Proceedings of the Annual Meeting of the Cognitive Science Society

Large language models (LLMs) like GPT-3 are revolutionizing artificial intelligence, leading to breakthroughs in question answering, natural language understanding, and machine translation. Recent work in a variety of social science disciplines, including psychology, economics, and political science has demonstrated remarkable similarity between the behavior of LLMs and human decision makers. At the same time, AI researchers and engineers struggle to understand these systems, leading to practical challenges and ethical questions about fair and safe deployment. This workshop aims to bring together researchers to discuss work on using psychological methods to understand LLMs and LLMs as tools for understanding humans. Along these lines, we have invited leading researchers from cognitive science, psychology, and machine learning to present their work on topics that include: When and why do LLMs exhibit biased behavior? How do these compare to human biases? What sorts of psychological tasks do LLMs struggle with? Can we use psychological theory to structure this search? And how does the knowledge encoded in LLMs differ from human knowledge?