Situation Awareness, Mental Workload, and Trust in Automation: Viable, Empirically Supported Cognitive Engineering Constructs

TLDR

Cognitive engineering requires robust constructs to predict human performance, yet the widely studied constructs of situation awareness, mental workload, and trust in automation have been criticized as unempirical folk models by Dekker and Hollnagel. This paper counters that criticism by outlining the extensive empirical evidence supporting these constructs. The authors demonstrate that situation awareness, mental workload, and trust can be operationalized through behavioral, physiological, and subjective measures, supplemented by computational modeling, and they identify errors in Dekker and Hollnagel’s description of their approach. They refute the claim that these constructs are unfalsifiable and conclude that they are viable, valuable tools for understanding and predicting human‑system performance in complex environments. Dekker and Hollnagel caricatured the authors’ framework for automated system design (Parasuraman, Sheridan, & Wickens, 2000) as “abracadabra.”.

Abstract

Cognitive engineering needs viable constructs and principles to promote better understanding and prediction of human performance in complex systems. Three human cognition and performance constructs that have been the subjects of much attention in research and practice over the past three decades are situation awareness (SA), mental workload, and trust in automation. Recently, Dekker and Woods (2002) and Dekker and Hollnagel (2004; henceforth DWH) argued that these constructs represent “folk models” without strong empirical foundations and lacking scientific status. We counter this view by presenting a brief description of the large science base of empirical studies on these constructs. We show that the constructs can be operationalized using behavioral, physiological, and subjective measures, supplemented by computational modeling, but that the constructs are also distinct from human performance. DWH also caricatured as “abracadabra” a framework suggested by us to address the problem of the design of automated systems (Parasuraman, Sheridan, & Wickens, 2000). We point to several factual and conceptual errors in their description of our approach. Finally, we rebut DWH's view that SA, mental workload, and trust represent folk concepts that are not falsifiable. We conclude that SA, mental workload, and trust are viable constructs that are valuable in understanding and predicting human-system performance in complex systems.