High Standards, Persistent Risks: Lessons from Boeing, Busan Airport and Beyond

Abstract

Airports like Schiphol maintain exceptionally high safety standards, employing rigorous protocols and advanced technologies. Yet, a persistent paradox exists: despite these efforts, airport accidents, including those resulting in human fatalities, continue to occur, often following a logarithmic stable Pareto distribution. This "fat tail" phenomenon (or called Black Swan in Nassim Taleb’s book) signifies that while minor incidents are relatively common, rare but catastrophic events remain a distinct possibility. This paper explores this paradox, examining the complex interplay of factors contributing to persistent risks, even within highly regulated environments. We analyze the limitations of current safety models and investigate the emerging challenges posed by increasing reliance on AI systems in aviation, exemplified by recent incidents involving automated flight control. Starting on Schiphol airport as a case study, we identify best practices and potential vulnerabilities. Furthermore, we extrapolate lessons learned to the broader aviation landscape, proposing a shift towards proactive, adaptive safety management strategies. These strategies emphasize robust training, explainable AI, enhanced redundancy, and a stronger safety culture to mitigate risks and improve resilience in the face of both known and unforeseen challenges, ultimately aiming to minimize the impact of the "fat tail" and enhance overall airport safety.