Biases in an artificial intelligence image-generator’s depictions of healthy aging and Alzheimer’s
The findings highlight AI's potential to reinforce stigmatizing stereotypes through biased image generation. Recommendations include selecting prompts carefully to avoid negative depictions and advocating for greater AI explainability and inclusivity by design. Future research should explore other AI models, other forms of bias, and strategies to mitigate biases.
Authors
- D.J.M. Steijger
- Marjolein Elizabeth de Vugt (ORCID: https://orcid.org/0000-0002-2113-4134)
- David T. Neal
- Natcha Jintaganon
- Channah Jamilla Osinga (ORCID: https://orcid.org/0009-0008-2830-1207)
Institutions
- Amsterdam UMC Location University of Amsterdam (NL)
- Maastricht University (NL)
- Amsterdam Neuroscience (NL)
- Amsterdam University Medical Centers (NL)
- Vrije Universiteit Amsterdam (NL)
- University of Amsterdam (NL)
Publication Details
- Journal
- Journal of the American Medical Informatics Association
- Published
- 2025-10-02
- DOI
- https://doi.org/10.1093/jamia/ocaf173
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00