Science of Trustworthy Generative Foundation Models

We are living through a moment that once belonged to science fiction: generative foundation models can write, reason, design, diagnose, and increasingly, decide. They are no longer just predicting the next word — they are shaping knowledge, influencing choices, and becoming collaborators in science, medicine, education, and daily life. But here's the tension: as their capabilities accelerate, our ability to trust them has not kept pace.

Trustworthiness can't remain a "patch after the failure" or a moral hope layered on top of engineering. It must evolve into a science—a discipline as rigorous as the one that created these models in the first place. In this tutorial, we explore what that science looks like: how we understand model behaviors, measure and stress-test trust, and design systems that earn it. We'll build the foundations together, then step into the frontier—where models begin to exhibit human-like cognitive behaviors that inspire wonder, but also demand responsibility and new forms of alignment.

This session is an invitation: to move beyond building models that impress us, toward building models we can trust with what matters.