Evidence map›Paper›PMID 40121220›Full record

ArticleScientific reports2025

Human cooperation with artificial agents varies across countries.

Jurgis Karpus, Risako Shirai, Julia Tovar Verba, Rickmer Schulte, Maximilian Weigert, Bahador Bahrami, Katsumi Watanabe, Ophelia Deroy

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Jurgis KarpusFaculty of Philosophy, Philosophy of Science and Religious Studies, LMU, Munich, Germany. jurgis.karpus@lmu.de.
Risako ShiraiFaculty of Science and Engineering, Waseda University, Tokyo, Japan.
Julia Tovar VerbaDivision of Evolutionary Biology, Faculty of Biology, LMU, Munich, Germany.
Rickmer SchulteStatistical Consulting Unit StaBLab, Department of Statistics, LMU, Munich, Germany.
Maximilian WeigertStatistical Consulting Unit StaBLab, Department of Statistics, LMU, Munich, Germany.
Bahador BahramiFaculty of Psychology and Educational Sciences, LMU, Munich, Germany.
Katsumi WatanabeFaculty of Science and Engineering, Waseda University, Tokyo, Japan.
Ophelia DeroyFaculty of Philosophy, Philosophy of Science and Religious Studies, LMU, Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

People are keen to exploit cooperative artificial agents for selfish gain. While this phenomenon has been observed in numerous Western societies, we show here that it is absent in Japan. We examined people's willingness to cooperate with artificial agents and humans in two classic economic games requiring a choice between self interest and mutual benefit. Our participants in the United States cooperated with artificial agents significantly less than they did with humans, whereas participants in Japan exhibited equivalent levels of cooperation with both types of co-player. We found a notable difference in how people felt about exploiting their cooperative partner: people in Japan emotionally treated artificial agents and humans alike, whereas people in the United States felt bad about exploiting humans, but not machines. Our findings underscore the necessity for nuanced cultural considerations in the design and implementation of such technology across diverse societies.

Indexed as

Cooperative BehaviorAdultFemaleHumansJapanMaleUnited StatesAlgorithm exploitationCooperationCross-cultural comparisonHuman–AI interaction

Identifiers

PMID40121220
PMCPMC11929925

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.