Detection of Groups with Biased Representation in Ranking

Jinyang Li, Yuval Moskovitch, H. V. Jagadish

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Real-life tools for decision-making in many critical domains are based on ranking results. With the increasing awareness of algorithmic fairness, recent works have presented measures for fairness in ranking. Many of those definitions consider the representation of different "protected groups", in the top-k ranked items, for any reasonable k. Given the protected groups, confirming algorithmic fairness is a simple task. However, the groups' definitions may be unknown in advance.In this paper, we study the problem of detecting groups with biased representation in the top-k ranked items, eliminating the need to pre-define protected groups. The number of such groups possible can be exponential, making the problem hard. We propose efficient search algorithms for two different fairness measures: global representation bounds, and proportional representation. Then we propose a method to explain the bias in the representations of groups utilizing the notion of Shapley values. We conclude with an experimental study, showing the scalability of our approach and demonstrating the usefulness of the proposed algorithms.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE 39th International Conference on Data Engineering, ICDE 2023
PublisherIEEE Computer Society
Number of pages13
ISBN (Electronic)9798350322279
StatePublished - 1 Jan 2023
Event39th IEEE International Conference on Data Engineering, ICDE 2023 - Anaheim, United States
Duration: 3 Apr 20237 Apr 2023

Publication series

NameProceedings - International Conference on Data Engineering


Conference39th IEEE International Conference on Data Engineering, ICDE 2023
Country/TerritoryUnited States


  • bias
  • fairness
  • ranking
  • representation

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Information Systems


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