%0 Journal Article
%T Knowing Behavior Helps Insure Models Against Breakage: A Commentary on Kaber¡¯s ¡°Issues in Human¨CAutomation Interaction Modeling¡±
%A Evan Byrne
%J Journal of Cognitive Engineering and Decision Making
%D 2018
%R 10.1177/1555343417725669
%X This commentary on Kaber¡¯s review of human¨Cautomation 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
%K human¨Cautomation interaction
%K safety
%K level of automation
%U https://journals.sagepub.com/doi/full/10.1177/1555343417725669