Ingroup Categorization of Robots Is Affected by Self-Cognitions and Level of Anthropomorphism

Objective: The purpose of this work was to examine the relationship between self-concept and ingroup/outgroup categorization of robots. Background: Social psychological literature can improve Human–Robot Interaction (HRI) through investigations about cultural differences, intergroup dynamics, and more. Parallel to human–human interaction, people categorize robots as ingroup (“my group”) or outgroup (“not my group”) based on a myriad of variables. They favor ingroup robots by viewing them as more positive and human-like versus outgroup robots or humans. Previous work has examined the effect of robot anthropomorphism (i.e., human-likeness) on this categorization process with diverse findings. Method: Examining the self-concept via the two-baskets theory of self-cognitions, we compared the ingroup categorization of Humans, Machine-like robots, Medium Human-like robots, and High Human-like robots using a simple categorization task. Results: Results indicate that robots and human are categorized to the ingroup correlating with the uncanny valley effect, with humans being most likely to the ingroup followed by Medium Human-like, Machine-like, and High Human-like. Conclusions: Self-concept may not be as important for categorization as other factors; however, important categorization differences exist following the trend of the uncanny valley. Application: Those who design and utilize robots should take categorization differences into consideration when designing robots for public interactions. Further, those who purchase robots for use should be careful to consider the implications of visual similarities to human beings to ensure optimal acceptance OSF: ( https://osf.io/x9rqn/?view_only=fd0894404e304422a6c77ccffa013bcd ). Precis: Considering the uncanny valley, we examine the social categorization of humans and robots and the relation of this categorization to the self-concept in the form of self-cognitions. Results demonstrate important differences in the categorization of various types of human and robot images based strongly on the uncanny valley effect.