Cultural variation in trust and acceptability of artificial intelligence diagnostics for dementia
Digital health innovations hold diagnostic and therapeutic promise but may be subject to biases for underrepresented groups. We explored perceptions of using artificial intelligence (AI) diagnostics for dementia through a focus group as part of the Automated Brain Image Analysis for Timely and Equitable Dementia Diagnosis (ABATED) study. Qualitative feedback from a diverse public engagement group indicated that cultural variations in trust and acceptability of AI diagnostics may be an unrecognised source of real-world inequity. Efforts focused on the adoption of AI diagnostics in memory clinic pathways should aim to recognise and account for this issue.
Authors
- Rifah Anjum
- S. Hussna Begum
- Avinash Chandra (ORCID: https://orcid.org/0009-0005-5072-7499)
- Laura Smith (ORCID: https://orcid.org/0000-0003-3275-1530)
- Charles R. Marshall (ORCID: https://orcid.org/0000-0002-8227-2354)
- Kaviya Senthilvel
- Ijeoma Uchegbu (ORCID: https://orcid.org/0000-0003-2952-8944)
- Helen Beaumont (ORCID: https://orcid.org/0000-0002-8446-3939)
- Reshma Punjabi
Institutions
- Queen Mary University of London (GB)
Publication Details
- Journal
- Journal of Alzheimer s Disease
- Published
- 2025-02-16
- DOI
- https://doi.org/10.1177/13872877251319353
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.65
Funders
- National Institute for Health and Care Research