Stop Drawing Scientific Claims from LLM Social Simulations Without Robustness Audits
The scientific claims drawn from LLM social simulations should be no stronger than the robustness audits that support them. Generative agents bring new expressive power to agent-based modeling, enabling simulations of collective social processes like cooperation, polarization, and norm formation. Yet they also introduce complexity through additional architectural choices, such as agent specification, memory representation, interaction protocols, and environment design. Small perturbations that appear minor to researchers can cascade into macro-level outcomes through repeated interaction, creating a "butterfly effect." Consequently, scientific claims drawn from LLM social simulations may r...
| Authors | Jinyi Ye, Lei Cao, Ding Chen et al. |
|---|---|
| Primary category | physics.soc-ph |
| Published | 17 May 2026 |
| Last updated at source | 17 May 2026 |
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