Universities everywhere have been struggling to figure out how AI fits into higher education. Is using these tools an essential skill or a shortcut that hinders learning? And can universities still even matter in AI research, when the frontier is moving so fast and requires resources only the world’s richest companies can muster?
The University of Southern California is betting more than $200 million on the question. With a grant from a venture capitalist alumnus, the school is reinventing its curriculum, recruiting researchers, and expanding AI education beyond engineering and computer science.
The offices of USC’s new Stevens School of Computing and Artificial Intelligence still kind of looked like a building site when we visited in June — there was scaffolding and lots of bare rooms.
“Some people haven’t moved in yet,” said the school’s director Gaurav Sukhatme as he showed me around a lab for physical AI, filled with robotic arms.
“Those two robot arms are using modern sort of techniques to learn how to collaborate with each other to do bimanual tasks,” he said.
The new school recombines some existing programs within engineering and adds new tracks: a dedicated AI major and minors for non-STEM students to apply the tech in disciplines like art or history.
“We have a very project-driven curriculum, which allows us to refresh the projects that the students do as part of their degree programs, and we keep changing those projects and updating them,” said Sukhatme.
But moving at the speed of AI isn’t really what universities are built for. And the state of the art is expensive. Training one of today’s advanced models is estimated to cost hundreds of millions of dollars.
“One of the things a university is really good at is posing questions about not about what’s happening today, but about what might happen a decade from now,” he said. “It is having the freedom to think about entirely new ways of doing things.”
Shri Narayanan, professor of engineering, linguistics and psychology at the University of Southern California, at his Signal Analysis and Interpretation Laboratory (SAIL).
Jesús Alvarado/Marketplace
It also means having the freedom to keep humans at the center of that inquiry, according to Shri Narayanan. He runs USC’s Signal Analysis and Interpretation Lab, which uses AI to analyze patterns in human “signals” to tackle big clinical questions. Researchers at SAIL study beat boxers to understand how vocalization works to help preserve it in cancer patients, and identify early signs of autism or depression when treatment can make the biggest difference.
“For me, humans are at the center of everything, right? For humans, by humans,” said Narayanan.
But AI that can infer details about our health, mind or identity carries real risks, as well as real benefits.
“Can we do it in the right way? And this is not something just computer scientists can do,” he said, noting these questions demand expertise from clinicians, social scientists, even philosophers.
It’s this kind of cross pollination USC is aiming to foster with its focus on applying AI across disciplines.
Hannah Murray, PhD candidate at USC’s Thomas Lord Department of Computer Science, uses AI to help protect wildlife from being illegally smuggled across borders.
Jesús Alvarado
That’s also the kind of work computer science PhD candidate Hannah Murray is doing.
“I will always be a conservation girl. That’ll always be the work that I’m most passionate about,” she said.
Murray created a tool using AI to map global airports that are likely to be used by animal smugglers.
“Two airports in the U.S. actually came up as some of our most highly confident undetected hotspots, which we had Dallas-Fort Worth was one of them, and then also in Denver,” she explained.
USC is betting they can scale this approach — teach students across campus to use AI for the questions they’re passionate about.
But can they embrace AI without the tool becoming a hindrance to learning itself?
Director Gaurav Sukhatme said they have to try.
“There are very few times when you get these sort of massive disruptive technologies and an entirely new set of sort of innovative ideas can be harnessed, so, I think that’s exciting,” he said. “But when you get rapid pace of change, it is also tricky.”
Like the fresh offices still under construction, much of higher education is racing to build something new, and figure out what it means at the same time.
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