Three Strikes and you are out!: The impacts of multiple human–robot trust violations and repairs on robot trustworthiness

Robots like human co-workers can make mistakes violating a human's trust in them. When mistakes happen, humans can see robots as less trustworthy which ultimately decreases their trust in them. Trust repair strategies can be employed to mitigate the negative impacts of these trust violations. Yet, it is not clear whether such strategies can fully repair trust nor how effective they are after repeated trust violations. To address these shortcomings, this study examined the impact of four distinct trust repair strategies: apologies, denials, explanations, and promises on overall trustworthiness and its sub-dimensions: ability, benevolence, and integrity after repeated trust violations. To accomplish this, a between-subjects experiment was conducted where participants worked with a robot co-worker to accomplish a task. The robot violated the participant's trust and then provided a particular repair strategy. Results indicated that after repeated trust violations, none of the repair strategies ever fully repaired trustworthiness and two of its sub-dimensions: ability and integrity. In addition, after repeated interactions, apologies, explanations, and promises appeared to function similarly to one another, while denials were consistently the least effective at repairing trustworthiness and its sub-dimensions. In sum, this paper contributes to the literature on human–robot trust repair through both of these original findings.