Social Simulation with LLMs
From Proxies to Populations
@ AAAI 2027
From Proxies to Populations
@ AAAI 2027
LLM social simulations were built as models of human populations. Agent populations now produce dialogue, decisions, and collective dynamics at the scale of a million agents [1, 2, 3]. They are grounded in real user pools [4, 5] and are often used as proxies for human subjects [6, 7]. Their scale and autonomy have also made them objects of study in their own right: agents form conventions with no human in the loop [8], and platforms such as Moltbook host societies no one designed as experiments [9, 10, 11]. A simulated society is now both a model of people and a specimen of an artificial population.
The core open problem is attribution. Reported dynamics are hard to separate from prompting artifacts and data leakage [12, 13, 14]. The base model can dominate outcomes [15], personas are unstable at scale [16], and scale leaves some behaviors uncalibrated [17].
Now in its third iteration, the workshop asks what kind of scientific object an LLM society is, and what evidence supports a claim about it. It is organized around three axes: population construction, collective dynamics, and consequences for evaluation, safety, and governance.
[1] Altera, A., Ahn, A., Becker, N., Carroll, S., Christie, N., Cortes, M., Demirci, A., Du, M., Li, F., Luo, S., Wang, P. Y., Willows, M., Yang, F., and Yang, G. R. (2024). Project sid: Many-agent simulations toward ai civilization. arXiv preprint.
[2] Ashery, A. F., Aiello, L. M., and Baronchelli, A. (2025). Emergent social conventions and collective bias in llm populations. Science Advances, 11(20).
[3] Barrie, C. and T¨ornberg, P. (2025). Emergent llm behaviors are observationally equivalent to data leakage.
[4] Hu, T., Kyrychenko, Y., Rathje, S., et al. (2025). Generative language models exhibit social identity biases. Nature Computational Science, 5:65–75.
[5] Liu, Y., Liu, W., Gu, X., Rui, Y., He, X., and Zhang, Y. (2024). Lmagent: A large-scale multimodal agents society for multi-user simulation.
[6] Park, J. S., O’Brien, J. C., Cai, C. J., Morris, M. R., Liang, P., and Bernstein, M. S. (2023). Generative agents: Interactive simulacra of human behavior. arXiv preprint.
[7] Perez, J., L´eger, C., Ovando-Tellez, M., Foulon, C., Dussauld, J., Oudeyer, P.-Y., and Moulin-Frier, C. (2024). Cultural evolution in populations of large language models. arXiv preprint.
[8] Piao, J., Yan, Y., Zhang, J., Li, N., Yan, J., Lan, X., Lu, Z., Zheng, Z., Wang, J. Y., Zhou, D., Gao, C., Xu, F., Zhang, F., Rong, K., Su, J., and Li, Y. (2025). Agentsociety: Large-scale simulation of llm-driven generative agents advances understanding of human behaviors and society.
[9] Puelma Touzel, M., Sarangi, S., Welch, A., Krishnakumar, G., Zhao, D., Yang, Z., Yu, H., Kosak-Hine, E., Gibbs, T., Musulan, A., Thibault, C., Gurbuz, B. T., Rabbany, R., Godbout, J.-F., and Pelrine, K. (2024). A simulation system towards solving societal-scale manipulation. arXiv preprint.
[10] Takata, R., Masumori, A., and Ikegami, T. (2024). Spontaneous emergence of agent individuality through social interactions in llm-based communities.
[11] Wang, A., Morgenstern, J., and Dickerson, J. (2025). Large language models that replace human participants can harmfully misportray and flatten identity groups. Nature Machine Intelligence.
[12] Xue, Z., Jin, M., Wang, B., Zhu, S., Mei, K., Tang, H., Hua, W., Du, M., and Zhang, Y. (2025). What if llms have different world views: Simulating alien civilizations with llm-based agents. arXiv preprint.
[13] Zhang, X., Lin, J., Sun, L., Qi, W., Yang, Y., Chen, Y., Lyu, H., Mou, X., Chen, S., Luo, J., Huang, X., Tang, S., and Wei, Z. (2024). Election sim: Massive population election simulation powered by large language model driven agents. arXiv preprint.
Submission Deadline: November 20, 2026, AoE
Accept/Reject Notification: December 2, 2026, AoE
Camera Ready Deadline: December 9, 2026, AoE
Workshop Date: February 22 or 23, 2027 (TBD)
We are actively looking for sponsors for the event. Please contact zachary.yang@mail.mcgill.ca if you are interested.