Nonverbal leakage in robots

Abstract

Human communication involves a number of nonverbal cues that are seemingly unintentional, unconscious, and automatic-both in their production and perception-and convey rich information on the emotional state and intentions of an individual. One family of such cues is called "nonverbal leakage." In this paper, we explore whether people can read nonverbal leakage cues-particularly gaze cues-in humanlike robots and make inferences on robots' intentions, and whether the physical design of the robot affects these inferences. We designed a gaze cue for Geminoid-a highly humanlike android-and Robovie-a robot with stylized, abstract humanlike features-that allowed the robots to "leak" information on what they might have in mind. In a controlled laboratory experiment, we asked participants to play a game of guessing with either of the robots and evaluated how the gaze cue affected participants' task performance. We found that the gaze cue did, in fact, lead to better performance, from which we infer that the cue led to attributions of mental states and intentionality. Our results have implications for robot design, particularly for designing expression of intentionality, and for our understanding of how people respond to human social cues when they are enacted by robots.