of the measures.