医疗失误责任在大型语言模型人工智能:法律审查和政策建议
David O Shumway1, Hayes J Hartman2
1Keesler Medical Center, Keesler Air Force Base, Biloxi, MS, USA.
Journal of osteopathic medicine
|January 31, 2024
概括
像大型语言模型 (LLM) 一样,生成性人工智能 (AI) 可能会改变医学,但会引发责任问题. 法律先例表明,临床医生和人工智能开发人员在医疗失误方面负有共同责任.
科学领域:
- 医疗保健法律 医疗保健法律
- 人工智能在医学中的应用
- 医疗不当行为 医疗不当行为
背景情况:
- 生成型大语言模型 (LLM) 代表了人工智能 (AI) 的重大进步,在医疗保健领域具有变革潜力.
- 将LLM AI纳入医疗决策引发了有关不良结果责任的重大担忧.
- 目前对人工智能的医疗失误责任的法律框架是分散的和不断发展的.
研究的目的:
- 分析在医学实践中使用LLM AI的临床医生潜在的法律漏洞.
- 审查有关第三方医疗指导的现有判例及其对AI的适用性.
- 为管理人工智能相关的医疗失误风险提出政策建议.
主要方法:
- 审查与第三方医疗指导有关的过去的判例法.
- 对当前管理人工智能和医疗失误责任的法规进行分析.
- 讨论涉及医疗保健中人工智能的类似情况的法律先例.
主要成果:
- 美国尚未对涉及LLM AI的医疗失职案件作出裁决.
- 存在足够的法律先例来预测未来关于LLM AI的不当行为诉讼.
- 确定了使用LLM AI工具的临床医生可能面临法律风险的领域.
结论:
- 需要采取积极的政策措施来解决与医疗保健中的LLM AI相关的责任问题.
- 建议包括FDA对算法透明度的强制执行和AI工具的严格验证.
- 倡导侵权纠纷改革,以建立医生和LLM开发者之间的共同责任至关重要.
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