Human Performance Consequences of Stages and Levels of Automation

By Linda Onnasch, C. Wickens, Huiyang Li, Dietrich Manzey. Hum. Factors, 2014

452 citations recorded by the source corpus.

Subfields: Information Systems and Management, Radiological and Ultrasound Technology, Social Psychology

View Paper: https://www.semanticscholar.org/paper/55235aed1ea73a7c728cd497a296fe655a64b2ee

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Citations in the corpus

From ‘automation’ to ‘autonomy’: the importance of trust repair in human–machine interaction (2018, background): “…between automated systems and systems that exhibit autonomy, previously iden tified problems with automation (e.g. out of the loop syndrome, mode awareness, complacency, trust) are expected to not only exist, but be mag nified , a phenomenon known as the lumberjack eff ect (Onnasch et al. 2014).”
Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy (2019, background): “This creates an automation paradox, where factors that positively in ﬂ uence performance when the automation is working well may undermine performance when the automation fails (Onnasch et al., 2014).”
Human factors of transitions in automated driving: A general framework and literature survey (2016, background): “…reaction times (Dambock, Weissgerber, Kienle, & Bengler, 2013; Strand, Nilsson, Karlsson, & Nilsson, 2014), a finding that corresponds to decades of research in psychological vigilance and human-automation interaction (see Cabrall, Happee, & De Winter, 2016; Onnasch et al., 2014, for reviews).”
Complacency and Automation Bias in the Use of Imperfect Automation (2015, result): “As such, these effects are consistent with the overall pattern of automation failure effects observed in the metaanalysis by Onnasch et al. (2014).”
Implementing Lumberjacks and Black Swans Into Model-Based Tools to Support Human–Automation Interaction (2017, result): “The results of the meta-analysis (Onnasch et al., 2014) are shown in Figure 2.”
From Here to Autonomy (2017, background): “This type of automation significantly reduces workload and can enhance both SA and performance with little negative effects (Endsley et al., 2003; Endsley & Selcon, 1997; Onnasch et al., 2014; Sarter & Schroeder, 2001).”