Eye tracking: a promising method for inferring trust in real time
Eye tracking: a promising method for inferring trust in real time
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眼动追踪：一种很有前途的实时推断信任的方法
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
N. Sarter
中科院分区：
文献类型：
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作者：
Yidu Lu;N. Sarter
自动化技术的广泛使用极大地提高了运营的安全性和效率。然而，当人们没有正确使用自动化时，它也会带来挑战。自动化的不当使用可能与人们对高度自治系统的不当信任密切相关。过去的研究表明，信任，即“在不确定和脆弱的情况下，代理人将帮助实现个人目标的态度”（Lee & See，2004），是影响自动化使用的关键因素（Hoff & Bashir，2015）。如果一个人对自动化的信任被错误校准，即，如果它与系统的实际功能和可靠性不匹配（Lee & See，2004），他们可能会滥用或废弃该系统。需要更好地理解信任的形成和变化过程，以支持信任校准并促进现代技术的安全和高效使用。迄今为止，
The increased use of automation technologies has largely improved the safety and efficiency of operations. However, it has also created challenges when people do not use automation appropriately. The improper use of automation can be closely related to a person’s inappropriate trust in highly autonomous systems. Past studies have shown that trust, i.e., “the attitude that an agent will help achieve an individual’s goals in a situation characterized by uncertainty and vulnerability” (Lee & See, 2004), is a critical factor affecting automation usage (Hoff & Bashir, 2015). If a person’s trust in automation is miscalibrated, i.e., if it does not match the actual capabilities and reliability of the system (Lee & See, 2004), they are likely to misuse or disuse the system. A better understanding of trust formation and change processes is needed to support trust calibration and promote safe and efficient use of modern technologies. To date,