We investigated the role of humanization in Visual Perspective-Taking (VPT) by testing whether and how agent's human-likeness and attractiveness ('hedonic quality') interact with social cues (action and eye gaze) in influencing the participants' disposition to embody another's perspective. In a VPT task, participants viewed scenes displaying an actor (human or robotic) grasping, gazing (or both) a target object, or adopting a still posture, and were required to judge the left/right location of the target, without receiving any instruction on the perspective to be assumed. Across two studies we selected human and robotic agents to use as actors in the VPT task. Results consistently demonstrated that participants could be effectively clustered by a data-driven method into two perspective-taking styles, depending on the presence of a systematic tendency to locate the target object in the VPT scenarios from own (egocentric) or the actor's (altercentric) point of view. The human vs. non-human nature of the agent seemed able to affect the participants' egocentric or altercentric tendency whereas both the agent's hedonic quality and social cues were not able to influence this propensity. Identifying the factors influencing altercentrism during human-robot interactions can be essential for developing artificial agents favouring user's acceptance and willingness to interact. In this respect, considering differences among individuals in their propensity to take another's point of view may be of central importance. Clustering approaches can represent a useful means to capture interindividual differences in this central aspect of human social cognition.
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