Balancing Automation and Human Expertise: A Comprehensive Approach to the Future of Air Safety

The future of air safety relies on a holistic approach that integrates advanced technologies, human factors, and comprehensive training programs. This paper examines the critical components of aviation safety, including the development of intelligible software, the importance of robust training, and the irreplaceable role of human intervention in complex and high-risk scenarios. Through the analysis of key incidents, such as the Boeing 737 MAX and Air France Flight 447, the study highlights the challenges and opportunities presented by automation and artificial intelligence (AI) in aviation. It emphasizes the need for a balanced approach where technology supports rather than replaces human expertise, underscoring the value of human judgment, adaptability, and decision-making under pressure. The findings suggest that by fostering a collaborative environment where humans and machines work together, the aviation industry can achieve enhanced safety and efficiency. This research calls for continued investment in both technological advancements and human-centered training strategies to create a more resilient and adaptable aviation safety framework.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-17
DOI
https://doi.org/10.5281/zenodo.15685328
Primary Topic
Imbalanced Data Classification Techniques
Type
article
Field-Weighted Citation Impact
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article

Balancing Automation and Human Expertise: A Comprehensive Approach to the Future of Air Safety

Zenodo (CERN European Organization for Nuclear Research)
Imbalanced Data Classification Techniques
article

Balancing Automation and Human Expertise: A Comprehensive Approach to the Future of Air Safety

article en

Abstract

The future of air safety relies on a holistic approach that integrates advanced technologies, human factors, and comprehensive training programs. This paper examines the critical components of aviation safety, including the development of intelligible software, the importance of robust training, and the irreplaceable role of human intervention in complex and high-risk scenarios. Through the analysis of key incidents, such as the Boeing 737 MAX and Air France Flight 447, the study highlights the challenges and opportunities presented by automation and artificial intelligence (AI) in aviation. It emphasizes the need for a balanced approach where technology supports rather than replaces human expertise, underscoring the value of human judgment, adaptability, and decision-making under pressure. The findings suggest that by fostering a collaborative environment where humans and machines work together, the aviation industry can achieve enhanced safety and efficiency. This research calls for continued investment in both technological advancements and human-centered training strategies to create a more resilient and adaptable aviation safety framework.

Zenodo (CERN European Organization for Nuclear Research)
Everglades University (US), Technical Database Services (United States) (US)
Openalex Percentile: Top 75%
Imbalanced Data Classification Techniques
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