人工智能与医学责任：平衡安全与创新。
Artificial Intelligence and Liability in Medicine: Balancing Safety and Innovation.
机构信息
Perelman School of Medicine, University of Pennsylvania.
Department of Internal Medicine, University of Pennsylvania.
出版信息
Milbank Q. 2021 Sep;99(3):629-647. doi: 10.1111/1468-0009.12504. Epub 2021 Apr 6.
Abstract
Policy Points With increasing integration of artificial intelligence and machine learning in medicine, there are concerns that algorithm inaccuracy could lead to patient injury and medical liability. While prior work has focused on medical malpractice, the artificial intelligence ecosystem consists of multiple stakeholders beyond clinicians. Current liability frameworks are inadequate to encourage both safe clinical implementation and disruptive innovation of artificial intelligence. Several policy options could ensure a more balanced liability system, including altering the standard of care, insurance, indemnification, special/no-fault adjudication systems, and regulation. Such liability frameworks could facilitate safe and expedient implementation of artificial intelligence and machine learning in clinical care.
摘要
政策要点 随着人工智能和机器学习在医学中的日益融合，人们担心算法不准确可能导致患者受伤和医疗责任。虽然之前的工作重点是医疗事故，但人工智能生态系统除了临床医生之外，还涉及多个利益相关者。当前的责任框架不足以鼓励人工智能的安全临床实施和颠覆性创新。一些政策选择可以确保更平衡的责任体系，包括改变护理标准、保险、赔偿、特别/无过错裁决制度和监管。这种责任框架可以促进人工智能和机器学习在临床护理中的安全和迅速实施。
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