Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?

Understand

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 used like economists use Homo economicus: they can be given endowments, information, preferences, and so on, and then their behavior can be explored in scenarios via simulation.
• Experiments using this approach, derived from Charness and Rabin (2002), Kahneman et al.
• (1986), Samuelson and Zeckhauser (1988), Oprea (2024b), and Horton (2025), show qualitatively similar results to the original, and when they differ, it is often generative for future research.