Relational AI: Creating long-term interpersonal interaction, rapport, and relationships with social robots
Children are now growing up with AI-enabled, socially interactive technology. As such, we need to deeply understand how children perceive, interact, and relate to this kind of technology. To this end, I explore questions about young children’s interactions and relationships with one such technology—social robots—during language learning activities. Through a series of nine empirical child-robot interaction studies involving 347 children and using both teleoperated and autonomous robots, I establish the role of social robots as a relational technology—that is, a technology that can build long-term, social-emotional relationships with users. I hypothesize that a key aspect of why social robots can benefit children’s learning is their social and relational nature. To that end, I demonstrate the capabilities of social robots as learning companions for young children that afford opportunities for social engagement and reciprocal interaction, particularly peer-to-peer mirroring. I discuss how we can understand children’s conceptualizations of social robots as relational agents and measure children’s relationships over time. I introduce the term relational AI to refer to autonomous relational technologies that change through time.Through testing an autonomous relational AI system in a longitudinal study with 49 children, I explore connections between children’s relationship and rapport with the robot and their engagement and learning. I discuss the ethical use and design implications of relational AI. I show that relational AI is a new, powerful educational tool, unlike any other existing technology, that we can leverage to support children’s early education and development.