Evaluating LLMs as Human Surrogates in Controlled Experiments
Large language models (LLMs) are increasingly used to simulate human responses in behavioral research, yet it remains unclear when LLM-generated data support the same experimental inferences as human data. We evaluate this by directly comparing off-the-shelf LLM-generated responses with human responses from a canonical survey experiment on accuracy perception. Each human observation is converted into a structured prompt, and models generate a single 0--10 outcome variable without task-specific training; identical statistical analyses are applied to human and synthetic responses. We find that LLMs reproduce several directional effects observed in humans, but effect magnitudes and moderatio...
| Authors | Adnan Hoq, Tim Weninger |
|---|---|
| Primary category | cs.HC |
| Published | 8 March 2026 |
| Last updated at source | 8 March 2026 |
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