The Many Facets of Data Equity

H. Jagadish; Julia Stoyanovich; Bill Howe

doi:10.1145/3533425

The Many Facets of Data Equity

H. Jagadish, Julia Stoyanovich, Bill Howe

Research output: Contribution to journal › Article › peer-review

Abstract

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 language	English (US)
Article number	27
Journal	Journal of Data and Information Quality
Volume	14
Issue number	4
DOIs	https://doi.org/10.1145/3533425
State	Published - Feb 7 2022

Keywords

Data equity
Fairness in AI
ethics
responsible data science

ASJC Scopus subject areas

Information Systems
Information Systems and Management

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10.1145/3533425

Cite this

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The Many Facets of Data Equity

Abstract

Keywords

ASJC Scopus subject areas

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