Meta claims BitTorrent piracy is fair use for AI training in bold legal defense

Meta's latest legal wheeze is to insist that pirating books is fair use, actually

In order to help train its AI models, Meta (and others) have been using pirated versions of copyrighted books, without the consent of authors or publishers. The company behind Facebook and Instagram faces an ongoing class-action lawsuit brought by authors including Richard Kadrey, Sarah Silverman, and Christopher Golden, and one in which it has already scored a major (and surprising) victory: The Californian court concluded last year that using pirated books to train its Llama LLM did qualify as fair use. That's not the whole story, however, as Meta still faces the charge that it infringed copyright by downloading and sharing these books via BitTorrent (thanks, TorrentFreak). Meta obtained the books from so-called shadow libraries by using aggregators such as Anna's Archive, and the nature of BitTorrent transfers means the company was both downloading the content and uploading it for other users. The authors bringing the case claim this is widespread and direct copyright infringement. You'd think this case would be as open-and-shut as it gets, but never underestimate an army of high-priced lawyers. Meta has now come up with the striking defense that uploading pirated books to strangers via BitTorrent qualifies as fair use. It further goes on to claim that this is double good, because it has helped establish the United States' leading position in the AI field. Fair warning: the argument is circular and at times confusing, which may well be part of the intention. Meta's argument is that, because anyone who uses BitTorrent automatically uploads content to others, it is inherent to the process: it's just how these things work. It says the use of BitTorrent was essential in order to get the (pirated) data in bulk, which was only possible through torrents. "Meta used BitTorrent because it was a more efficient and reliable means of obtaining the datasets, and in the case of Anna's Archive, those datasets were only available in bulk through torrent downloads," says Meta's legal counsel. "Accordingly, to the extent Plaintiffs can come forth with evidence that their works or portions thereof were theoretically 'made available' to others on the BitTorrent network during the torrent download process, this was part-and-parcel of the download of Plaintiffs' works in furtherance of Meta's transformative fair use purpose."" This argument is an Ouroboros: Meta is saying that it needed the millions of copyrighted works for what the court has already decided is fair use in training the LLM, that BitTorrent was the only practical way to get those works en masse, and that therefore the act of torrenting itself now comes under that fair use defense. Unsurprisingly, the authors bringing the case are not happy about such chutzpah, nor the fact it was filed late last week on Friday, right on a court deadline for discovery. Their lawyers say Meta had been aware of the BitTorrent claims around uploading since November 2024 but, even when asked specifically by the court, had never referenced such a fair use defense before this filing. "Meta (for understandable reasons) never once suggested it would assert a fair use defense to the uploading-based claims, including after this Court raised the issue with Meta last November," say the authors' lawyers, adding that Meta is trying to create a "loophole" for itself and avoid discovery on this defense. Meta's legal team says au contraire, pointing to a December 2025 case management statement in which it mentions the defense, and noting that the authors' legal team had addressed it at a hearing a few days later. "In short, Plaintiffs' assertion that Meta 'never once suggested it would assert a fair use defense to the uploading-based claims, including after' the November 2025 hearing, is false" says Meta's lawyer. Meta further argues that every author involved in the class-action has admitted they are unaware of any Llama LLM output that directly reproduces content from their books. It says if the authors cannot provide evidence of such infringing output or damage to sales, then this lawsuit is not about protecting their books but arguing against the training process itself (which the court has ruled is fair use). Judge Vince Chhabria now has to decide whether to allow this defense, a decision that will have consequences for not only this but many other AI lawsuits involving things like shadow libraries. The BitTorrent uploading and distribution claims are the last element of this particular lawsuit, which has been rumbling on for three years now, to be settled.

Meta Argues BitTorrent Seeding Is Fair Use in AI Training

Meta has argued that downloading books through torrents for AI training can still qualify as fair use, according to a recent court filing in an ongoing copyright dispute with authors over its Llama models. The statement appears in discovery responses in Kadrey v. Meta, a 2023 lawsuit brought by 13 authors, including Richard Kadrey and Sarah Silverman, who allege the company used pirated copies of their books to train its AI systems without permission. However, in June 2025, a US federal judge granted Meta summary judgment and dismissed claims for copyright infringement in AI training after finding that the authors had not shown sufficient market harm. However, the case is still ongoing surrounding disputes over the alleged distribution of books obtained through torrent downloads. Why This Matters: Meta's argument is significant because this lawsuit is part of a broader wave of copyright cases that will determine whether AI companies can legally train models on copyrighted material without permission. If Meta succeeds in justifying BitTorrent uploads during dataset downloads, it could widen the legal shield for AI developers sourcing training data from large online repositories. The outcome could influence how companies collect data for AI models, shape emerging markets for licensing training data, and determine whether creators must be compensated when their works are used to build generative AI systems.