Inteligencia artificial generativa en la educación médica universitaria: oportunidades, riesgos y desafíos curriculares en América Latina
DOI:
https://doi.org/10.62544/82z94136Keywords:
Inteligencia artificial generativa, educación médica, revisión de alcance, currículo médico, competencias digitales, América LatinaAbstract
Generative artificial intelligence has emerged as a tool with a growing impact on university medical education, transforming teaching, learning, assessment, and scientific research processes. The objective of this study was to analyze the curricular opportunities, risks, and challenges associated with the use of generative artificial intelligence in higher medical education. The research was conducted through a qualitative review of scientific literature following the PRISMA 2020 guidelines. The literature search was carried out during January and February 2026 in the Scopus, PubMed, SciELO, Web of Science, and Google Scholar databases. Thirty-eight scientific articles published between 2019 and 2026 were selected, considering inclusion criteria related to medical education, artificial intelligence, and health sciences. The results showed pedagogical benefits linked to personalized learning, immediate feedback, clinical simulation, and rapid access to scientific information. However, concerns also emerged related to academic plagiarism, technological dependence, algorithmic biases, and a decline in critical thinking. It is concluded that generative artificial intelligence has the potential to strengthen university medical education, although its implementation requires ethical regulation, specialized teacher training, and ongoing curriculum updates to ensure a critical, responsible, and inclusive use of these technologies.
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Copyright (c) 2026 Cristiana Andrade Mendes, Daiane Fontoura, Wilma Talavera, Francisco Javier Colman Ramírez
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