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The (Fe)male Robot: How Robot Body Shape Impacts First Impressions and Trust Towards Robots

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Abstract

Humanlikeness, including robot gender, impacts people’s impression of social robots (Eyssel and Hegel in J Appl Soc Psychol 42(9):2213–2230, 2012) and actual human robot interaction (HRI) (Kuchenbrandt et al. in Int J Soc Robot 6(3):417–427, 2014; Reich-Stiebert and Eyssel in Proceedings of the 2017 ACM/IEEE international conference on human–robot interaction, ACM, pp 166–176, 2017). Although robot gender has been manipulated in various ways in previous research (Alexander et al. in Proceedings of the annual meeting of the Cognitive Science Society, vol 36, 2014; Eyssel and Hegel, 2012), robot body shape as a gender cue has been neglected in this context. Therefore, the current research investigated the effects of manipulating a robot torso’s waist-to-hip ratio and shoulder width on social judgments of a robot. As hypothesized, a robot with a female body shape was perceived as more communal, it was preferred for stereotypically female tasks, and evoked more cognitive and affective trust than a robot with a male body shape. Unexpectedly, both robot types were perceived as equally agentic and they were deemed equally suitable for stereotypically male tasks. Above and beyond, participants’ motivation to respond in a socially desirable manner, their societal beliefs about agentic and communal traits considered appropriate for men and women, sexist attitudes, gender, and technology commitment affected their impression formation about robots. We point to the risks of designing gendered robots and recommend to manipulate robot gender deliberately with regard to the effects this might have on HRI.

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Acknowledgements

This research 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). The current research was approved by Bielefeld University’s local Ethics Committee. We report all data exclusions (if any), all manipulations, all measures in the study, and how sample sizes were calculated. The authors declare to have no conflicts of interest.

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  1. Cluster of Excellence Cognitive Interaction Technology (CITEC), Bielefeld University, Inspiration 1, 33619, Bielefeld, Germany

    Jasmin Bernotat, Friederike Eyssel & Janik Sachse

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  1. Jasmin Bernotat
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  2. Friederike Eyssel
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  3. Janik Sachse
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Correspondence to Jasmin Bernotat.

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Bernotat, J., Eyssel, F. & Sachse, J. The (Fe)male Robot: How Robot Body Shape Impacts First Impressions and Trust Towards Robots. Int J of Soc Robotics 13, 477–489 (2021). https://doi.org/10.1007/s12369-019-00562-7

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