Mapping AI Ethics Integration in Postgraduate Health Professions Education: A Scoping Review Through the Lenses of Principlism and Transformative Learning

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.

Authors

Institutions

Publication Details

Journal
The Clinical Teacher
Published
2026-10-05
DOI
https://doi.org/10.1111/tct.70541
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mapping AI Ethics Integration in Postgraduate Health Professions Education: A Scoping Review Through the Lenses of Principlism and Transformative Learning

M. M. Hussein, Claude Jeffrey Renaud, T. Wong, Ang Yu Chien Constance
The Clinical Teacher
Artificial Intelligence in Healthcare and Education
article

Mapping AI Ethics Integration in Postgraduate Health Professions Education: A Scoping Review Through the Lenses of Principlism and Transformative Learning

M. M. Hussein, Claude Jeffrey Renaud, T. Wong, Ang Yu Chien Constance
article en

Abstract

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.

The Clinical TeacherVol. 23(6)
Ministry of Health (SG), Nanyang Technological University (SG), Khoo Teck Puat Hospital (SG)
Openalex Percentile: Top 18%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.