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Ascribing gender to a social robot

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DOI

Gender ascription to robots may lead to willingly or inadvertently repeating gender stereotypes. To reduce this risk, it is important to delineate how gender is spontaneously assigned to robots. The present study explores spontaneous ascription of gender to a social robot with minimal visual gender cues. A total of N=63 participants partook and were engaged in interaction with the robot for 45-50 minutes. The majority (n=36) ascribed gender to the robot, mainly based on voice. The remaining participants still assigned mental capacities to the robot. The implications of the results are discussed.

Original languageEnglish
Title of host publicationCulturally Sustainable Social Robotics - Proceedings of Robophilosophy 2020 : Proceedings of Robophilosophy 2020 August 18–21, 2020, Aarhus University and online
EditorsMarco Nørskov, Johanna Seibt, Oliver Santiago Quick
Number of pages10
Place of publicationAmsterdam
PublisherIOS Press
Publication year2020
Pages247-256
ISBN (print)978-1-64368-154-2
ISBN (electronic)978-1-64368-155-9
DOIs
Publication statusPublished - 2020
EventRobophilosophy 2020 - Aarhus University and online, Denmark
Duration: 18 Aug 202021 Aug 2020

Conference

ConferenceRobophilosophy 2020
LandDenmark
ByAarhus University and online
Periode18/08/202021/08/2020
SeriesFrontiers in Artificial Intelligence and Applications
Volume335
ISSN0922-6389

    Research areas

  • Gender, individual differences, social robots

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