Invited Talk by Mark Riedl: Reasoning, Alignment, and Explainability

In this talk, I will present a vision for human-centered artificial intelligence that emphasizes two (non-exhaustive) properties: AI that understands humans, and AI that helps people understand AI systems. Alignment is often cast as the process of making AI systems helpful, harmless, and honest; we can also think of these principles as AI system needing to understand what behaviors human users view as helpful and harmful. Explainable AI (XAI) is one path toward AI that helps its users understand its behaviors. We explore how reasoning can act as a framework for unifying perspectives on alignment and explainability. I will present work from my lab on alignment, explainability, and reasoning as partial glimpses at what might be possible.