Ascribing Gender to a Social Robot

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.