AI music platform Suno has positioned itself as a tool for creative expression, but a deep dive into its copyright enforcement reveals a system that is critically broken. Despite Suno's stated policy of blocking copyrighted material, the filters are easily circumvented using simple and free software. This vulnerability opens the door to massive copyright infringement, allowing users to flood streaming platforms with unauthorized AI covers of chart-topping hits.
The core issue lies in Suno Studio, a feature available in the company's Premier Plan for $24 per month. While the filter is designed to reject direct uploads of well-known songs, it can be fooled by applying basic audio manipulations. Using a free tool like Audacity, a user can slow a track to half speed or speed it up to double speed, then add a short burst of white noise at the beginning and end. This altered file often bypasses Suno's detection entirely. Once uploaded, the speed and noise can be restored within the Suno Studio interface, and the copyrighted song becomes the seed for a new AI-generated cover.
The results are alarmingly close to the originals. During testing, reporters were able to generate convincing imitations of Beyoncé's "Freedom," Black Sabbath's "Paranoid," and Aqua's "Barbie Girl." While most listeners might detect a subtle difference, the tracks often sound like alternate takes or B-sides. The vocal mimicry is particularly striking—the AI reproduces the cadence, tone, and inflection of the original singer, creating what can only be described as an uncanny valley imitation. Instrumentals are also cloned with high fidelity, though they often strip away the artistic nuance and dynamic range of the originals, resulting in lifeless reproductions.
Lyrics are another point of failure. Suno's system is supposed to detect copyrighted lyrics pasted into the text box and replace them with gibberish. However, minimal changes—such as altering spelling or rephrasing a few words—are enough to bypass the filter. For example, changing "rain on this bitter love" to "reign on this bitter love" in Beyoncé's song allowed the system to generate recognizable vocals. After the first verse and chorus, the filter appears to drop its guard entirely, so the rest of the song can proceed with original lyrics intact.
Monetization and Impact on Independent Artists
The ability to generate these covers is concerning enough, but the real threat is monetization. Suno only scans uploaded audio at the time of upload; it does not recheck the final output or exported file for infringing content. This means a user can create an AI cover, export it, and then upload it to a streaming distribution service like DistroKid or CD Baby. From there, the track can appear on Spotify, Apple Music, and other platforms, generating streaming revenue that would typically go to the original songwriter. Independent artists, who lack the legal resources of major labels, are the most vulnerable.
Folk artist Murphy Campbell recently discovered AI covers of her own YouTube performances on her Spotify profile. The distributor Vydia filed copyright claims against her original videos, collecting royalties on her own work. Even more absurdly, the songs in question are public domain. While Spotify eventually removed the AI covers and Vydia rescinded its claims, the incident only garnered attention through a social media campaign. Other artists, such as experimental composer William Basinski and the band King Gizzard and The Lizard Wizard, have also found AI-generated fakes on their profiles, with some tracks siphoning streams directly from the artists' pages.
Spotify, Deezer, and Qobuz have implemented measures to combat spammy AI content. Spotify spokesperson Chris Macowski stated that the company uses "safeguards to help prevent unauthorized content from being uploaded," along with "systems that can identify duplicate or highly similar tracks" backed by human review. However, no system is perfect, and the flood of AI-generated slop—enabled by platforms like Suno—poses an ongoing challenge. Macowski acknowledged the technical difficulties, noting that Spotify is "continuing to invest in and evolve" its detection systems.
The Broader Context of AI and Copyright
The problems with Suno are part of a larger crisis in the music industry. Generative AI models are trained on vast datasets of copyrighted music without permission, leading to lawsuits from record labels and publishers. Suno itself is facing litigation from the Recording Industry Association of America (RIAA). The company has argued that its training falls under fair use, but the ability to produce near-identical covers of existing songs undermines that defense. If the model can reproduce a copyrighted work verbatim after simple audio manipulation, it suggests that the underlying training data is deeply entangled with protected material.
Furthermore, the ease of filter bypass highlights a design flaw. Suno's copyright filters are essentially a speed bump, not a wall. They rely on fingerprinting technology that can be fooled by basic signal processing. Adding a bit of noise or changing the playback speed is a trick as old as audio editing itself. This raises questions about whether Suno's filters are genuinely intended to prevent infringement or merely to provide a plausible deniability shield. The company declined to comment for this story.
The output quality also reveals a paradox. While the AI can mimic vocals and instrumentals with eerie precision, it lacks the human touch. Ozzy Osbourne's AI voice is accurate but devoid of the raw energy that defines his performances. A cover of the Dead Kennedys' "California Über Alles" loses its punk edge and becomes a folky jig. Pink Floyd's "Another Brick in the Wall" is stripped of its dark disco groove and turned into generic dance music, with David Gilmour's iconic guitar solo reduced to a mechanical string of notes. The uncanny valley applies not just to visual AI but to audio—these covers are recognizable yet hollow, more imitation than art.
For small artists, the stakes are existential. Streaming royalties are already painfully low—Spotify requires at least 1,000 streams before paying out—and the presence of AI fakes can dilute their revenue further. If a fraudulent AI cover accumulates streams, it may appear on the artist's official profile, confusing fans and potentially damaging their brand. The process of getting these tracks removed is cumbersome, requiring manual reporting and often social media pressure to get any action.
Suno's issue is not unique. Other AI music generators, such as Udio, face similar criticism. But Suno's prominent position in the market and its aggressive marketing make it a symbol of the industry's failure to adapt copyright law to the age of generative AI. Until platforms implement robust, auditable filters that actively monitor both inputs and outputs, artists will remain at risk. The current system is broken, and Suno is a central cog in that breakdown.
The technology itself is improving rapidly. Suno's Model v5 takes more liberties with source material, adding chugging guitars or galloping piano to covers, but it still produces recognizable derivatives. This suggests that even as the models evolve, the fundamental copyright issues persist. The only long-term solution may involve licensing agreements between AI companies and rightsholders, similar to the deals struck by stock music libraries. Until then, independent artists will have to rely on vigilant social media campaigns and the slow response of streaming platforms—weapons that are no match for a system that can generate a thousand fake songs in an hour.
As the legal battles continue and streaming services scramble to update their detection algorithms, the human musicians caught in the crossfire are left to fight for their own livelihoods. Their music, their voices, and their hard work are being repackaged by machines without compensation or consent. The ease with which Suno's filters can be bypassed is not just a technical oversight; it is a fundamental flaw that threatens the economic model of the modern music industry.
Source:The Verge News