>This commentary on Kaber’s review of human–automation interaction (HAI) modeling and levels of automation (LOA) highlights some of the challenges'/> Knowing Behavior Helps Insure Models Against Breakage: A Commentary on Kaber's 'Issues in Human-Automation Interaction Modeling'
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Knowing Behavior Helps Insure Models Against Breakage: A Commentary on Kaber's 'Issues in Human-Automation Interaction Modeling'

机译:知道行为有助于确保模型免受破坏:关于Kaber的“人-自动化交互模型问题”的评论

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>This commentary on Kaber’s review of human–automation interaction (HAI) modeling and levels of automation (LOA) highlights some of the challenges designers of automated systems face as a result of a heterogeneous user base. It advocates for understanding the variability in the intended user base to facilitate decisions on whether to constrain user behavior or the system design to optimize overall system performance and the need to anticipate adaptive user strategies before system deployment. It argues that the predictive efficacy of LOA models depends on the heterogeneity of the user base and an increased understanding of behavior through evaluation of breakdowns in HAI.
机译: >这篇关于Kaber对人与自动化交互(HAI)建模和自动化水平(LOA)的评论的评论强调了一些多样化的用户群给自动化系统的设计人员带来了挑战。它提倡了解预期用户群的可变性,以便于决定是限制用户行为还是要优化系统设计以优化总体系统性能,以及在系统部署之前需要预测自适应用户策略的需求。它认为,LOA模型的预测效力取决于用户群的异质性以及通过评估HAI中的故障来增强对行为的理解。

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