Evidence map›Paper›PMID 40851577›Full record

ArticleFrontiers in psychology2025

Are artificial agents perceived similarly to humans? Knowns, unknowns and the road ahead.

Marius Rubo, Isabel Neumann

Abstract read
In one paragraph

Article in Frontiers in 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.

Marius RuboCognitive Psychology, Perception and Research Methods, Institute of Psychology, University of Bern, Bern, Switzerland.
Isabel NeumannDepartment of Clinical Psychology, and Psychotherapy, Institute of Psychology, University of Würzburg, Würzburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Starting long before modern generative artificial intelligence (AI) tools became available, technological advances in constructing artificial agents spawned investigations into the extent to which interactions with such non-human counterparts bear resemblance to human-human-interactions. Although artificial agents are typically not ascribed a mind of their own in the same sense as humans, several researchers concluded that social presence with or social influence from artificial agents can resemble that seen in interactions with humans in important ways. Here we critically review claims about a comparability between human-agent interactions and human-human-interactions, outlining methodological approaches and challenges which predate the AI era but continue to influence work in the field. By connecting novel work on AI tools with broader research in the field we aim to provide orientation and background knowledge to researchers as they move forward in inquiring how artificial agents are used and perceived, and to further contribute to an ongoing discussion around appropriate experimental setups and measures. We argue that both when confronting participants with simple artificial agents or AI-driven bots, researchers should (1) scrutinize the specificity of measures which may indicate social as well as more general, non-social processes, (2) avoid deceptive cover stories which entail their own complications to data interpretation and (3) see value in understanding specific social-cognitive processes in interactions with artificial agents even when the most generalizable comparisons with human-human interactions may not be achieved in a specific experimental setup.

Indexed as

artificial agentsartificial intelligenceavatarsdeceptiondemand characteristics

Identifiers

PMID40851577
PMCPMC12368593

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.