Attention and complacency

By Neville Moray, T. Inagaki. 2000

137 citations recorded by the source corpus.

Subfields: Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/f0b842f71ab269f10b981bbc7f0eed7bac1ad7c2

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In Statistical and Nonlinear Physics

Citations in the corpus

Situation Awareness, Mental Workload, and Trust in Automation: Viable, Empirically Supported Cognitive Engineering Constructs (2008, background): “…tends to suggest willful and ill-advised neglect, whereas the empirical phenomenon of reduced monitoring does not and, in fact, could be considered a rational strategy (Moray & Inagaki, 2000) For historical reasons stemming from its long use in the aviation domain, the term continues to appear.”
From Here to Autonomy (2017, background): “Although concern has been expressed over the potential for operators to overtrust automation (Lee & See, 2004), Moray and Inagaki (2000) make the compelling case that operators employ an optimal attention allocation strategy in which highly reliable automation does not need to be monitored very…”
Human Performance Consequences of Automated Decision Aids (2012, methodology): “In typical supervisory control tasks, misuse of automation is reflected in an insufficient monitoring and checking of automated functions, a phenomenon that also has been referred to as “automation-induced complacency” (Moray & Inagaki; 2000, Parasuraman, Molloy, & Singh, 1993).”
Humans: Still Vital After All These Years of Automation (2008, background): “The effect was absent when there were no other manual tasks, suggesting that complacency reﬂects attention allocation away from the automated task to other concurrent tasks (Moray & Inagaki, 2000).”
Human-Automation Interaction (2005, methodology): “Consistent with the information-theoretic model of sampling (Senders, 1964), Moray and Inagaki (2001) proposed that automation should be monitored (or sampled) by the human at a rate set by the objective failure rate of the automation: The more reliable the automation, the less the operator should…”
Drivers' attitudes toward imperfect distraction mitigation strategies (2006, background): “However, situations with time-critical elements (e.g., impending crash) do require higher levels of automation (Moray & Inagaki, 2003).”
Implementing Lumberjacks and Black Swans Into Model-Based Tools to Support Human–Automation Interaction (2017, unknown): “As research indicates (Moray & Inagaki, 2000; Rovira, McGarry, & Parasuraman, 2007; Wickens, Hooey, et al., 2009), the more reliable a system, the less likely an operator is to expect a failure.”
Misuse of automated decision aids: Complacency, automation bias and the impact of training experience (2008, methodology): “First, taking the critique of Moray (2003) and Moray and Inagaki (2000) into account, complacency effects are investigated by direct assessment of the automation verification behavior of participants and comparing it to a normative model of optimal non-complacent behavior.”
Complacency and Bias in Human Use of Automation: An Attentional Integration (2010, methodology): “However, as proposed by Moray (2003; Moray & Inagaki, 2000), the mere fact that automated systems influence allocation of attentional resources cannot be regarded as an indication of complacency or automation bias.”
Measurement of Trust in Automation: A Narrative Review and Reference Guide (2021, background): “This act of double-checking the teammate’s advice or monitoring their performance is an indication of distrust (Ho et al., 2005) and may represent a relatively objective measure of trust (Moray and Inagaki, 2000; Bahner et al. 2008; Walliser et al., 2016).”