Evidence map›Paper›PMID 40719013›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Artificial Intelligence Is Stereotypically Linked More with Socially Dominant Groups in Natural Language.

Zixi Wang, Haodong Xia, Han Wu Shuang Bao, Yiming Jing, Ruolei Gu

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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

5 authors.

Zixi WangState Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.
Haodong XiaState Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.
Han Wu Shuang BaoSchool of Psychology and Cognitive Science, East China Normal University, Shanghai, 200062, China.
Yiming JingState Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.
Ruolei GuState Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.ORCID https://orcid.org/0000-0001-8722-2172

Funding

Beijing Municipal Office of Philosophy and Social Science Planning 24DTR063National Natural Science Foundation of China 32020103008National Natural Science Foundation of China 32371130
6 · The paper itself

Abstract

Despite the increasingly important role that artificial intelligence (AI) plays in society, its social representation remains underexplored. This study reveals that AI is asymmetrically stereotyped, being more closely associated with socially dominant groups. This conclusion is based on these investigations of AI's associations along the warmth-competence dimensions of the stereotype content model, its connections with socially advantaged (e.g., men, young, rich, white) versus disadvantaged (e.g., women, old, poor, non-white) demographic groups, and its perceived impact on high- versus low-prestige occupations. Across four studies using language-based analyses with static word embeddings, BERT-based models, and GPT-4o, as well as human-participant experiment validation, it is found that i) AI is strongly associated with high competence but exhibits variability in the warmth dimension (Study 1); ii) AI is more closely linked to advantaged demographic groups (Study 2); iii) advantaged demographic groups are semantically closer to AI than their disadvantaged counterparts along the warmth-competence dimensions (Study 3); and iv) high-prestige occupations (rather than low-prestige ones) are associated more strongly with AI's benefits than with its threats. Together, these findings indicate that public perceptions of AI are systematically biased toward socially dominant groups, potentially reinforcing existing social inequalities and raising concerns about an emerging "AI divide."

Indexed as

Artificial IntelligenceLanguageStereotypingAdultFemaleHumansMaleartificial intelligencenatural language processingsocial representationstereotype

Identifiers

PMID40719013
PMCPMC12533212

What OpenQuestion holds

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Registered trials

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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.