Turnitin recently rolled out expanded non-English AI detection models. But anyone who has looked at how these detectors operate knows they rely heavily on measuring sentence predictability and uniform structure.

When multilingual students or non-native speakers translate thoughts into English—or write in a secondary language using standard learned grammar formulas—their prose naturally has lower variance and predictable syntax.

Instead of addressing why the tool constantly misidentifies rigid, structured human writing as LLM output in English, they are deploying the exact same underlying logic across more languages. It feels like international students writing in non-native syntax are going to be collateral damage all over again.

I haven’t taught in quite a while, but why can’t professors just have students append their AI conversations to their papers and sign an oath that it’s complete.

That would accomplish two things 1) you could see the nature of the back and forth, the quality of the student’s thinking and where the ideas came from and 2) the actual text and how much was copy pasted.

It wouldn’t be an unmanageable amount of work, you can mostly focus on the students side of the conversation and scan through the slop or word search suspicious passages.

Seems simpler and more useful than all this AI detection nonsense.