This course addresses the verification and certification of vision-based landing systems in aeronautics under the ARP AI standard framework. Participants will explore robust testing via adversarial attacks, robust validation, and formal verification tailored to object detection metrics like IoU. The curriculum covers formal explainability for failure hazard analysis and provides hands-on Colab tutorials using PyTorch, auto_LiRPA solvers, and the LARD dataset to deliver actionable industrial certification assets.

Maximilian Kiener is Head of the Institute for Ethics in Technology at Hamburg University of Technology (tuhh.de/ethics) and Associate Research Fellow at the Oxford Uehiro Institute for Practical Ethics. He holds a BPhil and DPhil in Philosophy from the University of Oxford, where he also served as an Extraordinary Junior Research Fellow and Leverhulme Early Career Fellow. His research explores the ethics of artificial intelligence, with a particular emphasis on ethics by design and moral responsibility.

This talk presents deep ethics as an emerging field concerned with translating qualitative ethical reasoning into computational forms, including metrics, models, and decision procedures. Deep ethics promises to embed ethical reasoning directly into AI design. But it also risks excluding what cannot be measured, disguising assumptions as technical facts, and narrowing practical judgement. The central question is whether ethics can be made computable without losing the openness and contestability that make ethical deliberation possible.