Were, Martin Chieng, Li, Ang, Malin, Bradley A., Yin, Zhijun, Coco, Joseph R., Collins, Benjamin Xavier, Clayton, Ellen Wright, Novak, Laurie Lovett, Hendricks-Sturrup, Rachele M., & Oluyomi, Abiodun Olufemi. (2025). “Role and use of race in artificial intelligence and machine learning models related to health.” Journal of Medical Internet Research, 27, e73996. https://doi.org/10.2196/73996
The use of race in health-related artificial intelligence (AI) and machine learning (ML) models has become a topic of growing attention and debate. Despite the many complex issues involved, there is currently no clear framework to help guide researchers, developers, and other stakeholders in examining and addressing these challenges. This perspective offers a broad, organized overview of the problems related to race in AI and ML, structured around the typical steps in developing and using these models. It also provides “points to consider” to help guide thoughtful inquiry and decision-making.
Figure 1. An artificial intelligence and machine learning life cycle model used to frame discussion on race. Adapted from Collins et al [17]. AI: artificial intelligence; ML: machine learning.