Trustworthy Conflict Resolution in Human-Robot Interactions: Effects of Automation and Explainability

Abstract

TRUST in human-robot interactions (HRI) is essential for effective collaboration and user acceptance of robotic systems. However, trust can be challenged by conflicting goals between the user and the system, such as in the context of proxemics when a robot invades a human’s personal space. As robotic systems increasingly adapt their actions autonomously, intelligent conflict resolution is necessary to not undermine humans’ trust in the robot’s decisions due to a decreased sense of control and understanding. Therefore, this study investigates how humans can be involved and supported during automated conflict resolution to maintain their trust by exploring different degrees of explainability and automation. We applied a within-subjects experimental design, where 20 participants experienced four conditions varying in levels of automation and explainability during a simulated conflict between their need to preserve their personal space and the robot’s requirement to approach to perform a task. We measured the participants’ trust through questionnaires and interviews. Our findings suggest that trust is positively influenced by the level of control users have during conflict situations. However, the robot’s explanations did not significantly impact trust. Our insights highlight the need for conflict management strategies in HRI that balance automation with user involvement to foster greater levels of trust when collaborating with robots.