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人工智能辅助医疗保健中的法律风险评估与防范

[Legal Risk Assessment and Prevention in Artificial Intelligence-Assisted Health Care].

作者信息

Yang Jinming, Wang Na, Hu Yexun, Zhang Wei

机构信息

( 610041) West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China.

"+" ( 610041) Med-X Center for Informatics, Sichuan University, Chengdu 610041, China.

出版信息

Sichuan Da Xue Xue Bao Yi Xue Ban. 2025 Jan 20;56(1):143-148. doi: 10.12182/20250160301.

Abstract

With the wide application of new technologies such as large language models and generative artificial intelligence (AI) in the health care sector, artificial intelligence-assisted health care is confronted with new forms of legal risks. The algorithmic bias and data security issues in AI-assisted health care have given rise to risks of infringement on general personality rights and specific personality rights. The handling of health care data and the distribution of profits from health care data have spawned disputes over data property rights. Moreover, there will also be risks of uncertainties in the attribution of liability for medical harms once AI technology becomes deeply embedded in health care. Based on the emerging changes in the legal risks associated with AI-assisted health care, it is necessary to establish a corresponding algorithm review mechanism to eliminate algorithm biases, improve the data management system through a whole-life cycle approach to ensure data security, define hierarchical data property rights and establish authorization rules to resolve property rights disputes, and reasonably assign tort liability for medical harms based on specific faults.

摘要

随着大语言模型和生成式人工智能(AI)等新技术在医疗保健领域的广泛应用,人工智能辅助医疗保健面临着新形式的法律风险。人工智能辅助医疗保健中的算法偏见和数据安全问题引发了侵犯一般人格权和特定人格权的风险。医疗保健数据的处理和医疗保健数据利润的分配引发了数据产权纠纷。此外,一旦人工智能技术深度嵌入医疗保健领域,医疗损害责任的归属也将存在不确定性风险。基于人工智能辅助医疗保健相关法律风险的新变化,有必要建立相应的算法审查机制以消除算法偏见,通过全生命周期方法改进数据管理系统以确保数据安全,界定分层数据产权并建立授权规则以解决产权纠纷,并根据具体过错合理分配医疗损害的侵权责任。

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