A Scoping Review on the Ethical Governance for Using Generative AI Tools in Health Professions Education

Abstract

<p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="first" dir="auto" id="d536154e133"> <b>Background:</b> Generative Artificial Intelligence (GenAI) represents a paradigm shift in Health Professions Education (HPE), offering substantive potential to enhance pedagogical delivery, clinical simulation, and personalized learning. Despite its rapid expansion, the integration of GenAI remains largely heterogeneous and under-theorized. The absence of standardized regulatory frameworks and comprehensive institutional guidance presents significant challenges to the responsible and pedagogically sound application of these technologies, which potentially compromises academic integrity and educational quality. This study synthesizes current evidence regarding the implementation of GenAI in HPE, critically examining the opportunities and barriers to its adoption while identifying the ethical imperatives and regulatory gaps that necessitate a coordinated policy response. <p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" dir="auto" id="d536154e138"> <b>Methods:</b> Adhering to the JBI methodology for scoping reviews and the PRISMA-ScR guidelines, a comprehensive search was executed across major databases, including PubMed, ERIC, CINAHL, and Scopus. Data were extracted based on GenAI modalities, curricular integration, operational domains, reported outcomes, ethical and regulatory challenges, and existing or proposed policy frameworks. Findings were synthesized through narrative thematic mapping to identify emergent patterns in practice. <p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" dir="auto" id="d536154e143"> <b>Results:</b> The analysis revealed that GenAI is increasingly utilized to optimize curriculum design, facilitate automated feedback, and enhance learner engagement through sophisticated simulations. However, implementation is frequently characterized by a lack of structured oversight. Predominant challenges include algorithmic bias, data privacy concerns, and the reliability of AI-generated content. The review identified a critical need for developing multi-dimensional AI literacies among health professional educators and learners, including technical proficiency, ethical judgment, and the ability to critically evaluate AI-generated clinical insights. Existing regulatory frameworks are noted to be underdeveloped and fragmented. Successful integration is contingent upon proactive institutional safeguards, such as human-in-the-loop validation for high-stakes assessments and the alignment of AI tools with professional accreditation standards. <p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" dir="auto" id="d536154e148"> <b>Conclusion:</b> While GenAI offers transformative opportunities, its sustainable adoption is predicated on adaptive, evidence-based regulatory frameworks. Future initiatives must prioritize the definition of core AI competencies and the establishment of anticipatory governance models that evolve alongside technological advancements. HPE can serve as a global benchmark for responsible AI implementation by embedding transparency and ethical accountability into the core of its educational frameworks.

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