While artificial intelligence is already omnipresent in our everyday life, it can be assumed that we will collaborate more and more with AI systems in the future also in our everyday work. This project aims to develop guidelines for such approaches of a human-centered design of collaboration between users and AI systems. Hereby, the focus is on the area of activity in air traffic management, in which operators work collaboratively. The underlying AI shall be able to recognize intentional states of aviation workers and make its decisions explainable to them. That is where the responsibility of the machine learning group of the Institute of Data Science is located in this multi-disciplinary project. We aim to create a prototypical classification algorithm that classifies intentional states such as fatigue and attention based on behavioral- and gaze-data of the aviation workers. Moreover, the classification should be made explainable, meaning that the decision of the Machine Learning algorithm is explained to the aviation worker in order to make the use of artificial intelligence in air-traffic management more trustworthy and accepted.
Project runtime: 04/2022 - 03/2026
Spokeperson: Julia Fligge-Niebling