透明度提高了自动化使用的准确性,但自动化信心信息没有
Monica Tatasciore1, Luke Strickland2,3, Shayne Loft4
1The University of Western Australia, 35 Stirling Highway, Perth, WA, 6009, Australia. monica.tatasciore@uwa.edu.au.
Cognitive research: principles and implications
|October 8, 2024
概括
自动化透明度提高了决策准确性和效率. 值得信赖的信息没有显著改变结果,但影响了用户对自动化的依赖,为更好的人机自动化系统设计提供了信息.
科学领域:
- 人与计算机的交互
- 认知心理学 认知心理学
- 自动化科学 自动化科学
背景情况:
- 自动化透明度提高了理解,但可能会增加协议偏差.
- 自动化信心信息对错误预测和用户行为的影响尚不清楚.
研究的目的:
- 调查自动化透明度和信任信息对自动化使用准确性的影响.
- 检查透明度和信任之间的相互作用,以影响用户的决策和结果.
主要方法:
- 参与者管理无人驾驶车辆 (UV),为任务选择最佳的UV.
- 自动化透明度 (低/高) 和信任信息 (存在/不存在) 被操纵.
- 记录了用户对自动化咨询和决策结果的同意/不同意.
主要成果:
- 更高的自动化透明度提高了准确性,决策速度,信任和可用性,同时减少了工作量.
- 仅靠可信度信息并没有影响整体结果,但改变了对自动化的依赖.
- 当用户的信心较低时,用户对自动化的依赖程度会降低,这会影响准确性和决策时间.
结论:
- 自动化透明度对于优化人机交互和决策准确性至关重要.
- 信任信息虽然不能提高整体性能,但可以调节用户对自动化的依赖.
- 研究结果建议设计具有可调节的透明度和信任线索的自动化系统,以增强用户控制和性能.
相关概念视频
Uncertainty in Measurement: Accuracy and Precision
73.5K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.
73.5K
Accuracy and Errors in Hypothesis Testing
178
Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
178
Control Systems
1.1K
Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
At the heart...
1.1K
Improving Translational Accuracy
2.5K
2.5K
Uncertainty: Overview
526
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
526
Systematic Error: Methodological and Sampling Errors
1.4K
In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
1.4K


