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Reducing belief in conspiracy theories as they unfold using large language models

Research AI & Misinformation

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TL;DR - Two preregistered-style experiments (N = 472; N = 1035) show that multi-turn conversations with an LLM prompted to counter conspiracy beliefs significantly reduced U.S. adults' belief in conspiracies about breaking crisis events, with effects persisting weeks later. It matters because it demonstrates a scalable, dialogue-based intervention against misinformation at the moment it forms.

  • Tested in the immediate aftermath of two real events: the July 2024 Trump assassination attempt and the September 2025 Charlie Kirk assassination, targeting participants who already held conspiratorial views.
  • The LLM treatment outperformed two controls — an LLM conversation on an irrelevant topic and a static fact sheet — isolating the effect of tailored conversational rebuttal rather than mere information exposure.
  • Downstream generalization observed: reduced belief in different conspiracies arising from later crisis events one to two months after treatment.
  • Positions personalized, cognitively-focused LLM dialogue as a debunking mechanism for rapidly emerging (not just entrenched) conspiracy narratives.

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Reducing belief in conspiracy theories as they unfold using large language models

arXiv cs.HC Thomas H. Costello, Nathaniel Rabb, Michael Nicholas Stagnaro, Gordon Pennycook, David Rand 2026-08-06 arXiv:2608.06151
Public signals Semantic Scholar citations 2 · Semantic Scholar influential citations 1
Providers: Hugging Face · N/A OpenAlex · N/A Publisher · N/A Semantic Scholar · Citations 2 · Influential citations 1 X · N/A Fetched 2026-08-09 14:14:09.449427 UTC

TL;DR - Two preregistered-style experiments (N = 472; N = 1035) show that multi-turn conversations with an LLM prompted to counter conspiracy beliefs significantly reduced U.S. adults' belief in conspiracies about breaking crisis events, with effects persisting weeks later. It matters because it demonstrates a scalable, dialogue-based intervention against misinformation at the moment it forms.

  • Tested in the immediate aftermath of two real events: the July 2024 Trump assassination attempt and the September 2025 Charlie Kirk assassination, targeting participants who already held conspiratorial views.
  • The LLM treatment outperformed two controls — an LLM conversation on an irrelevant topic and a static fact sheet — isolating the effect of tailored conversational rebuttal rather than mere information exposure.
  • Downstream generalization observed: reduced belief in different conspiracies arising from later crisis events one to two months after treatment.
  • Positions personalized, cognitively-focused LLM dialogue as a debunking mechanism for rapidly emerging (not just entrenched) conspiracy narratives.
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