Physical and Moral Disgust in Socially Believable Behaving Systems in Different Cultures

Abstract

The aim of the present study is to use the GRID, online emotions sorting and corpus methodologies to illuminate different types of disgust that an emotion-sensitive socially interacting robot would need to encode and decode in order to competently produce and recognise these and other types of physical, moral and aesthetic types of complex emotions in social settings. We argue that emotions in general, and different types of disgust as an instance of these, differ with respect to the amount of cognitive grounding they need in order to arise and social robots will successfully use such emotions provided they do not only recognise and produce physical, bodily manifestations of emotions, but also have access to large knowledge bases and are able to process situational context clues. The different types of disgust are identified and compared cross-culturally to provide an evaluation of their relative salience. The study also underscores the conceptual viewpoint of emotions as clusters of emotions rather than solitary, individual representations. We argue that such clustering should be at the heart of emotions modelling in social robots. In order to successfully use the emotion of disgust in their interactions with humans, robots need to be sensitive to possible within-culture and cross-culture differences pertaining to such emotions, exemplified by British English and Polish in the present study. Given the centrality of values to the emotion of disgust, robots need to have the capacity to update from a knowledge base and learn from the situational context the set of values for each significant human that they interact with.