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人们屈从于AI的道德建议,但不是盲目地这样做

Ethan Landes¹, Kathryn B Francis², Jim A C Everett¹

¹University of Kent, United Kingdom.

|March 8, 2026

概括

人们在道德困境中被人工智能大语言模型 (LLM) 说服,即使他们更信任人类. 这表明了一个令人担忧的倾向,即在没有批判性评估的情况下屈从于AI的道德建议.

科学领域:

认知科学认知科学
人工智能伦理学人工智能伦理学
人与计算机的交互

背景情况:

大型语言模型 (LLM) 越来越多地融入日常生活.
法律法学对人类信仰的影响,特别是道德推理的影响,值得进行调查.
通过LLM产生的理由来说服可以促进增长,而屈从可能会阻碍增长.

研究的目的:

调查个人是否以及如何在收到法学士的建议后改变他们的道德判断.
检查影响LLM道德建议的说服因素,包括可信度和推理质量.

主要方法:

为了评估LLM在道德困境中的说服力,进行了三项研究.
研究1比较了LLM与人类顾问的说服力.
第二项研究使用了与真正的法学士的现实互动范式.
研究3操纵了LLM提供的理由的质量.

主要成果:

参与者对LLM和人类顾问表现出同等的说服力,尽管他们认为人类更值得信赖.
该LLM的过去表现和被认为值得信赖的可信度并没有显著影响其说服力.
高质量的理由并没有增强说服力;糟糕的理由积极地减少了它.
用户似乎会根据每个响应来接受LLM的建议.

结论:

个人可能会在没有深入的批判性评估的情况下屈从于AI的道德建议,采用"足够好"的启发式.
这种对人工智能道德顾问的依赖引发了人们对对道德和智力发展的潜在负面影响的担忧.
需要进一步的研究来了解AI道德指导的长期影响.

关键词:

人工智能说服力说服力人工道德顾问的人工道德顾问每天的道德困境每天的道德困境实验认识论是实验的认识论.

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