FTC Urged to Investigate AI Companies' Book Destruction Practices

On August 22, the Federal Trade Commission (FTC) of the United States is being urged to investigate the actions of certain AI companies that acquire AI training data by purchasing, scanning, and destroying books. Over a dozen civil society organizations are calling on the FTC to exercise its regulatory power to review what they describe as a "new method of destructive data acquisition" employed by large AI firms. Previously, court documents reported that Anthropic had spent millions of dollars purchasing books and removing their spines to scan the pages for training Claude; Google, Microsoft, and OpenAI have also faced similar copyright lawsuits.

These organizations hope the FTC will further assess whether such actions constitute unfair competition practices. They argue that by acquiring and destroying physical books, AI companies may be "draining the market" of critical data resources, particularly as some rare books may permanently disappear, leaving digital companies with the last few physical copies. The relevant organizations warn that this practice of "hoarding and destroying" could raise the data acquisition costs for competitors while cutting off vital original materials that startup AI companies rely on to train their models, thereby further expanding the competitive barriers for leading AI firms.

However, these organizations are not asking the FTC to restrict AI model training; rather, they hope the regulatory body will focus on reviewing the act of destroying existing works and take intervention measures before large AI companies establish a market advantage through this practice. The open letter states that this approach is not merely a data acquisition strategy but could become another structural means for leading AI firms to build a "formidable systemic moat." Currently, under the leadership of the Trump administration, the FTC aims to maintain a relatively business-friendly regulatory environment for U.S. companies while also continuing to express concerns about market competition and the monopolistic risks posed by large tech firms.

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