通过认知和情感镜头评估主管与实习生的信任观点:人工智能对反中偏见的调查
Brian C Gin1, Olle Ten Cate2,3, Patricia S O'Sullivan3,4
1Department of Pediatrics, University of California San Francisco, 550 16th St Floor 4, UCSF Box 0110, San Francisco, CA, 94158, USA. brian.gin@ucsf.edu.
Advances in health sciences education : theory and practice
|February 22, 2024
概括
这项研究使用了大型语言模型来分析医疗反,发现实习生记录的信任评级更高,但使用了更负面的语言. 人口偏见影响了实习生语言,而不是委托评级,影响了角色同化.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 信任的心理学信任的心理学
背景情况:
- 委托框架将医疗评估从能力转变为独立的临床任务准备.
- 在委托决策中,受训者和主管的信任谈判至关重要.
- 了解影响这些谈判的认知,情感和人口因素至关重要.
研究的目的:
- 检查临床委托的实习生-监督员信任谈判中的认知和情感因素.
- 在反文档中调查与实习生人口特征相关的潜在偏见.
- 分析大型语言模型如何在反对话中评估情绪和主题.
主要方法:
- 对24,187个医疗实习生-监督员反对话的文档分析与信任评级.
- 适应大型语言模型 (LLM) 用于定性主题识别和定量情绪分析.
- 在实习生和主管反文档之间比较主题和情绪.
主要成果:
- 监督人员的反主要集中在患者的演示;学员的反更广泛,包括表现和个人品质.
- 实习生使用了更多的负面语言 (较低的积极情绪),但报告的信任评级高于主管.
- 在实习生语言中观察到人口偏见 (男性和代表性较低的少数群体的积极情绪),但在信任评级中没有.
结论:
- 偏见对实习生反中的情感语言的影响比经验丰富的信任水平更大.
- 信任评级本身似乎没有反映观察到的人口偏差.
- 缓解这些基于语言的偏见对于实习生融合和信任发展至关重要.
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