Learning in the Age of AI
3 Considerations for Navigating AI in Higher Education
Artificial intelligence (AI) is rewriting the rules of higher education, from how students learn to how universities plan for the future. In a wide-ranging discussion as part of our Adaptations in Higher Education series, three leaders explored what’s changing, what challenges remain and why human connection must stay at the heart of innovation.
- Lance C. Pérez, Ph.D., Dean of the University of Nebraska-Lincoln College of Engineering
- John Licato, Ph.D., Associate Professor, Bellini College of Artificial Intelligence, Cybersecurity and Computing of the University of South Florida
- Eric Eaton, Ph.D., Research Associate Professor, Department of Computer and Information Science, the University of Pennsylvania
Pérez opened with a reality check: students are already using AI tools, and faculty are adapting fast. “We now teach courses in programming that are language-agnostic,” he said, describing a shift toward problem-solving with agents rather than memorizing syntax. It’s a sign of how deeply AI is reshaping the fundamentals of computing education.
For Eaton, the change is just as profound. AI has transitioned from a specialized subfield into the mainstream, and with it, topics like fairness and privacy (once reserved for advanced courses) are being introduced much earlier. "It's important students understand that these models, which are in increasingly widespread use, have limitations," Eaton said.
Meanwhile, Licato sounded a note of caution about the stakes of AI literacy. “We’re acutely aware of the dangers of letting misinformation go unchecked,” he said, pointing to the ease of creating deepfakes and other deceptive content. For him, critical thinking is as essential as technical skill.
1. Build AI Literacy and Safeguard Scholarship
Beyond the classroom, the panelists explored how AI is transforming the field of research. Eaton likened AI tools to “a really intelligent, but less experienced research assistant” capable of speeding up coding and drafting, but prone to errors that require expert oversight. Licato highlighted tools like Perplexity and Notebook LM, which can accelerate literature reviews and even convert papers into audio for quick familiarity. “It’s no substitute for actually reading the paper,” he admitted, “but it’s a huge time saver.”
Yet convenience comes with risk. Eaton warned of emerging integrity challenges, including AI-generated paper variants designed to game peer review. Speaking as the Associate General Chair of the Association for the Advancement of AI (AAAI) Conference — one of the world’s largest AI conferences — he explained how this tactic exploits randomness in the review process and burdens reviewers. “We’re combating papers where someone writes a research paper and then uses AI to generate 10 different variants,” he said.
2. Create Human-Centered, Tech-Ready Campuses
AI’s rise isn’t just a curricular issue; it’s a design challenge. Eaton described the University of Pennsylvania’s new data science building as a deliberate counterpoint to isolation, featuring open corridors, collaborative whiteboards, natural light and even mass timber elements, all designed to foster human connection in tech-heavy spaces. In addition, the university launched a GPU cluster to centralize computing power and enhance efficiency.
Licato noted that environmental considerations now permeate planning, from cooling systems to decisions about on-campus servers versus cloud services. “It’s like a gas,” he said. “It fills up whatever space it’s given.” In other words, as AI becomes more efficient, demand expands to match capacity, a dynamic that keeps sustainability at the forefront.
Regarding the University of Nebraska-Lincoln, Pérez described an AI makerspace designed to encourage experimentation while reinforcing ethical use. “We wanted to give students a place where they could try, fail and learn,” he said. Beyond research, his campus is applying AI to advising, scheduling and human resources analytics, proof that operational impacts are as significant as academic ones.
3. Preserve Human Connection
As AI becomes ubiquitous, what should universities emphasize? Licato offered a compelling answer: Highlight the human experiences students can’t get from generative tools — hands-on creation, art and person-to-person engagement. “Universities will want to emphasize the value beyond what you get from YouTube,” he said.
Pérez echoed that sentiment, warning against letting AI become a poor substitute for human contribution. “This is really about valuing the human experience,” he said. Eaton agreed, urging institutions to avoid overreacting to hype and instead to focus on what technology can actually do and how it can be used appropriately to benefit people.
The conversation left me with an optimistic and pragmatic frame of mind. AI can expand learning, speed research and inform operations, but it works best when paired with clearly articulated values and human-centered design. Our charge is to prepare students to think critically, design ethically and collaborate deeply while building infrastructures and policies that help AI serve the mission of higher education.
