Towards a SAFETY-AI framework for healthcare education
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Date
2025
Authors
Salim, Kinza
Nana, Vanita Kouomogne
Marshall, Mark T.
Nguyen, Harry
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Abstract
Safety is an integral part of healthcare professionalism, and with new technological developments, such as Artificial Intelligence (AI), there is an ongoing need to develop guardrails for healthcare education. The landscape of AI safety frameworks for healthcare education is evolving, with significant development in regulatory compliance, ethical governance, and practical implementation approaches. This paper addresses the need for building a SAFETY-AI framework for healthcare education and proposes a solution towards it. It also provides subjective insights regarding trustworthiness, reliability and the existing concepts of safety in healthcare setups. This work stands as a roadmap for safety in AI practices for healthcare policy makers, educators and clinicians.
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© 2025, the Authors. For the purpose of Open Access, the author has applied a CC-BY public copyright licence to any Author Accepted Manuscript version arising from this submission.
Keywords
Artificial intelligence , Safety , Education , Healthcare , Reliable AI , [Insight Centre for Data Analytics]
Citation
Salim, K, Nana, V K, Marshall, M T & Nguyen, H 2025, 'Towards a SAFETY-AI framework for healthcare education', Paper presented at ACML 2025 , Taipei, Taiwan, Province of China, 9/12/25 - 12/12/25.
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info:eu-repo/semantics/restrictedAccess