Latent Neural Coupling of Risk and Time Preferences in LLMs Mirrors Human Biases

Yan Leng

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Decision-Making and Behavioral Economics Ethics and Social Impacts of AI Experimental Behavioral Economics Studies

Abstract

Large language models (LLMs) now stand in for human decision makers in many settings, but it is unclear whether their choices arise from structured internal representations or surface-level pattern matching—and whether the economic preferences they express are correlated as in humans. We address these questions by analyzing three canonical preference domains - risk, time, and social - across several current LLMs.

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