{"title":"[Medical education and artificial intelligence: perspectives and ethical challenges].","authors":"Omar Chávez-Martínez, Leonardo Adriano Ragacini","doi":"10.5281/zenodo.16748310","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) drives innovation in medical education by enabling personalized learning, instant feedback, and clinical simulations. However, it raises concerns such as loss of human skills, misinformation, and ethical issues. ChatGPT has gained prominence for its natural language generation capabilities, despite lacking real understanding. The aim of this article was to analyze the use of AI, particularly ChatGPT, in medical education, identifying its benefits, limitations, and ethical implications, which is why a qualitative integrative review was conducted through a systematic search in PubMed (2020-2025), using MeSH descriptors related to artificial intelligence and medical education. A total of 37 open-access, full-text articles in English were included. The information was analyzed and synthesized using a thematic approach, organized into 4 categories: pedagogical applications, benefits, challenges, and ethical recommendations, thanks to which we had these results: AI supports clinical simulations, personalized learning, and equitable access. Benefits include enhanced clinical reasoning and autonomous learning. Challenges remain, such as bias, data privacy, and misinformation. Five pillars for integration are proposed, along with a professional classification into consumers, translators, and developers. Digital curation emerges as a key element to ensure quality and reliability. We conclude that AI can transform medical education if implemented ethically, critically, and with a human-centered approach.</p>","PeriodicalId":94200,"journal":{"name":"Revista medica del Instituto Mexicano del Seguro Social","volume":"63 5","pages":"e6736"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12377860/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista medica del Instituto Mexicano del Seguro Social","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5281/zenodo.16748310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence (AI) drives innovation in medical education by enabling personalized learning, instant feedback, and clinical simulations. However, it raises concerns such as loss of human skills, misinformation, and ethical issues. ChatGPT has gained prominence for its natural language generation capabilities, despite lacking real understanding. The aim of this article was to analyze the use of AI, particularly ChatGPT, in medical education, identifying its benefits, limitations, and ethical implications, which is why a qualitative integrative review was conducted through a systematic search in PubMed (2020-2025), using MeSH descriptors related to artificial intelligence and medical education. A total of 37 open-access, full-text articles in English were included. The information was analyzed and synthesized using a thematic approach, organized into 4 categories: pedagogical applications, benefits, challenges, and ethical recommendations, thanks to which we had these results: AI supports clinical simulations, personalized learning, and equitable access. Benefits include enhanced clinical reasoning and autonomous learning. Challenges remain, such as bias, data privacy, and misinformation. Five pillars for integration are proposed, along with a professional classification into consumers, translators, and developers. Digital curation emerges as a key element to ensure quality and reliability. We conclude that AI can transform medical education if implemented ethically, critically, and with a human-centered approach.