Looking good? Appearance preferences and robot personality inferences at zero acquaintance

Dag Sverre Syrdal, Kerstin Dautenhahn, Sarah N. Woods, Michael L. Walters, Kheng Lee Koay

Research output: Chapter in Book/Report/Conference proceedingConference contribution

50 Citations (Scopus)

Abstract

The study presented in this paper explored the relationships between participant personality, perceived robot personality and preferences for particular robot appearances. The participants (N=77) watched 3 videos of a HRI situation in which the appearance of the robot was altered to appear more or less anthropomorphic. Participant personality was assessed using the Big Five Domain Scale, while Robot Personality was measured using 5 items based on the traits from the Big Five Model. The results reveal that low Emotional Stability and Extraversion scores are related to preferences for mechanical robot appearances. Results for perceived robot personality suggest that participants clearly differentiated between the different robots on the dimensions of Extraversion, Agreeableness and Intelligence, but did not differentiate strongly between them on the Emotional Stability dimension. Compilation copyright

Original languageEnglish
Title of host publicationMultidisciplinary Collaboration for Socially Assistive Robotics - Papers from the 2007 AAAI Spring Symposium, Technical Report
Pages86-92
Number of pages7
Publication statusPublished - 28 Dec 2007
Event2007 AAAI Spring Symposium - Stanford, CA, United States
Duration: 26 Mar 200728 Mar 2007

Publication series

NameAAAI Spring Symposium - Technical Report
VolumeSS-07-07

Conference

Conference2007 AAAI Spring Symposium
Country/TerritoryUnited States
CityStanford, CA
Period26/03/0728/03/07

Keywords

  • Anthropomorphism
  • Human robot interaction
  • Personality
  • Robot appearance
  • Robot personality
  • Social robotics
  • Video trials

Fingerprint

Dive into the research topics of 'Looking good? Appearance preferences and robot personality inferences at zero acquaintance'. Together they form a unique fingerprint.

Cite this