Opportunities for a More Interdisciplinary Approach to Measuring Perceptions of Fairness in Machine Learning
Author:
Affiliation:
1. Brown University, USA
2. Brown University; Humboldt University of Berlin, Germany
3. Brown University; SeqHub Analytics, USA
4. University of Rhode Island, USA
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3465416.3483302
Reference74 articles.
1. Roles for computing in social change
2. Solon Barocas Moritz Hardt and Arvind Narayanan. 2019. Fairness and Machine Learning. fairmlbook.org. http://www.fairmlbook.org. Solon Barocas Moritz Hardt and Arvind Narayanan. 2019. Fairness and Machine Learning. fairmlbook.org. http://www.fairmlbook.org.
3. Big data’s disparate impact;Barocas Solon;Calif. L. Rev.,2016
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