Evaluating the Use of Large Language Models as Synthetic Social Agents in Social Science Research

• URL: http://arxiv.org/abs/2509.26080v2
• Date: Tue, 28 Oct 2025 13:00:46 GMT
• Title: Evaluating the Use of Large Language Models as Synthetic Social Agents in Social Science Research
• Abstract summary: Large Language Models (LLMs) are being increasingly used as synthetic agents in social science.<n>This paper outlines cautions that should be taken when interpreting outputs and proposes a pragmatic reframing.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Large Language Models (LLMs) are being increasingly used as synthetic agents in social science, in applications ranging from augmenting survey responses to powering multi-agent simulations. This paper outlines cautions that should be taken when interpreting LLM outputs and proposes a pragmatic reframing for the social sciences in which LLMs are used as high-capacity pattern matchers for quasi-predictive interpolation under explicit scope conditions and not as substitutes for probabilistic inference. Practical guardrails such as independent draws, preregistered human baselines, reliability-aware validation, and subgroup calibration, are introduced so that researchers may engage in useful prototyping and forecasting while avoiding category errors.

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