Emerging algorithmic bias: fairness drift as the next dimension of model maintenance and sustainability
Equitable and sustainable clinical artificial intelligence deployments will require novel methods to monitor algorithmic fairness, detect emerging bias, and adopt model updates that promote fairness.
Authors
- Michael E. Matheny (ORCID: https://orcid.org/0000-0003-3217-4147)
- Sharon E. Davis (ORCID: https://orcid.org/0000-0003-0792-8867)
- Chad Dorn (ORCID: https://orcid.org/0000-0002-4886-6159)
- Daniel Park (ORCID: https://orcid.org/0000-0003-2783-530X)
Institutions
- Veterans Health Administration (US)
- VA Tennessee Valley Healthcare System (US)
- Vanderbilt University Medical Center (US)
Publication Details
- Journal
- Journal of the American Medical Informatics Association
- Published
- 2025-03-13
- DOI
- https://doi.org/10.1093/jamia/ocaf039
- Citations
- 13
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 8.51