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互惠在言语说服机器人中的作用。

The Role of Reciprocity in Verbally Persuasive Robots.

作者信息

Lee Seungcheol Austin, Liang Yuhua Jake

机构信息

1 Department of Communication, Northern Kentucky University , Highland Heights, Kentucky.

2 School of Communication, Chapman University , Orange, California.

出版信息

Cyberpsychol Behav Soc Netw. 2016 Aug;19(8):524-7. doi: 10.1089/cyber.2016.0124. Epub 2016 Jul 22.

Abstract

The current research examines the persuasive effects of reciprocity in the context of human-robot interaction. This is an important theoretical and practical extension of persuasive robotics by testing (1) if robots can utilize verbal requests and (2) if robots can utilize persuasive mechanisms (e.g., reciprocity) to gain human compliance. Participants played a trivia game with a robot teammate. The ostensibly autonomous robot helped (or failed to help) the participants by providing the correct (vs. incorrect) trivia answers. Then, the robot directly asked participants to complete a 15-minute task for pattern recognition. Compared to no help, results showed that a robot's prior helping behavior significantly increased the likelihood of compliance (60 percent vs. 33 percent). Interestingly, participants' evaluations toward the robot (i.e., competence, warmth, and trustworthiness) did not predict compliance. These results also provided an insightful comparison showing that participants complied at similar rates with the robot and with computer agents. This result documents a clear empirically powerful potential for the role of verbal messages in persuasive robotics.

摘要

当前的研究考察了互惠原则在人机交互情境中的说服效果。这是对说服性机器人学的一项重要理论和实践拓展,通过测试(1)机器人是否能够运用口头请求,以及(2)机器人是否能够运用说服机制(如互惠原则)来促使人类服从。参与者与一个机器人队友玩了一个知识问答游戏。表面上自主的机器人通过提供正确(与错误相对)的知识问答答案来帮助(或未能帮助)参与者。然后,机器人直接要求参与者完成一项15分钟的模式识别任务。与未得到帮助相比,结果显示机器人先前的帮助行为显著增加了服从的可能性(60%对33%)。有趣的是,参与者对机器人的评价(即能力、温暖程度和可信度)并不能预测服从情况。这些结果还提供了一个有见地的比较,表明参与者对机器人和计算机代理的服从率相似。这一结果证明了口头信息在说服性机器人学中具有明显的、基于经验的强大潜力。

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