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Congruency Matters - How Ambiguous Gender Cues Increase a Robot’s Uncanniness

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Social Robotics (ICSR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9979))

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Abstract

Most research on the uncanny valley effect is concerned with the influence of human-likeness and realism as a trigger of an uncanny feeling in humans. There has been a lack of investigation on the effect of other dimensions, for example, gender. Back-projected robotic heads allow us to alter visual cues in the appearance of the robot in order to investigate how the perception of it changes. In this paper, we study the influence of gender on the perceived uncanniness. We conducted an experiment with 48 participants in which we used different modalities of interaction to change the strength of the gender cues in the robot. Results show that incongruence in the gender cues of the robot, and not its specific gender, influences the uncanniness of the back-projected robotic head. This finding has potential implications for both the perceptual mismatch and categorization ambiguity theory as a general explanation of the uncanny valley effect.

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Acknowledgements

Thanks to Lars Oestreicher for providing the two rightmost images of Fig. 1. C. Peters’ work is partly supported by the European Commission (EC) Horizon 2020 ICT 644204 project ProsocialLearn. The authors are solely responsible for the content of this publication. It does not represent the opinion of the EC, and the EC is not responsible for any use that might be made of data appearing therein.

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Authors and Affiliations

  1. Department of Information Technology, Uppsala University, Uppsala, Sweden

    Maike Paetzel, Ingela Nyström & Ginevra Castellano

  2. KTH Royal Institute of Technology, Stockholm, Sweden

    Christopher Peters

Authors
  1. Maike Paetzel
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  2. Christopher Peters
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  3. Ingela Nyström
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  4. Ginevra Castellano
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Corresponding author

Correspondence to Maike Paetzel .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, The University of Kansas, Lawrence, Indiana, USA

    Arvin Agah

  2. Department of Mechanical Engineering, Qatar University, Doha, Qatar

    John-John Cabibihan

  3. School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA

    Ayanna M. Howard

  4. Department of Systems Engineering and Automation, University Carlos III de Madrid, madrid, Spain

    Miguel A. Salichs

  5. Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, Tennessee, USA

    Hongsheng He

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Paetzel, M., Peters, C., Nyström, I., Castellano, G. (2016). Congruency Matters - How Ambiguous Gender Cues Increase a Robot’s Uncanniness. In: Agah, A., Cabibihan, JJ., Howard, A., Salichs, M., He, H. (eds) Social Robotics. ICSR 2016. Lecture Notes in Computer Science(), vol 9979. Springer, Cham. https://doi.org/10.1007/978-3-319-47437-3_39

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  • DOI: https://doi.org/10.1007/978-3-319-47437-3_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47436-6

  • Online ISBN: 978-3-319-47437-3

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