From the World Wide Web to AI: Why We Must Learn From Our Past to Transform the Future of Medical Education.

IF 5.3 2区 教育学 Q1 EDUCATION, SCIENTIFIC DISCIPLINES
Lisa D Howley, Alison J Whelan
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引用次数: 0

Abstract

Abstract: In 1989, the World Wide Web was proposed as a practical solution to connect scientists globally. That innovation later transformed how knowledge was accessed and shared across all sectors, including health care and education. While initially met with skepticism, the Web ultimately revolutionized broad sectors including health care and education. The Web reimagined medical education and enabled digital learning platforms, open-access resources, and new forms of collaboration. A new paradigm, artificial intelligence (AI)-particularly generative AI, is now poised to redefine how knowledge is created, synthesized, and applied in medical education and health care.This commentary draws parallels between medical educators' initial resistance to the Web and current hesitations with AI. Current concerns are echoing our past, such as misinformation and lack of credibility; technology replacing traditional teaching; inequity in access to the new technologies; and doubts about learning efficacy. We argue that these lessons learned from the Web era offer important insights into the ways AI in and for medical education will benefit our community.The authors build on insights and recommendations from the November 2024 Josiah Macy Jr. Foundation conference on AI in medical education, emphasizing the urgent need for a national set of AI competencies for and in medical education. These competencies should include knowledge of AI tools, their evaluation and ethical use, and their integration into clinical and educational processes.Ultimately, an AI-drive future is not predetermined-it is ours to shape. By learning from the past, medical educators can more effectively lead the ethical and equitable adoption of AI, ensuring it strengthens CBME and enhances the preparation of future physicians. This work represents both a challenge and an exciting opportunity to define the next chapter in the evolution of medical education.

从万维网到人工智能:为什么我们必须从过去学习以改变医学教育的未来。
摘要:1989年,万维网作为一种连接全球科学家的实用解决方案被提出。这一创新后来改变了包括卫生保健和教育在内的所有部门获取和共享知识的方式。虽然最初受到怀疑,但网络最终彻底改变了包括医疗保健和教育在内的广泛领域。网络重新构想了医学教育,使数字学习平台、开放获取资源和新的协作形式成为可能。一种新的范式,人工智能(AI),特别是生成式人工智能,现在正准备重新定义如何在医学教育和卫生保健中创造、合成和应用知识。这篇评论将医学教育者最初对网络的抵制与目前对人工智能的犹豫相提并论。当前的担忧与我们过去的担忧如出一辙,比如错误信息和缺乏可信度;技术取代传统教学;获得新技术的机会不平等;以及对学习效能的怀疑。我们认为,这些从网络时代汲取的经验教训,为人工智能在医学教育中的应用以及为医学教育服务的方式提供了重要的见解,将使我们的社区受益。作者以2024年11月Josiah Macy Jr.基金会关于医学教育中的人工智能会议的见解和建议为基础,强调迫切需要在医学教育中建立一套国家人工智能能力。这些能力应包括人工智能工具的知识,它们的评估和道德使用,以及它们与临床和教育过程的整合。最终,人工智能驱动的未来不是预先确定的,而是由我们来塑造的。通过向过去学习,医学教育工作者可以更有效地领导道德和公平地采用人工智能,确保它加强CBME并加强对未来医生的准备。这项工作既是一个挑战,也是一个令人兴奋的机会,可以定义医学教育发展的下一个篇章。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Academic Medicine
Academic Medicine 医学-卫生保健
CiteScore
7.80
自引率
9.50%
发文量
982
审稿时长
3-6 weeks
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.
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