Challenges from the Introduction of Artificial Intelligence in the European Air Traffic Management System

被引:4
作者
Stathis, Malakis [1 ]
Marc, Baumgartner [1 ]
Nora, Berzina [1 ]
Tom, Larsen [1 ]
Anthony, Smoker [1 ]
Andrea, Poti [1 ]
Gabriele, Fabris [1 ]
机构
[1] Int Federat Air Traff Controllers Assoc, IFATCA Joint Cognit Human Machine Syst JCHMS Grp, Montreal, PQ, Canada
来源
IFAC PAPERSONLINE | 2022年 / 55卷 / 29期
关键词
Cognitive Systems Engineering; Joint Cognitive Systems; Air Traffic Control; Air Traffic Management; Artificial Intelligence; Machine Learning; Digitalization; HUMANS;
D O I
10.1016/j.ifacol.2022.09.440
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The Air Traffic Management (ATM) system can be defined as a "Joint Cognitive System" of people, teams, and artifacts that adapts to the challenges and demands posed by familiar and unfamiliar situations in a dynamically evolving operational context. In the era of digitalization and Big Data we live, an incremental modernization of the ATM system is expected in the coming years with the pervasive implementation of Artificial Intelligence (AI) and Machine Learning (ML). In this paper, we present the findings from an initial attempt to detect and document the fundamental challenges of the introduction of AI, in the European ATM system through the lens of Cognitive Systems Engineering paradigm. We also discuss how these challenges give rise to difficult to resolve safety and performance related patterns in the ATM system. Copyright (C) 2022 The Authors.
引用
收藏
页码:1 / 6
页数:6
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