Kohn Spencer C, de Visser Ewart J, Wiese Eva, Lee Yi-Ching, Shaw Tyler H
George Mason University, Fairfax, VA, United States.
Warfighter Effectiveness Research Center, United States Air Force Academy, Colorado Springs, CO, United States.
Front Psychol. 2021 Oct 19;12:604977. doi: 10.3389/fpsyg.2021.604977. eCollection 2021.
With the rise of automated and autonomous agents, research examining Trust in Automation (TiA) has attracted considerable attention over the last few decades. Trust is a rich and complex construct which has sparked a multitude of measures and approaches to study and understand it. This comprehensive narrative review addresses known methods that have been used to capture TiA. We examined measurements deployed in existing empirical works, categorized those measures into self-report, behavioral, and physiological indices, and examined them within the context of an existing model of trust. The resulting work provides a reference guide for researchers, providing a list of available TiA measurement methods along with the model-derived constructs that they capture including judgments of trustworthiness, trust attitudes, and trusting behaviors. The article concludes with recommendations on how to improve the current state of TiA measurement.
随着自动化和自主智能体的兴起，在过去几十年里，研究自动化信任（TiA）的相关研究已引起了广泛关注。信任是一个丰富且复杂的概念，引发了众多研究和理解它的测量方法与途径。这篇全面的叙述性综述探讨了用于衡量TiA的已知方法。我们审视了现有实证研究中所采用的测量方式，将这些测量方法归类为自我报告、行为和生理指标，并在现有的信任模型框架内对其进行考察。最终成果为研究人员提供了一份参考指南，列出了可用的TiA测量方法以及它们所涵盖的源自模型的概念，包括对可信度的判断、信任态度和信任行为。文章最后给出了关于如何改进当前TiA测量状况的建议。
