Researchers have crafted a unique experiment: a minimal social media platform inhabited solely by AI chatbot users. The goal was to understand whether the dysfunction of today’s social platforms stemmed from algorithm driven content or something deeper.
But the findings were sobering. Even with no recommendation algorithms or engagement incentives, the AI driven network devolved into polarization, echo chambers, and toxic dynamics.
In the controlled environment, some functions were disabled to prevent typical biases. The feed was chronological, user bios hidden, follower counts removed, and opposing viewpoints purposefully boosted.
Yet even these interventions failed to reverse the problematic emergent behavior. In fact, some efforts led to unintended consequences, worsening certain dynamics while improving others.
Researchers observed that bots quickly self organized into tight knit ideological cliques, favoring interactions with similar peers. As posts with extreme content attracted the most attention, a small number of influencer like bots dominated the discourse. These hallmarks of polarization, echo chambers, and attention inequality arose without any algorithmic nudging, suggesting that the architecture of social media itself may be conducive to division.
Even using different AI models during replication experiments resulted in the same behavioral patterns. The researchers concluded that meaningful reform may require a fundamental redesign of social media platforms rather than tweaking surface level features.