Regulatory guidelines must keep pace with the rapid technological changes driving today's generative AI systems. For example a tool to prevent overprescribing antibiotics, designed by Singapore General Hospital, that will help combat the global threat of multidrug-resistant infections. However, current regulatory and governance approaches were built for AI tools designed to generate specific clinical decisions or recommendations.
MOH, along with the Health Sciences Authority (HSA) and health tech agency Synapxe, co-developed the MOH Artificial Intelligence in Healthcare Guidelines (AIHGle) – setting best practice for safe and responsible AI development and implementation in healthcare settings. The AIHGle guidelines are being constantly reviewed to strengthen governance on AI in healthcare. The review brings together key national and research bodies, including MOH, HSA, and the Centre of Regulatory Excellence at Duke-NUS Medical School. Singapore is also spearheading international partnerships to ensure AI adoption is ethically sound, trustable and safe across different healthcare systems.
Such steps are crucial to building models that clinicians and patients can trust, but more still needs to be done beyond guidelines and regulations. While healthcare institutions and universities are investing in workforce readiness through upskilling current staff and integrating AI training into medical education, this calls for significant reforms to an already crowded medical curriculum. More faculty with expertise in AI tools and their implications is needed to prepare students for AI-assisted medical practice.
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