Connect English

Yesterday, I attended a really interesting workshop on Academic Integrity. It was great to see how much thought and effort the school is putting into helping students use AI responsibly – not banning it, but guiding them towards understanding what ethical use means. There’s a lot of work being done to prepare students for a future where AI will be part of everyday life.

Still, as I listened to the discussion, I couldn’t help thinking that we are in a bit of a catch-22. The more we talk about using generative AI in positive ways, the more difficult it becomes to tell when it’s being used in ways that cross the line. Every week, it seems to get harder to recognise whether a piece of writing was produced by a student or by a machine – or, more likely, by both.

As Neil Postman once said, every new technology “giveth and taketh away.” It brings solutions, but it also creates new problems. On the one hand, AI helps students access language and ideas more easily than ever before. On the other, it challenges our traditional understanding of authorship. Where does a student’s voice end and the algorithm’s voice begin?

This uncertainty changes how we look at student writing. In the past, we could often spot plagiarism through differences in style or vocabulary, or by noticing when a text didn’t sound like the same person who spoke in class. Now, however, AI can reproduce a student’s tone quite convincingly after a few examples. It can generate citations, summaries, even reflections – some of which sound perfectly authentic.

This situation reminds me a bit of Foucault’s idea of the panopticon – a place where you never quite know who is being watched or who is in control. Teachers now find themselves in a similar position, unsure of what they’re really seeing in a student’s work.

At the same time, I don’t believe the answer lies in more suspicion or surveillance. As Paulo Freire reminded us, education should be a dialogue, not a form of control. Instead of trying to “catch” students, maybe we need to rethink assessment itself. Perhaps we should design tasks where genuine thinking and personal experience matter more than perfect wording – things like oral reflections, drafts showing the process, or collaborative projects.

I’m not saying I have the answers. It just feels like we’re all learning how to navigate this new landscape together. Maybe integrity in the age of AI isn’t only about detecting what’s artificial, but about helping students understand what’s real – what it means to learn, to think, and to express their own ideas, even when technology is there to help.

So yes, it’s a bit of a catch-22. But maybe that’s what progress looks like: not certainty, but curiosity – and the willingness to keep asking the right questions.