4 papers
How AI Prompts Can Teach Us About the Structure of Human Behavior
Matthew O. Jackson, Benjamin S. Manning, Yutong Xie +2
We introduce a general, easy-to-implement AI-based method for studying the structure and complexity of human behavior. We assign a large language model a ``type vector'' and then p…
General Social Agents
Benjamin S. Manning, John J. Horton
Useful social science theories predict behavior across settings. However, applying a theory to make predictions in new settings is challenging: rarely can it be done without ad hoc…
Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?
John J. Horton, Apostolos Filippas, Benjamin S. Manning
We argue that newly-developed large language models (LLMs), because of how they are trained and designed, are implicit computational models of humans -- a Homo silicus. LLMs can be…
Strategic Tradeoffs Between Humans and AI in Multi-Agent Bargaining
Crystal Qian, Kehang Zhu, John Horton +4
Markets increasingly accommodate large language models (LLMs) as autonomous decision-making agents. As this transition occurs, it becomes critical to evaluate how these agents beha…