TY  - JOUR
T1  - Ethics Education for AI-Mediated Care: A Scoping Review of Curricula, Competencies, Assessment, and Clinical Transfer
A1  - Ana Rodrigues
A1  - Tiago Martins
A1  - Bruno Lopes
JF  - Asian Journal of Ethics in Health and Medicine
JO  - Asian J Ethics Health Med
SN  - 3108-5059
Y1  - 2026
VL  - 6
IS  - 1
DO  - 10.51847/psKtlimTN1
SP  - 162
EP  - 173
N2  - Artificial intelligence is entering clinical decision-making faster than health-professions education has established shared expectations for the ethical capabilities clinicians need when using, questioning, explaining, or overriding AI-supported recommendations. Existing literature spans technical literacy, professionalism, ethics teaching, learner attitudes, competency frameworks, assessment, and implementation, but these domains should not be treated as equivalent evidence of clinical competence. This scoping review used PRISMA-ScR-compatible evidence-mapping logic to examine peer-reviewed literature published from 2017 through 2026 on AI-related curricula, competencies, teaching and learning methods, assessment, and transfer relevant to health-professions practice. The auditable selection ledger began with 56 unique candidate publications. All 56 proceeded to documented eligibility assessment; 18 were excluded, leaving 38 publications retained in the manuscript. Of these, 26 constituted the substantive educational evidence map and 12 served methodological, reporting, or contextual functions. Charting distinguished learner group, profession, curriculum focus, pedagogy, assessment construct, outcome level, contextual boundary, and evidential distance from clinical practice. The substantive evidence indicates movement from general AI awareness toward competency-oriented and ethics-explicit education. Recurrent emphases include understanding limitations, critical appraisal, bias and fairness, privacy, transparency, accountability, communication, professional oversight, and responsible use. Teaching ranges from web-based and didactic formats to case-based, problem-based, chatbot-supported, and simulation-oriented learning. Assessment is uneven: self-reported readiness and attitudes are easier to measure than observable ethical performance, and evidence of sustained workplace transfer remains comparatively sparse. Ethics education for AI-mediated care should be distinguished from generic AI literacy and from ethical governance of AI used in education. The review supports a proposed progression from curricular intent through learning and assessment toward near transfer and clinical transfer, while emphasizing that these evidential stages are not interchangeable or causally validated.
UR  - https://smerpub.com/article/ethics-education-for-ai-mediated-care-a-scoping-review-of-curricula-competencies-assessment-and-r8d7pcj29suifkj
ER  -