在医疗保健中用于LLM和AI算法的伦理数据采集
Marta Williams1, Wasie Karim2, Justin Gelman2
1Harvard Medical School, Boston, MA, USA. martawilliams@hms.harvard.edu.
NPJ digital medicine
|December 23, 2024
概括
医疗保健中的人工智能 (AI) 需要患者数据. 伦理数据采集优先考虑自主,所有权和隐私对于人工智能开发和患者信任至关重要.
科学领域:
- 医疗保健技术 医疗保健技术 医疗保健技术
- 医学伦理学医学伦理学
- 数据科学是数据科学.
背景情况:
- 人工智能 (AI) 在医疗保健系统中的整合正在迅速增加.
- 人工智能算法需要大量的患者数据来开发和改进.
- 目前在美国 (选择退出) 和其他地区 (选择加入) 的数据采集模式存在道德考虑.
研究的目的:
- 分析用于医疗保健的患者数据采集的伦理原则.
- 倡导一种优先考虑患者权利的数据采集范式.
- 突出人工智能开发中自主,数据所有权和隐私的重要性.
主要方法:
- 数据采集模型的伦理框架分析.
- 审查目前在美国和其他全球地区的做法.
- 伦理原则和人工智能数据需求的论证综合.
主要成果:
- 美国普遍存在的选择退出系统引发了有关知情同意和患者自主权的担忧.
- 自选模式可能为患者权利提供更强的保护,但可能会影响数据的可用性.
- 需要一种平衡的方法来在道德上获得人工智能进步的数据.
结论:
- 伦理考虑,包括患者自主权,数据所有权和隐私,必须指导医疗保健AI数据采集.
- 优先考虑这些道德原则对于建立患者信任和确保负责任的AI实施至关重要.
- 未来的医疗保健人工智能开发应该采用与强有力的道德标准一致的数据采集策略.
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