Abstract
Social interactions entail often complex and dynamic situations that follow non-explicit, unwritten rules. Comprehending those signals and knowing how to respond becomes the key to the success of any social communication. Thus, in order to integrate a robot into a social context it should be capable of (at least) understanding others’ emotional states. Nonetheless, mastering such skill is beyond reach for current robotics which is why we introduce the single internal state which we believe reveals the most regarding interactive communications. We named it Comfortability and defined it as (disapproving of or approving of) the situation that arises as a result of a social interaction which influences one’s own desire of maintaining or withdrawing from it.
Consequently, in this paper we aim to show that Comfortability can be evoked by robots, investigating at the same time its connection with other emotional states. To do that, we performed two online experiments on 196 participants asking them to imagine being interviewed by a reporter on a sensitive topic. The interviewer’s actions were presented in two different formats: the first experiment (the Narrative Context) presented the actions as text; whereas the second experiment (the Visual Context) presented the actions as videos performed by the humanoid robot iCub. The actions were designed to evoke different Comfortability levels. According to the experimental results, Comfortability differs from the other reported emotional and affective states and more importantly, it can be evoked by both, humans and robots in an imaginary interaction.
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Acknowledgements
Alessandra Sciutti is supported by a Starting Grant from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program. G.A. No. 804388, wHiSPER.
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Redondo, M.E.L., Vignolo, A., Niewiadomski, R., Rea, F., Sciutti, A. (2020). Can Robots Elicit Different Comfortability Levels?. In: Wagner, A.R., et al. Social Robotics. ICSR 2020. Lecture Notes in Computer Science(), vol 12483. Springer, Cham. https://doi.org/10.1007/978-3-030-62056-1_55
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