Anti-discrimination learning: a causal modeling-based framework
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Anti-discrimination rules to define legal policies may prevent dissemination of discrimination against certain groups in the algorithm.
“Anti-discrimination rules to define legal policies that may prevent dissemination of discrimination against certain group in the algorithm [163].”
From Artificial intelligence bias in medical system designs: a systematic review (2023) · cites this paper as [163]
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- Authors
- Zhang, L., & Wu, X.
- Affiliations
- University of Arkansas at Fayetteville (US)
- Corresponding author
- Wu, Xintao
- ORCID
- Venue
- International Journal of Data Science and Analytics
- Published
- 2017-05-18
- Volume
- 4
- Issue
- 1
- Pages
- 1-16
- ISSN
- 2364-415X (ISSN-L)
- 2364-4168
- OpenAlex
- W2616536620
- Cited by
- 48
- References
- 42
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 3 · 2023: 9 · 2022: 5 · 2021: 6 · 2020: 8 · 2019: 9 · 2018: 3 · 2017: 1
- FWCI
- 13.79
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Journal of Data Science and Analytics (publishedVersion)
- Journal of the Arkansas Academy of Science (submittedVersion, cc-by-nd)
- Funders
- Division of Information and Intelligent Systems (1646654)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Keywords
- discrimination prevention, causal models, association versus causation, direct and indirect discrimination, biased training data, algorithmic fairness
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