Shape It – The Influence of Robot Body Shape on Gender Perception in Robots

  • Jasmin Bernotat
  • Friederike Eyssel
  • Janik Sachse
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10652)


Previous research has shown that gender-related stereotypes are even applied to robots. In HRI, a robot’s appearance, for instance, visual facial gender cues such as hairstyle of a robot have successfully been used to elicit gender-stereotypical judgments about male and female prototypes, respectively. To complement the set of features to visually indicate a robot’s gender, we explored the impact of waist-to-hip ratio (WHR) and shoulder width (SW) in robot prototypes. Specifically, we investigated the effect of male vs. female appearance on perceived robot gender, the attribution of gender stereotypical traits, the robots’ suitability for stereotypical tasks, and participants’ trust toward the robots. Our results have demonstrated that the manipulation of WHR and SW correctly elicited gendered perceptions of the two prototypes. However, the perception of male robot gender did not affect the attribution of agentic traits and cognitive trust. Nevertheless, participants tended to rate the male robot as more suitable for stereotypically male tasks. In line with our predictions, participants preferred to use the female robot shape for stereotypically female tasks. They tended to attribute more communal traits and showed more affective trust toward the robot that was designed with a female torso versus a male robot torso. These results demonstrate that robot body shape activates stereotypes toward robots. These in turn, deeply impact people’s attitudes and trust toward robots which determine people’s motivation to engage in HRI.


Robot body shape Gender Gender stereotypes Cognitive and affective trust in HRI 



This research has been conducted in the framework of the European Project CODEFROR (FP7 PIRSES-2013-612555) and was supported by the Cluster of Excellence Cognitive Interaction Technology ‘CITEC’ (EXC 277) at Bielefeld University, which is funded by the German Research Foundation (DFG). We report all data exclusions, all manipulations, and all measures in the study.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jasmin Bernotat
    • 1
  • Friederike Eyssel
    • 1
  • Janik Sachse
    • 1
  1. 1.Cluster of Excellence Cognitive Interaction Technology (CITEC)Bielefeld UniversityBielefeldGermany

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