{"title":"AI's pivotal impact on redefining stakeholder roles and their interactions in medical education and health care.","authors":"Jayne S Reuben, Hila Meiri, Hadar Arien-Zakay","doi":"10.3389/fdgth.2024.1458811","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial Intelligence (AI) has the potential to revolutionize medical training, diagnostics, treatment planning, and healthcare delivery while also bringing challenges such as data privacy, the risk of technological overreliance, and the preservation of critical thinking. This manuscript explores the impact of AI and Machine Learning (ML) on healthcare interactions, focusing on faculty, students, clinicians, and patients. AI and ML's early inclusion in the medical curriculum will support student-centered learning; however, all stakeholders will require specialized training to bridge the gap between medical practice and technological innovation. This underscores the importance of education in the ethical and responsible use of AI and emphasizing collaboration to maximize its benefits. This manuscript calls for a re-evaluation of interpersonal relationships within healthcare to improve the overall quality of care and safeguard the welfare of all stakeholders by leveraging AI's strengths and managing its risks.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"6 ","pages":"1458811"},"PeriodicalIF":3.2000,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11573760/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in digital health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fdgth.2024.1458811","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial Intelligence (AI) has the potential to revolutionize medical training, diagnostics, treatment planning, and healthcare delivery while also bringing challenges such as data privacy, the risk of technological overreliance, and the preservation of critical thinking. This manuscript explores the impact of AI and Machine Learning (ML) on healthcare interactions, focusing on faculty, students, clinicians, and patients. AI and ML's early inclusion in the medical curriculum will support student-centered learning; however, all stakeholders will require specialized training to bridge the gap between medical practice and technological innovation. This underscores the importance of education in the ethical and responsible use of AI and emphasizing collaboration to maximize its benefits. This manuscript calls for a re-evaluation of interpersonal relationships within healthcare to improve the overall quality of care and safeguard the welfare of all stakeholders by leveraging AI's strengths and managing its risks.
人工智能(AI)有可能彻底改变医学培训、诊断、治疗计划和医疗服务,同时也会带来一些挑战,如数据隐私、过度依赖技术的风险以及批判性思维的保护。本手稿探讨了人工智能和机器学习(ML)对医疗互动的影响,重点关注教师、学生、临床医生和患者。人工智能和 ML 早期纳入医学课程将支持以学生为中心的学习;然而,所有利益相关者都需要接受专门培训,以弥合医疗实践与技术创新之间的差距。这凸显了在人工智能的道德和负责任使用方面开展教育的重要性,并强调通过合作来最大限度地发挥人工智能的优势。本手稿呼吁重新评估医疗保健领域的人际关系,通过利用人工智能的优势和管理其风险,提高医疗保健的整体质量,保障所有利益相关者的福利。