US Man Charged with Using AI to Generate Fake Music and Streamed Millions to Fraudulently Claim $8 Million in Royalties

A man in the United States used AI to generate hundreds of thousands of fake songs and manipulate streaming counts to fraudulently collect about $8 million in royalties, raising regulatory concerns over streaming revenue loopholes.

Using AI to mass-produce music, U.S. man involved in claiming approximately $8 million

The U.S. Department of Justice recently announced that Michael Smith from North Carolina has admitted to participating in a scheme to fraudulently collect music royalties using artificial intelligence and automation systems, involving approximately $8 million. The case is being tried in the Southern District of New York federal court. Smith pleaded guilty to conspiracy to commit wire fraud and agreed to forfeit the illegal proceeds, facing up to 5 years in prison.

Prosecutors stated that Smith used AI technology to generate大量虚假音乐作品，并配合自动化账户在各大流媒体平台反复播放，从而获取版税收益。 U.S. prosecutors said the scheme lasted for years, systematically converting fake plays into real cash flow, forming a highly scaled fraudulent operation. The case is now in sentencing proceedings, with a verdict expected on July 29, making it one of the landmark cases of AI misuse in the content industry in recent years.

Creating hundreds of thousands of fake songs and automated playback systems to evade platform detection

According to investigations, Smith expanded his operation by using AI to generate hundreds of thousands of music tracks and uploading them to platforms like Spotify, Apple Music, Amazon Music, and YouTube Music. These works were mostly generated automatically by algorithms, including melodies, lyrics, and arrangements, with minimal human involvement.

At the same time, he created大量虚假账户，通过自动化软件每天制造约66万次播放量，并将流量分散到庞大的曲库中，以降低被平台检测的风险。 Prosecutors pointed out that this strategy avoided concentrating plays on a single song, successfully bypassing some abnormal behavior detection mechanisms.

During peak operation, the scheme could generate about $1.2 million in royalties annually. Over time, the total fraudulent claims reached approximately $8 million. Prosecutors emphasized that although the songs and listeners were fictitious, the illicit earnings were real.

Streaming revenue sharing loophole accelerates scale of AI fraud

This case also highlights potential vulnerabilities in current music streaming revenue models. Most platforms distribute royalties based on play counts, making streaming volume a key revenue driver and creating incentives for manipulation.

With the rapid proliferation of AI music generation tools like Suno, Udio, and Google’s Lyria, ordinary users can now generate complete songs with simple commands, greatly lowering the barrier to content creation. While this technological development promotes content output, it also makes it easier to replicate and expand fraudulent activities.

Prosecutors stated that Smith initially attempted to develop in the music industry and had collaborations with industry players, but ultimately chose to profit through system manipulation. This reflects the increasing risk of technology abuse within highly data-driven content revenue systems.

AI-generated music and copyright disputes intensify, platform regulation faces challenges

As the case comes to light, issues surrounding AI music rights and regulation have gained renewed attention. The industry is beginning to discuss how to define rights for AI-generated content and how platforms should identify and handle non-authentic traffic.

Image source: YouTube. YouTube is also filled with大量由AI制作的音乐

Currently, most streaming platforms have not yet established comprehensive mechanisms for AI music recognition and regulation, leaving room for gray-area operations. Some companies have started to strengthen anti-cheat systems, but as AI and automation tools continue to evolve, protective measures are still being adjusted.

This case serves as a warning, illustrating that when AI merges with the content industry, without proper regulation and mechanisms, it can distort market revenue sharing and cause tangible harm to genuine creators.

This article is compiled by Crypto Agent from various sources, reviewed and edited by Crypto City. It is still in training and may contain logical biases or inaccuracies. Content is for informational purposes only and should not be considered investment advice.