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Abstract

Artificial intelligence (AI) offers transformative potential in healthcare, enhancing drug discovery, data processing, early detection, and clinical decision-making. However, its adoption poses significant risks, including client harm, misuse, automation bias, perpetuation of inequities, and security issues. Effective integration requires ongoing collaboration among healthcare professionals, developers, policymakers, and ethicists to ensure accountability and transparency. As AI becomes more prevalent, medical education must evolve to equip students with a deep understanding of AI technology, risk assessment, and mitigation strategies. Currently, medical curricula fall short in this area, necessitating educational reforms. We propose diverse and comprehensive teaching methods, including case studies, interdisciplinary projects, hackathons, interactive workshops, and cross-cultural design thinking, to better prepare medical students. By fostering an interdisciplinary approach, these methods aim to build a foundation for responsible AI use in healthcare, ensuring future professionals are well- equipped to navigate its complexities and ethical challenges.

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