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Ascribing gender to a social robot

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review


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
ISBN (print)978-1-64368-154-2
ISBN (electronic)978-1-64368-155-9
Publication statusPublished - 2020
EventRobophilosophy 2020 - Aarhus University and online, Denmark
Duration: 18 Aug 202021 Aug 2020


ConferenceRobophilosophy 2020
ByAarhus University and online
SeriesFrontiers in Artificial Intelligence and Applications

    Research areas

  • Gender, individual differences, social robots

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ID: 210933985