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

Webinar "Industry-driven Use Cases"
AI4REALNET project covers the perspective of AI-based solutions addressing critical systems (electricity, railway, and air traffic control), modelled by networks that can be simulated and traditionally operated by humans and where AI complements and

100-Driver: A Large-scale, Diverse Dataset for Distracted Driver Classification
A large-scale, diverse posture-based distracted diver dataset, with more than 470K images taken by 4 cameras observing 100 drivers over 79 hours from 5 vehicles.
We provide a detailed analysis of 100-Driver and present 4 settings for investigating p

SAFEXPLAIN Introduction to Trustworthy AI for Safety-Critical Systems
This introductory video provides an overview of the steps taken by the SAFEXPLAIN project to ensure that the AI-based solutions used in safety-critical systems are Trustworthy, explainable and comply with the safety guidelines of diverse industrial d