人类如何了解自动化的可靠性?
Luke Strickland1, Simon Farrell2, Micah K Wilson3
1The Future of Work Institute, Curtin University, 78 Murray Street, Perth, 6000, Australia. luke.strickland@curtin.edu.au.
Cognitive research: principles and implications
|February 16, 2024
概括
人类通过预测错误来学习自动化可靠性,学习速度对环境变化敏感. 然而,在本研究的参与者中,个体学习过程存在显著差异.
科学领域:
- 认知科学是一种认知科学.
- 人与计算机的互动.
- 自动化自动化自动化自动化自动化
背景情况:
- 人类操作员越来越依赖于决策的自动化.
- 人类监控自动化可靠性的机制尚未得到充分理解.
- 了解人类跟踪自动化可靠性对于安全有效的系统设计至关重要.
研究的目的:
- 调查解释人类如何跟踪自动化可靠性的认知模型.
- 识别与估计自动化性能相关的学习过程.
- 为人类与自动化交互提供洞察力.
主要方法:
- 学习的认知模型与参与者对自动化可靠性的判断相匹配.
- 采用了一项具有自动化建议的海事分类任务.
- 进行了三项实验,涉及8种疾病的240名参与者.
主要成果:
- 一个双核的三角洲规则模型最好地解释了观察到的学习过程.
- 学习是由预测错误驱动的,学习率适应环境波动.
- 在参与者之间观察到学习策略的显著个体差异.
结论:
- 这些发现支持基于预测错误的学习模型来跟踪自动化可靠性.
- 环境波动会影响人类在与自动化交互时的学习率.
- 人类学习过程中的大量异质性对设计自适应自动化系统和培训运营商产生影响.
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