Reducing the incidence of biased algorithmic decisions through feature importance transparency: an empirical study
Author:
Affiliation:
1. School of Accounting and Finance, University of Waterloo, Waterloo, Canada
2. Odette School of Business, University of Windsor, Windsor, Canada
3. DeGroote School of Business, McMaster University, Hamilton, Canada
Funder
Social Sciences and Humanities Research Council of Canada
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/0960085X.2024.2395531
Reference213 articles.
1. Big Data Research in Information Systems: Toward an Inclusive Research Agenda
2. Directly Discriminatory Algorithms
3. Inequity In Social Exchange
4. Integrating Behavioral, Economic, and Technical Insights to Understand and Address Algorithmic Bias: A Human-Centric Perspective
5. Algorithmic bias in data-driven innovation in the age of AI
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