The Gold and the Failed Results of Artificial Intelligence in Aviation

Abstract

When James Lee wrote his perceptive assessment of management theories in 1980, he described the achievements (gold) and failed results (garbage) as a caution to practitioners. Considered in the light of current applications of artificial intelligence (AI) in the aviation arena, this approach proves beneficial in examining the pros and cons currently and assessing the positive achievements as well as the less successful efforts. Following a brief review of the origins of AI, representative successes of AI applications in flight deck operations, air traffic management, maintenance, aircraft design, airport operations and airline management are provided with specific examples that demonstrate how AI is proving beneficial. Among these are uses in fleet operations, crew scheduling, safety risk management, fuel efficiency, and twelve other uses. Conversely, two seasons of AI growth and decline are explained and the ensuing resiliency which is propelling the current momentum of expectations. The Gartner Hype Cycle of AI is described with attendant promises and potential disappointments related to aviation. Then, an overlay of the AI roadmaps from aviation safety agencies are given to indicate timelines for expected development and growth. When the seasons, Hype Cycle, and roadmaps are considered together, patterns emerge indicating likely milestones and breakthroughs for AI in the aviation environment. These combine to show pathways that the gold and garbage may take. Illustrations of how AI fails are discussed with perspectives on operator trust in AI and limitations that are becoming more evident. Looking forward, technologies that are advancing AI in aviation are identified and the growing use of agenic AI is considered in the aviation context. Neural versions of AI and quantum computing are assessed as next generation AI applications.

Keywords: Artificial Intelligence, Aviation, Successful Applications, Failed Efforts

DOI: 10.54941/ahfe1007837