LLMs reproduce observed attitudinal patterns in climate interventions reasonably well but diverge on causal effect estimates, with descriptive fit failing to predict causal accuracy across interventions and outcomes.
Take caution in using llms as human surrogates.Proceedings of the National Academy of Sciences, 122(24):e2501660122
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When simulations look right but causal effects go wrong: Large language models as behavioral simulators
LLMs reproduce observed attitudinal patterns in climate interventions reasonably well but diverge on causal effect estimates, with descriptive fit failing to predict causal accuracy across interventions and outcomes.