Who’s Laughing NAO? Examining Perceptions of Failure in a Humorous Robot Partner
Haley N. Green, Md Mofijul Islam, Shahira Ali, Tariq Iqbal
HRI 2022
Session: Perceptions of Robots and Humans (2)
Abstract
Social robots are being deployed to interact with people in various scenarios, where they are expected to incorporate human-like conversational strategies to achieve fluency in interactions. For example, current robots are designed to perform advanced communication strategies (i.e., personal anecdotes, explanations, and apologies) to recover from task failure. However, these tactics are not always sufficient for failure recovery as they can be lengthy, unimaginative, and insufficient for encouraging future interactions. In human-human interactions, people often use humor as a low-risk and engaging method for managing failures. Thus, the successful execution of advanced, human-like humor could enable robots to recover from task failures more efficiently. In this paper, we present a human-robot interaction study (n = 288) exploring how a robot's utilization of various human-like humor types (i.e., affiliative, aggressive, self-enhancing, and self-defeating) are perceived by a human teammate and an external observer of the interaction. Additionally, we have explored the effects of performance, humor type, perspective, and previous experience with robots on the participants' perceptions of warmth, competence, and the robot as a teammate. Our results indicate that dyadic participants rated the successful robot to be more competent and a better teammate than the bystander participants. Additionally, the results indicate that participants with less experience with robots found the successful robot to be more competent than participants with high levels of experience. These findings will enable the human-robot interaction community to develop more engaging robots for fluent interactive experiences in the future.
WEB:: https://humanrobotinteraction.org/2022/
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