Toward an Understanding of Trust Repair in Human-Robot Interaction
Toward an Understanding of Trust Repair in Human-Robot Interaction
复制标题
理解人机交互中的信任修复
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
J. Keebler
中科院分区：
文献类型：
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作者：
Anthony L. Baker;Elizabeth Phillips;D. Ullman;J. Keebler
机器人单独运行、不与人直接互动的时代已经一去不复返了。相反，机器人越来越多地被部署在需要与人类进行复杂社交互动的环境和角色中。随着技术的发展和人机交互（HRI）研究的发展，人机团队的实施不断增加。信任是人际交往的重要组成部分，也是HRI的一个重要方面。然而，在HRI文献中，信任修复和信任侵犯的想法是欠研究的。信任修复是一方破坏另一方信任后重建信任的活动。这些信任破坏被称为信任违反。就像人类一样，机器人的信任违规是不可避免的;因此，必须对HRI信任修复过程有一个清晰的理解，以确保人类-机器人团队在信任违规后能够继续表现良好。以前对人-自动化信任和人-人信任的研究可以作为探索HRI中信任修复的起点。尽管现有的人与自动化和人与人之间的信任模型是有帮助的，但它们并没有考虑到在人类和机器人之间的独特关系中建立和保持信任的复杂性。本文的目的是通过借鉴人类-机器人，人类-自动化和人类-人类信任文献中的先前工作，为探索人类-机器人信任修复提供基础，最后提出推进这项工作的建议。
Gone are the days of robots solely operating in isolation, without direct interaction with people. Rather, robots are increasingly being deployed in environments and roles that require complex social interaction with humans. The implementation of human-robot teams continues to increase as technology develops in tandem with the state of human-robot interaction (HRI) research. Trust, a major component of human interaction, is an important facet of HRI. However, the ideas of trust repair and trust violations are understudied in the HRI literature. Trust repair is the activity of rebuilding trust after one party breaks the trust of another. These trust breaks are referred to as trust violations. Just as with humans, trust violations with robots are inevitable; as a result, a clear understanding of the process of HRI trust repair must be developed in order to ensure that a human-robot team can continue to perform well after a trust violation. Previous research on human-automation trust and human-human trust can serve as starting places for exploring trust repair in HRI. Although existing models of human-automation and human-human trust are helpful, they do not account for some of the complexities of building and maintaining trust in unique relationships between humans and robots. The purpose of this article is to provide a foundation for exploring human-robot trust repair by drawing upon prior work in the human-robot, human-automation, and human-human trust literature, concluding with recommendations for advancing this body of work.