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Challenges and context

The AI Decision Making's "Black Box"

In Air Transportation Management the Decision Making Process is already associated with AI. The algorithms are meant to help ATCOs in daily tasks, but they still face acceptability issues. Today’s automation systems with AI/Machine Learning do not provide additional information on top of the Data Processing result to support its explanation, making them not transparent enough. The Decision Making Process is expected to become a “White Box”, giving understandable outcome through an understandable process.

XAI Solutions
XAI solutions

Transparency and Explainability

ARTIMATION’s goal is providing a transparent and explainable AI model through visualization, data driven storytelling and immersive analytics. This project will take advantage of human perceptual capabilities to better understand AI algorithm with appropriated data visualization as a support for explainable AI (XAI), exploring in the ATM field the use of immersive analytics to display information

News and events
News

Intermediate Review Meeting

On the 1st of February the ARTIMATION project held online the Intermediate Review Meeting with the Project Officer Alessandro Prister, together with Karine Bansard, Reza

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