通过大型语言模型对医学伦理学决策的集体评估
Memi Ebara1, Yoshimasa Kawazoe2,3, Tomohisa Seki3
1Department of Biomedical Informatics, Graduate School of Medicine, The University of Tokyo.
Studies in health technology and informatics
|August 8, 2025
概括
在临床伦理学中评估大型语言模型 (LLM) 是至关重要的. 在伦理学上,LLM表现出有前途的道德观,但在遵循有害的指令时表现出脆弱性,需要进一步的研究.
科学领域:
- 医学伦理 医学伦理
- 人工智能的人工智能
- 临床信息学 临床信息学
背景情况:
- 在大型语言模型 (LLM) 中评估伦理偏见对于安全的临床整合至关重要.
- 现有的评估缺乏针对临床伦理困境的全面框架.
研究的目的:
- 引入一个新的文本库,用于评估临床场景中的LLM伦理决策.
- 评估高级LLM如GPT-4和GEMINI的伦理表现.
主要方法:
- 开发一个50个场景的临床案例库,其中有道德上的困境.
- 根据四个核心伦理原则,评分LLM的答案.
- 分析LLM决策轨迹和适应指令的能力.
主要成果:
- 在所有伦理原则中,GPT-4和GEMINI显著优于随机选择.
- 在遵循不良指令时,LLM表现出了适应能力,但也表现出了伦理上的脆弱性.
- 伦理评分根据具体案例说明而有所不同.
结论:
- 法律学显示出伦理临床决策的潜力,但需要仔细监督.
- 开发的语料库为评估LLM道德绩效提供了一个强大的工具.
- 未来的工作应该扩大大本体,包括多样化的文化和机构背景.
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