The Many Facets of Data Equity

H. Jagadish, Julia Stoyanovich, Bill Howe

    Research output: Contribution to journalArticlepeer-review


    Data-driven systems can induce, operationalize, and amplify systemic discrimination in a variety of ways. As data scientists, we tend to prefer to isolate and formalize equity problems to make them amenable to narrow technical solutions. However, this reductionist approach is inadequate in practice. In this article, we attempt to address data equity broadly, identify different ways in which it is manifest in data-driven systems, and propose a research agenda.

    Original languageEnglish (US)
    Article number27
    JournalJournal of Data and Information Quality
    Issue number4
    StatePublished - Feb 7 2022


    • Data equity
    • Fairness in AI
    • ethics
    • responsible data science

    ASJC Scopus subject areas

    • Information Systems
    • Information Systems and Management


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