在AI辅助医疗保健的社会技术模拟案例研究中,将算法公平性和公平结果连接起来
Emma A M Stanley1,2,3,4, Roger Y Tsang5,6, Haley Gillett7,8,9,10
1Biomedical Engineering Graduate Program, University of Calgary, Calgary, Alberta, Canada. emma.stanley@ucalgary.ca.
Nature communications
|December 19, 2025
概括
人工智能 (AI) 医疗保健工具中的算法公平性不能保证公平的患者结果. 在临床AI部署中,社会技术因素对于理解真正的公平性至关重要.
科学领域:
- 医疗保健 人工智能 (AI)
- 临床决策支持系统 临床决策支持系统
- 健康 公平与公平 公平与公平
背景情况:
- 人工智能 (AI) 为改善医疗保健提供提供了巨大的潜力.
- 对临床人工智能系统偏见的担忧,在实践中提出了关于公平性的关键问题.
- 现有的研究往往忽视了人工智能性能差异与现实世界的社会技术结果之间的联系.
研究的目的:
- 研究统计算法公平性定义的转化为长期患者结果.
- 分析人工智能辅助乳腺癌查对死亡率和社会经济差异的影响.
- 探索临床医生对人工智能的依赖和患者获得医疗保健对公平结果的影响.
主要方法:
- 开发了一个基于模拟的方法来在临床AI中模拟公平性.
- 评估了四个不同的统计公平标准.
- 纳入的变量,如临床医生对人工智能的依赖和患者获得护理的机会.
主要成果:
- 算法公平度指标并不能自动保证公平的健康结果.
- 该研究确定了人工智能公平性,临床决策和患者访问之间的复杂相互作用.
- 观察到,死亡率的社会经济差异受到这些因素的影响.
结论:
- 对于医疗保健AI来说,对算法公平性的纯粹技术方法是不够的.
- 整合社会技术视角对于全面了解临床AI中的公平至关重要.
- 未来的研究必须考虑人工智能部署的更广泛背景,以实现公平的医疗保健.
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