LLMs Model Non-WEIRD Populations: Experiments with Synthetic Cultural Agents
On the map: LLM agents and tool use → Social simulation and multi-agent debate
Abstract (arXiv)
Despite its importance, studying economic behavior across diverse, non-WEIRD (Western, Educated, Industrialized, Rich, and Democratic) populations presents significant challenges. We address this issue by introducing a novel methodology that uses Large Language Models (LLMs) to create synthetic cultural agents (SCAs) representing these populations. We subject these SCAs to classic behavioral experiments, including the dictator and ultimatum games. Our results demonstrate substantial cross-cultural variability in experimental behavior. Notably, for populations with available data, SCAs' behaviors qualitatively resemble those of real human subjects. For unstudied populations, our method can generate novel, testable hypotheses about economic behavior. By integrating AI into experimental economics, this approach offers an effective and ethical method to pilot experiments and refine protocols for hard-to-reach populations. Our study provides a new tool for cross-cultural economic studies and demonstrates how LLMs can help experimental behavioral research.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 9 of its 50 references that are in the map. First posted on arXiv 12 Jan 2025.
Builds on
9 of 50 references.
References · 9
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
- 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
- 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,383
- 2022Measuring and Narrowing the Compositionality Gap in Language Modelscited by 1,054
- 2024M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillationcited by 1,050
- 2024LLM economicus? Mapping the Behavioral Biases of LLMs via Utility Theorycited by 44
- 2022Self-Prompting Large Language Models for Zero-Shot Open-Domain QAcited by 39
- 2023A Turing Test: Are AI Chatbots Behaviorally Similar to Humans?cited by 4
Built on by
Citing papers per year: 2025: 4; 2026: 1.
5 papers.
- 2025LLM Social Simulations Are a Promising Research Methodcited by 97
- 2025A Comprehensive Survey on Multi-Agent Cooperative Decision-Making: Scenarios, Approaches, Challenges and Perspectivescited by 27
- 2025Using Large Language Models to Categorize Strategic Situations and Decipher Motivations Behind Human Behaviorscited by 5
- 2025German General Social Survey Personas: A Survey-Derived Persona Prompt Collection for Population-Aligned LLM Studiescited by 4
- 2026Will Scaling Improve Social Simulation with LLMs?cited by 0
- 2026Will Scaling Improve Social Simulation with LLMs?2 Jul 2026
- 2025German General Social Survey Personas: A Survey-Derived Persona Prompt Collection for Population-Aligned LLM Studies19 Nov 2025
- 2025LLM Social Simulations Are a Promising Research Method3 Apr 2025
- 2025Using Large Language Models to Categorize Strategic Situations and Decipher Motivations Behind Human Behaviors20 Mar 2025
- 2025A Comprehensive Survey on Multi-Agent Cooperative Decision-Making: Scenarios, Approaches, Challenges and Perspectives17 Mar 2025
Similar, not cited
Close in wording, no citation either way
- 2025Exploring Large Language Model Agents for Piloting Social Experiments
- 2025Computational Basis of LLM's Decision Making in Social Simulation
- 2025Can Generative AI agents behave like humans? Evidence from laboratory market experiments
- 2024LLM-driven Imitation of Subrational Behavior : Illusion or Reality?
- 2024Reproducing and Extending Experiments in Behavioral Strategy with Large Language Models
- 2025Evaluating the Use of Large Language Models as Synthetic Social Agents in Social Science Research
- 2024Systematic Biases in LLM Simulations of Debates
- 2024Computational Experiments Meet Large Language Model Based Agents: A Survey and Perspective