Training Data Sourcing

Training data sourcing refers to the process of identifying, acquiring, and validating datasets used to build and fine-tune machine learning models. For AI governance, this is critical because the quality, legality, and ethical provenance of training data directly impact model bias, performance, and regulatory compliance. Organizations must establish clear procedures for data sourcing that address intellectual property rights, consent, privacy regulations, and potential contamination with sensitive or biased information.

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Corporate PolicyGlobal2026-08-12

Anthropic's 'Project Panama' Exposes Training Data Sourcing as a Supply-Chain Risk

Reports from rare booksellers and a 2025 lawsuit have revealed that Anthropic ran a covert program called 'Project Panama' under which millions of print books were purchased and destroyed to extract training data. The accounts raise concerns about deceptive procurement, irreplaceable cultural loss, and undisclosed data sourcing practices. Enterprise compliance teams that rely on commercially-licensed AI models now face heightened exposure across training data provenance, vendor due diligence, and IP risk programs.

Anthropic training data sourcing intellectual property vendor due diligence AI transparency corporate governance Project Panama