LLMs predict social science experiment results as accurately as human forecasters

Large language models (LLMs) can estimate the results of social science experiments with roughly the same accuracy as groups of human forecasters, even for studies published after the models' training cutoff. However, LLMs consistently tended to overestimate effect sizes. The finding raises questions about the potential role of AI in scientific peer review and forecasting.