Leveraging AI to Democratize the Hidden Curriculum in Medical Education: An Implementation Framework

利用人工智能实现医学教育中隐性课程的民主化:一个实施框架

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Abstract

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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