HomeAmerican man scammed $10M using AI to rig music charts
In the age of music streaming, artificial intelligence hasn't just transformed how music is made—it's also opened the door to new types of fraud. Recently, 52-year-old Michael Smith from North Carolina pleaded guilty in the U.S. District Court for the Southern District of New York. He was accused of using AI to generate thousands of songs and coordinating with bot networks to manipulate streaming charts, stealing over $10 million in royalties over the past seven years.
Smith's approach was strikingly systematic: he used AI tools to churn out thousands of simple, repetitive melodies each day, then uploaded them to major platforms like Spotify, Apple Music, and Amazon Music. To avoid triggering fraud detection systems, he didn't concentrate plays on a few tracks. Instead, he deployed thousands of automated bot accounts to distribute streams across hundreds of thousands of AI-generated songs.
According to prosecutors, Smith's scheme generated roughly 660,000 streams per day, with annual royalty earnings stabilizing at around $1.2 million. As one social media comment put it: "He used AI to make music, then used AI to make listeners — and ultimately took real money from real artists."
The case has sent shockwaves through the music industry. Streaming platforms typically use a proportional distribution model for royalties, where all revenue is pooled and distributed based on play counts. Every dollar Smith stole effectively came from independent musicians and copyright holders who had genuine audiences.
This marks the first successful prosecution in the U.S. targeting AI-powered streaming fraud. Smith now faces multiple charges, including conspiracy to commit wire fraud, and could receive up to five years in prison, along with forfeiting more than $8 million in illegal proceeds.
As AI music generation tools like Suno become more accessible, streaming platforms now receive tens of thousands of AI-created tracks daily. This case not only serves as a warning to those seeking quick profits but also forces the industry to confront a deeper question: when "nonexistent songs" are consumed by "nonexistent listeners," how should the foundation of digital music value be reimagined?
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In the age of music streaming, artificial intelligence hasn't just transformed how music is made—it's also opened the door to new types of fraud. Recently, 52-year-old Michael Smith from North Carolina pleaded guilty in the U.S. District Court for the Southern District of New York. He was accused of using AI to generate thousands of songs and coordinating with bot networks to manipulate streaming charts, stealing over $10 million in royalties over the past seven years.
Smith's approach was strikingly systematic: he used AI tools to churn out thousands of simple, repetitive melodies each day, then uploaded them to major platforms like Spotify, Apple Music, and Amazon Music. To avoid triggering fraud detection systems, he didn't concentrate plays on a few tracks. Instead, he deployed thousands of automated bot accounts to distribute streams across hundreds of thousands of AI-generated songs.
According to prosecutors, Smith's scheme generated roughly 660,000 streams per day, with annual royalty earnings stabilizing at around $1.2 million. As one social media comment put it: "He used AI to make music, then used AI to make listeners — and ultimately took real money from real artists."
The case has sent shockwaves through the music industry. Streaming platforms typically use a proportional distribution model for royalties, where all revenue is pooled and distributed based on play counts. Every dollar Smith stole effectively came from independent musicians and copyright holders who had genuine audiences.
This marks the first successful prosecution in the U.S. targeting AI-powered streaming fraud. Smith now faces multiple charges, including conspiracy to commit wire fraud, and could receive up to five years in prison, along with forfeiting more than $8 million in illegal proceeds.
As AI music generation tools like Suno become more accessible, streaming platforms now receive tens of thousands of AI-created tracks daily. This case not only serves as a warning to those seeking quick profits but also forces the industry to confront a deeper question: when "nonexistent songs" are consumed by "nonexistent listeners," how should the foundation of digital music value be reimagined?
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