在医疗保健中的道德参与和脱离 开发人工智能
Ariadne A Nichol1, Meghan Halley1, Carole Federico1
1Center for Biomedical Ethics, Stanford University School of Medicine, Stanford, California, USA.
AJOB empirical bioethics
|April 8, 2024
概括
医疗保健中的机器学习 (ML) 开发人员对减轻潜在危害的看法各不相同. 大多数人表达了道德上的承诺,但很少有人完全接受责任,强调了对伦理ML发展的指导的需要.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 生物伦理学生物伦理学
背景情况:
- 机器学习 (ML) 在医疗保健中越来越多地使用,对患者和系统构成潜在风险.
- 监管机构建议将减轻危害的责任转移到ML开发人员身上.
- 了解开发人员对其道德义务的看法至关重要.
研究的目的:
- 探索医疗保健ML开发人员对减轻潜在危害的责任的看法.
- 识别促进者和阻碍伦理ML发展的障碍.
主要方法:
- 进行了40个半结构化采访,与美国的开发者进行了医疗保健的ML预测分析.
主要成果:
- 开发人员对责任的看法各不相同,观察到道德上的参与和脱离.
- 70%的参与者表现出道德承诺,但往往只是意识,而不是完全接受责任.
- 确定了八种类型的道德脱离,旨在尽量减少伤害或转移责任.
结论:
- 研究结果表明,伦理ML开发存在促进者和障碍.
- 仅仅依赖开发者责任的监管方法可能在没有教育和指导的情况下是不够的.
- 需要进一步的支持来鼓励ML开发人员的道德参与,并阻止ML开发人员的脱离.
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