元认知
心理学
认知心理学
认知科学
认知
语言习得
发展心理学
任务分析
社会心理学
人类语言
作者
Mark Steyvers,Megan A. K. Peters
标识
DOI:10.1177/09637214251391158
摘要
Metacognition—the capacity to monitor and evaluate one’s own knowledge and performance—is foundational to human decision-making, learning, and communication. As large language models (LLMs) become increasingly embedded in both high-stakes and widespread low-stakes contexts, it is important to assess whether, how, and to what extent they exhibit metacognitive abilities. Here, we provide an overview of the current knowledge of LLMs’ metacognitive capacities, how they might be studied, and how they relate to our knowledge of metacognition in humans. We show that although humans and LLMs can sometimes appear quite aligned in their metacognitive capacities and behaviors, it is clear many differences remain; attending to these differences is important for enhancing the collaboration between humans and artificial intelligence. Last, we discuss how endowing future LLMs with more sensitive and more calibrated metacognition may also help them develop new capacities such as more efficient learning, self-direction, and curiosity.
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