It almost seems a cliche to say that generative AI is both the greatest threat, and the greatest opportunity, for higher education. That doesn't make the statement any less true. And there are many commentators who are trying to work out what happens next for higher education. I think one of the best is Hollis Robbins, whose Substack Anecdotal Value is well worth subscribing to.
Robbins was recently interviewed by Jay Caspian Kang of The New Yorker (paywalled, but you can find an ungated version here) about the future of higher education. The whole interview is worth reading, but I want to highlight this bit in particular, where Robbins says:
I was in Austin, Texas, a couple of times in March with a bunch of twenty-five-year-old billionaires. This is what they’re looking at. Instead of having the credential from the institution, why not have the credential from the professor? If you have a Hollis Robbins education, what would that signal? What would that credential mean as opposed to a degree from a university? There was some conversation about what that would look like, and one guy at the end of the dinner said, “Instead of OnlyFans, it’s like OnlyProfessors.”
The correct analogy here would be that it would be OnlyStudents, not OnlyProfessors (since the name contains the audience, not the performer). However, Robbins makes a good point. Higher education is, in part, an exercise in signalling (as I've noted before here and here). In fact, Bryan Caplan argued in his book The Case Against Education (which I reviewed here) that one third of the benefit of higher education is signalling (the other two-thirds is made up of genuine learning, socialisation, and transferable skills).
The diploma that a student receives at the end of their higher education journey is a signal to employers of the student's quality as a future employee. The signal is credible to the employer because it is costly for the student to obtain, and costly in such a way that low-quality students wouldn't attempt the signal. University reputation matters here, because it is an assurance of the second of those conditions - low-quality students wouldn't attempt the signal of a Harvard degree, firstly because they wouldn't gain admission to Harvard in the first place. So, part of the signal comes from getting into Harvard. Second, low-quality students wouldn't attempt the signal of a Harvard degree because passing courses at Harvard is hard (or, at least, harder than at many other universities). The quality of the education at Harvard has traditionally been higher than elsewhere.
In the interview, Robbins makes a further important point, which is that we've spent the last several decades making higher education a commodity. Students studying a degree in a particular subject learn the same things, often using the same teaching materials, the same textbook, and the same style of assessment, regardless of which university they go to. That means that the quality of signal that arises from the education itself has reduced over time, meaning that most of the value of the signal arises from the admission process. Once a student has been admitted to Harvard, their signal is in place, and the further signalling from their education is lower than for comparable students in years past.
Robbins argues that generative AI is accelerating and expanding this commodification of education. Since generative AI has access, through its training corpus, to a large store of human knowledge, to add value over and above generative AI a professor must be a true expert in a very specific subfield. For students, learning a subject from a true expert still retains value, because generative AI cannot as easily replicate the learning that would occur from the expert. At that point, the university becomes less important as a mediator of education.
In other words, Robbins is arguing that the university could be disintermediated, with individual professors issuing credentials instead of universities. Who needs a Harvard degree, when you could have a Hollis Robbins degree? And since Robbins is an expert (in African American sonnet tradition, she says), the signal retains high value. However, that is true only to the extent that employers find the Hollis Robbins degree a credible signal.
That brings me to this Substack post by Auren Hoffman. Hoffman also argues that generative AI has diminished the value of the higher education signal. However, Hoffman argues for a different solution, this time from the perspective of the graduating student:
you have to show you can add value. that is it. that is the only thing.
the test the smart hiring manager applies in 2026 is simple. can you learn something on your own? can you finish what you started? can you do what you said you would do? these were always the skills that mattered. the difference is they are now the ONLY skills that matter, because the credential stopped doing the screening.
if you have a few years of experience, your resume can show you have these skills. if you are a new grad, you have to show what you have created and built.
Hoffman is overstating things a little, as university degrees are unlikely to disappear overnight. However, his critique is still important, as is the implication he draws. Hoffman argues that graduates (or young people, generally, since the solution doesn't depend on a student attending a university or completing a degree) need to become builders:
the most valuable thing a 22 year old can do in 2026 is create something. an app. a screenplay. a side business. an internal tool you wrote for a club you were in. a dinner series. a script that automates something annoying. a website. a chrome extension. a sculpture. a dance party. a discord bot. a substack with 32 readers and a real point of view. anything that moved from idea to working.
will the thing make money? probably not. that is not the point.
the point is that you taught yourself something. you finished it. you can describe what you learned, what broke, what you fixed, why you made the calls you made. that story is the new resume.
every hiring manager would rather interview a 22 year old with a launched app and a github full of weird side projects than a 22 year old with a 3.9 GPA from a top 50 school. it is not close. when one candidate has tangible evidence of what they can ship and the other has a transcript, the transcript will lose every time.
According to Hoffman, the best signal for young people to be sending in future is that they can build. Our students will ultimately be more successful if they can show off their skills (both technical and transferable skills) by building something. That is a signal that is costly, and costly in such a way that low-quality students will not attempt it. The signal is credible, and for the most part it retains currency even in the face of generative AI. Indeed, if the student builds something while effectively leveraging generative AI, then the signalling value to employers may be even greater. The key distinction is between the student using generative AI as a tool and the student using it as a substitute for doing the work. A student who can explain what they built, what broke, what they learned, and why they made the choices they made, is still sending a costly signal. A student who simply lets generative AI build for them is not. Employers would likely see through the latter pretty quickly.
Hoffman's idea isn't exactly new. When I think about some of my best students over the past two decades, they tend to be those that built something either while they were studying, or immediately after. For some, this was their own small business or entrepreneurial activity. For others, it was writing and publishing a research paper. Those were challenging tasks that set them apart from other students - a clear signal of quality. What Hoffman is essentially saying is that, with the signal from higher education itself being removed, the only remaining signal of quality is the signal from being a builder.
Where does that leave higher education staff? I think we can combine Robbins's and Hoffman's ideas, and chart a path forward. We don't need to start an OnlyStudents, and issue our own degrees, but we do need to cultivate closer relationships with our best students. Teach them to be builders. Encourage them to create things. Work with them and chart a path forward for their success. In other words, be a mentor.
Universities are absolutely going to hate this. Mentoring is not an activity that can be offered at scale. For example, there are simply not enough hours in the day for me to individually mentor all of the 350-plus students in my first-year economics class. Nor is mentoring easy to timetable, measure, standardise, or reward under current academic workload models. Universities are built around papers, credit points, learning outcomes, assessment rubrics, and student evaluations, all of which can be offered at scale. One-on-one mentoring doesn't work so well in that system. For example, postgraduate supervision already sits awkwardly within the system, with it being unclear whether it counts as teaching, or research. Nevertheless, mentoring may be one of the few ways that higher education can continue to offer something that is both valuable and difficult for generative AI to replicate.
If generative AI significantly reduces the signalling value of university education, and if students increasingly use it to avoid genuine learning, then the current mass higher education model looks increasingly fragile. Moreover, what remains is going to cost students a lot more. If having a high-quality mentor who can encourage a student to build is the path to their future employment, then it may be worth it. After all, high-quality signals are costly. That aspect of education, at least, won't have changed.
[HT: Marginal Revolution, for both the Hollis Robbins interview and the Auren Hoffman post]
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