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This paper responds to Kaber’s reflections on the empirical grounding and design utility of the levels-of-automation (LOA) framework. We discuss the suitability of the existing human performance data for supporting design decisions in complex work environments. We question why human factors design guidance seems wedded to a model of questionable predictive value. We challenge the belief that LOA frameworks offer useful input to the design and operation of highly automated systems. Finally, we seek to expand the design space for human–automation interaction beyond the familiar human factors constructs. Taken together, our positions paint LOA frameworks as abstractions suffering a crisis of confidence that Kaber’s remedies cannot restore.
Jamieson et al. (Thu,) studied this question.
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