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The university sector in is at a tipping point due to chronic underfunding, shifting enrolments and increasing costs from inflation. In response, the government has established to assess the health of the sector and provide recommendations for the future.

Meanwhile, universities find themselves increasingly beholden to the education technology (EdTech) industry, which claims to improve student learning by selling hardware and software – often built with artificial intelligence (AI).

Most universities already pay for services from EdTech companies such as Turnitin, Grammarly, CampusTalk and Studiosity, all of which use AI in their products.

But critics say this trust in EdTech is misplaced and amounts to what technology writer Evgeny Morozoc calls – “the idea that given the right code, algorithms and robots, technology can solve all of mankind’s problems”.

Intellectual property and profit

To better understand how EdTech providers work, consider the plagiarism-detection company , used by .

Student essays are intellectual property (IP). According to university policy, students and universities have a shared licence over any IP written by students.

But when teachers require students to upload their essays to Turnitin, students must a “non-exclusive, royalty-free, perpetual, worldwide, irrevocable licence” to use their IP.

Turnitin adds those essays to its massive database, which it uses to build its plagiarism detection tool. The tool – built with student IP – is then sold back to universities so educators can police student writing in the name of academic integrity.

After 20 years of growth with this business model, Turnitin was by Advance Publications for US$1.75 billion. On Twitter (now X), higher education researcher : “How much of that $1.75B do you think is going to the students who have fed their database for years? I have a pretty good guess: zero billion.”

By claiming ownership over student IP, Turnitin also profits from Indigenous students’ ideas. But this threatens – that data produced by or about Indigenous communities should be governed by those communities.

AI teaching clones

EdTech organisations such , and are now developing new AI teaching clones. These “” are trained on educators’ own course materials and can interact with students around the clock.

For overworked teachers, an AI clone might seem appealing. In one , a lecturer praises the clone for helping him teach biochemistry to more than 800 students.

Of course, another way to improve the teaching of such a large course is to hire more teachers. The Tertiary Education Union will surely emphasise this point in its this year.

But it’s not surprising universities are looking for cheaper options, given the sector has endured .

Here’s the catch, though: we don’t yet know the full cost of AI agents in education. They may be free or cheap now, but it takes a lot of computing power to create and engage with a customised AI agent – almost certainly more power than teachers and students have on their personal computers.

For that reason, organisations that develop AI agents rely on access to high-performance servers provided by the likes of Microsoft and Amazon Web Services. After sufficient market penetration, though, these multinational companies will want a return on their investment. Will AI agents still be cheaper than teachers then?

Energy-intensive investment

We also don’t know how much energy it takes to build and operate hundreds of AI clones for tens of thousands of students. But we do know Microsoft recently of being carbon-negative by 2030 due to AI’s increasing demand for “energy-hungry data centres”.

Many New Zealand universities also aim to be carbon-neutral by 2030. Will they too have to renege on their green commitments? Or will outsourcing AI to EdTech companies allow them offload responsibility?

Historically, it has been difficult for teaching institutions to untangle themselves from EdTech investments. This is despite “85% of EdTech tools are poor fits or poorly implemented”.

If AI is “” is it worth the financial and environmental cost to create AI agents for educators?

Product or public good?

Without sufficient government funding, EdTech products look appealing to universities. But tertiary stakeholders must question whether EdTech “solutions” really contribute to a university education.

If a university education is primarily viewed as a product in a global marketplace, then EdTech tools might add monetary value.

But if a university education is viewed as a public good that contributes to the improvement of society, then EdTech tools might be less valuable.

Now is the time for a broader conversation about the cost and value of a university education, and the role of EdTech within it.