Designing fair ranking schemes

Abolfazl Asudeh, H. V. Jagadish, Julia Stoyanovich, Gautam Das

    Research output: Chapter in Book/Report/Conference proceedingConference contribution


    Items from a database are often ranked based on a combination of criteria. The weight given to each criterion in the combination can greatly affect the fairness of the produced ranking, for example, preferring men over women. A user may have the flexibility to choose combinations that weigh these criteria differently, within limits. In this paper, we develop a system that helps users choose criterion weights that lead to greater fairness. We consider ranking functions that compute the score of each item as a weighted sum of (numeric) attribute values, and then sort items on their score. Each ranking function can be expressed as a point in a multidimensional space. For a broad range of fairness criteria, including proportionality, we show how to efficiently identify regions in this space that satisfy these criteria. Using this identification method, our system is able to tell users whether their proposed ranking function satisfies the desired fairness criteria and, if it does not, to suggest the smallest modification that does. Our extensive experiments on real datasets demonstrate that our methods are able to find solutions that satisfy fairness criteria effectively (usually with only small changes to proposed weight vectors) and efficiently (in interactive time, after some initial pre-processing).

    Original languageEnglish (US)
    Title of host publicationSIGMOD 2019 - Proceedings of the 2019 International Conference on Management of Data
    PublisherAssociation for Computing Machinery
    Number of pages18
    ISBN (Electronic)9781450356435
    StatePublished - Jun 25 2019
    Event2019 International Conference on Management of Data, SIGMOD 2019 - Amsterdam, Netherlands
    Duration: Jun 30 2019Jul 5 2019

    Publication series

    NameProceedings of the ACM SIGMOD International Conference on Management of Data
    ISSN (Print)0730-8078


    Conference2019 International Conference on Management of Data, SIGMOD 2019


    • Data Ethics
    • Fairness
    • Responsible Data Management

    ASJC Scopus subject areas

    • Software
    • Information Systems


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