AI ‘blind spots’ the biggest threat to universities

Universities that only recognise academic integrity implications are ‘really missing the picture’

April 19, 2024
Person wearing VR headset to illustrate AI ‘blind spots’ hide risks and limit potential rewards for HE
Source: Joan Cros/NurPhoto/Getty Images

“Blind spots” are the biggest danger for administrators balancing the risks and rewards from artificial intelligence (AI), according to the head of a global council helping universities and other organisations navigate the rapidly evolving technological landscape.

Danny Bielik said universities were selling themselves short if they viewed AI exclusively as a tool to aid or catch cheats. “If you think the only impact AI is going to have on your university is [around] academic integrity, then you’re really missing the picture,” said Mr Bielik, Singapore-based president of the Digital Education Council (DEC).

“It’s the blind spots that often cause the most change. Where are you looking? Where aren’t you looking? What is best practice? What are people testing in other parts of the world?”

DEC’s seven institutional founding members – in Australia, Hong Kong, Italy, Mexico, Singapore, South Africa and Spain – generate strategies and policy statements to underpin discussions with decision-makers.

Mr Bielik, a former adviser to New South Wales education minister Adrian Piccoli, said some universities were “super-focused” on generative AI’s use in cheating and had pinned their hopes on AI detection tools as an antidote.  

This “whack-a-mole” approach was unlikely to work, and risked blinding administrators to other applications such as AI impersonation. “It’s only a short matter of time before people are able to generate videos that look and sound like other people and react in real time. Some…image generation [tools can] generate passports that can pass through identity checking software.

“You’ve got to take a step back and think about what a resilient educational value chain looks like and how you maintain it…from beginning to end, from all the documents that a student gives you before they arrive, to their identity, to the way that teaching and learning is done, to the way that you credential them and so on.”

An excessive focus on the dangers also risked obscuring the potential of AI in teaching and learning, through things like automated translation, predictive analytics – used to identify students at risk of failing, for example – and sentiment analysis to determine whether students understood the subject matter during online classes. AI tools could remove “some of the drudgery” from admissions and “dramatically reduce the time it takes to get an offer out”.

But educators needed to be wary of the downsides, including biased datasets and the need to handle information carefully – for example, the information amassed by a student support “chatbot”.

“Where does the data you’ve trained it with go? What happens to the data that the students provide when they ask questions? Where is it located? Who has access to it? These are sometimes questions that universities are not prepared to ask. Or…when they get the answer, they’re not prepared to deal with it.”

Nevertheless, universities could not afford to ignore AI because it was revolutionising many of the disciplines they taught, from medicine to information technology. Students denied insights into these changes faced a “complete mismatch” between their subject knowledge and workplace realities after they graduated.

“Regulatory, technological, pedagogical, societal – you need to be aware of it on all of these levels,” Mr Bielik said.


Print headline: AI ‘blind spots’ hide risks and limit potential rewards for HE

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Reader's comments (4)

The flip side is unis jumping on a bandwagon before it is even clear what the destination is or whether it is road-worthy. You should equally ask are you preparing your students for a future where any use of "AI" is heavily regulate or even curtailed As for use of AI in analysing student performance and risk . Exam boards have managed to do that with nothing more sophisticated than sheets of paper showing performance in all years and activities beyond the numerical data such a process also allows professionals to bring contextual data on circumstances that have affected students a capability still beyond "AI". If its not broken don't fix it.
To DJ Duke at Leeds, I am a recovering Luddite but even I can see that AI might have many positive uses. I think we might risk a rickety ride for a few years (?months) to get the measure of what AI can bring to education and broader society. Don't forget that "without vision we perish". BW
I encourage my students to use AI in their research, even in class. Students find that AI does not always help them with critical thinking, so we go back to the first principles of critical thinking and the class discussions are more engaged. We also see if students can spot AI generated work. Fun!
This piece has a very AI generated feel to it. I think it is missing the bigger elephant herd in the room of AI in society as a whole. Employees of many graduates will also/are currently using AI to fulfil the roles that would be normally be carried out by those with some modest HE training. We need to get our current charges to put their organic thinking caps on to have a jolly good think about what kind of society they want to live in.