大语言模型中出现的类人直觉行为与推理偏差——且在GPT-4中消失
Human-Like Intuitive Behavior and Reasoning Biases Emerged in Language Models -- and Disappeared in GPT-4
AI总结：
该研究用认知反思测试和语义错觉探测大语言模型，发现GPT-3存在类人直觉行为与认知偏差，而ChatGPT、GPT-4可避免此类错误呈超理性表现，证明心理学方法能揭示LLM的未知涌现特性。
摘要：
大语言模型（LLM）目前处于人工智能系统与人类沟通及日常生活融合的前沿，因此评估其涌现能力至关重要。本研究表明，LLM（尤其是GPT-3）展现出与人类直觉惊人相似的行为，以及伴随而来的认知错误。然而，认知能力更强的LLM（特别是ChatGPT和GPT-4）已学会避免陷入这类错误，表现出超理性的行为模式。实验中，我们采用最初用于研究人类直觉决策的认知反思测试（CRT）及语义错觉对LLM进行探测，还探究了类直觉决策倾向的稳固程度。本研究证明，用心理学方法研究LLM有望揭示其他方式无法发现的涌现特性。
英文摘要：
Large language models (LLMs) are currently at the forefront of intertwining AI systems with human communication and everyday life. Therefore, it is of great importance to evaluate their emerging abilities. In this study, we show that LLMs, most notably GPT-3, exhibit behavior that strikingly resembles human-like intuition -- and the cognitive errors that come with it. However, LLMs with higher cognitive capabilities, in particular ChatGPT and GPT-4, learned to avoid succumbing to these errors and perform in a hyperrational manner. For our experiments, we probe LLMs with the Cognitive Reflection Test (CRT) as well as semantic illusions that were originally designed to investigate intuitive decision-making in humans. Moreover, we probe how sturdy the inclination for intuitive-like decision-making is. Our study demonstrates that investigating LLMs with methods from psychology has the potential to reveal otherwise unknown emergent traits.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
