A senior academic writes an opinion piece, advising students not to cut corners. It turns out she didn't actually write it. LLMs wrote the piece for her.

I treasure the fact that at the present moment, we can still see the absurdity in this story.

We can still find this story funny. We can still laugh at this pompous cheat, Professor #CathEllis, a Pro Vice-Chancellor at #WesternSydneyUniversity. In a year's time, Professor Ellis's lazy inauthenticity will be standard. Very likely I will have to meet HR to explain why I don't do the same.

https://www.theguardian.com/australia-news/2026/jun/05/trust-in-ai-roy-morgan-australia-university-professor-opinion-piece-technology

#noLLM #HigherEducation #StopTheAICorruption

A uni professor admitted using AI to write an opinion piece. Here’s what it revealed about trust in the technology

Without disclosing that work has been generated using the technology, faith in existing industries will continue to be undermined

The Guardian

@the_roamer It's one of the biggest issues at universities right now. Students are being penalised, including being stripped of degrees, after computer programs determine they've used AI.

Meanwhile, the subjects they're paying thousands for are often written using generative AI tools, and gen AI tools are being used to mark their work without teachers or the university disclosing it.

@fullfathomfive

Yes, the genAI challenge is the defining current issue for higher education. As you can see in my #StopTheAICorruption posts, I am not happy. But things aren't quite as bad as your post might suggest. Most of my worries are about the direction of travel, not the actual current practice.

Things vary between countries and institutions. I am in the UK, in a research+teaching university (Russell Group). My university is probably more pro-AI than most.

Plagiarism: my institution has systematic procedures for dealing with the unauthorised use of AI in a student's submitted work. These are entirely human-based, involving personal interviews and academic judgement. Automated AI detection tools play a very minor role.

Marking: for certain small course components, staff may experiment with AI-supported feedback loops. All major assessments are marked unaided by human markers, and that marking is double-checked by human moderators.

The battle hasn't been lost yet.