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A study from Chicago Booth researchers finds that parents' fear of their children falling behind peers drives demand for AI tools despite knowing about potential cognitive harms, with willingness to pay for AI subscriptions rising significantly as peer adoption rates increase.
This paper evaluates whether off-the-shelf LLMs can reliably simulate human responses in controlled behavioral experiments by comparing LLM-generated data with human survey responses on accuracy perception. The findings show that while LLMs capture directional effects and aggregate belief-updating patterns, they do not consistently match human-scale effect magnitudes, clarifying when synthetic LLM data can serve as behavioral proxies.