Examining developer perspectives on medical AI regulatory frameworks
Regulatory frameworks ensure the trustworthiness of artificial intelligence in medicine (AI-MD). Yet, developers' perspectives on these frameworks remain underexplored. We surveyed 122 AI-MD developers online, examining their awareness, familiarity, and adoption of regulatory frameworks, alongside their views on ethical principles and stakeholder responsibilities. About half (57.4%, n = 70) were aware of any frameworks while reporting moderate familiarity. A third (33.6%, n = 41) indicated that their organizations had formally adopted such frameworks. Developers identified robustness as the most critical ethical principle and viewed themselves as primarily responsible for implementing regulatory standards. Independent t-tests indicated marginal and significant differences in awareness (p = 0.051) and familiarity (p < 0.001), respectively, between developers from adopting and non-adopting organizations. Senior and junior developers differed significantly on both measures (p < 0.05). These findings highlight developers' strong sense of professional accountability but also reveal limited familiarity and adoption, underscoring the need for greater education and organizational support to foster responsible AI-MD practices.
Authors
- Mengling Feng (ORCID: https://orcid.org/0000-0002-5338-6248)
- Joseph J.Y. Sung (ORCID: https://orcid.org/0000-0003-3125-5199)
- Shelly Malik (ORCID: https://orcid.org/0000-0003-2407-8470)
- May O. Lwin (ORCID: https://orcid.org/0000-0003-1832-8242)
- Hong Xu
- Cameron M. Choo
- Nan Liu (ORCID: https://orcid.org/0000-0003-3610-4883)
- Wilson W. B. Goh
Institutions
- National University of Singapore (SG)
- Nanyang Technological University (SG)
- Duke-NUS Medical School (SG)
- Institute of Mental Health (SG)
- National University Health System (SG)
- Imperial College London (GB)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2026-05-08
- DOI
- https://doi.org/10.1038/s41746-026-02689-0
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Research Foundation
- National Research Foundation Singapore