Nuts and Bolts About You: Finding the Right Match in Gendered Robots

Abstract

Robotic systems are becoming more relevant in our daily lives. Robots are built in such a way that manufacturers hope consumers will feel comfortable integrating the robot into their everyday lives. Companies take into account physical traits, social cues, and responses given by the robot, to design a system that is fit for the task at hand. Many robots are built without consideration of gender and how that could affect users’ perceptions of the robots. In the present study, participants were shown a video in which a robot walked to a box, picked it up, and placed it on the table, while narrating what it was doing. Robot body, gait, and voice were manipulated, independently of one another, to reflect masculine or feminine features. The users’ perceptions of gender were measured, along with trust in the system, amount of liking, and perceived competence of the robot. Finally, participants were shown pictures of eight different robots of ambiguous form and were asked to indicate perceived gender on a continuum from “very feminine” to “very masculine”. Results indicated that robot voice strongly predicted perceptions of gender, whereas the body and gait of the robot did not. Additionally, participants ranked the Amazon Echo as being the most feminine of the eight additional robots shown, despite having no obvious feminine physical characteristics.