Although recent research confirms that a college degree remains a sound financial and personal investment, there is a trust gap between institutions and the public. Part of closing that trust gap is talking openly about what is actually on people’s minds. AI is one of those topics.
My college recently approved a new certificate program in artificial intelligence, and the faculty conversations that preceded the vote were expansive and thoughtful.
Colleagues raised serious questions: What are the environmental costs of large-scale AI systems? How do we protect students’ ability to think independently when powerful tools can generate plausible-sounding answers in seconds? What happens to trust—in information, in institutions, in each other—when it becomes harder to distinguish the human from the automated?
Are there things we should deliberately not use AI for, because the difficulty is the point of the learning? And, at the fundamental level, how does this application of technology align with our pedagogical foundation in the liberal arts?
Thinking, learning, and doing together
The certificate was not our starting point. It came after a full year of conversation through participation in the AAC&U Institute on AI and Curriculum, with a specific focus on curricular integration.
Faculty developed an AI literacy framework for Rollins, which we refer to as likely always in draft form and always evolving, that combines foundational knowledge, practical skills, and ethical and social awareness. One principle emerged clearly from those conversations: we value AI fluency, but the core experience at Rollins will remain human-centered.
We will build opportunities for students to combine AI with their own judgment, while continuing to protect the kind of deep, effortful learning that builds cognitive capacity over time. We will keep on thinking, learning, and doing together, not from a place of fear, but making a path using our values.
We didn’t resolve all of those questions. We’re still working on them.
Higher education is an ideal place to grapple with these issues. Here is what I believe about AI and the liberal arts, offered not as a finished argument but as one I’m still making as the conversation unfolds on our campus: AI has not weakened the case for liberal arts education. In fact, it has made that case more urgent, and more complicated.
Reasons to engage with Al
The urgency is real. In a world where technical skills become outdated quickly, the enduring value of a liberal arts education is intellectual flexibility: the ability to think deeply, shift frameworks, and tackle problems that don’t come with a manual.
When AI can automate increasingly sophisticated technical and repetitive work, the skills that remain distinctly human—discernment, ethical judgment, communication, the ability to ask the right question—become more valuable, not less. This is precisely the preparation students need for the world they are entering.
But the complication is equally real. AI is not a neutral tool. It carries embedded values, consumes significant resources, shapes how people think, and concentrates power in ways that deserve scrutiny.
And it poses a particular risk to learning when students offload cognitive work they have not yet learned to do themselves. The struggle of writing a first draft, working through a difficult problem, sitting with uncertainty long enough to form a real view, is not inefficiency. It is how human beings build the mental capacity for complex thought.
These are not reasons to avoid AI. They are reasons to engage with it exactly the way a liberal arts education teaches us to engage with everything: closely, critically, and with attention to consequences we cannot yet fully see.
At Rollins, that looks different in different classrooms, which is also true to our liberal arts ethos. In some courses, students are learning to use AI as a genuine intellectual partner—testing ideas, stress-testing arguments, exploring what the tools can and cannot do, and creating agents as an extension of their own expertise.
Some faculty have made a deliberate pedagogical choice to restrict AI use entirely because the productive difficulty of working something out by hand is itself the learning. In other classrooms, AI ethics and AI’s societal implications are embedded into the curriculum as disciplinary questions: for computer scientists, yes, but also for historians, ethicists, and economists.
What all of these share are the three pillars of what liberal-arts institutions do—critical thinking, ethical reasoning, and civic responsibility—applied to one of the most consequential developments of our time. We are not teaching students what to think about AI. We are teaching them how to think about it, and modeling that process ourselves.
Preparation for a good life
The pessimism about young people that surfaces in so many conversations about higher education’s future is, in my experience, misplaced. We serve both traditional-age students coming straight out of high school and adult learners in undergraduate and graduate programs, and the students I spend time with are serious, curious, and clear-eyed about the world they’re entering.
They don’t need us to protect them from complexity. They need us to give them the tools to navigate it.
What we offer, at our best, is preparation for a good life: doing the things that matter, pursuing knowledge as a habit of mind, staying curious long after graduation. Optimism is not our strategy, but realistic optimism is our ethos, and it comes from serious conversations with each other and with our students.
I hope that our students will live for the eulogy, not the resume. That is not a soft aspiration. It is a rigorous educational philosophy.
And the moment we stop being honest about how hard it is to deliver on that philosophy, including when we’re sitting in faculty sessions arguing about whether to trust a machine, we lose the essential human qualities that make colleges like ours worth trusting.