Responsible AI integration in psychiatry GME requires staged introduction aligned with trainee developmental level, faculty engagement, human oversight in evaluation and decision-making, transparent communication of AI use, robust data governance, and prioritization of tools that deepen rather than replace human connection.
The literature indicates that AI can facilitate personalized learning pathways, augment simulation-based training, and aid in the integration of longitudinal assessment data, particularly in educational contexts characterized by distributed supervision and diverse learner requirements.
C. Wiedermann, Anne Wiedermann, Hendrik Reismann· Journal of Medical Education...· 0 citations
The goal is not to deter innovation but to ensure that GenAI tools enhance rather than replace the clinical judgment, empathy, and professional accountability that lie at the heart of psychiatric practice.
Cong Zhou, Ao-Xue Zhang, Sen Li· Frontiers in Psychiatry· 0 citations
GenAI should be viewed as a powerful augmentative tool, not a replacement for human educators, and its successful integration will depend on leveraging its strengths to enhance efficiency and scalability while preserving the essential humanistic elements of medical practice through expert oversight and validation.
R. Xie, Bei-En Zhang, Li-Feng Xiao· Frontiers in Medicine· 0 citations
It is argued that AI-focused CME should be designed as a longitudinal organizational learning system rather than a discrete instructional event, and implications are offered for technology integration, faculty development, and organizational learning in clinical education.
T. Murphy, Rob E. Carpenter· International Journal on Int...· 1 citation
Insight is provided into developing AI-ready medical education models that balance technical competence with humanistic values and factors influencing AI adoption in medical training, including performance expectancy, effort expectancy, social influence, and facilitating conditions.
T. Murphy, Ginger Vaughn, Rob E. Carpenter et al.· International Medical Educat...· 0 citations
The clinical impact of psychiatric AI will likely depend less on algorithmic novelty alone than on clearer clinical targets, prospective validation, implementation trials, patient‐centered evaluation, equity‐sensitive generalizability, and mental health–specific governance.
Esteban Zavaleta-Monestel, L. Herrera-Jiménez, Sofía Suárez-Sánchez et al.· Psychiatric Research and Cli...· 0 citations
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