The detection problem is genuinely hard. Even desktop AI agents I've been working with recently can control Spotify, fill forms, navigate apps — all indistinguishable from human interaction at the OS level. If that's hard to detect at the application layer, detecting AI-generated music at the audio layer seems like a cat and mouse game that Tidal will struggle to win without self-reporting from uploaders.
I feel like audio-level heuristics will be easier, but ultimately who's to say?
> Generative models synthesize sound mathematically. These synthesis methods leave unnatural dips, specific spectral noise profiles, or phase alignments that rarely occur in real, human-recorded audio
Then the slop merchants will simply move to controlling a DAW with AI and use the same software synths that everyone else does. It's a little more involved and slower, but far from hard.
Ultimately this isn't really solvable without a way of marking audio with a verifiable signature that it was produced by a specific human, with some kind of reputation algorithm.
This is a totally fascist musical bias -- I have been using spectral techniques in music since the late 1980s. It has been common for decades. "Unnatural" spectral packet distortion is a component of a wide-breadth of existing music that pre-dates modern generative AI. I am confident that the false positives will be overwhelming and unfair to many artists. Such a cowardly and lossy solution.
You are correct, but I think having a good policy - and trying earnestly to enforce it - is a good start, even if that enforcement is very imperfect.
Maybe if enough AI produces self-report their work as AI, and enough non-AI producers are honest about uploading non-AI work, they'll quickly have the necessary amount of good-enough data to train good classifiers?
I mean you can outsource it to users, which also allows you to organically make exceptions for AI music that is actually popular.
You really just want your users, who hate AI, to see a big "REPORT AI" button they can click. The problem you are trying to solve is the perception among your users that your platform is dominated by AI slop. So at the end of the day the only thing you actually have to figure out is what your users think is AI slop, have a quick trigger on un-popular stuff, and basically never enforce on popular stuff unless there is actually some controversy.
Let's go with impossible.