Theoretical framework demonstrates how AI can reduce inequities in professional integration for underrepresented students.
The “hidden curriculum” in medical education—comprising unwritten rules, values, and expectations—significantly impacts student success, yet remains inaccessible to students from underrepresented backgrounds. This paper presents a theoretical framework and practical implementation strategy for using artificial intelligence (AI) to democratize access to this hidden curriculum. We analyze how cognitive load theory and the Fast/Slow Thinking paradigm explain inequities in professional integration, then propose a comprehensive implementation approach to guide equitable AI integration. This model demonstrates how AI tools, when thoughtfully implemented, can reduce cognitive burdens on disadvantaged students, accelerate professional acculturation, and contribute to building an inclusive medical workforce.
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Martín et al. (2025) studied this question.
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