AI in Psychiatric Education and Training From 2016 to 2024: Scoping Review of Trends.

Background: Artificial intelligence (AI) is rapidly changing both clinical psychiatry and the education of medical professionals. However, little is currently known about how AI is being discussed in the education and training of psychiatry for medical students and doctors around the world. Objective: This paper aims to provide a snapshot of the available data on this subject as of 2024. A deliberately broad definition of AI was adopted to capture the widest range of relevant literature and applications, including machine learning, natural language processing, and generative AI tools. Methods: A scoping review was conducted using both peer-reviewed publications from PubMed, Embase, PsycINFO, and Scopus databases, and gray literature sources. The criterion for inclusion was a description of how AI could be applied to education or training in psychiatry. Results: A total of 26 records published between 2016 and 2024 were included. The key themes identified were (1) the imperative for an AI curriculum for students or doctors training in psychiatry, (2) uses of AI to develop educational resources, (3) uses of AI to develop clinical skills, (4) uses of AI for assessments, (5) academic integrity or ethical considerations surrounding the use of AI, and (6) tensions relating to competing priorities and directions. Conclusions: Although a nascent field, it is clear that AI will increasingly impact assessment, clinical skills training, and the development of teaching resources in psychiatry. Training curricula will need to reflect the new knowledge and skills required for future clinical practice. Educators will need to be mindful of academic integrity risks and to emphasize development of critical thinking skills. Attitudes of psychiatrists toward the rise of AI in training remain underexplored.