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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 st…

By the Truvace desk1 min read1 sourcePeer-reviewedTRV-2026-1341· cite & verify
Mapping AI Ethics Integration in Postgraduate Health Professions Education: A Scoping Review Through the Lenses of Principlism and Transformative Learning
Conditions pour IA digne de confiance conditions requirements for Trustworthy AI by Lamiot. CC BY 4.0 · https://creativecommons.org/licenses/by/4.0

In brief

Researchers searched six databases covering 2000 to 2025 and found sixteen eligible sources on how AI ethics is taught to postgraduate and continuing professional development learners in the health professions. They mapped the teaching approaches against principlism (autonomy, beneficence, non-maleficence, justice) and transformative learning theory.

The review matters because AI is already disrupting healthcare, and clinicians need practical ethical competence beyond high-level governance frameworks. The review finds that the teaching has not kept pace. Its authors propose structured, theory-anchored curricula, but it does not test whether such curricula improve ethical preparedness.

Main points

  1. Sixteen eligible sources were found across six databases searched for 2000 to 2025.
  2. Only 31% of the sources were empirical studies.
  3. Principlism appeared frequently but mostly implicitly, and explicit use of transformative learning theory was rare.
  4. Most studies predated generative AI, so the evidence is out of step with current tools.
  5. Interprofessional approaches were minimal, and the evidence reflected a strong Western worldview.

The problem

AI ethics teaching for postgraduate and continuing-development health learners is limited, superficial and weakly evaluated. That leaves doubts about whether clinicians are ethically prepared for AI in healthcare.

The rundown

The review set out to map how AI ethics is taught in postgraduate and CPD health professions education. It captured study design, educational setting, pedagogical strategies and ethical themes, then synthesised the findings descriptively and narratively.

The sources used a variety of teaching methods, but these were weakly evaluated. The review identified gaps in empirical and pedagogical rigour, and the minimal interprofessional teaching meant few real-world reflective strategies.

The authors conclude that the field is conceptually rich but pedagogically underdeveloped. They suggest that integrating principlism and transformative learning theory may strengthen ethical competence, which is a recommendation rather than a demonstrated result.

Sources

  1. Peer-reviewedThe Clinical Teacher2026-12-01

The debate