Using Robot Social Agency Theory to Understand Robots’ Linguistic Anthropomorphism

Cloe Z Emnett and Terran Mott and Tom Williams

Companion Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction (HRI LBRs)

Robots' use of natural language is one of the key factors that leads humans to anthropomorphize them. But it is not yet well understood what types of language most lead to such language-based anthropomorphization (or, Linguistic Anthropomorphism). In this paper, we present a brief literature survey that suggests six broad categories of linguistic factors that lead humans to anthropomorphize robots: autonomy, adaptability, directness, politeness, proportionality, and humor. By contextualizing these six factors through the lens of Jackson and Williams' Theory of Social Agency for Human-Robot Interaction, we are able to show how and why these particular factors are those responsible for language-based robot anthropomorphism.