Seattle Times and Newsday Sue OpenAI and Microsoft, Seeking Destruction of AI Models

The Seattle Times and Newsday filed a lawsuit against OpenAI and Microsoft on September 4, 2026, marking a significant escalation in the legal battle between news organizations and the developers of generative artificial intelligence. Filed in the U.S. District Court for the Southern District of New York, the complaint moves beyond seeking monetary damages, requesting a court order for the “destruction” of training datasets and AI models that incorporate the publishers’ copyrighted works.

This demand for what some legal analysts describe as a “death penalty” for specific AI iterations highlights the existential threat midsize publishers feel from the rapid expansion of ChatGPT and Microsoft’s Copilot. The filing cites internal industry data showing that search referral traffic to midsize publishers plummeted by 47% year-over-year as of December 2025, a decline the plaintiffs attribute to AI-generated summaries that keep users on search pages rather than clicking through to original news sources.

A digital chart showing a sharp decline in traffic represented by a falling line.
Publishers reported a 47% year-over-year drop in search referral traffic as of late 2025.

The complaint alleges that OpenAI and Microsoft methodically scraped news articles in a way that intentionally bypassed paywalls, essentially using high-quality journalism to train commercial products that then compete directly with the publications. Seattle Times CEO Alan Fisco stated that the company spends millions of dollars annually to produce local reporting, arguing that the business model cannot survive if its core product is ingested and redistributed without compensation or consent.

A distinct element of this lawsuit involves claims of trademark dilution regarding AI “hallucinations.” The newspapers allege that OpenAI’s models have frequently generated fabricated facts and attributed them to The Seattle Times or Newsday, damaging their reputations for accuracy. By falsely presenting AI-generated errors as reported facts from these outlets, the plaintiffs argue the tech companies are diluting the value of their brand names.

The Partnership Paradox

The legal action creates a notable rift between The Seattle Times and the technology giants it is now suing. In 2024, the publication was part of a $10 million journalism fellowship program funded by Microsoft and OpenAI through the Lenfest Institute. That initiative was designed to help newsrooms explore AI integration; however, the relationship has clearly soured as the economic impact of AI-generated search results became clearer throughout 2025 and 2026.

Microsoft spokesperson Drew Born expressed “surprise” at the filing, stating that the company had been in ongoing discussions with various publishers and remains willing to explore collaborative solutions. Despite these previous partnerships, the Seattle-based newspaper is now taking a hardline stance against its local tech neighbor.

Conceptual image of a broken bridge between a news institution and a technology company.
The lawsuit marks a rift following previous AI fellowship partnerships between the parties.

This lawsuit mirrors some of the arguments made in the landmark 2023 case brought by The New York Times, but it places a heavier emphasis on the specific survival of regional and mid-market media. By focusing on the 47% drop in referral traffic, the plaintiffs are attempting to demonstrate that the current AI ecosystem does not just supplement the news industry, but is actively replacing the audience-to-publisher pipeline that sustains local journalism.

If the court were to grant the request for the destruction of models, it could force OpenAI and Microsoft to retrain massive Large Language Models (LLMs) from scratch, omitting any data sourced from these publishers. While legal experts consider the actual destruction of models a high hurdle to clear, the request serves as a powerful bargaining chip in the broader industry push for mandatory licensing fees and stricter controls over how news content is used to train future AI systems.

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