>In this reaction to David Kaber’s article in this volume, the author points to an inherent problem in applying any “levels” scheme to the continu'/> The Risks of Discretization: What Is Lost in (Even Good) Levels-of-Automation Schemes
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The Risks of Discretization: What Is Lost in (Even Good) Levels-of-Automation Schemes

机译:离散化的风险:(良好)自动化水平计划中的损失

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>In this reaction to David Kaber’s article in this volume, the author points to an inherent problem in applying any “levels” scheme to the continuous, multidimensional space of human–automation relationships and behaviors. Discretization inherently carves a continuous, analog space into discrete blocks that, the claim is, one can treat homogenously. The author provides a counterexample using a common automated e-mail filtering system as an example of how applying a single “level-of-automation” category to the whole system (or even to information-processing stages of components within it) misrepresents and suppresses details about what the system is actually doing and how it interacts with human users. Discretization can be highly productive if it pares away confusing detail that distracts from underlying explanatory relationships, but, the author argues, not enough is known about human–automation interaction in all its variability to effectively suppress detail. Thus one needs the better models Kaber is calling forbeforebeing able to create an effective levels-of-automation scheme, not vice versa.
机译: >在对本卷中David Kaber文章的反应中,作者指出了在应用任何“级别”方案时存在的固有问题。到人类自动化关系和行为的连续多维空间。离散化本质上将连续的模拟空间雕刻成离散的块,声称可以将它们均匀地对待。作者使用通用的自动电子邮件过滤系统提供了一个反例,以作为一个示例,说明如何将单个“自动化级别”类别应用于整个系统(甚至应用于其中的组件的信息处理阶段),以歪曲和抑制有关系统实际上在做什么以及如何与人类用户交互的详细信息。如果离散化消除了分散了潜在的解释性关系的令人困惑的细节,那么它可能会非常有生产力。但是,作者认为,关于人与自动化交互的各种可变性,人们对其了解不足以有效地抑制细节。因此,人们需要Kaber要求的更好的模型,即之前能够创建有效的自动化水平方案,反之亦然。

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