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NASA NTRS · Conference Paper
A Data-Driven Approach to Recognizing and Understanding Human Contributions to Aviation Safety
Attribution
This is the abstract and citation. Full text lives at NASA NTRS — we link out rather than host. All credit to the authors and Langley Research Center.
Abstract
Verbatim from NASA NTRS. Not paraphrased, not summarized.
Data-driven decisions about safety management and design of safety-critical systems are limited by the available data, which influence, and are influenced by, how decision makers characterize problems and identify solutions. In the commercial aviation domain, large volumes of data are collected and analyzed on the failures and errors that result in infrequent incidents and accidents, but in the absence of data on safety-producing behaviors, safety management and system design decisions are based on a small sample of non-representative safety data. Analysis of aviation accident data suggests that human error is implicated in up to 80% of accidents, which has been used to justify future visions for aviation in which the roles of human operators are greatly diminished or eliminated in the interest of creating a safer aviation system. However, failure to fully consider the human contributions to aviation safety represents a significant and largely unrecognized risk when making policy decisions about safety management and system design. Opportunities exist to leverage the vast amount of data that have already been collected, or could be easily obtained, to increase our understanding of human contributions to safety in commercial aviation. This presentation will focus on those opportunities as well as the challenges associated with collecting and analyzing data on operators’ safety-producing behaviors.
Author
- Jon Holbrook Langley Research Center
Keywords
- Safety
- Recognizing
- Understanding
- Human contributions
- Aviation safety
Citation: Jon Holbrook (2020). A Data-Driven Approach to Recognizing and Understanding Human Contributions to Aviation Safety. Langley Research Center. NASA NTRS ID 20205003347. https://ntrs.nasa.gov/citations/20205003347 ↗