Gender and Robots: A Literature Review

TL;DR

This literature review examines how gender influences human interactions with social robots, revealing default perceptions of robots as male, gender stereotype absorption, and gender differences in engagement, while highlighting open research questions.

Contribution

It provides a comprehensive analysis of 46 empirical studies on gender effects in social robot interactions and offers guidelines for future gender-inclusive research.

Findings

Robots are generally perceived as male by default

Robots tend to absorb human gender stereotypes

Men tend to engage more with robots than women

Abstract

Here, I ask what we can learn about how gender affects how people engage with robots. I review 46 empirical studies of social robots, published 2018 or earlier, which report on the gender of their participants or the perceived or intended gender of the robot, or both, and perform some analysis with respect to either participant or robot gender. From these studies, I find that robots are by default perceived as male, that robots absorb human gender stereotypes, and that men tend to engage with robots more than women. I highlight open questions about how such gender effects may be different in younger participants, and whether one should seek to match the gender of the robot to the gender of the participant to ensure positive interaction outcomes. I conclude by suggesting that future research should: include gender diverse participant pools, include non-binary participants, rely on self-identification for discerning gender rather than researcher perception, control for known covariates of gender, test for different study outcomes with respect to gender, and test whether the robot used was perceived as gendered by participants. I include an appendix with a narrative summary of gender-relevant findings from each of the 46 papers to aid in future literature reviews.