Relational AI : creating long-term interpersonal interaction, rapport, and relationships with social robots
Author(s)Kory-Westlund, Jacqueline M.(Jacqueline Marie)
Relational artificial intelligence
Creating long-term interpersonal interaction, rapport, and relationships with social robots
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
MetadataShow full item record
Children are now growing up with Al-enabled, socially interactive technology. As such, we need to deeply understand how children perceive, interact, and relate to this kind of technology, especially given the many ethical concerns that arise in the context of human-machine interactions, most of which are most contentious with children. To this end, I explore questions about young children's interactions and relationships with one such technology--social robots-during language learning activities. Language learning is a ripe area for exploring these questions because of the social, interactive, interpersonal nature of the activity. In addition, literacy, language, and interpersonal skills are some of the most important skills any child will learn, as they can greatly impact children's later educational and life success.Through a series of 9 empirical child-robot interaction studies with 347 children and using both teleoperated and autonomous robots, I establish the role of social robots as relational technology-that is, 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.I develop a computational relational Al system to examine how using relational Al in a social robot can impact child-robot learning interactions. Through testing the autonomous 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 AL. 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.
Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2019Cataloged from PDF version of thesis.Includes bibliographical references (pages 266-294).
DepartmentProgram in Media Arts and Sciences (Massachusetts Institute of Technology)
Massachusetts Institute of Technology
Program in Media Arts and Sciences