Role and Use of Race in Artificial Intelligence and Machine Learning Models Related to Health
The role and use of race within health-related artificial intelligence (AI) and machine learning (ML) models have sparked increasing attention and controversy. Despite the complexity and breadth of related issues, a robust and holistic framework to guide stakeholders in their examination and resolution remains lacking. This perspective provides a broad-based, systematic, and crosscutting landscape analysis of race-related challenges, structured around the AI and ML life cycle and framed through "points to consider" to support inquiry and decision-making.
Authors
- Chao Yan (ORCID: https://orcid.org/0000-0002-6719-1388)
- Rachele Hendricks‐Sturrup (ORCID: https://orcid.org/0000-0002-3390-2583)
- Abiodun O. Oluyomi (ORCID: https://orcid.org/0000-0002-6603-6941)
- Benjamin Collins (ORCID: https://orcid.org/0000-0002-6884-3819)
- Martin C. Were (ORCID: https://orcid.org/0000-0003-3010-011X)
- Zhijun Yin (ORCID: https://orcid.org/0000-0002-3075-1337)
- Laurie Lovett Novak (ORCID: https://orcid.org/0000-0002-0415-4301)
- Joseph Coco (ORCID: https://orcid.org/0000-0001-6195-5757)
- Shilo Anders (ORCID: https://orcid.org/0000-0002-2327-7323)
- Bradley Malin (ORCID: https://orcid.org/0000-0003-3040-5175)
- Ellen Wright Clayton (ORCID: https://orcid.org/0000-0002-0308-4110)
- Ang Li (ORCID: https://orcid.org/0000-0002-9222-3521)
Institutions
- Baylor College of Medicine (US)
- Vanderbilt University (US)
- Duke Institute for Health Innovation (US)
- Vanderbilt University Medical Center (US)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2025-06-18
- DOI
- https://doi.org/10.2196/73996
- Citations
- 1
- Primary Topic
- Health, Environment, Cognitive Aging
- Type
- article
- Field-Weighted Citation Impact
- 1.20