From the American College of Radiology Data Science Institute, Reston, Va (J.R.G.); Department of Radiology, National Jewish Health, 3401 Shore Rd, Fort Collins, CO 80524 (J.R.G.); Mercy University Hospital, Cork, Ireland (A.B.); University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); MIT, Department of Linguistics and Philosophy, Cambridge, Mass (J.S.); Netherlands Cancer Institute, Amsterdam, the Netherlands (E.R.); Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Alberta, Canada (J.L.J.); Radiology Department-Mayo Clinic, Rochester, Minn (S.G.L.); Lahey Hospital & Medical Center, Burlington, Mass (A.B.K.); Pelvic Pain Support Network, Poole, UK (J.B.); General Counsel, American College of Radiology, Reston, Va (W.F.S.); Center of Law and Internet, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands (R.v.d.H.v.G.); Department of Radiology, University Medical Center, Freiburg, Germany (E.K.); Department of Interventional Radiology, Oregon Health & Science University, Portland, Ore (J.W.G.); Department of Radiology and Imaging Sciences, Emory University, Atlanta, Ga (J.W.G., N.MS.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (T.S.C.); Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah (M.B.M.); Centre de Recherche du Centre Hospitalier de L'Université de Montréal, Quebec, Canada (A.T.); and Department of Radiology and Biomedical Imaging, UCSF, San Francisco, Calif (M.K.).
Radiology. 2019 Nov;293(2):436-440. doi: 10.1148/radiol.2019191586. Epub 2019 Oct 1.
This is a condensed summary of an international multisociety statement on ethics of artificial intelligence (AI) in radiology produced by the ACR, European Society of Radiology, RSNA, Society for Imaging Informatics in Medicine, European Society of Medical Imaging Informatics, Canadian Association of Radiologists, and American Association of Physicists in Medicine. AI has great potential to increase efficiency and accuracy throughout radiology, but it also carries inherent pitfalls and biases. Widespread use of AI-based intelligent and autonomous systems in radiology can increase the risk of systemic errors with high consequence and highlights complex ethical and societal issues. Currently, there is little experience using AI for patient care in diverse clinical settings. Extensive research is needed to understand how to best deploy AI in clinical practice. This statement highlights our consensus that ethical use of AI in radiology should promote well-being, minimize harm, and ensure that the benefits and harms are distributed among stakeholders in a just manner. We believe AI should respect human rights and freedoms, including dignity and privacy. It should be designed for maximum transparency and dependability. Ultimate responsibility and accountability for AI remains with its human designers and operators for the foreseeable future. The radiology community should start now to develop codes of ethics and practice for AI that promote any use that helps patients and the common good and should block use of radiology data and algorithms for financial gain without those two attributes. This article is a simultaneous joint publication in , , , and . Published under a CC BY-NC-ND 4.0 license.
这是一份关于放射学人工智能（AI）伦理的国际多学会声明的精简摘要，由美国放射学会（ACR）、欧洲放射学会（ESR）、北美放射学会（RSNA）、医学影像学信息学会（SIIM）、欧洲医学影像学信息学会（CERS）、加拿大放射学家协会（CAR）和美国医学物理学家协会（AAPM）共同制定。AI 具有极大提高放射学效率和准确性的潜力，但也存在固有缺陷和偏见。在放射学中广泛使用基于 AI 的智能和自主系统可能会增加具有高后果的系统性错误风险，并凸显出复杂的伦理和社会问题。目前，在各种临床环境中使用 AI 进行患者护理的经验有限。需要进行广泛的研究，以了解如何在临床实践中最佳地部署 AI。本声明强调了我们的共识，即放射学中 AI 的伦理使用应促进福祉、将伤害最小化，并确保利益和危害在利益相关者之间以公正的方式分配。我们认为 AI 应尊重人权和自由，包括尊严和隐私。它应设计为具有最大的透明度和可靠性。在可预见的未来，AI 的最终责任和问责制仍由其人类设计者和操作人员承担。放射学社区应立即开始制定促进有助于患者和共同利益的任何使用的 AI 道德规范和实践准则，并阻止在没有这两个属性的情况下使用放射学数据和算法谋取经济利益。本文是在 、 、 和 同时联合发表的。根据 CC BY-NC-ND 4.0 许可证发布。
