Evidence map›Paper›PMID 39230876›Full record

ArticleBritish journal of psychology (London, England : 1953)2026

People have different expectations for their own versus others' use of AI-mediated communication tools.

Zoe A Purcell, Mengchen Dong, Anne-Marie Nussberger, Nils Köbis, Maurice Jakesch

Abstract read
In one paragraph

Article in British journal of psychology (London, England : 1953), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

5 authors.

Zoe A PurcellLaPsyDÉ, Université Paris Cité, CNRS, Paris, France.ORCID https://orcid.org/0000-0002-3051-9191
Mengchen DongCenter for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany.ORCID https://orcid.org/0000-0001-8547-3808
Anne-Marie NussbergerCenter for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany.
Nils KöbisCenter for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany.
Maurice JakeschCornell Tech, Cornell University, New York, New York, USA.

Funding

L'Agence nationale de la recherche (ANR)-19-PI3A-0004L'Agence nationale de la recherche (ANR)-19-PI3A-0006Stiftung Mercator
6 · The paper itself

Abstract

Artificial intelligence (AI) can enhance human communication, for example, by improving the quality of our writing, voice or appearance. However, AI mediated communication also has risks-it may increase deception, compromise authenticity or yield widespread mistrust. As a result, both policymakers and technology firms are developing approaches to prevent and reduce potentially unacceptable uses of AI communication technologies. However, we do not yet know what people believe is acceptable or what their expectations are regarding usage. Drawing on normative psychology theories, we examine people's judgements of the acceptability of open and secret AI use, as well as people's expectations of their own and others' use. In two studies with representative samples (Study 1: N = 477; Study 2: N = 765), we find that people are less accepting of secret than open AI use in communication, but only when directly compared. Our results also suggest that people believe others will use AI communication tools more than they would themselves and that people do not expect others' use to align with their expectations of what is acceptable. While much attention has been focused on transparency measures, our results suggest that self-other differences are a central factor for understanding people's attitudes and expectations for AI-mediated communication.

Indexed as

Artificial IntelligenceCommunicationAdolescentAdultAgedFemaleHumansMaleMiddle AgedYoung AdultAI‐mediated communicationartificial intelligencecomputer‐mediated communicationhuman–AI interactiontechnology risk assessmenttrust

Identifiers

PMID39230876
PMCPMC13051031

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.