Female chatbots are helpful, male chatbots are competent?

Abstract Chatbots have in recent years increasingly been used by organizations to interact with their customers. Interestingly, most of these chatbots are gendered as female, displaying stereotypical notions avatars, profile pictures and language. Considering the harmful effects associated gender-based stereotyping at a societal level—and particular detrimental women—it is crucial understand such when transferred perpetuated chatbots. The current study draws on Stereotype Content Model (SCM) explores how warmth (high vs. low) chatbot’s language assigned gender elicit stereotypes that affect perceived trust, helpfulness, competence chatbot. In doing so, this shows established stereotype theory can be framework for human-machine communication research. Moreover, its results serve foundation explore ways mitigating perpetuation bring forward broader discussion ethical considerations communication.