医学教育中的大型语言模型的伦理考虑和基本原则:观点
Li Zhui1, Li Fenghe1, Wang Xuehu1
1Department of Vascular Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Journal of medical Internet research
|July 6, 2024
概括
大型语言模型 (LLM) 在医学教育中提出了伦理挑战,从人工智能幻觉到公平问题. 为负责任的LLM整合提出了一个由8个原则组成的统一的伦理框架.
科学领域:
- 医疗教育 医学教育
- 人工智能伦理学 人工智能伦理学
- 大型语言模型
背景情况:
- 大型语言模型 (LLM) 在医学教育中提供了潜力,但也引发了重大的伦理问题.
- 挑战包括人工智能幻觉,数据偏见,隐私风险,缺乏透明度以及情绪智能和学术诚信的问题.
研究的目的:
- 探索医学教育中LLM应用的伦理挑战.
- 分析现有的AI法律和伦理框架及其局限性.
- 提出一个统一的伦理框架,以负责任地将LLM纳入医学教育.
主要方法:
- 观点文章分析道德和法律挑战.
- 审查现有的AI道德和法律框架.
- 提出基于8个基本原则的新伦理框架.
主要成果:
- 在医学教育中的LLM开发和应用中确定了伦理挑战.
- 突出了目前用于LLM整合的AI框架的局限性.
- 为负责任的LLM使用提出了8个原则的伦理框架.
结论:
- 统一的伦理框架对于安全和负责任的医学教育LLM实施至关重要.
- 拟议的框架确保了技术进步和道德保障之间的平衡.
- 这种方法促进公平,患者安全和公平的教育环境.
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