Creating Genuinely Interesting Conversational Partners
Conversational agents and digital assistants are increasingly becoming part of our lives. However, current agents are usually dry data delivery mechanisms bereft of any of the charm or wit that we prize within human interlocutors. What does it take to create conversational agents that can be genuinely interesting conversational partners? I suggest that the function of human conversation is not to deliver useful information, but to display mind-reading and perspective-taking abilities–to demonstrate ourselves to be astute socio-political actors. This can be achieved through showing we know another person's goals and desires, and by empathising and understanding. It can also be done through the creative demonstration of an ability to combine concepts in the minds of other that they had not yet noticed were related–using analogy, humour, and story-telling. Therefore, to create engaging conversational agents we must focus on the development of these empathic and creative abilities. We need to ensure that agent models can develop conversational common ground, emotional connection and empathy, and be creative and humorous. These are not simple tasks but they are necessary if digital agents are to become truly engaging conversational partners capable of developing longer term relationships with humans that humans seek to sustain.
Gary McKeown is a senior lecturer and social psychologist in the School of Psychology, Queens University Belfast. He has a primary research and theoretical interest in human communication and social interaction. His research profile is interdisciplinary with both theoretical, experimental and methodological papers in psychology journals and also many within the domains of social signal processing and affective computing. Often this research involves understanding natural human communication to inform the development of embodied conversational agents. Building on a long history of emotion and affective computing research in the School of Psychology – including the HUMAINE network, he had important roles in the SEMAINE, ILHAIRE project and within the SSPNet network. He has produced a theoretical account of the evolution of human communication with a particular emphasis on mind-reading and perspective-taking known as the Analogical Peacock Hypothesis; this has led to research work in understanding laughter, humour and storytelling. His research interests have led to many collaborations with non-academic partners, particularly commercial and industrial partnerships for the transfer of knowledge and techniques to commercial settings. From a methodological perspective, the fields of social signal processing and affective computing address challenging data collection issues from a behavioural science stance–often using dynamic scenarios with multiple streams of synchronised information. This requires new ways of thinking about data and novel statistical approaches to develop analyses that can usefully address social science questions. Dr McKeown has been actively involved in the creation of both new data gathering techniques and the statistical approaches required to address them.