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81.7 terabytes of data: Meta downloads entire digital libraries without permission
The information revealed suggests that among the 81.7 terabytes of downloaded data, at least 35.7 terabytes include library books

- February 10, 2025
- Updated: July 1, 2025 at 10:26 PM

Meta, the company of Mark Zuckerberg that was previously called Facebook, is facing serious accusations in the Kadrey case against the company, in which it is accused of using copyrighted works to train artificial intelligence models.
Recent revelations have highlighted the systematic nature of these activities, with evidence suggesting massive downloads of books from platforms like Z-Library and LibGen, reaching a total of 81.7 terabytes of data.
Judicial documents have revealed internal emails that demonstrate Meta employees’ awareness of the illegality of their actions.
Meta has been stealing content for years to train its AI
In October 2022, employee Melanie Kambadur expressed her doubts about the ethics of downloading books using torrents from a corporate computer. Later, in April 2023, Nikolay Bashlykov, a project manager, was cautious about using the corporate network for these downloads, suggesting that it could involve legal risks.
Despite these questions, Meta has filed a motion to dismiss the allegations, arguing that there is no concrete evidence that its employees have downloaded material illegally.
However, the information revealed suggests that among the 81.7 terabytes of downloaded data, at least 35.7 terabytes include books from unauthorized digital libraries.
These practices are not unique to Meta, as other artificial intelligence companies, such as Google and OpenAI, have also faced criticism for the misuse of protected content to train their models.
The industry seems to be normalizing these copyright violations under the concept of “fair use,” an argument that has been widely questioned in the context of AI growth.
However, while “fair use” allows for the limited use of protected material, the constant reports of copyright violations in the field of generative AI suggest that this justification is losing relevance.
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