Phys.org — Political Science · October 23, 2026 · On the brief until November 6, 2026

AI agents can form political camps—and changing their conversation partners does little to soften their views

Political ScienceSociology

THE AI ANGLE

Simulating political polarization and dialogue interventions in network experiments

Researchers simulated political debates among language model agents and observed the spontaneous emergence of polarized camps. Interventions that randomized conversation partners had minimal effect, while instructing agents to be receptive reduced polarization by 11.8 percent. These results provide social scientists with a model to examine internal processing rules alongside network exposure.

Summary written by AI Business Lens with an AI model from the article at phys.org. It is not the article, and the publisher has not reviewed it. For publishers.

THE TEACHING ANGLE

Classes can examine why exposing agents to opposing viewpoints failed to depolarize the network without explicit instructions to be receptive.

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AI agents can form political camps—and changing their conversation partners does little to soften their views

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