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AI companies are buying used books by the thousands. Some may be destroyed for training

Not too many years ago, before the dawn of Kindles , used bookstores were a refuge for budget-minded, voracious readers. As the industry evolved, many suffered. Now they’re seeing a resurgence in sales, but the customers increasingly aren’t bookworms. They’re AI companies. Barter Books, for instance, typically sells 2,000 to 3,000 books per week, which isn’t bad for a used bookstore in…

AI companies are buying used books by the thousands. Some may be destroyed for training

In recent years, used bookstores have experienced a resurgence in sales, but the customers are no longer just avid readers. They are increasingly AI companies seeking to acquire source material. Barter Books, a used bookstore in Northumberland, England, typically sells 2,000 to 3,000 books per week, but recently received a bulk order of that quantity from a Canadian company in a single day.

Other nearby bookstores are also witnessing similar demand. While the exact use of the books remains unclear, a court ruling offers insight into one potential use. The ruling allows AI companies to train their models using copyrighted material if they pay for the books used. This method, known as "destructive scanning," physically disassembles bound books to extract individual pages and feed them into large language models.

Although Anthropic, an AI company, has stated that none of its data acquisition programs buy and destroy rare or antiquarian books, other companies may not have the same restrictions. Such practices could potentially impact the availability of rare books, which often contain unique information not found in other publications. Despite ethical concerns, used bookstores are benefiting from the influx of cash, as sales have seen a slight recovery in recent years.

However, many bookstores have had to adapt their business models or close permanently due to the decline in sales since their peak in 2007.

Written by urgent.news from Fast Company's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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