As students push back on AI, UW’s first Nobel laureate is taking a different approach

This year’s University of Washington speaker has decades of experience in a field that continues to benefit from AI and machine learning — but unlike some of his colleagues this graduation season, he likely won’t be busted on stage.

Mary E. Brunkow is a UW student and scientist whose research in immune regulation helped scientists better understand how the body regulates its own defenses. He and his colleagues won the 2025 Nobel Prize in Physiology or Medicine for their research. He will be the featured speaker Saturday at UW’s 151st Commencement.

Brunkow works at Seattle’s Institute for Systems Biology, where machine learning and AI-driven methods have been part of the research toolkit for years. He’s not a tech executive, he’s not a capitalist, and he’s not in the business of predicting the future of work.

This year, commencement speakers on campuses across the country have faced massive backlash when promoting AI. At the University of Arizona, former Google CEO Eric Schmidt was repeatedly challenged after telling students that the question was not whether AI will shape the future, but whether they will help shape it.

At Middle Tennessee State University, music industry major Scott Borchetta told graduates that AI was rewriting production and, when the students pushed back, they responded: “Work with it. Like I said, it’s a tool.”

But graduates aren’t just tinkering with AI. They rise and fall to the people they say – managers who have an obvious hand in the future they describe, speaking with certainty about the life they are not living.

At a time when students have spent four years watching AI reshape classrooms, recruiting, and the creative industries, many seem more willing to listen to voices based on inquiry than conviction.

Brunkow understands fatigue.

“AI affects everything people do; often, it’s presented in shocking or scary terms,” ​​he said in an interview. “I understand the backlash.”

Instead of dismissing that concern, he acknowledges it – while making the case that humanity has been in similar positions before. “It’s not the first time that there has been a new revolutionary technology or a new way of thinking, and the human race is very good at adapting and using those new things,” said Brunkow.

His perspective comes from years within research environments where computer tools revolutionized discovery long before AI became a cultural flashpoint. That exposure gradually builds a more balanced view of both the promise and limitations of the technology.

“If you’re going to throw something into your analysis that you don’t fully understand how it works, then how are you going to judge the final results?” Brunkow said.

In the scientific tradition, new tools are only valuable if they produce results that resist scrutiny: a very different stance from the “disruption is inevitable” stance that is common in technical circles.

He sees AI accelerating discovery without taking a judgmental position behind it.

“You’re still going to need subject matter experts,” said Brunkow. “The human brain will still need to ask the right questions and look at the results, so you can ask the next right question.”

That’s a more measured view of AI than the one many undergraduates got from the first stages this spring. Technology can speed up discovery, Brunkow says, but it doesn’t eliminate the need for curiosity, judgment, or the ability to know what question to ask next.

“It’s not like we’re going to solve all the problems, just because we have powerful and fast tools, but we can get to the answers quickly,” said Brunkow.

Brunkow doesn’t plan to warn graduates about AI, or urge them to be aware of the latest trends. He will talk about something less predictable: staying curious. Activities and discoveries, he said, rarely happen according to plan.

“Serendipity is an underrated part of human life,” Brunkow said. “Keep your eyes and ears open for unexpected things.”