Don’t overthink: fast decision making combined with behavior variability perceived as more human-like
Serena Marchesi, Jairo Pérez-Osorio, Davide De Tommaso, Agnieszka Wykowska
Abstract
Understanding the human cognitive processes involved in the interaction with artificial agents is crucial for designing socially capable robots. During social interactions, humans tend to explain and predict others' behavior adopting the intentional stance, that is, assuming that mental states drive behavior. However, the question of whether humans would adopt the same strategy with artificial agents remains unanswered. The present study aimed at identifying whether the type of behavior exhibited by the robot has an impact on the attribution of mentalistic explanations of behavior. We employed the Instance Questionnaire (ISQ) pre and post-observation of two types of behavior (decisive or hesitant). The ISQ probes participants' stance towards a humanoid robot by requiring them to choose the likelihood of an explanation (mentalistic vs. mechanistic) of iCub depicted in sequences of photographs. We found that decisive behavior, with rare and unexpected "hesitant" behaviors, lead to more mentalistic attributions relative to primarily hesitant behavior. Findings suggest that higher expectations regarding the robots' capabilities and unexpected actions might lead to more mentalistic descriptions.