在医疗保健中找到对人工智能信任的共识:国际专家小组的建议
Georg Starke1,2, Felix Gille3,4, Alberto Termine1,2,5
1Institute for History and Ethics of Medicine, Technical University of Munich, Munich, Germany.
Journal of medical Internet research
|February 19, 2025
概括
在医疗保健中建立对人工智能 (AI) 的信任需要了解上下文因素并优先考虑沟通. 这一共识分析为未来关于人工智能对医疗保健应用的信任研究提供了建议.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能的人工智能
- 人与计算机的交互
背景情况:
- 人工智能 (AI) 在医疗保健中的整合正在推动数字化转型.
- 用户信任度低,对人工智能信任定义缺乏专家共识,阻碍了采用.
- 解决信任问题对于实现AI在各种医疗领域的潜力至关重要.
研究的目的:
- 在医疗保健中建立第一个基于共识的对人工智能信任的分析.
- 为医疗保健应用定义对人工智能的信任,使人们能够讨论人类-人工智能交互场景.
- 促进跨学科专家之间的共同理解.
主要方法:
- 采用了框架分析和与18名国际专家一起进行的三步共识过程.
- 包括计算机科学,医学,技术哲学,伦理学和社会科学的专家.
- 在5个案例研究中采用了同步研讨会和反复的异步改进信任概念.
主要成果:
- 确定了信任的关键上下文因素:人工智能系统环境,参与者和框架.
- 分析了信任的原因和影响,强调了需要多学科,以人为中心和以技术为中心的方法.
- 强调沟通和积极的用户体验是信任的至关重要,以及监管和设计特征.
结论:
- 倡导对人工智能对医疗保健的信任有精细,细微的概念理解.
- 综合了案例研究的见解,为未来关于在医疗保健中信任人工智能的讨论提供了基础.
- 为未来研究对对人工智能医疗保健应用的信任提出了具体建议.
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