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In this paper, we present a study aimed at understanding whether theembodiment and humanlikeness of an artificial agent can affect people'sspontaneous and instructed mimicry of its facial expressions. The studyfollowed a mixed experimental design and revolved around an emotion recognitiontask. Participants were randomly assigned to one level of humanlikeness(between-subject variable: humanlike, characterlike, or morph facial texture ofthe artificial agents) and observed the facial expressions displayed by a human(control) and three artificial agents differing in embodiment (within-subjectvariable: video-recorded robot, physical robot, and virtual agent). To studyboth spontaneous and instructed facial mimicry, we divided the experimentalsessions into two phases. In the first phase, we asked participants to observeand recognize the emotions displayed by the agents. In the second phase, weasked them to look at the agents' facial expressions, replicate their dynamicsas closely as possible, and then identify the observed emotions. In both cases,we assessed participants' facial expressions with an automated Action Unit (AU)intensity detector. Contrary to our hypotheses, our results disclose that theagent that was perceived as the least uncanny, and most anthropomorphic,likable, and co-present, was the one spontaneously mimicked the least.Moreover, they show that instructed facial mimicry negatively predictsspontaneous facial mimicry. Further exploratory analyses revealed thatspontaneous facial mimicry appeared when participants were less certain of theemotion they recognized. Hence, we postulate that an emotion recognition goalcan flip the social value of facial mimicry as it transforms a likableartificial agent into a distractor.

Does the Goal Matter? Emotion Recognition Tasks Can Change the Social Value of Facial Mimicry towards Artificial Agents