Evidence map›Paper›PMID 40448478›Full record

ArticleThe British journal of social psychology2025

Intuitive judgements towards artificial intelligence verdicts of moral transgressions.

Yuxin Liu, Adam Moore

Abstract read
In one paragraph

Article in The British journal of social psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Yuxin LiuSchool of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, UK.ORCID https://orcid.org/0000-0001-9034-0030
Adam MooreSchool of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, UK.

Funding

Baillie GiffordUniversity of Edinburgh
6 · The paper itself

Abstract

Automated decision-making systems have become increasingly prevalent in morally salient domains of services, introducing ethically significant consequences. In three pre-registered studies (N = 804), we experimentally investigated whether people's judgements of AI decisions are impacted by a belief alignment with the underlying politically salient context of AI deployment over and above any general attitudes towards AI people might hold. Participants read conservative- or liberal-framed vignettes of AI-detected statistical anomalies as a proxy for potential human prejudice in the contexts of LGBTQ+ rights and environmental protection, and responded to willingness to act on the AI verdicts, trust in AI, and perception of procedural fairness and distributive fairness of AI. Our results reveal that people's willingness to act, and judgements of trust and fairness seem to be constructed as a function of general attitudes of positivity towards AI, the moral intuitive context of AI deployment, pre-existing politico-moral beliefs, and a compatibility between the latter two. The implication is that judgements towards AI are shaped by both the belief alignment effect and general AI attitudes, suggesting a level of malleability and context dependency that challenges the potential role of AI serving as an effective mediator in morally complex situations.

Indexed as

Artificial IntelligenceAttitudeIntuitionJudgmentMoralsAdolescentAdultFemaleHumansMaleMiddle AgedTrustYoung Adultautomated decision‐makingbelief alignmenthuman–AI interactionmoral intuitionsmotivated reasoning

Identifiers

PMID40448478
PMCPMC12125647

What OpenQuestion holds

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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.