The $8 million AI music scam
Episode
38 min
Read time
2 min
Topics
Artificial Intelligence, Economics & Policy
AI-Generated Summary
Key Takeaways
- ✓AI Streaming Fraud Mechanics: Smith generated hundreds of thousands of songs using Boomi, an early AI music generator predating Suno and Udio, uploaded them under fictitious artist names via distribution services, then deployed bot networks to loop streams repeatedly. The scheme worked because uploading AI music was never prohibited — only artificial stream inflation violated platform terms of service.
- ✓Scale vs. Detection Risk: Spotify detected and removed Smith within the early phase, recovering only tens of thousands of dollars. Other platforms took longer. Fraud experts note Smith's critical error was operating from the United States rather than abroad, making him easily identifiable. Smaller-scale operators running similar schemes from overseas remain largely undetected and unprosecuted today.
- ✓Legal Ambiguity of AI Fraud: No single action Smith took was clearly criminal in isolation. Prosecutors bundled his actions into a wire fraud charge, with the decisive factor being his repeated written denials to platforms when confronted. Lying to platforms while continuing to collect payments converted a terms-of-service violation into prosecutable fraud, according to the case outcome.
- ✓Platform Incentive Problem: Streaming platforms lack strong financial incentive to aggressively police AI-generated content because bot streams cost them nothing directly — royalty pools simply redistribute among rights holders. Spotify removed 75 million AI-generated songs in 2024 primarily for reputational reasons, not profit protection. This misaligned incentive structure means enforcement remains reactive and incomplete across the industry.
- ✓Prediction Market Amplification: A new fraud vector has emerged layering prediction markets on top of streaming manipulation. Bad actors bot Spotify streams to move measurable metrics, then profit from prediction market bets tied to those same metrics. This two-layer scheme creates additional financial incentive beyond royalties alone, complicating platform integrity efforts and expanding the attack surface significantly.
What It Covers
Wired journalist Kate Nibbs joins The Vergecast to detail how Mike Smith used AI music generation tool Boomi and bot networks to fraudulently collect $8,091,843 in streaming royalties across major platforms, resulting in the first criminal conviction for AI-based streaming fraud and an 18-month prison sentence.
Key Questions Answered
- •AI Streaming Fraud Mechanics: Smith generated hundreds of thousands of songs using Boomi, an early AI music generator predating Suno and Udio, uploaded them under fictitious artist names via distribution services, then deployed bot networks to loop streams repeatedly. The scheme worked because uploading AI music was never prohibited — only artificial stream inflation violated platform terms of service.
- •Scale vs. Detection Risk: Spotify detected and removed Smith within the early phase, recovering only tens of thousands of dollars. Other platforms took longer. Fraud experts note Smith's critical error was operating from the United States rather than abroad, making him easily identifiable. Smaller-scale operators running similar schemes from overseas remain largely undetected and unprosecuted today.
- •Legal Ambiguity of AI Fraud: No single action Smith took was clearly criminal in isolation. Prosecutors bundled his actions into a wire fraud charge, with the decisive factor being his repeated written denials to platforms when confronted. Lying to platforms while continuing to collect payments converted a terms-of-service violation into prosecutable fraud, according to the case outcome.
- •Platform Incentive Problem: Streaming platforms lack strong financial incentive to aggressively police AI-generated content because bot streams cost them nothing directly — royalty pools simply redistribute among rights holders. Spotify removed 75 million AI-generated songs in 2024 primarily for reputational reasons, not profit protection. This misaligned incentive structure means enforcement remains reactive and incomplete across the industry.
- •Prediction Market Amplification: A new fraud vector has emerged layering prediction markets on top of streaming manipulation. Bad actors bot Spotify streams to move measurable metrics, then profit from prediction market bets tied to those same metrics. This two-layer scheme creates additional financial incentive beyond royalties alone, complicating platform integrity efforts and expanding the attack surface significantly.
Notable Moment
Smith was simultaneously running a legitimate music career — including a Snoop Dogg collaboration and a BET reality show he personally financed — while executing the fraud scheme. His business partner noticed they were charting on Billboard with zero recognizable fan base, which eventually triggered suspicion.
Episode Transcript
Support for the show comes from AWS AI. AWS AI is helping the world's leading organizations transform their industries in production at scale right now. From bringing fans inside every swing at the PGA Tour to helping small businesses grow online with GoDaddy to taking vehicles from concept to customer with Audi, AWS AI is how businesses innovate, lead, and revolution ize. AWS AI is how. This episode is brought to you by On Investing, an original podcast from Charles Schwab. Each week hosts Liz Ann Saunders, Schwab's chief investment strategist, and Colin Martin, head of fixed income research and strategy for the Schwab Center for Financial Research, bring you fresh insights on what's happening in the markets and why, and what the implications might be for your portfolio. Join Colin and Liz Ann as they explore questions like, how do you evaluate corporate bonds that look interesting? And what sectors are on the move right now? Download the latest episode and subscribe at schwab.com/oninvesting or wherever you get your podcasts. Support for the show comes from Jira by Atlassian. Your work is scattered. A thread here, a DM there, docs everywhere. And it's not only your team searching for context, your AI agents need it too. Jira taps Atlassian's Teamwork Graph to bring that context together across Jira, Confluence, Slack, GitHub, and more, and makes it easy to share with agents you already use, like Claude, Cursor, and GitHub Copilot. Assign them work directly or connect your agents through MCP. The result? Less token waste, more accuracy, and more time moving forward. Learn more at jira.com. That's jira.com. Hello, and welcome to the Vergecast, the flagship podcast of BotFarms. I'm your friend David Pierce, and today on the show, we're gonna talk about one man's scheme to AI his way into millions of dollars of music royalty. The guy's name is Mike Smith, and he became one of the most important and, frankly, first cases to figure out what is streaming fraud, can you use AI to make and listen to music, And what does it all mean? Kate Nibbs from Wired has been covering this story for years now and is gonna come on the show and tell us all about it. But first, here's everything else happening on The Verge today. This is ninety seconds on The Verge for Wednesday, 10/14/2026. Everybody is still getting used to the idea of the Apple Home View. Apple's $299 smart display is up for preorder now, and it's designed to be kind of your family's central control system. It's for your smart home, communications, everything. I will say I've been pretty surprised at how much of the reaction to this has been from people who watched that three minute video about family chaos and the home view and decided they just simply do not want another screen, another device, another thing to manage and worry about and have listening all the time. At this point, it's been a long time …
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