Department of Brain and Cognitive Sciences, MIT, United States of America; Department of Psychology, Harvard University, United States of America.
Department of Brain and Cognitive Sciences, MIT, United States of America; Department of Psychology, Harvard University, United States of America.
Cognition. 2024 Nov;252:105914. doi: 10.1016/j.cognition.2024.105914. Epub 2024 Aug 22.
Loopholes offer an opening. Rather than comply or directly refuse, people can subvert an intended request by an intentional misunderstanding. Such behaviors exploit ambiguity and under-specification in language. Using loopholes is commonplace and intuitive in everyday social interaction, both familiar and consequential. Loopholes are also of concern in the law, and increasingly in artificial intelligence. However, the computational and cognitive underpinnings of loopholes are not well understood. Here, we propose a utility-theoretic recursive social reasoning model that formalizes and accounts for loophole behavior. The model captures the decision process of a loophole-aware listener, who trades off their own utility with that of the speaker, and considers an expected social penalty for non-cooperative behavior. The social penalty is computed through the listener's recursive reasoning about a virtual naive observer's inference of a naive listener's social intent. Our model captures qualitative patterns in previous data, and also generates new quantitative predictions consistent with novel studies (N = 265). We consider the broader implications of our model for other aspects of social reasoning, including plausible deniability and humor.
漏洞提供了一个开口。人们可以通过故意误解来颠覆原本的请求,而不是遵守或直接拒绝。这种行为利用了语言中的歧义性和不明确性。在日常社交互动中,利用漏洞是很常见和直观的,既熟悉又有后果。漏洞在法律中也受到关注,在人工智能中也越来越受到关注。然而,漏洞的计算和认知基础还没有得到很好的理解。在这里,我们提出了一个效用理论的递归社会推理模型,该模型形式化并解释了漏洞行为。该模型捕获了一个漏洞感知的听众的决策过程,该听众在自己的效用和说话者的效用之间进行权衡,并考虑了对不合作行为的预期社会惩罚。社会惩罚是通过听众对虚拟天真观察者对天真听众的社会意图的推断的递归推理来计算的。我们的模型捕捉了之前数据中的定性模式,并且还生成了与新研究一致的新的定量预测(N=265)。我们考虑了我们的模型对其他方面的社会推理的更广泛影响,包括似是而非的否认和幽默。