Study questions realism of language-model agents in farming decision simulations

A new arXiv paper examines whether language-model agents can credibly stand in for human respondents in surveys and social simulations. The authors argue that judging realism from population averages or distributional similarity can be misleading, an effect they call the "average-farmer illusion." Their experiments test what such aggregate evidence actually demonstrates about individual-level behavior.