Seattle Times and Newsday join wave of lawsuits against OpenAI
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| Source: TechCrunch · via Yahoo News | Original article
The Seattle Times and Newsday have joined other outlets in filing lawsuits against OpenAI and Microsoft, alleging unauthorized use of their journalism.
The Seattle Times and Newsday have filed a federal lawsuit against OpenAI and Microsoft, accusing the two firms of copying the newspapers’ journalism without permission to train their artificial‑intelligence systems. The complaint was lodged in the U.S. District Court for the Southern District of New York on September 4, 2026, and argues that the unlicensed use of copyrighted articles threatens to “break” the journalism industry beyond repair.
The case adds to a wave of legal actions targeting AI developers for alleged copyright violations. As we reported on September 5, 2026, the Trump administration sided with OpenAI in a separate lawsuit brought by the New York Times, underscoring how quickly the issue is moving from the newsroom to the courtroom. The Seattle Times and Newsday claim that OpenAI’s large‑language models were trained on their content, a practice they say infringes on their exclusive rights and undermines the economic model of news publishing.
The lawsuit matters because it could set a precedent for how copyrighted material may be used in AI training. A ruling in favor of the newspapers would force AI firms to obtain licenses or otherwise limit the data they ingest, potentially reshaping the supply chain for large‑scale models. Conversely, a decision that upholds the current practice could cement a de‑facto exemption for AI developers, further eroding publishers’ control over their work.
What to watch next includes the courts’ handling of the complaint, any motions for summary judgment, and whether other media outlets join the litigation. Both OpenAI and Microsoft have yet to comment publicly, but the case is likely to intensify regulatory scrutiny of AI data practices and could spur new industry standards or legislative proposals on copyright and machine‑learning training data.
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