
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.
Artificial intelligence, Flight deck design, Emergency response, Cognitive workload, Air France Flight 447, Aviation safety, Situational awareness, Automation, Pilot training, Human-machine interaction, Boeing 737 MAX, Intelligible software, Human factors, Decision-making
Artificial intelligence, Flight deck design, Emergency response, Cognitive workload, Air France Flight 447, Aviation safety, Situational awareness, Automation, Pilot training, Human-machine interaction, Boeing 737 MAX, Intelligible software, Human factors, Decision-making
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
