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.

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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

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article

Examining developer perspectives on medical AI regulatory frameworks

Mengling Feng, Joseph J.Y. Sung, Shelly Malik, May O. Lwin et al.
npj Digital Medicine
Artificial Intelligence in Healthcare and Education
article

Examining developer perspectives on medical AI regulatory frameworks

Mengling Feng, Joseph J.Y. Sung, Shelly Malik, May O. Lwin, Hong Xu, Cameron M. Choo, Nan Liu, Wilson W. B. Goh
article en

Abstract

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.

npj Digital Medicine
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)
National Research Foundation, National Research Foundation Singapore
Openalex Percentile: Top 9%
Artificial Intelligence in Healthcare and Education
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