[人工智能辅助医疗保健中的法律风险评估和预防]
Jinming Yang1,2, Na Wang1, Yexun Hu1
1( 610041) West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China.
概括
医疗保健中的人工智能 (AI) 引入了新的法律风险,包括偏见和数据安全问题. 解决这些问题需要算法审查,强大的数据管理,以及人工智能辅助医疗服务的明确责任框架.
科学领域:
- 法律研究 法律研究
- 医疗信息学 医疗信息学
- 人工智能伦理学 人工智能伦理学
背景情况:
- 将大型语言模型和生成人工智能 (AI) 等先进技术集成到医疗保健中,带来了新的法律挑战.
- 现有的法律框架受到人工智能在医疗环境中带来的独特风险的压力,包括算法偏见和数据安全漏洞.
研究的目的:
- 识别和分析与人工智能辅助医疗相关的新兴法律风险.
- 提出一项全面的法律战略,以减轻这些风险,并确保在卫生部门负责任地实施人工智能.
主要方法:
- 在人工智能辅助医疗保健中分析算法偏见,数据安全,数据财产权和责任归因引起的法律风险.
- 审查当前的法律先例和对医疗保健中人工智能的潜在立法需求.
主要成果:
- 由于算法偏见和数据安全漏洞,人工智能辅助医疗保健面临侵犯人格权利的风险.
- 关于健康数据财产权的争议以及对人工智能相关的医疗伤害的责任分配的不确定性是严重的担忧.
- 该研究强调了需要主动的法律和道德治理结构.
结论:
- 建立算法审查机制对于消除人工智能医疗应用中的偏见至关重要.
- 实施全生命周期数据管理系统对于确保数据安全和通过定义的层次权利和授权规则解决财产权纠纷至关重要.
- 对于人工智能引起的医疗伤害,需要建立一个基于特定错误的合理赋予侵权责任的框架.
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