EDIT: Sorry, I misread your comment above. Yeah, hopefully orders of magnitude fewer kids than the number who are getting falsely accused of cheating with LLMs now.
Increasing the accuracy of these systems - both in terms of false positives and false negatives - seems like a good thing.
If some kids are false positives (detected as using ai but didn’t)then how are they lazy?
A proper watermarking system should be able to have an arbitrarily high accuracy - as many nines as you want. And it should be able to actually report the accuracy of its judgements.
If you're worried about kids being falsely accused of cheating using LLMs, you should be cheering on these developments.
Probability of a false positive is 3 x 10^-5 in one example.
Seems like about 3 collisions per 100 million pictures. If everyone have 1000 pictures that is 3 collisions per 100 000 users.
Raiding 2 people in my city for made up CSAM pictures would be way to high false positive rate.
But you can also make any picture match a CSAM hash by adding picked noise.