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Prebunking Elections Rumors: Artificial Intelligence Assisted Interventions Increase Confidence in American Elections

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  • Mitchell Linegar
  • Betsy Sinclair
  • Sander van der Linden
  • R. Michael Alvarez

Abstract

Large Language Models (LLMs) can assist in the prebunking of election misinformation. Using results from a preregistered two-wave experimental study of 4,293 U.S. registered voters conducted in August 2024, we show that LLM-assisted prebunking significantly reduced belief in specific election myths,with these effects persisting for at least one week. Confidence in election integrity was also increased post-treatment. Notably, the effect was consistent across partisan lines, even when controlling for demographic and attitudinal factors like conspiratorial thinking. LLM-assisted prebunking is a promising tool for rapidly responding to changing election misinformation narratives.

Suggested Citation

  • Mitchell Linegar & Betsy Sinclair & Sander van der Linden & R. Michael Alvarez, 2024. "Prebunking Elections Rumors: Artificial Intelligence Assisted Interventions Increase Confidence in American Elections," Papers 2410.19202, arXiv.org.
    • Handle: RePEc:arx:papers:2410.19202
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    References listed on IDEAS

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    1. Cecilie S. Traberg & Jon Roozenbeek & Sander van der Linden, 2022. "Psychological Inoculation against Misinformation: Current Evidence and Future Directions," The ANNALS of the American Academy of Political and Social Science, , vol. 700(1), pages 136-151, March.
    2. R. Michael Alvarez & Jian Cao & Yimeng Li, 2021. "Voting Experiences, Perceptions of Fraud, and Voter Confidence," Social Science Quarterly, Southwestern Social Science Association, vol. 102(4), pages 1225-1238, July.
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