[dartharva]

It can be useful for small-scale verification in academics - TAs and schoolteachers can use it to ensure the assignments and homework submitted were actually worked on. Yes, an incumbent can spend more time and brains on making it look authentic despite using LLMs but you've already gone past a typical tardy student's usage pattern at that point - if she is too lazy to do her homework she can be safely assumed to be too lazy to spend time refining her prompts and weights as well.

[StrauXX]

I would not want to trust grades, in some cases even decisions about pass or fail, to a system which is prone to false positives.

[_puk]

Agreed, we shouldn't trust the system, but using it as a bloom filter to flag those that should be reviewed manually seems warranted.

If all we're getting is false positives then it can be used to reduce the workload.

If we also get false negatives then we'd be better off using existing techniques (manual or otherwise).

[a_bonobo]

How do you do this manual review? How can a human spot LLM-generated text? The internet is full of horror stories of good students getting failing grades due to false positive LLM detectors where the manual review was cursory at best.

[gmerc]

Or you know, assess people fairly face to face.

[klyrs]

Which we know to be unfair due to learned biases...