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Social categorization of social robots: Anthropomorphism as a function of robot group membership

Authors

  • Friederike Eyssel,

    Corresponding author
    1. Cluster of Excellence in Cognitive Interaction Technology, University of Bielefeld, Germany
      Friederike Eyssel, Cluster of Excellence in Cognitive Interaction Technology, University of Bielefeld, Universitätsstr. 21–23, 33615 Bielefeld, Germany (e-mail: feyssel@cit-ec.uni-bielefeld.de).
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  • Dieta Kuchenbrandt

    1. Cluster of Excellence in Cognitive Interaction Technology, University of Bielefeld, Germany
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  • Parts of this research were presented as a poster at the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, Workshop on Cognitive Neuroscience Robotics. This research was funded by the German Research Council (COE 277).

Friederike Eyssel, Cluster of Excellence in Cognitive Interaction Technology, University of Bielefeld, Universitätsstr. 21–23, 33615 Bielefeld, Germany (e-mail: feyssel@cit-ec.uni-bielefeld.de).

Abstract

Previous work on social categorization has shown that people often use cues such as a person's gender, age, or ethnicity to categorize and form impressions of others. The present research investigated effects of social category membership on the evaluation of humanoid robots. More specifically, participants rated a humanoid robot that either belonged to their in-group or to a national out-group with regard to anthropomorphism (e.g., mind attribution, warmth), psychological closeness, contact intentions, and design. We predicted that participants would show an in-group bias towards the robot that ostensibly belonged to their in-group – as indicated by its name and location of production. In line with our hypotheses, participants not only rated the in-group robot more favourably – importantly, they also anthropomorphized it more strongly than the out-group robot. Our findings thus document that people even apply social categorization processes and subsequent differential social evaluations to robots.

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