在人机系统中建立和衡量信任

Lida Ghaemi Dizaji, Yaoping Hu
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引用次数: 3

摘要

在人机系统(HMS)中,人对机器的信任是一个复杂的概念,引起了越来越多的研究。在此,我们回顾了最近的研究建立和测量信任的医疗服务。该评估基于一个综合信任模型-影响,该模型具有意图、可测量性、性能、适应性、沟通、透明度和安全性7个特征。回顾发现,在过去的5年里,医疗服务管理系统满足了意图、可测量性、沟通性和透明度的特征。大多数HMS考虑的是性能特性。然而,所有的HMS都很少考虑自适应特性,而由于使用独立模拟而忽略了安全性特性。这些发现表明,考虑适应性和/或安全性特征的未来工作对于培养人类对HMS的信任是必不可少的。
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Building And Measuring Trust In Human-Machine Systems
In human-machine systems (HMS), trust placed by humans on machines is a complex concept and attracts increasingly research efforts. Herein, we reviewed recent studies on building and measuring trust in HMS. The review was based on one comprehensive model of trust – IMPACTS, which has 7 features of intention, measurability, performance, adaptivity, communication, transparency, and security. The review found that, in the past 5 years, HMS fulfill the features of intention, measurability, communication, and transparency. Most of the HMS consider the feature of performance. However, all of the HMS address rarely the feature of adaptivity and neglect the feature of security due to using stand-alone simulations. These findings indicate that future work considering the features of adaptivity and/or security is imperative to foster human trust in HMS.
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