Inclusive AI in Medical Education: Bridging Equity Gaps in Training and Access

Abstract

Inclusive Artificial Intelligence (AI) in medical education has the potential to bridge longstanding equity gaps in training and access, offering personalized and adaptive learning environments for diverse student populations. AI technologies, such as machine learning algorithms, natural language processing, and virtual simulations, can support medical educators by providing real-time feedback, identifying knowledge gaps, and adapting curricula to the unique needs of individual learners. By incorporating inclusive design principles, AI can address disparities in medical education that often arise from socio-economic, racial, and geographical barriers.