Artificial Intelligence - Stanford Webinar - Building Safe and Reliable Autonomous Systems

AI is changing fast. Building safe, trustworthy AI systems and establishing confidence in their behavior and robustness is crucial for their success and adoption in society. In this conversation with Dr. Anthony Corso, he discusses techniques for building safe and reliable autonomous systems using state of the art machine learning techniques for high-stakes applications such as healthcare, transportation, and critical infrastructure. View Anthony's course: https://online.stanford.edu/courses/xaa101-designing-reliable-and-robust-ai-systems About the speaker: Anthony is the executive director of the Stanford Center for AI Safety and the associate director of research for the SAIL-Toyota Center. His current research is split between developing verifiably robust autonomy and the using AI algorithms to tackle climate change. Learn more about Anthony: https://anthonylcorso.com/ Chapters 0:00 Introduction 01:38 Dr. Corso intro to reliable AI 03:24 Risks with Autonomous Systems 04:43 How AI Systems Fail 06:13 Can AI be more safe than humans? 07:44 Challenges & Scalability 08:58 Generalizability 11:19 Existential Risks of AI 13:17 AI Ethics 14:39 Applications of AI Systems 15:29 How to build safe AI Systems 21:00 Testing for Rare Events 22:05 Testing & Formal Verification 26:40 What is Robustness? 29:20 Uncertainty Quantification & Fallback Strategies