Analysis of Gender Stereotypes for the Design of Service Robots
Zixuan Wang, Jiawen Huang, Costa Fiammetta
Abstract
Service robots are entering all kinds of business areas, and the outbreak of COVID-19 speeds up their application. Many studies have shown that robots with matching gender-occupational roles receive larger acceptance. However, this can also enlarge the gender bias in society. In this paper, we identified gender norms embedded in service robots by iteratively coding 67 humanoid robot images collected from the Chinese e-commerce platform Alibaba. We then generated four-step guidance for designers to identify and challenge the gender norms in the robot design. Our research provides both the fundamental grounding and practical guidance for designing catering robots that challenge gender norms and promote social equality.