Human machine teaming in the air traffic control operations rooms: The IFATCA’s perspective

An adaptive 21 st century organization is archetypically digitally powered, leading many organizations to pursue digital transformation. Air Navigation Service Providers (ANSPs), which are the building blocks of the Air Traffic Management (ATM) system, are not an exception to this rule. Sustained adaptability is a relentless call for ANSPs and refers to the ability to continue to adapt to changing environments, stakeholders, demands, contexts, and constraints within the wider aviation system. In this context Artificial Intelligence (AI) and Machine learning (ML) are finding their way into the ATM operational environment. This paper presents the results of an initial attempt to design a Human Machine Teaming (HMT) guide in the ATM domain. The aim of the HMT guide is to assist Air Traffic Controllers in integrating technology in the various forms of new intelligent, autonomous systems, automation and AI/ML that can work in adaptive partnership with the human practitioners in the operations rooms. We followed a Cognitive Systems Engineering (CSE) approach to develop an HMT guide based on a set of generic principles and an iterative process. We used a range of methods over several phases of fieldwork, documentation analysis and finally divergent thinking, comparative reasoning, and integrative thinking to compile a set of generic principles and an iterative process of four stages before fielding a technology system in the operations rooms. The proposed HMT framework could provide a viable solution to the efficient introduction of innovative technology in the Air Traffic Control Operations Rooms.