A randomized audit of five LLM APIs finds verified survey-country metadata improves held-out response forecasts, while disclosing that a country label was randomly assigned does not reliably attenuate its influence.
InProceedings of the 2024 Conference on Em- pirical Methods in Natural Language Processing, 15811– 15837
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Signal or Spurious Cue? A Randomized Audit of Survey-Country Metadata in LLM Social Inference
A randomized audit of five LLM APIs finds verified survey-country metadata improves held-out response forecasts, while disclosing that a country label was randomly assigned does not reliably attenuate its influence.