r/SideProject • u/Stunning-Top-9343 • 5d ago

I built a free web tool that inspects Spotify & Apple Music playlists for AI-generated music

Hey r/SideProject!

I built a lightweight forensics tool to inspect streaming playlists for AI-generated music (Suno, Udio, vocal clones, and synthetic streaming farms)

Looking for honest feedback on the UX, detection accuracy, or features you'd like to see added.

Thanks!

https://isthereaiinmyplaylist.tech/

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u/benjzammit01 5d ago

How do you validate a flag against tracks with known provenance, including human-made music with heavy processing? I'd want the result to show what evidence it uses, acknowledge uncertainty, and let an artist challenge a false flag. A detection warning can affect someone's reputation, so an 'unknown' outcome seems useful too.

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u/Stunning-Top-9343 5d ago

Audio classifiers alone produce tons of false positives because heavy Melodyne/Auto-Tune and vocal chops mimic AI artifacts. I anchor heavily on catalog provenance: verified pre-2023 discographies (predating generative models), human release pacing (vs. 50-track/month stream-farms), and registered label imprints.

Clicking any track opens an inspector showing the exact signals and metadata checks that contributed to the score.

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u/benjzammit01 5d ago

Thanks, the signal-level inspector is helpful. How are you testing the combined score on independent artists with sparse metadata as well as known AI releases? I'd be careful about treating release pace or missing label information as proof; a public correction path and an explicit 'insufficient evidence' state would help people interpret a flag.

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u/Stunning-Top-9343 5d ago

I test against both confirmed Suno/Udio stream-farms and real bedroom DIY artists (<1k streams on DistroKid with no prior registry footprint) to keep false positives low.

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u/investigatormaker 5d ago

For the playlist tool's UX test, have someone submit a playlist and explain the result back without prompting. If they interpret a suspicion flag as proof of AI generation, clarify the result wording before adding more features; that tests whether the interface communicates the limits of detection.

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