• What are the challenges to step from fail-safe to fail-operational architectures as a foundation of ML systems in HAD?
• What do we still need to do to achieve functional safety for deep learning algorithms?
• What solutions could be applied to address challenges in simulation, testing & validation of AI & sensor fusion systems?
• What methods should we use to test and validate synthetic data for real world environments?
• How to address the interpretability and transparency challenges of machine learning models to ensure compliance with functional safety standards?

Presenting the results of our World Cafés: The moderators summarize the key takeaways of their World Café Round Tables on the main stage and share the main findings with all attendees.