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How Higher Ed Should Tackle AI

Chris Kanan is a clear-eyed voice on the future of universities in the age of AI.

Jan 27, 2026

2 min

Christopher Kanan


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Higher learning in the age of artificial intelligence isn’t about policing AI, but rather reinventing education around the new technology, says Chris Kanan, an associate professor of computer science at the University of Rochester and an expert in artificial intelligence and deep learning.


“The cost of misusing AI is not students cheating, it’s knowledge loss,” says Kanan. “My core worry is that students can deprive themselves of knowledge while still producing ‘acceptable work.’”


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Kanan, who writes about and studies artificial intelligence, is helping to shape one of the most urgent debates in academia today: how universities should respond to the disruptive force of AI.


In his latest essay on the topic, Kanan laments that many universities consider AI “a writing problem,” noting that student writing is where faculty first felt the force of artificial intelligence. But, he argues, treating student use of AI as something to be detected or banned misunderstands the technological shift at hand.


“Treating AI as ‘writing-tech’ is like treating electricity as ‘better candles,’” he writes.


“The deeper issue is not prose quality or plagiarism detection,” he continues. “The deeper issue is that AI has become a general-purpose interface to knowledge work: coding, data analysis, tutoring, research synthesis, design, simulation, persuasion, workflow automation, and (increasingly) agent-like delegation.”


That, he says, forces a change in pedagogy.


What Higher Ed Needs to Do


His essay points to universities that are “doing AI right,” including hiring distinguished artificial intelligence experts in key administrative leadership roles and making AI competency a graduation requirement.


Kanan outlines structural changes he believes need to take place in institutions of higher learning.


• Rework assessment so it measures understanding in an AI-rich environment.

• Teach verification habits.

• Build explicit norms for attribution, privacy, and appropriate use.

• Create top-down leadership so AI strategy is coherent and not fractured among departments.

• Deliver AI literacy across the entire curriculum.

• Offer deep AI degrees for students who will build the systems everyone else will use.


For journalists covering AI’s impact on education, technology, workforce development, or institutional change, Kanan offers a research-based, forward-looking perspective grounded in both technical expertise and a deep commitment to the mission of learning.


Connect with him by clicking on his profile.



Connect with:
Christopher Kanan

Christopher Kanan

Associate Professor of Computer Science

Christopher Kanan's research focuses on deep learning and Artificial Intelligence (AI)

AI and Machine LearningApplied Machine Learning (e.g. Medical Computer Vision)Language-guided Scene UnderstandingArtificial IntelligenceDeep Learning
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