Conversations over students using artificial intelligence to cheat on their exams are masking wider discussions about how to improve assessment, a leading professor has argued.

Phillip Dawson, co-director of the Centre for Research in Assessment and Digital Learning at Deakin University in Australia, argued that “validity matters more than cheating,” adding that “cheating and AI have really taken over the assessment debate.”

Speaking at the conference of the U.K.’s Quality Assurance Agency, he said, “Cheating and all that matters. But assessing what we mean to assess is the thing that matters the most. That’s really what validity is … We need to address it, but cheating is not necessarily the most useful frame.”

Dawson was speaking shortly after the publication of a survey conducted by the Higher Education Policy Institute, which found that 88 percent of U.K. undergraduates said they had used AI tools in some form when completing assessments.

But the HEPI report argued that universities should “adopt a nuanced policy which reflects the fact that student use of AI is inevitable,” recognizing that chat bots and other tools “can genuinely aid learning and productivity.”

Dawson agreed, arguing that “assessment needs to change … in a world where AI can do the things that we used to assess,” he said.

Referencing—citing sources—may be a good example of something that can be offloaded to AI, he said. “I don’t know how to do referencing by hand, and I don’t care … We need to take that same sort of lens to what we do now and really be honest with ourselves: What’s busywork? Can we allow students to use AI for their busywork to do the cognitive offloading? Let’s not allow them to do it for what’s intrinsic, though.”

It was a “fantasy land” to introduce what he called “discursive” measures to limit AI use, where lecturers give instructions on how AI use may or may not be permitted. Instead, he argued that “structural changes” were needed for assessments.

“Discursive changes are not the way to go. You can’t address this problem of AI purely through talk. You need action. You need structural changes to assessment [and not just a] traffic light system that tells students, ‘This is an orange task, so you can use AI to edit but not to write.”

“We have no way of stopping people from using AI if we aren’t in some way supervising them; we need to accept that. We can’t pretend some sort of guidance to students is going to be effective at securing assessments. Because if you aren’t supervising, you can’t be sure how AI was or wasn’t used.”

He said there are three potential outcomes for the impact on grades as AI develops: grade inflation, where people are going to be able to do “so much more against our current standards, so things are just going to grow and grow”; and norm referencing, where students are graded on how they perform compared to other students.

The final option, which he said was preferable, was “standards inflation,” “where we just have to keep raising the standards over time, because what AI plus a student can do gets better and better.”

Over all, the impact of AI on assessments is fundamental, he said, adding, “The times of assessing what people know are gone.”