OpenAI's 550+ Publisher Coalition Grows as Fair-Use Summary Judgment Looms

Platkin LLP says it represents 60 publishers in the litigation ^[2], which is about one in nine of the 550-plus figure the coalition now claims ^[16]. The rest sit across other actions. Richner Communications has been folded into the OpenAI litigation, and The Seattle Times and Newsday sued OpenAI and Microsoft separately over website material, including paid content, used in ChatGPT, Microsoft Copilot and Bing AI ^[15]. Wednesday's 26 additions moved the headcount by under five per cent ^[17].

Matt Platkin, a partner at the firm, said, "The scale of this coalition should be a wake-up call." ^[5] He argues that the coalition's growth shows publishers now treat the conduct as a threat both to copyright protection and to the economics of journalism ^[19]. Scale is a bargaining input. What would move a cost base is a rate, and no rate has surfaced: no damages demand, no per-work licence figure ^[18].

Gartner expects worldwide spending on AI models and platforms to reach 64.25 billion dollars in 2026 ^[14]. That is buyer spending on models. A licence for training corpora would be a deduction from that pool, at a rate this litigation has yet to establish.

The two theories in front of the court are narrow ones. The copyright owners say the copying done to build the models cannot be fair use and harms both their existing markets and markets they might have sold into ^[7]. OpenAI and Microsoft say training is transformative because the models are taught to recognise patterns and do not acquire information from the underlying works, according to the Center for AI and Digital Policy ^[8].

Stein could hold that copying for training is fair use, in which case the coalition's value falls back to its sourcing and copyright-notice claims. He could hold that it is not, in which case 550-plus parties become a damages queue and licensing becomes compulsory in commercial practice without Congress legislating it. Or the defendants settle in volume first, pricing training data publisher by publisher, in agreements that never reach a judge.

I would put most weight on the third. A defendant with a serious transformation argument still prefers a known number to a docket of 550 counterparties, and litigating all the way to judgment leaves unsigned the voluntary licences that would establish a market rate. A ruling from Stein that training copying is not fair use would change that view. So would a disclosed settlement carrying a per-work rate that other publishers can anchor to.