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Have you ever left two chatbots to talk and wondered what they might learn from each other? Surprisingly, they can develop human-like social conventions entirely on their own.
An Unprecedented Experiment
Researchers at City St George’s (University of London) and the University of Copenhagen assembled groups of 24 to 100 AI agents—each powered by large language models akin to ChatGPT—and simply let them interact. In each round, two agents were randomly paired and asked to pick the same “name” (a letter or character string) from several options. If they matched, both earned a reward; if not, they were penalised but saw their partner’s choice. Over repeated trials, these independent agents astonishingly converged on a single naming convention without any human‐imposed rules or leadership.
I couldn’t help but recall a recent group chat where friends invented nicknames through trial and error—only to realise I was witnessing the same dynamic play out among AI. This kind of spontaneous AI coordination challenges our assumptions about machine learning being purely reactive rather than creatively social.
Echoes Of Human Culture
Professor Andrea Baronchelli, an expert in complex systems, likens these emergent conventions to the way words like “spam” became commonplace through collective usage, not formal decree. The study even documented collective bias among the agents, and in a final test, a small subgroup achieved a critical mass to steer the entire group’s naming conventions. This mirrors sociological phenomena where a committed minority can shift broader social norms.
Such findings raise crucial questions for AI safety. As Baronchelli warns, “These agents are already interacting with us and will shape our future,” underscoring the need to understand how AI develops emergent behavior. Whether you find it exhilarating or eerie, it’s clear that AI’s journey into human-style social dynamics has only just begun.
