Crowe Byron, Shah Shreya, Teng Derek, Ma Stephen P, DeCamp Matthew, Rosenberg Eric I, Rodriguez Jorge A, Collins Benjamin X, Huber Kathryn, Karches Kyle, Zucker Shana, Kim Eun Ji, Rotenstein Lisa, Rodman Adam, Jones Danielle, Richman Ilana B, Henry Tracey L, Somlo Diane, Pitts Samantha I, Chen Jonathan H, Mishuris Rebecca G
Division of General Internal Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Harvard Medical School, Boston, MA, USA.
J Gen Intern Med. 2025 Feb;40(3):694-702. doi: 10.1007/s11606-024-09102-0. Epub 2024 Nov 12.
Generative artificial intelligence (generative AI) is a new technology with potentially broad applications across important domains of healthcare, but serious questions remain about how to balance the promise of generative AI against unintended consequences from adoption of these tools. In this position statement, we provide recommendations on behalf of the Society of General Internal Medicine on how clinicians, technologists, and healthcare organizations can approach the use of these tools. We focus on three major domains of medical practice where clinicians and technology experts believe generative AI will have substantial immediate and long-term impacts: clinical decision-making, health systems optimization, and the patient-physician relationship. Additionally, we highlight our most important generative AI ethics and equity considerations for these stakeholders. For clinicians, we recommend approaching generative AI similarly to other important biomedical advancements, critically appraising its evidence and utility and incorporating it thoughtfully into practice. For technologists developing generative AI for healthcare applications, we recommend a major frameshift in thinking away from the expectation that clinicians will "supervise" generative AI. Rather, these organizations and individuals should hold themselves and their technologies to the same set of high standards expected of the clinical workforce and strive to design high-performing, well-studied tools that improve care and foster the therapeutic relationship, not simply those that improve efficiency or market share. We further recommend deep and ongoing partnerships with clinicians and patients as necessary collaborators in this work. And for healthcare organizations, we recommend pursuing a combination of both incremental and transformative change with generative AI, directing resources toward both endeavors, and avoiding the urge to rapidly displace the human clinical workforce with generative AI. We affirm that the practice of medicine remains a fundamentally human endeavor which should be enhanced by technology, not displaced by it.
生成式人工智能(生成式AI)是一项新技术,在医疗保健的重要领域可能有广泛应用,但对于如何在生成式AI的前景与采用这些工具产生的意外后果之间取得平衡,仍存在严重问题。在本立场声明中,我们代表普通内科协会就临床医生、技术专家和医疗保健组织如何使用这些工具提供建议。我们关注医疗实践的三个主要领域,临床医生和技术专家认为生成式AI将在这些领域产生重大的直接和长期影响:临床决策、卫生系统优化以及医患关系。此外,我们强调了针对这些利益相关者的最重要的生成式AI伦理和公平性考量。对于临床医生,我们建议以类似于其他重要生物医学进展的方式对待生成式AI,批判性地评估其证据和效用,并谨慎地将其纳入实践。对于为医疗保健应用开发生成式AI的技术专家,我们建议进行重大的思维转变,摒弃临床医生将“监督”生成式AI的期望。相反,这些组织和个人应该以对临床工作人员同样高的标准要求自己和他们的技术,并努力设计高性能、经过充分研究的工具,以改善护理并促进治疗关系,而不仅仅是提高效率或市场份额。我们还建议与临床医生和患者建立深入且持续的合作关系,作为这项工作中必要的合作伙伴。对于医疗保健组织,我们建议在使用生成式AI时,将渐进式变革和变革性变革相结合,为这两项工作都投入资源,并避免急于用生成式AI迅速取代人类临床工作人员。我们坚信,医学实践仍然是一项 fundamentally human endeavor,应该通过技术得到加强,而不是被技术取代。 (注:原文中“fundamentally human endeavor”直译为“根本上是人类的努力”,这里根据语境意译为“本质上是人的事业”更通顺,但需注意与原文保持一致,所以保留了英文表述。)