Near-Perfect Automation: Investigating Performance, Trust, and Visual Attention Allocation
| العنوان: | Near-Perfect Automation: Investigating Performance, Trust, and Visual Attention Allocation |
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| المؤلفون: | Richard Pak, Cyrus K. Foroughi, Noelle L. Brown, Shannon P. Devlin, Ciara Sibley, Joseph T. Coyne |
| المصدر: | Human Factors: The Journal of the Human Factors and Ergonomics Society. 65:546-561 |
| بيانات النشر: | SAGE Publications, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Behavioral Neuroscience, Human–computer interaction, business.industry, Computer science, Visual attention, Human Factors and Ergonomics, business, Automation, Applied Psychology |
| الوصف: | Objective Assess performance, trust, and visual attention during the monitoring of a near-perfect automated system. Background Research rarely attempts to assess performance, trust, and visual attention in near-perfect automated systems even though they will be relied on in high-stakes environments. Methods Seventy-three participants completed a 40-min supervisory control task where they monitored three search feeds. All search feeds were 100% reliable with the exception of two automation failures: one miss and one false alarm. Eye-tracking and subjective trust data were collected. Results Thirty-four percent of participants correctly identified the automation miss, and 67% correctly identified the automation false alarm. Subjective trust increased when participants did not detect the automation failures and decreased when they did. Participants who detected the false alarm had a more complex scan pattern in the 2 min centered around the automation failure compared with those who did not. Additionally, those who detected the failures had longer dwell times in and transitioned to the center sensor feed significantly more often. Conclusion Not only does this work highlight the limitations of the human when monitoring near-perfect automated systems, it begins to quantify the subjective experience and attentional cost of the human. It further emphasizes the need to (1) reevaluate the role of the operator in future high-stakes environments and (2) understand the human on an individual level and actively design for the given individual when working with near-perfect automated systems. Application Multiple operator-level measures should be collected in real-time in order to monitor an operator’s state and leverage real-time, individualized assistance. |
| تدمد: | 1547-8181 0018-7208 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36ce4604a3004116e5f5c7b4d93dd1cd https://doi.org/10.1177/00187208211032889 |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi.dedup.....36ce4604a3004116e5f5c7b4d93dd1cd |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15478181 00187208 |
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