

Fairlearn
Fairlearn is an open-source, community-driven project to help data scientists improve fairness of AI systems.

Holistic framework for AI in critical network infrastructures
This document establishes the main foundations of the AI4REALNET project, in particular, the following key outcomes: - The formal specification of domain-specific use cases (UCs), replicating real-world operating scenarios involving human operator

Position paper on AI for the operation of critical energy and mobility network infrastructures
This position paper outlines AI4REALNET’s approach to applying AI in network infrastructure operations, translating application needs into algorithmic proposals for effective human-AI collaboration in decision-making processes.

Online course on Data Spaces for Mobility
Discover the world of mobility data spaces in this online course tailored for mobility professionals with a solid background in mobility planning, operations, data, and management.

I-AR project
The project aimed to implement fair automatic recognition by offering guidance in policy development on an European and national level.