Social signals, such as changes in gaze direction, are essential cues to predict others’ mental states and behaviors (i.e., mentalizing). Studies show that humans can mentalize with non-human agents when they perceive a mind in them (i.e., mind perception). Robots that physically and/or behaviorally resemble humans likely trigger mind perception, which enhances the relevance of social cues and improves social-cognitive performance. The current ex-periments examine whether the effect of physical and behavioral influencers of mind perception on social-cognitive processing is modulated by the lifelikeness of a social interaction. Participants interacted with robots of varying degrees of physical (humanlike vs. robot-like) and behavioral (reliable vs. random) human-likeness while the lifelikeness of a social attention task was manipulated across five experiments. The first four experiments manipulated lifelikeness via the physical realism of the robot images (Study 1 and 2), the biological plausibility of the social signals (Study 3), and the plausibility of the social con-text (Study 4). They showed that humanlike behavior affected social attention whereas appearance affected mind perception ratings. However, when the lifelikeness of the interaction was increased by using videos of a human and a robot sending the social cues in a realistic environment (Study 5), social attention mechanisms were affected both by physical appearance and behavioral features, while mind perception ratings were mainly affected by physical appearance. This indicates that in order to understand the effect of physical and behavioral features on social cognition, paradigms should be used that adequately simulate the lifelikeness of social interactions.
Visual Non-verbal Social Cues Data Modeling