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Semantic Scholar · Article (Proceedings of the Human Factors and Ergonomics Society Annual Meeting)

Cognitive Biases in Commercial Aviation: Empirical Review of Accident Reports

Published 2024-08-12 From Proceedings of the Human Factors and Ergonomics Society Annual Meeting 4 authors

Attribution

This is the abstract and citation. Full text lives at Semantic Scholar — we link out rather than host. All credit to the authors and Proceedings of the Human Factors and Ergonomics Society Annual Meeting.

Abstract

Verbatim from Semantic Scholar. Not paraphrased, not summarized.

Cognitive biases in commercial aviation can coax pilots into disregarding established protocols or overlooking potential hazards, a concern that the Federal Aviation Administration (FAA) has acknowledged. However, the concrete impact of these biases on aviation operations has not been adequately quantified; empirical evidence remains limited. Recognizing this research gap, our study seeks to provide a comprehensive analysis of cognitive biases within commercial aviation. We conducted a review of National Transportation Safety Board flight incident reports for air carriers across the United States, from 2014 to 2024. We also conducted an expert interview with an instructor who is an experienced pilot to ascertain current training material and its adequacy in addressing cognitive biases. Our analysis revealed cognitive biases not identified by the FAA (e.g., overconfidence) and training material gaps. Our research lays the groundwork for improved training protocols and the potential for a more nuanced understanding of pilot behavior and safety.

Authors

  • Chihab Nadri
  • Jordan Regalado
  • Thomas K. Ferris
  • Maryam Zahabi

Keywords

  • Engineering
  • Psychology
  • Environmental Science

Citation: Chihab Nadri, Jordan Regalado, Thomas K. Ferris , et al. (2024). Cognitive Biases in Commercial Aviation: Empirical Review of Accident Reports. Proceedings of the Human Factors and Ergonomics Society Annual Meeting. Semantic Scholar ID 7ff88d6675f100d2744f8b03eee545e6a6677555. https://doi.org/10.1177/10711813241262980 ↗