
Major music publishers file copyright lawsuit against Anthropic
Sony Music Publishing, Warner Chappell, and several other music publishers have filed a lawsuit against Anthropic. The complaint alleges the artificial intelligence laboratory engaged in widespread copyright infringement to train its Claude models.
Published by Jin · 2 min read · 30 AUG 2026
Major music publishers, including Sony Music Publishing and Warner Chappell, have filed a lawsuit against artificial intelligence lab Anthropic alongside co-founders Dario Amodei and Benjamin Mann. Filed in the U.S. District Court for the Northern District of California, the complaint alleges that the company engaged in a systematic campaign of illegally torrenting, scraping, and downloading copyrighted works.
The allegations
The publishers state that Anthropic utilized thousands of copyrighted musical compositions and lyric works without authorization to train its Claude language model. According to the court filing, the acquisition methods included obtaining millions of copies of books containing sheet music and lyrics through unauthorized channels.
An Anthropic spokesperson responded to the legal action by stating that the company disagrees with the claims made by the publishers and intends to defend itself robustly in court.
Prior legal context
This filing follows a pattern of intellectual property challenges directed at the artificial intelligence lab. Earlier legal actions include a suit led by Concord Music Group and Universal Music Group, as well as the Bartz v. Anthropic case involving authors who accused the company of using copyrighted material for product training.
While the legal arguments share similarities with previous complaints, the current publisher lawsuit is notably broad. It specifically incorporates allegations regarding the acquisition of materials used for lyric and sheet music processing.
As the intersection of generative artificial intelligence and copyright law continues to face judicial scrutiny, these ongoing proceedings will likely help establish clearer boundaries for how foundational training datasets are assembled across the technology sector.
Source — Original announcement ↗
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