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<p>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%, <i>n</i> = 70) were aware of any frameworks while reporting moderate familiarity. A third (33.6%, <i>n</i> = 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 <i>t</i>-tests indicated marginal and significant differences in awareness (<i>p</i> = 0.051) and familiarity (<i>p</i> &lt; 0.001), respectively, between developers from adopting and non-adopting organizations. Senior and junior developers differed significantly on both measures (<i>p</i> &lt; 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.</p>

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Examining developer perspectives on medical AI regulatory frameworks

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月8日

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

摘要

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.