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A Framework for Supporting Adaptive Human-AI Teaming in Air Traffic Control

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Engineering Psychology and Cognitive Ergonomics (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14018))

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Abstract

In recent years, the growth of cognitively complex systems has motivated researchers to study how to improve these systems’ support of human work. At the same time, there is a momentum for introducing Artificial Intelligence (AI) in safety critical domains. The Air Traffic Control (ATC) system is a prime example of a cognitively complex safety critical system where AI applications are expected to support air traffic controllers in performing their tasks. Nevertheless, the design of AI systems that support effectively humans poses significant challenges. Central to these challenges is the choice of the model of how air traffic controllers perform their tasks. AI algorithms are notoriously sensitive to the choice of the models of how the human operators perform their tasks. The design of AI systems should be informed by knowledge of how people think and act in the context of their work environment. In this line of reasoning, the present study has set out to propose a framework of cognitive functions of air traffic controllers that can be used to support effectively adaptive Human - AI teaming. Our aim was to emphasize the “staying in control” element of the ATC. The proposed framework is expected to have meaningful implications in the design and effective operationalization of Human - AI teaming projects at the ATC Operations rooms.

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Author information

Authors and Affiliations

  1. IFATCA Joint Cognitive Human Machine System (JCHMS) Group, International Federation of Air Traffic Controllers Associations, Montreal, Canada

    Stathis Malakis, Marc Baumgartner, Nora Berzina, Tom Laursen, Anthony Smoker, Andrea Poti, Gabriele Fabris, Sergio Velotto & Marcello Scala

  2. Cognitive Ergonomics and Industrial Safety Laboratory, Department of Production Engineering and Management, Technical University of Crete, Chania Hellas, Greece

    Tom Kontogiannis

Authors
  1. Stathis Malakis
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  2. Marc Baumgartner
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  3. Nora Berzina
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  4. Tom Laursen
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  5. Anthony Smoker
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  6. Andrea Poti
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  7. Gabriele Fabris
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  8. Sergio Velotto
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  9. Marcello Scala
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  10. Tom Kontogiannis
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Corresponding author

Correspondence to Stathis Malakis .

Editor information

Editors and Affiliations

  1. Coventry University, Coventry, UK

    Don Harris

  2. Cranfield University, Cranfield, UK

    Wen-Chin Li

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Malakis, S. et al. (2023). A Framework for Supporting Adaptive Human-AI Teaming in Air Traffic Control. In: Harris, D., Li, WC. (eds) Engineering Psychology and Cognitive Ergonomics. HCII 2023. Lecture Notes in Computer Science(), vol 14018. Springer, Cham. https://doi.org/10.1007/978-3-031-35389-5_22

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  • DOI: https://doi.org/10.1007/978-3-031-35389-5_22

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  • Online ISBN: 978-3-031-35389-5

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