Submitted the Tidal policy to Hacker News where it reached 277 points, signaling strong developer/industry interest. The framing treats Tidal's three-pronged approach — training prohibition, ingestion disclosure, and removal rights — as a credible first attempt at the kind of clear DSP-level rules the industry has been waiting for.
Argues that Tidal's document implicitly requires four primitives the music industry has not standardized: a master-level opt-out signal, a disclosure field carried through every distributor pipeline, a defensible AI-output detector, and a litigation-grade audit log. ISRCs, DDEX, and C2PA each cover only fragments of this stack, and Suno/Udio do not voluntarily watermark, so the policy declares obligations the underlying infrastructure cannot yet enforce.
Notes that Tidal alone has roughly 5% of paid streaming share, so the policy's direct effect on AI training pipelines is limited. The significance is precedential — a DSP publishing obligations ahead of the standards needed to enforce them follows the GDPR-style pattern of regulation shipping before infrastructure, which often forces the infrastructure to catch up.
Tidal published an AI policy at tidal.com/ai-policy that takes a harder line than any other major music streaming service has put in writing. The document does three things at once: it prohibits the use of Tidal's catalog for training generative AI models without explicit license, it requires labels and distributors to disclose AI-generated or AI-assisted tracks at ingestion, and it reserves Tidal's right to demote, label, or remove tracks that violate either rule. The post hit 277 on Hacker News, where the comment thread split between people calling it the first sane DSP-level AI policy and people pointing out that policies are easy and enforcement is hard.
The interesting part of the document isn't the prohibition — it's the implicit engineering bill of materials. To honor what Tidal has written, the platform needs at least four primitives that the music industry has not standardized: a machine-readable opt-out signal at the master-recording level, a disclosure field carried through every distributor pipeline (DistroKid, CD Baby, The Orchard, Believe, Sony's in-house tooling), a detector capable of flagging undisclosed AI output with a defensible false-positive rate, and an audit log strong enough to survive a label dispute or a lawsuit.
None of those four exist as industry-wide infrastructure today. ISRCs identify recordings, not training permissions. DDEX messages, the lingua franca between labels and DSPs, have proposed AI-disclosure extensions but adoption is uneven. C2PA, the provenance standard Adobe and Microsoft have pushed for images, has no production-grade audio profile. Suno and Udio do not voluntarily watermark their outputs in any format Tidal can independently verify.
The story matters less for what Tidal can do alone — it has roughly 5% of paid streaming market share — and more for the precedent of a DSP publishing obligations it cannot yet enforce. The pattern is familiar from other domains. GDPR shipped before the consent-management ecosystem existed; the ecosystem then materialized because the rule was real. PCI-DSS forced tokenization vendors into being. When a platform commits in writing to a rule it lacks the tooling to enforce, the tooling tends to follow, because the alternative is admitting the policy was theater.
The second-order effect is on the labels. A major label catalog spans millions of recordings across dozens of rights-holders per track. To respond to Tidal's opt-out language, a label has to either declare a blanket no-training position for everything it controls — which it cannot do, because some of those rights belong to estates, co-writers, or producers with separate deals — or build a per-recording permissions database it has never needed before. Universal and Sony already have rights-management systems that approximate this; indie distributors do not. Expect a wave of vendor pitches over the next twelve months from companies promising to be the SSL-cert authority of training-data permissions.
The third-order effect is on the AI music vendors. Suno and Udio are both in active litigation with the RIAA over alleged training on copyrighted material, with depositions ongoing. A platform-level no-training declaration from Tidal doesn't create new legal liability for those vendors, but it does create a clean evidentiary record: every track they ingested from Tidal-distributed catalog after the policy date carries documented non-consent. That's the kind of detail that matters at summary judgment.
Spotify, Apple Music, Amazon Music, and YouTube Music have all made AI-related statements over the past eighteen months, but none have committed to the disclosure-plus-demotion combination Tidal has. Spotify's policy bans content designed to impersonate other artists but is silent on training. Apple's posture is mostly inferred from its Apple Intelligence rollout and Logic Pro features. The competitive question is whether being the strictest DSP attracts artists who care about provenance — Neil Young's exit from Spotify two years ago over a different issue showed there is a real artist segment willing to vote with their catalog — or whether it just makes Tidal harder to upload to and accelerates its market-share decline.
If you build anything that touches user-generated audio — a podcast host, a video platform with original music, a sample marketplace, a UGC game with player-uploaded tracks — Tidal's policy is the template you will be asked about in your next compliance review. The specific asks will be: do you carry through a disclosure flag from upload, can you produce an audit log of training-permission state at any point in time, and do you have a takedown pipeline for AI-generated content that meets the same SLA as your DMCA pipeline. Most platforms today can answer 'no' to all three and survive; in eighteen months, 'no' will start to mean you lose label deals.
For anyone shipping a generative audio product, the operational change is the documentation burden. Training-data provenance is becoming the audio equivalent of an SBOM. You will need to be able to answer, in a non-hand-waving way, where every second of your training corpus came from and what license terms governed it. The companies that win the next round of music-AI funding will be the ones whose due-diligence package can answer that in a spreadsheet rather than a vibes-based assertion. Stability AI's struggles, and Suno's discovery fights, both started with that question.
For backend engineers on the DSP side or label side, the immediate work is unglamorous: extending ingestion schemas to carry a few new fields, plumbing them through every queue between the distributor API and the streaming endpoint, and standing up a detector pipeline that you will be embarrassed by for at least the first six months. The detector is the hard part. There is no public benchmark for AI-music classification with the kind of recall and precision a takedown system needs, and the underlying models are improving faster than detectors can track. Expect a vendor stack here too, with the same accuracy claims and the same quiet asterisks that AI-image detectors carry.
Tidal's bet is that writing the policy now, ahead of the infrastructure, will force the infrastructure into existence — and that the reputational benefit of being first is worth eating the enforcement gap in the interim. That bet has worked before for platforms that committed to standards earlier than the industry was ready (think of Cloudflare's posture on TLS 1.3, or GitHub's on commit signing). It has also failed for platforms whose policies quietly softened once the engineering bill came due. The tell over the next two quarters will be whether Tidal publishes implementation details — a DDEX extension, a public detector accuracy number, a takedown volume report — or whether the policy page stays static while the catalog quietly fills with undisclosed AI tracks. One of those is a standard in the making. The other is a press release.
I really hope someone makes a music platform in the future that is verified as human-made. Music is about connecting to human emotions, not poor facsimiles of it.Tie it to in-person concerts and it might actually work as a business, as well as logistically – maybe the company can be a record produce
AI music has taken over small businesses like coffee shops and restaurants. AI music drives me nuts because, to me, it still is very much deep in an uncanny valley. That said, I can't blame the businesses because they are all (dis)incentive driven.The music industry has stepped up its efforts g
I just want Tidal and Spotify to give me the option to fully opt-out of AI generated music. I don't want it mixed in with my music. If others want it great, but I want the option to not engage with the content.
I'm a Tidal subscriber, something like this is needed.My Tidal "feed" is full of new releases that are clearly AI-generated. They use the same artist name as artists that I really like, but the music is clearly not from the artist as advertised.I have no problem with AI-generated musi
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> Tidal will accept AI-generated music.> Tidal will hold AI-generated music to a higher standard of content integrity. We will not tolerate AI-generated music that exploits an individual’s or group’s music, name or likeness, deceives listeners, or diminishes the quality of our service.I think