Leveraging Social Judgment Theory to Examine the Relationship between Social Cues and Signals in Human-Robot Interactions

Abstract

Human-robot interaction (HRI) research requires new techniques for understanding the social dynamics that occur at the interface between humans and robots. Prior work has focused on incorporating the social cues and social signals distinction from the field of social signal processing and complementing this with recent advances in understanding human social cognition that specify two primary types of cognitive processes. A related account, stemming from Social Judgment Theory (SJT), specifies a Lens Model for which cues can be interpreted as well as the task conditions that would induce either of the types of cognitive processes. Surprisingly, SJT-based research has not yet examined the social cue and signal relationship. We argue it provides an ideal path forward for such research and we integrate these related disciplines of study to provide a theoretically derived account that can be useful for both the design of humanhuman and HRI experiments focused on social interaction dynamics.