Human-robot interactions are becoming prevalent in a varied number of fields, with trust being essential for efficient collaboration between humans and robots. Robots, just like humans, are bound to make mistakes leading to a violation of trust. Research investigating how to repair this broken trust has produced mixed results. This work investigates the effects of five communicative trust repair strategies (apology, denial, explanation, compensation, and silence) on participants’ trust in the robot, following trust violations of two kinds (moral and performance violation). In an online between-subjects experiment, participants engaged in a collaborative task with a robot that repeatedly committed trust violating acts and responded with a repair message. The findings indicate the higher severity of moral violations on moral trust and willingness to collaborate in the future, with compensation showing to be the most effective repair strategy, enhancing trust and willingness to collaborate, while also reducing discomfort. This work advances the understanding of trust relationships in collaborative HRI contexts.

The growing implementation of robots in societal contexts necessitates a deeper exploration of the dynamics of trust between humans and robots. This exploration should expand beyond traditional viewpoints that primarily emphasize the influence of robot performance. In the burgeoning area of social robotics, fine-tuning a robot’s personality traits is increasingly recognized as a crucial element in shaping users’ experiences during human-robot interaction (HRI). Research in this field has led to the creation of trust scales that encompass various trust dimensions in HRI. These scales include aspects related to performance as well as moral dimensions. Our previous study revealed that breaches of moral trust by robots impact human trust more negatively than performance trust breaches, and humans take retaliatory approaches in response to morality breaches by robots. In the present study, our main aim was to explore if trust loss and retaliation tendencies differ based on the identity of the teammates following the violations of these different trust aspects. Through multiple versions of an online search task, we examined our research questions and found that breaches of morality by robotic teammates cause a significantly higher trust loss in humans compared to human teammates. These findings highlight the importance of a robot’s morality in determining how humans view a robot’s trustworthiness. For effective robot design, robots must meet ethical and moral standards, which are higher than the ethical and moral standards expected from humans.

The increasing use of robots in social applications requires further research on human-robot trust. The research on human-robot trust needs to go beyond the conventional definition that mainly focuses on how human-robot relations are influenced by robot performance. The emerging field of social robotics considers optimizing a robot’s personality a critical factor in user perceptions of experienced human-robot interaction (HRI). Researchers have developed trust scales that account for different dimensions of trust in HRI. These trust scales consider one performance aspect (i.e., the trust in an agent’s competence to perform a given task and their proficiency in executing the task accurately) and one moral aspect (i.e., trust in an agent’s honesty in fulfilling their stated commitments or promises) for human-robot trust. The question that arises here is to what extent do these trust aspects affect human trust in a robot? The main goal of this study is to investigate whether a robot’s undesirable behavior due to the performance trust violation would affect human trust differently than another similar undesirable behavior due to a moral trust violation. We designed and implemented an online human-robot collaborative search task that allows distinguishing between performance and moral trust violations by a robot. We ran these experiments on Prolific and recruited 100 participants for this study. Our results showed that a moral trust violation by a robot affects human trust more severely than a performance trust violation with the same magnitude and consequences.