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JRC exploratory workshop: Towards explainable, robust and fair AI in automated and autonomous vehicles: challenges and opportunities for safety and security

JRC organises a multi-disciplinary workshop dedicated to new testing approaches of automated & autonomous vehicles.

This JRC exploratory workshop is dedicated to the safety and security of automated and autonomous vehicles (A&AV), and aims to bring together leading scientist and engineers to explore and discuss the state-of-the-art research on accuracy, robustness, fairness and explainability of artificial intelligence (AI) and machine learning (ML) and testing of modern vehicles.

The workshop explores if and how explainability of their core AI and ML algorithms can be used to answer the following questions:  

  • How can we test the AI-ML layers in automotive environment?
  • How to define and quantify robustness, fairness, accuracy, repeatability, and reproducibility  of an A&AV’s AI-ML component?
  • Can we test the AI and ML separately from the vehicle?
  • How can we validate whether decisions made by AI and ML systems are correct in terms of safety and security?
  • How to detect biases in automated decisions and assess their impact in terms of fairness and robustness?
  • sustainable mobility | intelligent transport system
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  • Online only

Practical information

Online only
Who should attend
On invitation