{"slug": "meta-ordered-to-name-executives-behind-torrenting-of-books-for-ai-training", "title": "Meta ordered to name executives behind torrenting of books for AI training", "summary": "Magistrate Judge Thomas Hixson of the Northern District of California ordered Meta Platforms on October 20, 2026 to identify every person involved in the decision to use BitTorrent to download datasets from shadow libraries Anna's Archive and Library Genesis (LibGen), including discussions about seeding LibGen's Scimag collection. The discovery order, first reported by TorrentFreak, follows testimony from Meta employees who said supervisors, managers and executives greenlit the torrenting, and affects the Kadrey v. Meta class action brought by authors including Richard Kadrey and Sarah Silverman and a separate suit from Entrepreneur Media. Meta allegedly downloaded over 81 TB from Anna's Archive alone plus tens of additional terabytes from LibGen between 2022 and 2024 to train its Llama models; earlier rulings held the training qualifies as fair use, leaving the downloading and seeding as the remaining dispute.", "body_md": "Meta official logo (public domain, Wikimedia Commons) — CryptoBriefing brand treatment\n\n# Meta ordered to name executives behind torrenting of books for AI training\n\nA federal magistrate judge wants Meta to identify who approved downloading pirated books from Anna's Archive and LibGen\n\n[Meta](https://cryptobriefing.com/markets/meta/) has spent weeks pointing at rank-and-file staff over the torrenting of pirated books used to train its AI models. A federal judge now wants the names of the people above them.\n\nMagistrate Judge Thomas Hixson has ordered Meta Platforms to identify everyone involved in deciding to use [BitTorrent](https://cryptobriefing.com/markets/bittorrent/) to pull datasets from shadow libraries like Anna’s Archive and Library Genesis, better known as LibGen. The order, first reported by TorrentFreak, could move the spotlight from the engineers who ran the downloads to the managers and executives who allegedly signed off.\n\n## What the court ordered\n\nThe ruling, dated October 20, 2026, is a discovery order. Meta must clearly identify the key decision makers behind the choice to torrent books from Anna’s Archive and LibGen.\n\nThe order also reaches discussions about seeding during downloads, particularly involving LibGen’s Scimag collection. Seeding means a torrent user uploads pieces of a file to other users while downloading it. In plain terms, a seeder is not just taking copies but also handing them out.\n\nThe order follows testimony from Meta employees who handled the torrenting. Those staffers said supervisors, managers, and executives greenlit the activity, which is exactly the chain of command the plaintiffs now want on the record.\n\n## Meta’s defense, and why it is wobbling\n\nMeta’s position so far has leaned on two arguments. The company said the torrenting was carried out by lower-level employees, and that many decisions came out of team consensus rather than formal approval from higher management.\n\nMeta previously disclosed some data-related staff involved in the work. It also claimed no formal approvals for the torrenting were documented, even though internal reservations about the legality of the practice existed.\n\n### AI, tech, and the markets they move—in one daily briefing.\n\nDaily. Free. Join 34,000+ readers across crypto, finance, and policy.\n\nThis ruling also builds on earlier discovery fights. In September 2026, Meta was directed to provide server command histories for the machines used in the torrenting.\n\n## The scale of the downloads\n\nMeta allegedly downloaded over 81 TB from Anna’s Archive alone, along with tens of additional terabytes from LibGen. The downloads reportedly took place between 2022 and 2024.\n\n## The lawsuits behind the order\n\nThe discovery order affects two cases in the Northern District of California. The first is a class action known as Kadrey v. Meta, brought by book authors including Richard Kadrey and comedian Sarah Silverman. The second is a separate lawsuit from publisher Entrepreneur Media. Both target the way Meta gathered material to train its Llama large language models.\n\nEarly court decisions have concluded that training AI models such as Llama on these materials qualifies as fair use. The remaining dispute centers on the act of downloading the files in the first place, and on any seeding that occurred along the way.\n\nThe plaintiffs argue those acts amount to willful infringement and contributory copyright infringement. Willful infringement means the defendant knew it was violating copyright and did it anyway. Contributory infringement means helping someone else infringe, which is where seeding comes in.\n\n## What this means\n\nFor Meta, the stakes have changed shape. If AI training itself is protected as fair use, the company’s exposure rests heavily on how it acquired the books and whether it redistributed them.\n\nWillfulness is about knowledge and intent, and intent lives in the heads of specific people. A list of names, combined with internal reservations about legality, gives the plaintiffs a far more concrete case to argue that Meta acted knowingly.\n\nThe seeding question, especially around LibGen’s Scimag collection, may prove to be the most consequential thread in the case.\n\n**Disclosure:** This article was edited by Diego Almada Lopez. For more information on how we create and review content, see our\n\n[Editorial Policy](https://cryptobriefing.com/editorial-policy/).", "url": "https://wpnews.pro/news/meta-ordered-to-name-executives-behind-torrenting-of-books-for-ai-training", "canonical_source": "https://cryptobriefing.com/meta-ordered-name-executives-ai-torrenting/", "published_at": "2026-10-20 17:44:23+00:00", "updated_at": "2026-10-20 17:45:57.667709+00:00", "lang": "en", "topics": ["ai-policy", "artificial-intelligence", "large-language-models"], "entities": ["Meta Platforms", "Thomas Hixson", "Anna's Archive", "Library Genesis", "Kadrey v. Meta", "Richard Kadrey", "Sarah Silverman", "Entrepreneur Media"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/meta-ordered-to-name-executives-behind-torrenting-of-books-for-ai-training", "markdown": "https://wpnews.pro/news/meta-ordered-to-name-executives-behind-torrenting-of-books-for-ai-training.md", "text": "https://wpnews.pro/news/meta-ordered-to-name-executives-behind-torrenting-of-books-for-ai-training.txt", "jsonld": "https://wpnews.pro/news/meta-ordered-to-name-executives-behind-torrenting-of-books-for-ai-training.jsonld"}}