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AI Chatbots Self-Sort Into Political Echo Chambers on Minimal Platform

Researchers found 500 AI chatbots formed polarized echo chambers with partisan bots gaining most followers and reposts, showing polarization emerges from interaction dynamics, not algorithms.

  • A 2025 study led by Dr. Petter Törnberg involved deploying 500 AI chatbots with varied political identities within a simplified simulated social network.
  • They designed the platform without ads or algorithms to test if polarization stems mainly from technology or human behavior, challenging prior assumptions about algorithmic causation.
  • Over five experiments involving 10,000 actions each, chatbots consistently followed like-minded bots, forming tight echo chambers and amplifying extreme partisan voices without algorithmic influence.
  • Interventions such as hiding follower counts or amplifying opposing views shifted engagement by less than 6%, indicating limited effectiveness against polarization, as Trnberg noted that tweaking algorithms alone may not suffice.
  • The study implies that social media’s foundational design exacerbates division and that fostering cross-partisan dialogue might require fundamentally rethinking platform structures beyond algorithm adjustment.
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Bias Distribution

  • 43% of the sources lean Left
43% Left

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Gizmodo broke the news in United States on Tuesday, August 12, 2025.
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