治理医疗人工智能的商业行为者的生态系统方法
1Stanford Center for Biomedical Ethics, Stanford, CA.
概括
美国对医疗保健人工智能 (AI) 的监管环境面临着过度依赖自我监管和缺乏透明度等挑战. 要改善治理并确保人工智能的安全性和有效性,需要采用涉及各种利益相关者的生态系统方法.
科学领域:
- 卫生保健人工智能治理
- 监管科学
- 医疗技术评估
背景情况:
- 人工智能 (AI) 在医疗领域的日益普及,需要对美国的监管框架进行评估.
- 目前的治理模式与开发人员的知识差距,与人工智能相关的危害不清楚的责任以及安全性和有效性的证据不足而扎.
研究的目的:
- 批判性地评估当前美国医疗人工智能监管环境的有效性.
- 在医疗保健领域管理人工智能应用的挑战.
- 提出基于生态系统的方法来加强医疗保健人工智能治理.
主要方法:
- 对美国现有的医疗人工智能监管挑战的分析.
- 确定关键利益相关者及其在人工智能治理中的潜在角色.
- 倡导生态系统方法来开发治理解决方案.
主要成果:
- 关键的挑战包括过度依赖自我监管,开发者缺乏监管意识,对人工智能危害的不确定的责任以及评估人工智能的安全性和有效性的有限透明度.
- 建议采用生态系统方法来解决这些治理缺陷.
- 针对民间社会,资助者,购买者和支付人的具体行动是为了推进人工智能治理.
结论:
- 美国目前的监管体系不足以有效地管理医疗人工智能.
- 为了提高医疗人工智能的透明度和独立评估,必须采用多方利益相关者的生态系统方法.
- 公民社会,资助者,购买者和支付者可以在填补监管缺口和确保在医疗保健中负责任地部署人工智能方面发挥重要作用.
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