Evidence map›Paper›PMID 41345316›Full record

ArticleNature2025

Persuading voters using human-artificial intelligence dialogues.

Hause Lin, Gabriela Czarnek, Benjamin Lewis, Joshua P White, Adam J Berinsky, Thomas Costello, Gordon Pennycook, David G Rand

Abstract read
PubMed Publisher
In one paragraph

Article in Nature, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. The "synthetic validity" problem in AI-generated science.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Article
  3. On the optimal integration of intelligent agents into network systems to steer cooperation.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Hause LinSloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0003-4590-7039
Gabriela CzarnekInstitute of Psychology, Jagiellonian University, Kraków, Poland.
Benjamin LewisSloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA.
Joshua P WhiteSloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0003-3129-5473
Adam J BerinskyDepartment of Political Science, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0001-7827-9396
Thomas CostelloDepartment of Social and Decision Sciences, Carnegie Mellon University, Pittsburgh, PA, USA.
Gordon PennycookDepartment of Psychology, Cornell University, Ithaca, NY, USA. gordon.pennycook@cornell.edu.ORCID 0000-0003-1344-6143
David G RandSloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA. dgr7@cornell.edu.ORCID 0000-0001-8975-2783

Funding

Canadian Social Sciences and Humanities Research Council Tri-Agency
6 · The paper itself

Abstract

There is great public concern about the potential use of generative artificial intelligence (AI) for political persuasion and the resulting impacts on elections and democracy

Indexed as

Artificial IntelligencePersuasive CommunicationPoliticsAdultCanadaFemaleHumansMaleMassachusettsUnited StatesVoting

Identifiers

PMID41345316

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.