Given the scale, I think that automated solutions are required to have any reasonable enforcement. However automated (and non-automated) solutions will have false positives. Right now it seems like there is no cost to a false positive (claiming that a video is copyrighted when it is not), and so systems are happy to be aggressive with these notices. Likewise, the cost of a false negative (missing a copyrighted video) is high to the rights holder, as they are losing revenue.
Since these systems use machine learning, it seems that it’s easy to add noise and fool them. I’ve seen videos that are flipped, slightly skewed, and have audio sped up or slowed down, presumably to get around the system. So I would assume that the system would have to be a bit aggressive to catch added noise.
I think it’s ultimately an economics problem though. Since there’s basically no cost to the person making the claim when there’s a false positive, there’s less incentive to avoid false positives. However, it seems hard to charge fees here - if you’re charging people to take down content that they hold the rights to, that’s basically extortion.
Any thoughts on what could be done to improve it? I think long term, we have to evolve our understanding of copyright and licensing, but given the current regime, is there even a solution?