Modern machine learning techniques are a key enabler of the autonomous driving systems in development today, a fact which leads many to describe the technology as an “artificial intelligence (AI) problem.” In fact, ensuring safety-critical autonomous driving performance is not simply a matter of training data and algorithms, but requires a carefully constructed system to support and enable core AI functions. In this panel, leading experts will explain how autonomous vehicle (AV) developers architect complementary technologies and capabilities into systems whose safety can be assured in ways that “AI” alone cannot. We’ll also explore how systems engineering enables validation and the safety case, allowing developers to demonstrate the safety of their vehicles to the public and win their trust.