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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月6日

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  • James Keith Martin II,
  • Mercedes Byrd

摘要

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.