Measuring Fundamental Aspects of the Social Perception of Robots

Development and Validation of a Shortened Version of the RoSAS (RoSAS-SF)

Bibliographic Data

ID21199535
AuthorsKelsey L Neuenswander (0000-0002-3441-344X, University of California, Los Angeles, corresponding author), Abhinanda Dash (University of California, Los Angeles), Prianka D Koya (University of California, Los Angeles), Lin Lin (0000-0002-6342-5618, University of California, Los Angeles), Grace S R Gillespie (University of California, Los Angeles), Steven J Stroessner (0000-0003-3846-5893, University of California, Los Angeles)
Year2025
Volume17
Issue6
Pages1097-1112
Publication date2025-06-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Social Robotics (JOURNAL)
Journal identifiersISSN: 1875-4791 • E-ISSN: 1875-4805
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s12369-025-01251-4
OpenAlexW4409967377
LanguageEN
Citations received1
References cited86

The robotic social attributes scale (RoSAS) is an 18-item measure used to assess the social perception of robots (Carpinella et al. in ACM/IEEE International Conference on Human-Robot Interaction, 2017:254–262). The full scale has sound psychometric properties, but its length makes it suboptimal for use in many studies of human-robotic interaction (HRI). Here, we report the development of a shortened form of the RoSAS (the RoSAS-SF), a 6-item scale useful for assessing judgments of warmth (compassionate, social), competence (competent, reliable), and discomfort (scary, awkward) toward robots. Across two studies, the psychometric properties of the RoSAS-SF are compared with the full RoSAS using participants’ judgments of both synthetic and real images of robots. Results indicate that the RoSAS-SF yields patterns of trait inferences and effect sizes comparable to the original scale. Moreover, confirmatory factor analyses reveal that the RoSAS-SF offers acceptable model fit with a 3-factor solution. One notable finding is that the discomfort subscale showed variable reliability in capturing responses across different robot types, suggesting caution in relying upon the RoSAS-SF as an exclusive measure of this judgment dimension. Applications, advantages, and recommendations for using the RoSAS-SF in HRI research are discussed

Mechatronics · Perception · Robot · Robotics · AI in Service Interactions · Computer Science · Psychology · Psychology of Moral and Emotional Judgment · Social Robot Interaction and HRI · Artificial Intelligence

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