医疗人工智能的伦理悖论及应对策略
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陕西省科技厅重点研发计划(2025GH-YBXM-032).


Ethical paradoxes and coping strategies of medical artificial intelligence
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Supported by Key Research and Development Project of Science and Technology Department of Shaanxi Province (2025GH-YBXM-032).

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    摘要:

    近年来,人工智能(AI)技术在医疗领域的应用日益广泛。研究显示医疗AI不仅能提升诊疗效率,还能够进行个体化健康管理、优化医疗资源分配,展现出巨大潜力。然而,医疗AI在“技术赋能”的同时,也伴随着一系列伦理悖论,主要体现为技术创新与人文价值守护的冲突。本文基于意大利科技哲学和伦理学家Floridi提出的AI伦理框架,系统分析了医疗AI在尊重自主、不伤害、行善、公平性、可解释性五大核心伦理原则上的悖论表现,从技术层面、社会层面、哲学层面解释了这些悖论的成因,并提出以下应对策略:一是提高可解释性、算法审计技术、差异化数据采集技术、隐私保护技术、人类监督和控制技术,加强技术治理;二是完善伦理规制,建立适应技术发展节奏的动态伦理治理机制、分级分类管理模式、负责任创新机制,进一步完善数据安全、算法伦理责任认定等方面的法律法规;三是建立全球协同体系,构建医疗AI全球性治理框架,建立统一的开发与应用标准,促进跨国政策协调与技术标准对接。

    Abstract:

    In recent years, artificial intelligence (AI) has been widely used in the medical field. Research shows that medical AI can not only improve diagnosis and treatment efficiency, but also enable personalized health management and optimize the allocation of medical resources, demonstrating enormous potential. However, while “technology empowers”, medical AI is also accompanied by a series of ethical paradoxes, mainly manifested as the conflict between technological innovation and the protection of humanistic value. Based on the AI ethical framework proposed by Italian philosophy and ethicist Floridi, this paper systematically analyzes paradoxical manifestations of medical AI and the possible causes in 5 core ethical principles: respecting autonomy, not harming, doing good, fairness, and interpretability. It also explains the causes of these paradoxes from technical, social, and philosophical levels, and puts forward the following coping strategies: first, to improve explainability, algorithm audit technology, differentiated data collection technology, privacy protection technology, and human supervision and control technology, strengthening technical governance; second, to improve ethical regulations and establish a dynamic ethical governance mechanism that adapts to the pace of technological development, a hierarchical management model, and a responsible innovation mechanism, further improving the legal and regulatory frameworks in terms of data security, algorithm ethical responsibility recognition, etc; and third, to establish a global collaborative system, build a global governance framework for medical AI, establish unified development and application standards, and promote cross-border policy coordination and technical standard docking.

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  • 收稿日期:2025-06-03
  • 最后修改日期:2025-07-03
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  • 在线发布日期: 2025-08-19
  • 出版日期: 2025-08-20
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