通讯作者: 戴辉, 13889903995@139.com

DOI：10.12201/bmr.202511.00057

Clinical Ethical Governance of Generative Medical Artificial Intelligence (GMAI): A Three-Dimensional Collaborative Pathway and Chinese Practices

• 摘要：目的 / 意义揭示生成式医学人工智能（GMAI）在临床应用中的算法黑箱、责任模糊等核心伦理挑战，构建适配中国医疗场景的伦理治理体系，为平衡 GMAI 技术创新与伦理约束、推动医疗 AI 高质量发展提供理论支撑与实践参考。方法 / 过程基于中国医疗体系、数据生态及文化特点，对比中外 GMAI 治理场景差异；从技术、制度、社会三维度构建协同治理框架，结合患者、医生、技术平台等多主体责任分析，细化联邦学习、分级监管、伦理沙盒等关键实践路径。结果 / 结论提出 “技术安全保障 - 制度动态规制 - 社会多元共治” 的 GMAI 临床伦理三维协同治理方案：技术层通过联邦学习实现数据安全共享，制度层建立 “高风险严控、低风险宽管” 分级监管机制，社会层融入伦理沙盒与多元共治模式。该方案可有效回应中国场景下 GMAI 治理特殊性需求，为全球医疗 AI 伦理治理提供可借鉴的中国实践经验，未来需进一步优化基层数字鸿沟破解及动态责任机制司法衔接等问题。

  关键词： AI医疗伦理；联邦学习；梯度渗透治理；动态责任机制；中国实践; ; ; ; 

   

  Abstract: Purpose/SignificanceThis study aims to address core ethical challenges such as algorithmic black boxes and ambiguous liability in the clinical application of Generative Medical Artificial Intelligence (GMAI), construct an ethical governance system adapted to China’s healthcare context, and provide theoretical support and practical references for balancing GMAI technological innovation with ethical constraints to promote the high-quality development of medical AI.Methods/ProcessBased on the characteristics of China’s healthcare system, data ecosystem, and cultural context, this paper compares differences in GMAI governance scenarios between China and other countries. A three-dimensional collaborative governance framework (technology, institution, and society) is established, with a detailed analysis of the responsibilities of multiple stakeholders including patients, physicians, and technology platforms. Key practical pathways such as federated learning, hierarchical supervision, and ethical sandboxes are elaborated.Results/ConclusionsA three-dimensional collaborative governance scheme for GMAI clinical ethics is proposed: technological security guarantee - dynamic institutional regulation - multi-stakeholder social governance. At the technical level, federated learning enables secure data sharing; at the institutional level, a hierarchical supervision mechanism of strict control for high-risk applications and flexible management for low-risk ones is established; at the social level, ethical sandboxes and multi-stakeholder governance models are integrated. This scheme effectively responds to the specific needs of GMAI governance in the Chinese context and provides replicable Chinese practices for global medical AI ethical governance. Future efforts should focus on bridging the digital divide at the grassroots level and optimizing the judicial connection of dynamic liability mechanisms.

  Key words: AI medical ethics; federal learning; gradient penetration governance; dynamic responsibility mechanism; Chinese practice

  提交时间：2025-11-20

  版权声明：作者本人独立拥有该论文的版权，预印本系统仅拥有论文的永久保存权利。任何人未经允许不得重复使用。
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• 序号	提交日期	编号	操作
  1	2025-08-30	10.12201/bmr.202511.00057V1	下载

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