AI in higher education

If you have the privilege of teaching in an IT program, change comes with the territory. Over the past twenty years, the nature of those changes was neatly dictated by the industry; we just had to follow along. Today is different. The disruption caused by AI is so immense that there seems to be no clarity yet on where we should be heading. The result is a lot of well-intentioned initiatives shooting off in all directions.

The context

AI is a disruptive technology that is already having a massive impact on the IT industry. No need to waste more words on that; nobody needs convincing there.

The dilemma

How education should deal with this, however, is much less clear to me. Specifically with IT skills like programming, the question quickly surfaces as to what knowledge is still necessary, and at what point AI can take over. On one extreme end of the spectrum is the view that you can only code well with AI if you are already a good developer; on the other extreme, programming knowledge has become obsolete. I’ll leave it to the experts to decide where it lands, and the truth likely lies somewhere in the middle.

Either way, it is getting more and more attention in the curriculum, bringing new dilemmas to light. One observation, for instance, is that AI threatens to quickly lead to higher pass rates for those who have the money to buy the most expensive and best models on their own initiative. This becomes obvious every day in the lab, where students working with free tools sit shoulder to shoulder with students who sometimes hold multiple subscriptions to the likes of OpenAI and Anthropic.

Heading into the next academic year, the decision will likely be made to provide students with an AI subscription so everyone competes on a level playing field. There are several choices here, and there is something to be said for each.

The three options:

Option 1: We have all students buy a Claude subscription. That way, we give them tools on par with what is used in the professional field. This is an extra cost for students, but IT studies are already very cheap compared to other degree programs.
Option 2: You don’t learn to drive in a Porsche either, and education has a moral duty to give European alternatives room to grow and build a user base—even if statistics show those models lag about a year behind their American counterparts. By having students buy a subscription to Mistral, we send a clear signal and give a push toward a stronger European AI footprint.
Option 3: A university of applied sciences is primarily a place where research and development must have a home. Instead of subscriptions for students (which amounts to roughly EUR 75,000 annually), it would be better to invest in in-house AI servers that students can use and that also benefit research. The experience gained from hosting models ourselves can then, in turn, be shared with the industry.