Towards a Deeper Understanding of Automation Transparency in the Operation of Nuclear Plants

2019

Objective The objective of this study was to test the predictions of the routine-failure trade-off (or lumberjack) model in a full-scope simulator study with expert operators performing realistic control tasks. Background A meta-study of degree of automation (DOA) studies concluded that DOA predicts task performance under both routine and automation failure conditions, workload, and situation awareness. Empirical support for this conclusion appears to be weak for complex work situations. Method A full-scope nuclear power plant simulator experiment was conducted in which licensed operating crews completed realistic procedure execution tasks. Dependent measures selected from the lumberjack model were collected and analyzed for systematic effects. Results Situation awareness increased with increasing DOA, which contradicts the lumberjack model. Anticipated workload and failure task performance effects were not observed. Conclusion The experimental results add further evidence challenging the applicability of the lumberjack model to complex work situations. Application Practitioners should use caution when extending the predictions of the lumberjack model based on data from simple work situations to complex work situations. Researchers should invest more resources in testing the predictive power of the lumberjack model in complex work situations.

Section: Discussionsupporting

confidence: 57%

Section: Methodsmentioning

confidence: 99%

Section: Acknowledgmentsmentioning

confidence: 99%

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The Absence of Degree of Automation Trade-Offs in Complex Work Settings

2019

“…The reported experiments were among seven HAI studies that the authors reanalyzed and reinterpreted in a technical report prepared for the Organisation for Economic Co-operation and Development (OECD) Halden Reactor Project (Skraaning & Jamieson, 2017), an international center of research excellence for safe and reliable operation of nuclear power facilities (https://ife.no/en/project/the-halden-reactor-project/). Our main contributions were extraction of new findings through complete reanalysis of archival data, discovery of patterns across experiments, and reinterpretation of the findings in light of the recent research literature on automation transparency.…”

Section: Experiments 1 Andmentioning

confidence: 99%

Human Performance Benefits of The Automation Transparency Design Principle

2019

Objective: Test the automation transparency design principle using a full-scope nuclear power plant simulator. Background: Automation transparency is a long-held human factors design principle espousing that the responsibilities, capabilities, goals, activities, and/or effects of automation should be directly observable in the human–system interface. The anticipated benefits of transparency include more effective reliance, more appropriate trust, better understanding, and greater user satisfaction. Transparency has enjoyed a recent upsurge in use in the context of human interaction with agent-oriented automation. Method: Three full-scope nuclear power plant simulator studies were conducted with licensed operating crews. In the first two experiments, transparency was implemented for interlocks, controllers, limitations, protections, and automatic programs that operate at the local component level of the plant. In the third experiment, procedure automation assumed control of plant operations and was represented in dedicated agent displays. Results: Results from Experiments 1 and 2 appear to validate the human performance benefits of automation transparency for automation at the component level. However, Experiment 3 failed to replicate these findings for automation that assumed control for executing procedural actions. Conclusion: Automation transparency appears to yield expected benefits for component-level automation, but caution is warranted in generalizing the design principle to agent-oriented automation. Application: The automation transparency design principle may offer a powerful means of compensating for the detrimental impacts of hidden automation influence at the component level of complex systems. However, system developers should exercise caution in assuming that the principle extends to agent-oriented automation.

“…Over the past 4 years we have reviewed and reanalyzed several degree of automation (DOA) studies conducted through the OECD Halden Reactor Project (Skraaning & Jamieson, 2017). In 2015, after reading Onnasch et al (2014), we recognized that we had data from a full-scope nuclear power plant simulation study that would serve as a partial test of the lumberjack model (Wickens et al, 2010).…”

mentioning

confidence: 99%

The Harder They Fall? A Response to Wickens et al. (2019) Regarding the Generalizability of Lumberjack Predictions to Complex Work Settings

2020

Objective This article is a response to Wickens et al.’s (2019) critique of Jamieson and Skraaning (2019). Background Wickens et al. (2019) offer a five-point critique of Jamieson and Skraaning (2019) that they claim tempers the strength of our conclusions. Approach We first correct a misrepresentation in the critique and then respond to each of the criticisms. Results We preserve the strength of our skeptical conclusions about the applicability of the lumberjack model to complex work settings. Applications We continue to caution system designers about the lack of evidence supporting the lumberjack model in the context of complex work systems.