Supporting the transition to higher levels of automation in aviation by creating and empirically evaluating next generation computer-based tools  

In the emerging age of Artificial Intelligence and Machine Learning, the MAHALO SESAR Exploratory Research project aims to answer simple, yet profound questions: should we be developing automation that is conformal to the human, or should we be developing automation that is transparent to the human? Do we need both? Further, are there tradeoffs / interactions between the concepts, in terms of air traffic controller trust, acceptance, or performance?

In order to answer these questions, MAHALO will develop an AI-based conflict detection and resolution tool, in which the levels of conformance and transparency can be manipulated by the researchers.

Air traffic controllers will use the tool in realistic scenarios, experiencing different levels of transparency and conformance. The impact on trust, acceptance, system understanding and performance will be measured and conclusions will be derived on the best trade-off between those two concepts.

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