EDM producer Max “H4RRIS” Harris has posted videos identifying artists he believes are using AI‑generated music, saying the practice misrepresents human art and threatens creators' livelihoods. Harris argues that AI‑generated tracks function as “decoy art” and are driven by profit rather than meaningful expression. He says that audible cues such as a persistent hiss and synchronized vocal stuttering often indicate AI origins, a point he made while describing his own production workflow, which relies on tools including Ableton Live, a Novation Launchkey 49 controller, and various synthesizers. Harris cites specific tracks—MANSA’s “Midnight on My Mind,” Danny and Ian Asher’s “Take Me (To The Moon),” and a cover of Madonna’s “Like a Prayer” by Josh Fawaz—as examples that may have been created with AI, though no public confirmation has been provided. Italian turntablist‑producer Nihil Young reported similar concerns after his Threads posts about AI music on Suno, stating that the platform enables the upload of copyrighted songs for remixing without permission. Young said he experienced hacking attempts and online harassment, and that fake followers may have been used to undermine his credibility, leading him to pause public criticism. He added that AI tools lower the barrier to producing entire songs with minimal effort, which he believes reduces genuine creativity and can diminish demand for human musicians. Industry examples illustrate the growing acceptance of AI music: Metro Boomin’s “BBL Drizzy” gained widespread attention and was later rapped over by Drake, while Vinih Pray’s “A Million Colors” reached the top of TikTok’s Viral 50 chart; AI artists Breaking Rust and Cain Walker also appeared on Billboard’s Country Digital Song sales chart. Hallwood Media signed the AI avatar Xania Monet to a $3 million recording deal, and Kapwing estimates that the ten most followed AI music creators on Spotify and YouTube earned over $6 million in 2025. Deezer reports that AI songs account for more than half of new uploads, making them increasingly difficult for listeners to distinguish. Detection tools exist but their reliability and adoption remain uncertain, and many listeners continue to consume music through phone speakers or background playback, limiting their ability to discern differences.