Title | It Will Not Take Long! Longitudinal Effects of Robot Conflict Resolution Strategies on Compliance, Acceptance and Trust |
Publication Type | Conference Paper |
Year of Publication | 2022 |
Authors | Babel, Franziska, Hock, Philipp, Kraus, Johannes, Baumann, Martin |
Conference Name | 2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI) |
Date Published | mar |
Keywords | Behavioral sciences, Filling, Human Behavior, human factors, human-robot cooperation, Humanoid robots, longitudinal study, persuasive robots, pubcrawl, resilience, Resiliency, robot assertiveness, robot request, Robot Trust, robots, Service robots, Task Analysis |
Abstract | Domestic service robots become increasingly prevalent and autonomous, which will make task priority conflicts more likely. The robot must be able to effectively and appropriately negotiate to gain priority if necessary. In previous human-robot interaction (HRI) studies, imitating human negotiation behavior was effective but long-term effects have not been studied. Filling this research gap, an interactive online study (\$N=103\$) with two sessions and six trials was conducted. In a conflict scenario, participants repeatedly interacted with a domestic service robot that applied three different conflict resolution strategies: appeal, command, diminution of request. The second manipulation was reinforcement (thanking) of compliance behavior (yes/no). This led to a 3x2x6 mixed-subject design. User acceptance, trust, user compliance to the robot, and self-reported compliance to a household member were assessed. The diminution of a request combined with positive reinforcement was the most effective strategy and perceived trustworthiness increased significantly over time. For this strategy only, self-reported compliance rates to the human and the robot were similar. Therefore, applying this strategy potentially seems to make a robot equally effective as a human requester. This paper contributes to the design of acceptable and effective robot conflict resolution strategies for long-term use. |
DOI | 10.1109/HRI53351.2022.9889492 |
Citation Key | babel_it_2022 |