While there are interesting comments here looking at technical solutions like fuzzy/partial hashing, the solution for a professor is likely a bit different. Ra

While there are interesting comments here looking at technical solutions like fuzzy/partial hashing, the solution for a professor is likely a bit different. Rather than prove the student used Chat GPT (hard for reasons you point out), isn't this better handled as a suspected cheating scenario (collusion, candidate impersonation etc.) Many institutions have a regulation on the books to allow for oral examination to be carried out for any course at the discretion of the course leader, for the purpose of evaluating a student for award of a grade. If you suspected a student had used significant outside help, you'd presumably do the same - have an oral examination, and discuss the work, ask them to discuss the subject matter, and test their understanding of it. At that point, either the student crumbles and doesn't have any level of understanding beyond "paper thin" (like if they paid an essay mill to write the paper), or they have a good understanding. If the latter, then they meet the learning outcomes of the class and have demonstrated this satisfactorily. And if they have learned the content and show an understanding of it, it's effectively acted as a study aid and actually helped them to learn. They now have shown they know the material, so they have passed the course legitimately. I suspect in the longer term we'll see attempts to ask questions which can't be so easily answered by generative waffle, which actually should be an improvement on many types of examination. How this works in less scientific disciplines will be more challenging - I imagine they'll struggle to create "un-GPT'able" questions. But colleges adapted (or at least good professors did) to remote examinations during the pandemic - declare the exam "open book", and ask questions that require robust understanding of topics, such that sitting and reading the book will run you out of time. Give students questions with generated parameters so each student gets a slightly different variant of numerical questions, etc. The solution to language models generating believable or compelling waffle doesn't need to be technical - I suspect non technical solutions may win out. Whether they scale enough (or a professor cares enough to actually sit down with students for a few minutes) is another question, but maybe they should be doing that in the first place?