As the parent of two children, I very much understand the desire for the people we care about to become fully realized, happy, complex, engaged members of society who make the world a better place while living lives of consequence and joy.
I also understand wanting them to have an income, health care, a retirement plan, and perhaps ultimately a domicile that is not my basement.
So imagine that you are responsible for designing a college education in 2026, and you ask a reasonable but deceptively complicated question:
What should an 18-year-old study and experience to prepare for a series of careers that might last from 2030 to 2075, while also living a fulfilling life along the way?
Looking back through history, and even considering the moment we are in now, I hope it is obvious that the answer cannot simply be: learn whatever technical skill employers happen to want in September of 2026.
Students certainly need technical skills. They need disciplinary knowledge. They need experience using the tools of their fields, whether those are developed through courses, research, internships, summer programs, or other experiences.
But perhaps most importantly, they need to become exceptionally good at learning things they do not yet know.
The enduring value of a liberal arts education lies in its combination of breadth, depth, and intellectual flexibility. It prepares students not simply for a particular job, but for a future we cannot fully anticipate.
We cannot know exactly what information today’s students will need 20 or 30 years from now. We cannot even know what many of their jobs will look like 10 years from now. So a great education cannot simply consist of transferring a fixed inventory of information from professors to students.
We are trying to develop people who can encounter something they do not understand and figure out how to understand it.
- People who can read carefully.
- Ask good questions.
- Recognize a weak argument and construct a strong one.
- Work with quantitative evidence.
- Understand perspectives very different from their own.
- Communicate complicated ideas clearly.
- Make judgments when the evidence is incomplete.
- Have enough intellectual confidence to reach a conclusion and enough intellectual humility to recognize that they may be wrong.
And that is one reason the Ƶ curriculum has the structure that it does.
Students develop depth through a major. They also encounter very different ways of understanding the world through the Liberal Arts Core, electives, research, off-campus study, and experiences outside the classroom.
The design allows considerable choice and broad exploration while encouraging students to become intellectually flexible enough to approach complicated problems from more than one perspective.
A scientist benefits from understanding how a historian thinks. An economist benefits from understanding culture and language. A writer benefits from understanding science and quantitative evidence.
I think AI makes another feature of this education more important, although perhaps a little harder to explain.
Students today can produce astonishingly good-looking work with very little effort.
They can generate a summary of an article they have not read. They can produce an outline before they have decided what they think. They can ask AI to solve a problem, write code, analyze data, edit prose, or explain a difficult idea.
A challenge we are facing is ensuring that students see the distinction between producing a product and developing their minds.
I sometimes use an analogy with our Division 1 student athletes: the goal of a strength and conditioning program is to become stronger, faster, more durable, and better prepared to perform.
A coach or trainer may ask an athlete to lift 225 pounds for 12 repetitions or run three miles, but nobody thinks the purpose of the exercise is simply to get the repetitions or miles recorded. Having a forklift do the lifting or using a scooter to cover the three miles would superficially deliver the requested “product” but fail on producing the desired adaptation.
Academic assignments work in much the same way. When a professor asks a student to write an eight-page paper, please trust me when I say that the world generally does not desperately need another undergraduate paper on Pride and Prejudice, World War I, or Freud.
But we think the student needs the process involved in producing that paper.
The student has to read carefully, decide which information matters, reconcile sources that disagree, determine what they think, construct an argument, evaluate evidence, anticipate objections, and then take something complicated in their head and make it understandable to another human being.
The work associated with the paper is the workout. It is what produces the learning we actually care about.
This means that your students are sometimes going to be asked to do things that may feel like running three miles when they own a car and could simply drive.
- They will be asked to read an original text rather than a summary.
- To work through a computational or mathematical problem before reaching for software.
- To write the first draft themselves.To put the phone away.
- To sit with a difficult idea longer than feels comfortable.
There is an important idea from cognitive psychology called “desirable difficulties.” Some forms of learning that feel slower and harder in the moment can produce stronger learning later. The point is not that difficulty is inherently good. It is that removing every difficulty can also remove some of the cognitive work that produces learning.
AI has complicated this entire enterprise considerably. It can give us a polished answer before we possess the understanding that would allow us to produce, evaluate, or challenge that answer ourselves. So one of the questions I hope our students learn to ask is not, “Can I use AI to do this?” but instead, “What is the intellectual work here? Is AI helping me do that work and learn from it, or is AI doing the work instead of me?”
I do not mean this to be anti-AI. I use AI frequently. In some situations, it can be extraordinarily useful. But using AI to bypass the processes through which we acquire understanding, knowledge, judgment, and cognitive skill can leave us with a better product in the moment and a less developed mind moving forward.
And this may ultimately be one of the strongest cases for a liberal arts education in the age of AI. We are not preparing students to compete against artificial intelligence at tasks machines will increasingly perform better than humans.
We are preparing them to live and work in a world with extraordinarily powerful technologies while bringing to the table the capacities that allow them to decide what questions are worth asking, whether an answer makes sense, what evidence deserves trust, what ought to be done, how to persuade another human being, how to work with people unlike themselves, and when the machine may simply be wrong.
That combination of human judgment and technological capability may be one of the most important advantages our students carry into life after college.
The tools will change. The interfaces will change. The technical skills that seem indispensable today may look very different ten years from now. But students who know how to learn, how to think, how to judge, and how to adapt will be much better positioned to keep changing with them.
Ƶ students continue to find success in their next opportunity after graduating. And as I mentioned at the start, that first job or graduate school placement after Ƶ, and perhaps not living in our basements forever, is indeed something we care about as parents.
I do hope, though, that the value of a Ƶ education is not measured only by the first job after graduation.
The larger test is whether our graduates can navigate the opportunities and disruptions they encounter in their 20s, 30s, 40s, 50s, and 60s; whether they can adapt when their professions change; whether they can continue learning when the tools change; whether they can make good judgments in circumstances neither they nor their parents or professors could have anticipated; and whether they become thoughtful, curious, capable human beings who contribute meaningfully to their communities.
That has always been the aspiration of liberal education.
AI does not make that aspiration obsolete. It makes it more urgent.