Addendum: The Kadrey v. Meta ruling and the escalating case for Copyrighted-as-a-Service (CaaS)

The recent summary judgment in Kadrey v. Meta Platforms, which found Meta’s training of its LLaMA model to be fair use, has been widely misread as a setback for copyright holders.

In reality, the decision introduces a profound level of legal and operational risk for the AI industry, creating an even more urgent and compelling case for the New Internet Media (NIM) Copyright-as-a-Service (CaaS) model. By creating a direct conflict with the earlier Bartz v. Anthropic ruling, the court has exposed the fair use defense as an unstable foundation upon which to build a multi-trillion-dollar industry, making the certainty of licensing platforms like NIM a strategic necessity.

A fractured legal landscape and the specter of market harm

The core of the issue lies in the contradictory guidance from two federal judges in the Northern District of California, the epicenter of AI development.

• The Anthropic ruling: In this case, the court established a clear framework: the use of copyrighted works for AI training constitutes a transformative fair use, whereas the acquisition of those works through piracy constitutes a distinct and indefensible infringement. Crucially, the judge dismissed concerns that AI-generated content would compete with and harm the market for original works, likening it to teaching students to write well and stating it is “not the kind of competitive or creative displacement that concerns the Copyright Act.”
• The Meta ruling: This decision overturns Anthropic reasoning. The judge explicitly stated his disagreement, calling the previous analogy “inapt” and criticizing it for “blowing off the most important factor in the fair use analysis.” He argued forcefully that generative AI has the potential to “flood the market” and “dramatically undermine the incentive for human beings to create.” The only reason Meta prevailed was the plaintiffs’ failure to present sufficient evidence of this market harm. The ruling is not a vindication of Meta’s practices but an indictment of the plaintiffs’ legal strategy, stating the decision “does not stand for the proposition that Meta’s use of copyrighted materials to train its language models is lawful.”

This judicial split creates an untenable situation for the AI industry. The legality of an AI company’s core business practice now depends entirely on which judge hears their case and how effectively a given set of plaintiffs can quantify market dilution.

The unacceptable risk of a “fair use” gamble

The Meta ruling does not provide a safe harbor for AI developers; it provides a roadmap for future litigants. By emphasizing the failure to prove market harm, the court has shown future plaintiffs exactly how to win: develop a robust evidentiary record of market dilution. This guarantees a new wave of more sophisticated, better-prepared, and far more dangerous lawsuits.

Relying on a fair use defense is no longer a legal strategy; it is a corporate gamble of the highest order. The risk profile for any AI company that trains on unlicensed data has increased exponentially. Their potential liability is no longer a theoretical legal question but a practical, case-by-case vulnerability. This level of uncertainty is antithetical to any stable business operation, investor confidence, and long-term technological planning.

CaaS as the definitive solution

This legal chaos makes the value proposition of NIM and the CaaS model self-evident.

We replace unacceptable risk with predictable cost.

• Certainty in an uncertain market: The NIM platform offers a definitive “safe harbor” from the stormy legal seas. By facilitating transparent, scalable, and legally sound licensing agreements, we eliminate the risk of fair use. AI companies can secure the data they need without betting their existence on the shifting sands of judicial opinion.
• The inevitable path to compensation: The judge in the Meta case provided the most compelling argument for NIM’s existence: “If using copyrighted works to train the models is as necessary as the companies say, they will figure out a way to compensate copyright holders for it.” NIM is that way. Our CaaS platform is the purpose-built infrastructure for this new, essential market of AI data licensing.
• Solving the acquisition problem: Nothing in the Meta ruling negates the central finding from Anthropic: theft is theft. The court in Meta noted the company acquired its training data from “shadow libraries.” The condemnation of this practice remains a critical point of liability. NIM addresses this foundational problem by providing a legitimate and authorized channel for data acquisition.

The collision of the Anthropic and Meta rulings has made one thing clear: the era of acquiring data without consequence is over. The escalating legal risk has transformed data licensing from a niche concern into a board-level strategic imperative. By providing the market architecture to manage this risk, NIM’s CaaS platform is poised to become the indispensable utility for responsible AI development, accelerating the final reclassification of copyright as a liquid, high-value financial asset.