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Ascribing Gender to Social Robots

Pre-recorded talk | DESIGN

This video is not available any longer from this site; check the author’s personal websites for any additional postings;  the paper will appear in the RP2020 Proceedings in December

Authors

Malene Flensborg Damholdt, Aarhus University (DK)

 

Malene Flensborg Damholdt is a psychologist and an associate professor at the Department of Clinical Medicine, Aarhus University. Her research focuses on the effect of individual differences on human-robot interactions, interdisciplinary methodology and development of new research methods in robotics.

Christina Vestergaard, Aarhus University (DK)

 

Christina Vestergaard is a postdoctoral at the Department of Philosophy and the History of Ideas, University of Aarhus. She is an anthropologist with research interests is interdisciplinary methodology, anthropology of technology, and robo-philosophy.

Abstract

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.