AI-informed healthcare pedagogy: a review of the literature and application to pedagogical practice informed by case studies from dental education
TL;DR
It is argued that open, reflective classroom discussions around ethical concerns and climate impacts of AI are as important as the positive clinical applications to endow students with the knowledge to make decisions that align with social justice and social accountability.
Abstract
Artificial intelligence (AI) applications in healthcare continue to grow at a rapid pace. Healthcare education is struggling to effectively integrate the manifold applications and opportunities presented by AI to education. Concerns and fears around negative impacts on student learning and potential for misuse alongside a paucity of guidance has led to a sluggish response across much of healthcare education. This paper offers a short review of the applications of AI in healthcare including clinical dentistry and makes suggestions for bridging the gap between education and practice so that educators can better prepare students for their professional careers. This paper argues that open, reflective classroom discussions around ethical concerns and climate impacts of AI are as important as the positive clinical applications to endow students with the knowledge to make decisions that align with social justice and social accountability. Two widely used assessments in dental and wider healthcare education − reflective assessments and evidence-based practice projects − are explored as case studies to develop an updated, AI-informed approach to teaching. Drawing on pedagogical literature, the author offers suggestions for educators to support thoughtful and ethical integration of AI within a student's learning repertoire so that AI becomes supplementary to, and not a substitute for, learning. Artificial intelligence (AI) is being increasingly adopted in clinical practice and applied to support patient communication, diagnostics and treatment. Healthcare education has been slower to integrate AI into teaching and learning for students. Reflective assessments and evidence-based practice projects build critical thinking and self-awareness. Suggestions to integrate AI into these are made. Artificial intelligence (AI) is being increasingly adopted in clinical practice and applied to support patient communication, diagnostics and treatment. Healthcare education has been slower to integrate AI into teaching and learning for students. Reflective assessments and evidence-based practice projects build critical thinking and self-awareness. Suggestions to integrate AI into these are made.