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机器人信任的演变:通过序列和对比元分析的规范。

Evolving Trust in Robots: Specification Through Sequential and Comparative Meta-Analyses.

机构信息

6243University of Central Florida, Orlando, USA.

6243Institute for Simulation and Training, University of Central Florida, Orlando, USA.

出版信息

Hum Factors. 2021 Nov;63(7):1196-1229. doi: 10.1177/0018720820922080. Epub 2020 Jun 10.

Abstract

OBJECTIVE

The objectives of this meta-analysis are to explore the presently available empirical findings on the antecedents of trust in robots and use this information to expand upon a previous meta-analytic review of the area.

BACKGROUND

Human-robot interaction (HRI) represents an increasingly important dimension of our everyday existence. Currently, the most important element of these interactions is proposed to be whether the human trusts the robot or not. We have identified three overarching categories that exert effects on the expression of trust. These consist of factors associated with (a) the human, (b) the robot, and (c) the context in which any specific HRI event occurs.

METHOD

The current body of literature was examined and all qualifying articles pertaining to trust in robots were included in the meta-analysis. A previous meta-analysis on HRI trust was used as the basis for this extended, updated, and evolving analysis.

RESULTS

Multiple additional factors, which have now been demonstrated to significantly influence trust, were identified. The present results, expressed as points of difference and points of commonality between the current and previous analyses, are identified, explained, and cast in the setting of the emerging wave of HRI.

CONCLUSION

The present meta-analysis expands upon previous work and validates the overarching categories of trust antecedent (human-related, robot-related, and contextual), as well as identifying the significant individual precursors to trust within each category. A new and updated model of these complex interactions is offered.

APPLICATION

The identified trust factors can be used in order to promote appropriate levels of trust in robots.

摘要

目的

本荟萃分析旨在探讨目前关于信任机器人的前因的实证研究结果,并利用这些信息对该领域的先前荟萃分析综述进行扩展。

背景

人机交互(HRI)代表了我们日常生活中越来越重要的一个维度。目前,这些交互的最重要的元素被认为是人类是否信任机器人。我们已经确定了三个对信任表达有影响的总体类别。这些类别包括与(a)人、(b)机器人和(c)发生任何特定 HRI 事件的背景相关的因素。

方法

对当前的文献进行了检查,并将所有与机器人信任相关的合格文章纳入荟萃分析。先前关于 HRI 信任的荟萃分析被用作本次扩展、更新和不断发展的分析的基础。

结果

确定了多个额外的因素,这些因素现已被证明会显著影响信任。目前的结果以当前和以前分析之间的差异点和共同点的形式表示,进行了识别、解释,并在新兴的 HRI 浪潮背景下进行了阐述。

结论

本荟萃分析扩展了先前的工作,并验证了信任前因(与人类相关、与机器人相关和与背景相关)的总体类别,以及在每个类别中确定信任的重要个体前因。提出了一个新的和更新的这些复杂交互模型。

应用

确定的信任因素可用于促进机器人的适当信任水平。

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