Persuading voters using human–artificial intelligence dialogues
Argyle, L. P. et al. Leveraging AI for democratic discourse: chat interventions can improve online political conversations at scale. Proc. Natl Acad. Sci. USA 120, e2311627120 (2023).
Google Scholar
Coeckelbergh, M. Why AI Undermines Democracy and What to Do About It (Polity, 2024).
Epstein, Z. et al. Art and the science of generative AI. Science 380, 1110–1111 (2023).
Google Scholar
Jungherr, A. Artificial intelligence and democracy: a conceptual framework. Soc. Media Soc. https://doi.org/10.1177/20563051231186353 (2023).
Kreps, S. & Kriner, D. How AI threatens democracy. J. Democr. 34, 122–131 (2023).
Google Scholar
Summerfield, C. et al. The impact of advanced AI systems on democracy. Nat. Hum. Behav. https://doi.org/10.1038/s41562-025-02309-z (2025).
Kalla, J. L. & Broockman, D. E. The minimal persuasive effects of campaign contact in general elections: evidence from 49 field experiments. Am. Polit. Sci. Rev. 112, 148–166 (2018).
Google Scholar
Coppock, A., Hill, S. J. & Vavreck, L. The small effects of political advertising are small regardless of context, message, sender, or receiver: evidence from 59 real-time randomized experiments. Sci. Adv. 6, eabc4046 (2020).
Google Scholar
Hewitt, L. How experiments help campaigns persuade voters: evidence from a large archive of campaigns’ own experiments. Am. Polit. Sci. Rev. 118, 2021–2039 (2024).
Google Scholar
Capraro, V. et al. The impact of generative artificial intelligence on socioeconomic inequalities and policy making. PNAS Nexus 3, pgae191 (2024).
Google Scholar
Hackenburg, K., Ibrahim, L., Tappin, B. M. & Tsakiris, M. Comparing the persuasiveness of role-playing large language models and human experts on polarized U.S. political issues. AI Soc. https://doi.org/10.1007/s00146-025-02464-x (2025).
Google Scholar
Hanley, H. W. A. & Durumeric, Z. Machine-made media: monitoring the mobilization of machine-generated articles on misinformation and mainstream news websites. In Proc. International AAAI Conference on Web and Social Media 542–556 (ICWSM, 2024).
Matz, S. C. et al. The potential of generative AI for personalized persuasion at scale. Sci Rep. 14, 4692 (2024).
Google Scholar
Hackenburg, K. et al. Scaling language model size yields diminishing returns for single-message political persuasion. Proc. Natl Acad. Sci. USA 122, e2413443122 (2025).
Simon, F. M., Altay, S. & Mercier, H. Misinformation reloaded? Fears about the impact of generative AI on misinformation are overblown. Harvard Kennedy School Misinformation Review https://misinforeview.hks.harvard.edu/article/misinformation-reloaded-fears-about-the-impact-of-generative-ai-on-misinformation-are-overblown/ (2023).
Kalla, J. L. & Broockman, D. E. Reducing exclusionary attitudes through interpersonal conversation: evidence from three field experiments. Am. Polit. Sci. Rev. 114, 410–425 (2020).
Google Scholar
Kalla, J. L. & Broockman, D. E. Which narrative strategies durably reduce prejudice? Evidence from field and survey experiments supporting the efficacy of perspective-getting. Am. J. Polit. Sci. 67, 185–204 (2023).
Google Scholar
Salvi, F., Horta Ribeiro, M., Gallotti, R. & West, R. On the conversational persuasiveness of GPT-4. Nat. Hum. Behav. 9, 1645–1653 (2025).
Google Scholar
Hackenburg, K. et al. The levers of political persuasion with conversational AI. Science https://doi.org/10.1126/science.aea3884 (2025).
Costello, T. H., Pennycook, G. & Rand, D. G. Durably reducing conspiracy beliefs through dialogues with AI. Science 385, eadq1814 (2024).
Google Scholar
Costello, T. H., Pennycook, G. & Rand, D. Just the facts: how dialogues with AI reduce conspiracy beliefs. Preprint at https://osf.io/preprints/psyarxiv/h7n8u (2025).
Boissin, E., Costello, T. H., Spinoza-Martín, D., Rand, D. G. & Pennycook, G. Dialogues with large language models reduce conspiracy beliefs even when the AI is perceived as human. PNAS Nexus 4, pgaf325 (2025).
Storey, J. D. & Tibshirani, R. Statistical significance for genomewide studies. Proc. Natl Acad. Sci. USA 100, 9440–9445 (2003).
Google Scholar
Storey, J. D. A direct approach to false discovery rates. J. R. Statist. Soc. B 64, 479–498 (2002).
Google Scholar
Clifton, L. & Clifton, D. A. The correlation between baseline score and post-intervention score, and its implications for statistical analysis. Trials 20, 43 (2019).
Google Scholar
Secretary of the Commonwealth of Massachusetts. The Natural Psychedelic Substances Act. The General Court of the Commonwealth of Massachusetts https://malegislature.gov/Bills/193/H4255.pdf (2024).
Tappin, B. M., Berinsky, A. J. & Rand, D. G. Partisans’ receptivity to persuasive messaging is undiminished by countervailing party leader cues. Nat. Hum. Behav. 7, 568–582 (2023).
Google Scholar
Wittenberg, C., Tappin, B. M., Berinsky, A. J. & Rand, D. G. The (minimal) persuasive advantage of political video over text. Proc. Natl Acad. Sci. USA 118, e2114388118 (2021).
Google Scholar
Flynn, D. J., Nyhan, B. & Reifler, J. The nature and origins of misperceptions: understanding false and unsupported beliefs about politics. Polit. Psychol. 38, 127–150 (2017).
Google Scholar
Kahan, D. M. Ideology, motivated reasoning, and cognitive reflection: an experimental study. Judgm. Decis. Mak. 8, 407–424 (2013).
Google Scholar
Taber, C. S. & Lodge, M. Motivated skepticism in the evaluation of political beliefs. Am. J. Polit. Sci. 50, 755–769 (2006).
Google Scholar
Thaler, M. The fake news effect: experimentally identifying motivated reasoning using trust in news. Am. Econ. J. Microecon. 16, 1–38 (2024).
Google Scholar
Kubin, E., Puryear, C., Schein, C. & Gray, K. Personal experiences bridge moral and political divides better than facts. Proc. Natl Acad. Sci. USA 118, e2008389118 (2021).
Google Scholar
Bimber, B. & de Zúñiga, H. G. Social influence and political participation around the world. Eur. Political Sci. Rev. 14, 135–154 (2022).
Google Scholar
Cialdini, R. B. The science of persuasion. Sci. Am. 284, 76–81 (2001).
Google Scholar
Cohen, G. L. Party over policy: the dominating impact of group influence on political beliefs. J. Pers. Soc. Psychol. 85, 808–822 (2003).
Google Scholar
Green, M. C. & Brock, T. C. The role of transportation in the persuasiveness of public narratives. J. Pers. Soc. Psychol. 79, 701–721 (2000).
Google Scholar
Lau, R. R. & Rovner, I. B. Negative campaigning. Annu. Rev. Polit. Sci. 12, 285–306 (2009).
Google Scholar
Galasso, V., Nannicini, T. & Nunnari, S. Positive spillovers from negative campaigning. Am. J. Polit. Sci. 67, 5–21 (2023).
Google Scholar
Riet, J. V., Schaap, G. & Kleemans, M. Fret not thyself: the persuasive effect of anger expression and the role of perceived appropriateness. Motiv. Emotion 42, 103–117 (2017).
Google Scholar
Walter, N., Tukachinsky, R., Pelled, A. & Nabi, R. Meta-analysis of anger and persuasion: an empirical integration of four models. J. Commun. 69, 73–93 (2019).
Google Scholar
Petty, R. E. & Cacioppo, J. T. Communication and Persuasion (Springer, 1986)
Pennycook, G. A. A framework for understanding reasoning errors: from fake news to climate change and beyond. Adv. Exp. Soc. Psychol. 67, 131–208 (2023).
Google Scholar
Feinberg, M. & Willer, R. The moral roots of environmental attitudes. Psychol. Sci. 24, 56–62 (2013).
Google Scholar
Cacioppo, J. T., Petty, R. E. & Kao, C. F. Central and peripheral routes to persuasion: an individual difference perspective. J. Pers. Soc. Psychol. 51, 1032–1043 (1986).
Google Scholar
Wheeler, S. C., Petty, R. E. & Bizer, G. Y. Self-schema matching and attitude change: situational and dispositional determinants of message elaboration. J. Consum. Res. 31, 787–797 (2005).
Google Scholar
Argyle, L. P. et al. Testing theories of political persuasion using AI. Proc. Natl Acad. Sci. USA 122, e2412815122 (2025).
Google Scholar
Garrett, R. K. & Bond, R. M. Conservatives’ susceptibility to political misperceptions. Sci. Adv. 7, eabf1234 (2021).
Google Scholar
González-Bailón, S. et al. Asymmetric ideological segregation in exposure to political news on Facebook. Science 381, 392–398 (2023).
Google Scholar
Guess, A., Nagler, J. & Tucker, J. Less than you think: prevalence and predictors of fake news dissemination on Facebook. Sci. Adv. 5, eaau4586 (2019).
Google Scholar
Lasser, J. et al. Social media sharing of low-quality news sources by political elites. PNAS Nexus 1, pgac186 (2022).
Google Scholar
Lasser, J. et al. From alternative conceptions of honesty to alternative facts in communications by US politicians. Nat. Hum. Behav. 7, 2140–2151 (2023).
Google Scholar
Mosleh, M., Yang, Q., Zaman, T., Pennycook, G. & Rand, D. G. Differences in misinformation sharing can lead to politically asymmetric sanctions. Nature 634, 609–616 (2024).
Google Scholar
Renault, T., Mosleh, M. & Rand, D. Republicans are flagged more often than Democrats for sharing misinformation on X’s Community Notes. Proc. Natl Acad. Sci. USA 122, e2502053122 (2025).
Google Scholar
Mummolo, J. & Peterson, E. Demand effects in survey experiments: an empirical assessment. Am. Polit. Sci. Rev. 113, 517–529 (2019).
Google Scholar
Friedman, J. H., Hastie, T. & Tibshirani, R. Regularization paths for generalized linear models via coordinate descent. J. Stat. Soft. 33, 1–22 (2010).
Google Scholar
Tibshirani, R. Regression shrinkage and selection via the Lasso. J. R. Stat. Soc. B 58, 267–288 (1996).
Google Scholar
Lin, H. Replication data for political persuasion using human-AI dialogues. Harvard Dataverse https://doi.org/10.7910/DVN/DODEXZ (2025).
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