Evaluating Effects of User Experience and System Transparency on Trust in Automation
Evaluating Effects of User Experience and System Transparency on Trust in Automation
复制标题
评估用户体验和系统透明度对自动化信任的影响
DOI：
10.1145/2909824.3020230
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
J. Shah
中科院分区：
文献类型：
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作者：
X. J. Yang;Vaibhav Unhelkar;Kevin Li;J. Shah
评估人类操作员对自动化和机器人的信任的现有研究主要将信任作为一个稳态变量进行研究，很少强调信任随时间的演变。为了解决这一研究空白，我们提出了一项研究，探索信任的动态性质。我们将整体信任定义为一种衡量人类与自动化的整个交互体验中的信任的指标，并首先确定了使用实时信任测量对其进行量化的替代方案。其次，我们提供了一个新的模型，试图解释当用户与自动化反复交互时，整体信任是如何演变的。最后，我们研究了自动化透明度对信任瞬时变化的影响。研究结果表明，与传统的实验后信任测度相比，“信任曲线下面积”的平均测度更能量化整体信任。此外，我们发现，整体的信任随着操作员与技术的反复交互而发展并最终稳定下来。最后，我们观察到，更高级别的自动化透明度可能会减轻“狼来了”效应-其中人类操作员开始拒绝自动化系统由于重复的错误警报。
Existing research assessing human operators' trust in automation and robots has primarily examined trust as a steady-state variable, with little emphasis on the evolution of trust over time. With the goal of addressing this research gap, we present a study exploring the dynamic nature of trust. We defined trust of entirety as a measure that accounts for trust across a human's entire interactive experience with automation, and first identified alternatives to quantify it using real-time measurements of trust. Second, we provided a novel model that attempts to explain how trust of entirety evolves as a user interacts repeatedly with automation. Lastly, we investigated the effects of automation transparency on momentary changes of trust. Our results indicated that trust of entirety is better quantified by the average measure of “area under the trust curve” than the traditional post-experiment trust measure. In addition, we found that trust of entirety evolves and eventually stabilizes as an operator repeatedly interacts with a technology. Finally, we observed that a higher level of automation transparency may mitigate the “cry wolf’ effect - wherein human operators begin to reject an automated system due to repeated false alarms.