When Robots Say No: Temporal Trust Recovery Through Explanation

TL;DR

This study shows that providing explanations for robot refusals during high-stakes tasks can help recover user trust over time, despite initial trust drops after refusals.

Contribution

It demonstrates that explanations can effectively mitigate trust violations in human-robot teams during critical missions.

Findings

Trust drops after robot declines help initially.

Providing explanations improves trust recovery over time.

Trust variability is significant during high-stakes tasks.

Abstract

Mobile robots with some degree of autonomy could deliver significant advantages in high-risk missions such as search and rescue and firefighting. Integrated into a human-robot team (HRT), robots could work effectively to help search hazardous buildings. User trust is a key enabler for HRT, but during a mission, trust can be damaged. With distributed situation awareness, such as when team members are working in different locations, users may be inclined to doubt a robot's integrity if it declines to immediately change its priorities on request. In this paper, we present the results of a computer-based study investigating on-mission trust dynamics in a high-stakes human-robot teaming scenario. Participants (n = 38) played an interactive firefighting game alongside a robot teammate, where a trust violation occurs owing to the robot declining to help the user immediately. We find that when the robot provides an explanation for declining to help, trust better recovers over time, albeit following an initial drop that is comparable to a baseline condition where an explanation for refusal is not provided. Our findings indicate that trust can vary significantly during a mission, notably when robots do not immediately respond to user requests, but that this trust violation can be largely ameliorated over time if adequate explanation is provided.