{
  "id": 17252923,
  "title": "The Wikimedia Foundation weighs in on the NYT's case against OpenAI",
  "url": "https://urgent.news/2026/10/30/the-wikimedia-foundation-weighs-in-on-the-nyts-case-against-openai",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-30T15:47:12.000Z",
  "source": {
    "name": "Engadget",
    "slug": "engadget",
    "url": "https://www.engadget.com/2302374/the-wikimedia-foundation-weighs-in-on-the-nyts-case-against-openai/"
  },
  "original_language": "en",
  "account": "The Wikimedia Foundation has commented on a copyright lawsuit filed by The New York Times against OpenAI and Microsoft. Wikipedia, part of the Wikimedia Foundation, has urged caution in the case, which examines whether or not OpenAI and Microsoft's use of content from The New York Times for purposes such as AI model training infringes on copyright law. The New York Times claims that entities like OpenAI should not have unrestricted access to its content. Conversely, OpenAI and Microsoft argue that training and deploying AI models based on published data is essential for technological progress and would fall under fair use. The Wikimedia Foundation, however, favors a different approach. The amicus brief supports Microsoft and OpenAI's stance but also cautions that a ruling in favor of unrestricted fair use could stifle technological innovation. On the other hand, it argues that a decision supporting blanket fair use could result in a \"closed web\" where knowledge suffers due to a lack of secondary source materials. The Wikimedia Foundation proposes considering fair use in two specific scenarios for AI companies: certain model training scenarios and retrieval-augmented generation (RAG). RAG is a method that enhances the output of large language models (LLMs) by referencing authoritative knowledge bases not included in their training data. However, the organization does not endorse RAG if an LLM simply reproduces pre-existing articles without attribution. The Wikimedia Foundation states that scraping copyrighted content could be deemed fair use if it's used to train LLMs that are substantially different from the original sources. It's worth noting that Wikipedia is one of the highest-quality datasets used to train LLMs. A ruling that fails to apply fair use principles appropriately could jeopardize the sustainability of free knowledge and hinder the development of open-source technologies, ultimately affecting access to information for everyone. The court is expected to issue a summary judgment in the lawsuit soon, which could have significant implications for this and over a dozen similar cases currently in the courts, potentially setting an important precedent.",
  "summary": "The folks behind Wikipedia say that an extreme decision in either direction could threaten the open web.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}