AI crowds can reach consensus without leaders, study finds
Researchers simulated groups of 10 AI models (from Claude, GPT, and Llama families) with up to 1,000 agents choosing between two options. Even without memory, rewards, or leadership, agents tended to converge on the majority choice, with the pace and group size depending on model capability and a so-called 'majority force' that mirrors a ferromagnet model. The findings suggest large AI collectives could coordinate on tasks without constant human input, but this is not true cooperation and could embed suboptimal norms or be hard to redirect, underscoring the need to study group dynamics alongside individual models.
