A position piece from the Electronic Frontier Foundation. Its argument is that copyright is the wrong instrument for the harms attributed to AI, and that using it would produce the opposite of the intended distributive effect.
The competition argument
The piece takes on the strongest case for copyright expansion — that permitting AI training under fair use "would only enrich a handful of tech behemoths" — and argues the remedy inverts it:
"Imposing onerous new copyright licensing requirements to train models would lock in the market advantages enjoyed by Big Tech and Big Media — the only companies that own large content libraries or can afford to license enough material to build a deep learning model — profiting entrenched incumbents at the public's expense."
The mechanism is a barrier-to-entry argument: a licensing regime is a fixed cost that scales with corpus size, which the largest firms can absorb and new entrants cannot. Content owners large enough to hold their own libraries are advantaged twice, as licensors and as trainers.
EFF's stated alternative: "what neither Big Tech nor Big Media will say is that stronger antitrust rules and enforcement would be a much better" instrument for the competition problem — with the general principle that "specific policies are far more likely to succeed in resolving the problems society faces" than a broad expansion of copyright.
Position in the debate
The piece is the clearest statement of the position opposing the plaintiff-side theory in the training-data litigation — NYT v. Microsoft, OpenAI et al., Bartz v. Anthropic, Kadrey v. Meta, and the derivative theory in Anderson v. Microsoft — Shareholder Derivative Complaint (June 2026). It accepts the factual premise those cases rest on (models are trained on copyrighted work without licence) and disputes the legal characterization (that this is infringement rather than fair use) and the policy consequence (that a licensing market would help creators rather than incumbents).
Relationships
- contradicts: AI Copyright — argues against the copyright-expansion position in that debate
- related: NYT v. Microsoft, OpenAI et al., Bartz v. Anthropic, Kadrey v. Meta
- related: Electronic Frontier Foundation (EFF), AI Antitrust, AI Copyright