Evidence map›Paper›PMID 37788311›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2023

Leveraging AI for democratic discourse: Chat interventions can improve online political conversations at scale.

Lisa P Argyle, Christopher A Bail, Ethan C Busby, Joshua R Gubler, Thomas Howe, Christopher Rytting, Taylor Sorensen, David Wingate

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
–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

28 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Why depolarization is hard: Evaluating attempts to decrease partisan animosity in America.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Pooled it
  2. AI-generated language remains systematically distinguishable from human communication.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  15. Testing theories of political persuasion using AI.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  16. Listen for a change? A longitudinal field experiment on listening's potential to enhance persuasion.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  19. Complex systems perspective in assessing risks in artificial intelligence.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2024
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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.

Lisa P Argyle *Department of Political Science, Brigham Young University, Provo, UT, 84602.ORCID 0000-0003-3109-2537
Christopher A Bail *Department of Sociology, Political Science, and Public Policy, Duke University, Durham, NC, 27708.
Ethan C Busby *Department of Political Science, Brigham Young University, Provo, UT, 84602.ORCID 0000-0002-8931-6348
Joshua R Gubler *Department of Political Science, Brigham Young University, Provo, UT, 84602.ORCID 0000-0003-1635-8210
Thomas Howe *Department of Computer Science, Brigham Young University, Provo, UT, 84602.
Christopher Rytting *Department of Computer Science, Brigham Young University, Provo, UT, 84602.ORCID 0000-0002-7373-9741
Taylor Sorensen *Department of Computer Science, University of Washington, Seattle, WA, 98195.ORCID 0000-0002-3251-3527
David Wingate *Department of Computer Science, Brigham Young University, Provo, UT, 84602.ORCID 0000-0003-1850-6926

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Political discourse is the soul of democracy, but misunderstanding and conflict can fester in divisive conversations. The widespread shift to online discourse exacerbates many of these problems and corrodes the capacity of diverse societies to cooperate in solving social problems. Scholars and civil society groups promote interventions that make conversations less divisive or more productive, but scaling these efforts to online discourse is challenging. We conduct a large-scale experiment that demonstrates how online conversations about divisive topics can be improved with AI tools. Specifically, we employ a large language model to make real-time, evidence-based recommendations intended to improve participants' perception of feeling understood. These interventions improve reported conversation quality, promote democratic reciprocity, and improve the tone, without systematically changing the content of the conversation or moving people's policy attitudes.

Indexed as

LanguagePolicyHumanscomputational social sciencedemocratic deliberationgenerative AIpolitical science

Identifiers

PMID37788311
PMCPMC10576030

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.