ISSN 2097-6054(网络) ISSN 1672-9234(印刷) CN 11-5289/R
主管:中国科学技术协会 主办:中华护理学会
出版:中华护理杂志社
收录:中国科学引文数据库(CSCD)来源期刊
   中国期刊全文数据库
   中国核心期刊(遴选)数据库
   Scopus

中华护理教育 ›› 2026, Vol. 23 ›› Issue (2): 165-170.doi: 10.3761/j.issn.1672-9234.2026.02.006

• 专题策划——人工智能赋能护理教育 • 上一篇    下一篇

大语言模型在护理教育中应用的伦理挑战与应对路径

练璇1(), 于颖1, 叶萌1,*(), 沈小平1, 纪海燕2, 王凤2   

  1. 1.上海思博职业技术学院 上海市 201399
    2.上海交通大学医学院附属第九人民医院 上海市 200011
  • 收稿日期:2025-06-18 出版日期:2026-02-15 发布日期:2026-02-11
  • 通讯作者: * 叶萌,E-mail:yemeng@sipo.sicfl.edu.cn
  • 作者简介:练璇:女,硕士,助教,E-mail:lianxuan2020@foxmail.com
  • 基金资助:
    上海高职高专医药健康类专业教指委教学研究项目立项(yyjk-2024-002)

Ethical challenges and governance approaches of applying large language models in nursing education

LIAN Xuan1(), YU Ying1, YE Meng1,*(), SHEN Xiaoping1, JI Haiyan2, WANG Feng2   

  1. 1. Shanghai Sipo Polytechnic,Shanghai 201399,China
    2. Shanghai Ninth People’s Hospital,Shanghai JiaoTong University School of Medicine,Shanghai 200011,China
  • Received:2025-06-18 Online:2026-02-15 Published:2026-02-11
  • Contact: * YE Meng,E-mail:yemeng@sipo.sicfl.edu.cn
  • Supported by:
    Approved Teaching Research Project of the Shanghai Teaching Guidance Committee for Medical and Health Majors in Higher Vocational Colleges(yyjk-2024-002)

摘要:

以大语言模型(large language models,LLMs)为基础的生成式人工智能(generative artificial intelligence,GenAI)的出现,标志着人工智能技术取得突破性进展。研究表明,将人工智能(artificial intelligence,AI)技术引入护理教育实践,可以提升教师的教学效率和学生的学习体验。然而,AI的广泛应用所伴随的核心伦理挑战亟待系统性探讨。该研究梳理LLMs在护理教育中应用时可能引发的多种伦理挑战(包括数据隐私与安全问题、算法偏见与教育公平性问题、知情同意与透明度缺失、责任归属模糊与问责困境、人文关怀与情感联结缺位,以及诚信侵蚀与能力评估失真)的基础上,提出涵盖数据安全强化、偏见消减、知情同意落实、责任明确、人文关怀及诚信建设加强等的多元化应对路径,旨在为护理教育工作者合理、安全、有效地应用LLMs提供实践指引,并助力AI技术与护理教育实现伦理兼容的发展提供参考。

关键词: 人工智能, 大语言模型, 教育, 护理, 伦理学, 护理, 治理路径

Abstract:

The emergence of generative artificial intelligence(GenAI) based on large language models(LLMs) marks a breakthrough in artificial intelligence technology. Studies have shown that integrating AI technology into nursing education practice can significantly enhance teachers’ teaching efficiency and improve students’ learning experiences. However,the core ethical challenges accompanying the widespread application of AI urgently require systematic investigation. This study reviews the various ethical challenges that may arise when LLMs are applied in nursing education practice,including data privacy and security risks,algorithm bias and educational equity concerns,insufficient informed consent and transparency,ambiguous liability and accountability dilemmas,absence of humanistic care and emotional connection,and erosion of academic integrity and distortions in competency assessment. Based on this,this study proposes a diversified governance path covering data security safeguards,bias mitigation strategies,standardized informed consent,clear liability delineation,strengthened humanistic care,and integrity enhancement measures. The research results can provide practical guidance for nursing educators to reasonably,safely,and effectively apply LLMs,and offer theoretical references for promoting the ethically aligned development of artificial intelligence technology and nursing education.

Key words: Artificial Intelligence, Large Language Models, Education, Nursing, Ethics, Nursing, Governance Pathways