For the project “How people use theory of mind to explain robot behavior”, I have investigated whether people infer mental states such as beliefs, desires, and intentions to explain robotic agents’ behavior, just as they do for humans. As a first step in our research program, we ran a series of pretests. The goal was to create a pool of stimulus behaviors that are similarly judged on properties of behavior that influence people’s explanations, regardless of whether these behaviors were performed by humans or by robots. We were successful in developing a stimulus behavior pool that can be used to rigorously examine whether people explain robot and human behaviors in similar or distinct ways. However, in the course of identifying this robust set of behaviors, we also discovered several behaviors that showed markedly discrepant judgments on these properties of behavior (i.e., intentionality, surprisingness, and desirability). These results were published as a Late-Breaking-Report at HRI 2018. Below, you can find the full set of behavior stimuli.
By assessing several theories and models explaining and predicting the acceptance of technology, I have developed a theory-based model of social robot acceptance which was tested among the general Dutch population (n = 1168 participants) using structural equation modeling. The results show a strong role of normative believes that both directly and indirectly affect the anticipated acceptance of social robots for domestic purposes. Below, you can find the full theoretical model as well as the full survey with all items.