The clinical teacher · 2026
Mapping AI Ethics Integration in Postgraduate Health Professions Education: A Scoping Review Through the Lenses of Principlism and Transformative Learning.
СтатьяScoping ReviewОбзорНазвание и аннотация: Перевод пока не подготовлен
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Wong Tricia Mae, Constance Ang Yu Chien, Hussein Muhamed Shamir Jaffar, Renaud Claude J
Аннотация
BACKGROUND: Artificial intelligence (AI) is disrupting healthcare and health professions education (HPE), creating complex ethical challenges. Despite existing governance frameworks, postgraduate and continuing professional development (CPD) learners require stronger micro-level ethical competence. However, AI-ethics remains insufficiently integrated into postgraduate/CPD curricula with few real-world reflective and interprofessional strategies, raising concerns regarding ethical preparedness. The aim of this study is to map how AI ethics is taught within postgraduate/CPD HPE, drawing on principlism, an ethical framework espousing the principles of autonomy, beneficence, non-maleficence and justice and transformative learning theory (TLT), which explains how critical reflection transforms professional assumptions, perspectives and practice.
METHOD: A systematic search of six databases (2000-2025) was conducted to identify relevant sources. Data extraction captured study design, educational setting, pedagogical strategies and ethical themes. Findings were synthesised descriptively and narratively to examine empirical rigour, theoretical alignment and relevance to contemporary generative-AI developments.
RESULTS: Sixteen eligible sources were identified. Only 31% were empirical studies. The evidence reflected a strong Western worldview. AI-ethics education for postgraduate/CPD learners was limited, often superficial and reliant on varied but weakly evaluated pedagogies. Principlism appeared frequently but mostly implicitly, whereas explicit application of TLT was rare. Major gaps included low empirical and pedagogical rigour, minimal interprofessionalism and marked temporal anachronism, as most studies predated the advent of generative AI.
CONCLUSION: AI-ethics education in postgraduate/CPD HPE remains conceptually rich but pedagogically underdeveloped. Effective curricula require structured, theory-anchored, interprofessional and culturally responsive approaches. Integrating principlism and TLT as ethical and pedagogical frameworks may strengthen ethical competence and preparedness.
METHOD: A systematic search of six databases (2000-2025) was conducted to identify relevant sources. Data extraction captured study design, educational setting, pedagogical strategies and ethical themes. Findings were synthesised descriptively and narratively to examine empirical rigour, theoretical alignment and relevance to contemporary generative-AI developments.
RESULTS: Sixteen eligible sources were identified. Only 31% were empirical studies. The evidence reflected a strong Western worldview. AI-ethics education for postgraduate/CPD learners was limited, often superficial and reliant on varied but weakly evaluated pedagogies. Principlism appeared frequently but mostly implicitly, whereas explicit application of TLT was rare. Major gaps included low empirical and pedagogical rigour, minimal interprofessionalism and marked temporal anachronism, as most studies predated the advent of generative AI.
CONCLUSION: AI-ethics education in postgraduate/CPD HPE remains conceptually rich but pedagogically underdeveloped. Effective curricula require structured, theory-anchored, interprofessional and culturally responsive approaches. Integrating principlism and TLT as ethical and pedagogical frameworks may strengthen ethical competence and preparedness.