Evidence map›Paper›PMID 41513710›Full record

ArticleScientific reports2026

Stability of value perception: minimal influence of framing on moral attributions to a humanoid robot.

Serena Marchesi, Kinga Ciupińska, Davide De Tommaso, Agnieszka Wykowska

Erratum issuedAbstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Serena MarchesiSocial Cognition in Human-Robot Interaction, Italian Institute of Technology, Genova, Italy.
Kinga CiupińskaSocial Cognition in Human-Robot Interaction, Italian Institute of Technology, Genova, Italy.
Davide De TommasoSocial Cognition in Human-Robot Interaction, Italian Institute of Technology, Genova, Italy.
Agnieszka WykowskaSocial Cognition in Human-Robot Interaction, Italian Institute of Technology, Genova, Italy. agnieszka.wykowska@iit.it.

Funding

HORIZON EUROPE European Innovation Council 101070930
6 · The paper itself

Abstract

As robots are becoming collaborators in various domains, understanding if humans perceive them as moral and intentional agents is pivotal. This study investigated the malleability of human attributions of value alignment and intentionality to a humanoid robot (iCub). We designed an experiment to test whether brief experimental framing strategies could influence these perceptions. Three experimental groups were exposed to different strategies regarding background information concerning the robot’s moral-decision making abilities: a no Information group; a verbal description group; and a social interaction (or video) group, where the robot reacted to moral decision-making movie scenes. Our results showed that our manipulations did not produce the expected differences in perceived robot–human value alignment or intentionality, suggesting that participants’ initial impressions of the robot are robust and not easily shifted by brief experimental framing. Furthermore, attributions of intentionality remained generally high regardless of the informational strategy employed. On the contrary, our exploratory findings indicate a small, significant correlation between participants’ own pre-existing moral orientations and their perceptions of the robot’s values. These findings suggest that moral impressions of complex artificial agents are less malleable than anticipated. They highlight that pre-existing moral frameworks shape how humans interpret artificial agents.

Indexed as

MoralsPerceptionRoboticsAdultDecision MakingFemaleHumansMaleYoung Adult

Identifiers

PMID41513710
PMCPMC12800177

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.