Jacob T Rosenthal, Frederic W Hafferty, Kulamakan Mahan Kulasegaram, Claire L Wendland, Janelle S Taylor
{"title":"人工智能满足整体审查:自动化医学教育招生过程的承诺和陷阱。","authors":"Jacob T Rosenthal, Frederic W Hafferty, Kulamakan Mahan Kulasegaram, Claire L Wendland, Janelle S Taylor","doi":"10.1097/ACM.0000000000005964","DOIUrl":null,"url":null,"abstract":"<p><strong>Abstract: </strong>Holistic review has been widely adopted in medical education as a means of promoting equity in the application process and diversity in the medical workforce. Artificial intelligence (AI) is a rapidly emerging technology already having an impact on the medical school and residency application process as students and faculty alike increasingly turn to AI tools to automate some steps in the preparation and evaluation of application materials. While AI may have the potential to improve the holistic admissions process by increasing efficiency and adding some measure of standardization among reviewers, the authors caution that this promise does not come without certain pitfalls. AI models may introduce new sources of bias and amplify existing ones, which, when combined with a lack of transparency regarding their use in the admissions process, may perpetuate the very inequities that holistic review seeks to minimize. The authors call for the medical education community to establish clear regulations to govern the acceptable use of AI in the admissions process and for a principled adoption of AI tools in a way that is sustainable for applicants and reviewers in the future.</p>","PeriodicalId":50929,"journal":{"name":"Academic Medicine","volume":" ","pages":"541-546"},"PeriodicalIF":5.3000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12120830/pdf/","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence Meets Holistic Review: Promises and Pitfalls of Automating the Medical Education Admissions Process.\",\"authors\":\"Jacob T Rosenthal, Frederic W Hafferty, Kulamakan Mahan Kulasegaram, Claire L Wendland, Janelle S Taylor\",\"doi\":\"10.1097/ACM.0000000000005964\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Abstract: </strong>Holistic review has been widely adopted in medical education as a means of promoting equity in the application process and diversity in the medical workforce. Artificial intelligence (AI) is a rapidly emerging technology already having an impact on the medical school and residency application process as students and faculty alike increasingly turn to AI tools to automate some steps in the preparation and evaluation of application materials. While AI may have the potential to improve the holistic admissions process by increasing efficiency and adding some measure of standardization among reviewers, the authors caution that this promise does not come without certain pitfalls. AI models may introduce new sources of bias and amplify existing ones, which, when combined with a lack of transparency regarding their use in the admissions process, may perpetuate the very inequities that holistic review seeks to minimize. The authors call for the medical education community to establish clear regulations to govern the acceptable use of AI in the admissions process and for a principled adoption of AI tools in a way that is sustainable for applicants and reviewers in the future.</p>\",\"PeriodicalId\":50929,\"journal\":{\"name\":\"Academic Medicine\",\"volume\":\" \",\"pages\":\"541-546\"},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2025-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12120830/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Academic Medicine\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://doi.org/10.1097/ACM.0000000000005964\",\"RegionNum\":2,\"RegionCategory\":\"教育学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/2/21 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"EDUCATION, SCIENTIFIC DISCIPLINES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Academic Medicine","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1097/ACM.0000000000005964","RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/21 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
Artificial Intelligence Meets Holistic Review: Promises and Pitfalls of Automating the Medical Education Admissions Process.
Abstract: Holistic review has been widely adopted in medical education as a means of promoting equity in the application process and diversity in the medical workforce. Artificial intelligence (AI) is a rapidly emerging technology already having an impact on the medical school and residency application process as students and faculty alike increasingly turn to AI tools to automate some steps in the preparation and evaluation of application materials. While AI may have the potential to improve the holistic admissions process by increasing efficiency and adding some measure of standardization among reviewers, the authors caution that this promise does not come without certain pitfalls. AI models may introduce new sources of bias and amplify existing ones, which, when combined with a lack of transparency regarding their use in the admissions process, may perpetuate the very inequities that holistic review seeks to minimize. The authors call for the medical education community to establish clear regulations to govern the acceptable use of AI in the admissions process and for a principled adoption of AI tools in a way that is sustainable for applicants and reviewers in the future.
期刊介绍:
Academic Medicine, the official peer-reviewed journal of the Association of American Medical Colleges, acts as an international forum for exchanging ideas, information, and strategies to address the significant challenges in academic medicine. The journal covers areas such as research, education, clinical care, community collaboration, and leadership, with a commitment to serving the public interest.