Abstract
Recent advances in the areas of human-robot interaction (HRI) and robot autonomy are changing the world. Today robots are used in a variety of applications. People and robots work together in human autonomous teams to accomplish tasks that, separately, cannot be easily accomplished. Trust between robots and humans in teams is vital to task completion and effective team cohesion. For the optimal performance and safety of human teammates, their level of trust should be adjusted to the performance of the robotic system. The method of adjusting levels of human trust by a robot is called trust calibration. The cost of poor trust calibration in HRI, is at a minimum, low performance, and at higher levels it causes human injury or critical task failures. A robot is able to calibrate trust through policies that use trust calibration cues (TCCs). Verbal cues are often used to help calibrate trust. In this experiment we test the difference between two verbal TCCs, an apology and a denial. Both of which were meant to repair trust that the robot lost during the course of a search and rescue teaming situation. This study included 219 participants whom were spilt across 6 search and rescue (S &R) simulations. The simulations were composed of two different multi-round interaction games to study the effectiveness of competence violations and moral violations were created to simulate these different trust violations. While most of the TCCs were shown to be ineffective at significantly increasing the amount of trust in the robot after a trust violations. The use of a apology when the robot was being selfish was shown to be effective.
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Khavas, Z. R., S. Ahmadzadeh, S. R.: Do humans trust robots that violate moral-trust? unpublished
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Perkins, R., Khavas, Z.R., McCallum, K., Kotturu, M.R., Robinette, P. (2022). The Reason for an Apology Matters for Robot Trust Repair. In: Cavallo, F., et al. Social Robotics. ICSR 2022. Lecture Notes in Computer Science(), vol 13818. Springer, Cham. https://doi.org/10.1007/978-3-031-24670-8_56
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