This post is coming a bit late, but a few months back some colleagues and I submitted a journal article manuscript to the ACM Transactions on Interactive Intelligent Systems (TiiS) special issue on Trust and Influence in Intelligent Human-Machine Interaction. We're really excited about this piece and hope to hear back about it soon.
Baker, T., Phillips, E., Ullman, D., & Keebler, J. (Submitted). Toward an understanding of trust repair in human-robot interaction: Current research and future directions. Transactions on Interactive Intelligent Systems
Title: Toward an Understanding of Trust Repair in Human-Robot Interaction: Current Research and Future Directions
Abstract
Traditional notions of robots operating in settings removed from people are no longer true. In fact, robots are increasingly being deployed in environments and roles that require complex social interactions with humans. Therefore, the importance of human-robot interaction (HRI) research is also growing. The implementation of human-robot teams continues to increase as technology develops in tandem with the state of HRI research. Trust, a major component of much human interaction, is an important facet of HRI as well. However, little studied in the HRI literature are the ideas of trust repair and trust violations. Trust repair is the activity of rebuilding trust after one party breaks the trust of another. These trust breaks are referred to as trust violations. As HRI becomes widespread, so will trust violations, so a clear understanding of the process of HRI trust repair must be developed in order to ensure that a human-robot team can continue to perform well after trust is violated. Prior research on human-automation trust and human-human trust can serve as starting places for exploring trust repair in HRI. Although existing models of human-automation and human-human trust are helpful, they do not account for some of the complexities of building and maintaining trust in unique relationships of humans and robots. As such, the purpose of this paper is to provide a foundation for exploring human-robot trust repair by drawing upon prior work in the human-robot and human-human trust literature, and we conclude with recommendations for advancing this body of work.
