青少年情绪分类任务中概念体现对人机信任的影响

De'Aira G. Bryant, Jin Xu, Kantwon Rogers, A. Howard
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引用次数: 0

摘要

交互式机器人越来越多地用于社交环境,为人类提供信息、指导甚至推荐。用户信任在人类是否接受或拒绝机器人推荐的决策过程中起着重要的作用。HRI先前的工作已经调查了影响人机信任的各种与机器人相关、与任务相关和与用户相关的因素。这项工作进一步研究了在机器人辅助情感分类任务中影响用户信任的任务和用户相关因素,当机器人的实施例留给用户概念化时。所选择的与任务相关的因素操纵了待标记图像的确定性水平,以及图像刺激中的个体与参与者之间的性别一致性。我们进一步考虑了参与者的性别、父母地位、与孩子的互动水平、与机器人的舒适程度和概念机器人的体现。对241名参与者进行了在线受试者间实验。实验结果表明,任务确定性和性别一致性以及与机器人的舒适程度、与儿童的互动程度和概念体现都对人与机器人的信任有显著影响。值得注意的是,那些将机器人的概念体现描述为人类特征的参与者比那些没有描述的参与者报告了更高的信任水平。这些发现提供了见解,有助于更好地理解在涉及机器人推荐的情境中影响人机信任的因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Effect of Conceptual Embodiment on Human-Robot Trust During a Youth Emotion Classification Task
Interactive robots are increasingly being used in social environments to provide humans with information, guidance and even recommendation. User trust plays an important role in the human decision-making process for whether to accept or reject a robot's recommendation. Prior work in HRI has investigated various robot-related, task-related, and user-related factors that influence human-robot trust. This work further examines task and user-related factors influencing user trust during a robot-assisted emotion classification task when the embodiment of the robot is left for the user to conceptualize. The chosen task-related factors manipulate the level of certainty in the images to be labeled and the gender alignment between the individual in the image stimuli and the participant. We further consider participant gender, parental status, level of interaction with children, level of comfortability with robots and conceptual robot embodiment. An online between-subjects experiment was conducted with 241 participants. Experimental results show that task certainty and gender alignment along with level of comfortability with robots, level of interaction with children and conceptual embodiment all had significant effects on human-robot trust. Notably, participants who described their conceptual embodiment of the robot with human-like characteristics reported higher levels of trust than those who did not. These findings provide insights that contribute to a greater understanding of factors influencing human-robot trust during a situated scenario involving robot recommendation.
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