The Robot That Showed Remorse: Repairing Trust with a Genuine Apology

Abstract

In the current state-of-the-art, robots are bound to make errors in a human-robot interaction (HRI). Trust is one of the important concepts in HRI that is often lowered by these errors. Fortunately, research has shown there are strategies that can help rebuild trust. An apology made by the robot is one of those strategies. However, apologies can take different forms. We designed a study in which Nao first built trust with the users, then violated that trust by making a speech recognition error, and then tried to restore it by either an apology with display of remorse, without remorse, or no apology at all. The results showed expected trends; an apology with remorse in most cases rebuilt trust the strongest. Although the effect of the type of apology on the trusting beliefs were not significant, the effect on the trusting behaviours was found to be just significant. Suggestions for future research include repeating the study without its current limitations (small sample size, offline) and investigating the accuracy of the portrayed remorse by the robot.