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This talk introduces a working paper on using LLMs as simulated economists. We argue that newly-developed 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. We discuss potential applications, conceptual issues, and why this approach can inform the study of humans. The talk will also introduce the Expected Parrot Domain-Specific Language (EDSL), a package that streamlines computational social science and market research using AI. EDSL enables researchers to design and run surveys and experiments with large numbers of AI agents or LLMs simultaneously, as well as perform complex data-labeling and related research tasks efficiently.