As AI-powered audio tools become more sophisticated, the internet is increasingly saturated with music that was never played or sung by a human. Melodies and vocals are algorithmically derived from the work of real artists, and while some creators immediately admit to using generative technology, others deny it until public pressure forces them to come clean. Now, a growing number of musicians are turning into detectives, using technical knowledge and sharp ears to expose AI grifters who are passing off machine-made tracks as genuine human art.
For musicians, especially those working in the technology-forward world of electronic dance music (EDM), the question of what is real and what is generated has become both personal and urgent. Professional courtesy often complicates things: listeners can call out performers they suspect of using gen AI, but it’s much harder for artists to publicly accuse their peers. Yet some are taking a stand. Among them is 26-year-old EDM producer Max “H4RRIS” Harris, who creates videos calling out anyone he believes is trying to pass off AI slop as human-made art.
Max H4RRIS: “A Decoy Art Form”
Harris, originally from Maine, told a reporter that he sees AI-generated music as “a kind of decoy art form.” He thinks the people making it don’t have anything meaningful to say with their creations. “I don’t consider AI-generated material to be art, and I don’t think this technology is really advancing art in any meaningful way,” he said. “It’s a technological advancement that’s giving people a way to steal real art and pass it off as their own.”
Harris describes his own workflow as a highly deliberate process of creative decisions. He starts with a core concept, then “throw[s] more ideas down until I find something that sticks.” His production setup includes Ableton Live, a Novation Launchkey 49 MIDI controller, Ableton Push 3, Launchpad X, a couple of analog synthesizers, Serum, Diva, and the software sampler Kontakt. To an outsider, it may look complex, but Harris insists it’s “really just me making creative decisions” that culminate in a sound that feels right. “Each of those decisions — and there’s hundreds of them to go into each song — brings me closer to evoking a specific kind of idea or emotion,” he explained. “And then once I have a song mapped out, I have to start making even more choices about how to mix it in a way that makes it sound good and presentable.”
In Harris’s view, being a real artist means being able to make experimental but informed creative decisions using a studied understanding of the medium. One of his biggest issues with gen AI is that it eliminates the need to think about how songs, books, films, or podcasts come together. But he is equally dismayed by how AI posers muddy the listening audience’s understanding of what human-made EDM actually sounds like.
The Sonic Tells of AI Music
So what does AI-generated music sound like? Harris points to some common traits. “Aside from the similar vocals, you can usually hear a sharp hissing throughout the track,” he said. “I think that comes from the way that these models often work by starting with a big white noise block and then making guesses about waveforms by referencing data taken from real songs.”
He also notices that vocals and melodic elements often stutter at the exact same time. “Something I’ve noticed with a lot of Suno-generated tracks is that a lot of the time, you’ll hear the vocals and other melodic elements will start stuttering at the same exact time,” Harris explained. “These models still have a hard time fully separating different parts of the songs they’re trained on, and they treat these elements like one big instrument. As a music producer, all of these things come across like choices that a human just wouldn’t make with their compositions because it just doesn’t make sense.”
Visual tells can be just as damning. AI-created characters often have fingers that vanish and reappear, and overly glossy videos immediately scream “AI slop” to discerning viewers. Harris points to evangelical Christian AI persona Lionsaddle and Christian house musician Midnite Manna as examples where the visuals make obvious that generative tools were used.
Harris specifically names MANSA’s “Midnight on My Mind” and Danny and Ian Asher’s “Take Me (To The Moon)” as what he believes are examples of AI-produced songs that embody what he jokingly calls “the AI revolution” polluting the EDM space. Neither act has publicly commented on whether they use generative tools, and there is no definitive evidence that these songs were AI-generated. Harris may be wrong about those specific tracks, but his insistence reflects a larger culture of mistrust that has developed in response to AI content online.
Nihil Young and the Backlash
Harris’s callout videos were inspired by the Threads posts of Nihil Young, a 39-year-old Italian turntablist-turned-producer. Young has spent months watching EDM newcomers rise after posting music he believes was generated with tools like Suno. While he isn’t usually one to engage in online discourse, he felt it was important to speak out about the flood of AI tracks. “These songs are the sound of Suno, which to me means that the people behind the songs are just straight up uploading original, copyrighted tracks of artists like Madonna and asking the platform to remix them,” Young said. He cited Josh Fawaz’s “Like a Prayer” cover, which now includes AI credits after a wave of online backlash. “If they can do it with major artists like her, they can do it with you, me, and everyone else, which just isn’t cool. They can take your entire catalog, feed it to Suno, and generate ‘new’ songs from that stolen work.”
Young’s advocacy came at a cost. He told a reporter that he received multiple hacking attempts and a wave of online harassment from AI defenders. He also suspects that people bought fake followers to boost his Spotify numbers as a way of casting doubt on his authenticity. Spooked and dealing with the pressures of raising a young daughter and promoting a new album, Young has taken a break from callouts. But he still believes it’s important to understand how AI music is harming human artists.
The financial impact has been real. “Music production is where most of my income comes from, and almost as soon as AI began rolling out, I started losing many of my clients,” said Young, who has done audio mixing and mastering work for Sony Music, Warner, and Universal. “I can only imagine what it’s been like for singers, graphics artists, and people working in other creative fields.”
Young emphasizes how easy it is to generate entire songs. Suno’s Simple Mode allows users to select a musical genre and click a button, requiring virtually no creative input. In his opinion, most people using AI to make music “aren’t actually doing anything creative and they don’t have a true artistic process.” (Suno hasn’t responded to requests for comment.)
The Mainstreaming of AI Music
Despite the objections of traditional artists, AI-generated tracks are making their way into the mainstream. In 2024, Metro Boomin took shots at Drake with a beat sampling comedian King Willonius’s “BBL Drizzy” — an AI track generated by AI music startup Udio. Metro Boomin posted the beat to SoundCloud and invited other performers to rap over it. Drake subsequently rapped over it on Sexyy Red’s “U My Everything,” peaking at No. 44 on the Billboard Hot 100.
Wholly AI-generated songs and artists are finding success, too. Last summer, Vinih Pray’s Suno-created “A Million Colors” peaked at No. 44 on TikTok’s Viral 50 chart. AI artists Breaking Rust and Cain Walker made it onto Billboard’s Country Digital Song Sales chart. Hallwood Media, a label founded by former Geffen Records president Neil Jacobson, signed AI avatar Xania Monet to a $3 million recording deal.
There’s serious money in this space. Kapwing estimates that the top 10 most-followed or most-streamed AI music creators on Spotify and YouTube collectively took in over $6 million in 2025. And with platforms like Deezer reporting that AI songs now account for more than 50 percent of new uploads, generative music is becoming harder to avoid — even if many listeners can’t recognize it. While streaming platforms are beginning to label AI content more clearly, surveys suggest that many users can’t hear the difference between generative and human-made tracks.
The Future of Authenticity
Aside from the people uploading these songs, no one can be absolutely certain whether a track was generated with AI or made by an actual artist. AI music detection tools may offer a solution, but it’s unclear how listeners might integrate them into their daily habits. Given the billions of streams earned by AI-generated material, there are clearly listeners who don’t mind the sound of Suno and Udio.
Young knows that most people’s ears aren’t well-attuned to identifying audio slop, but he still believes music lovers owe it to themselves to find real, human artists. “In my opinion, it becomes obvious that you’re listening to AI-generated music when you put on a good pair of headphones,” Young said. “But I also think that a lot of people these days are consuming music like fast food and listening to it through the speakers on their phone. Or they just have it on a background noise, and they don’t necessarily care what it sounds like.”
Source: The Verge News