Legal battle intensifies as NYT reporter leads copyright suit against AI giants over training data

A New York Times reporter has become the lead plaintiff in a landmark lawsuit accusing major AI companies of using journalistic work without permission, signalling a significant shift in the legal and ethical debates surrounding generative AI and media rights.

A New York Times reporter has become the lead plaintiff in a sweeping copyright lawsuit that accuses major AI companies of using journalists’ work without permission to train large language models, escalating a legal battle that has already begun reshaping how the news industry confronts generative AI. According to the report by OpenTools, the complaint names xAI, Anthropic, Google, OpenAI, Meta and Perplexity among the defendants and frames the dispute as central to where the line should be drawn between technological innovation and creators’ rights. ^[1]

The lawsuit joins a string of recent legal challenges brought by media organisations and creators alleging that AI firms systematically ingested copyrighted material from news sites, books and other sources to build their models. The New York Times, alongside other newspapers, has previously sued OpenAI and Microsoft in Manhattan, arguing that their systems reproduced Times content and diverted web traffic, while separate suits from outlets including The Intercept, Raw Story and AlterNet target OpenAI for similar uses of journalism. According to AP, those plaintiffs seek statutory damages and say the practice diminishes the commercial value of original reporting. ^[3][2][4]

Industry observers say the litigation tests competing legal theories about fair use and infringement as applied to large-scale model training. Government filings and court rulings so far have produced mixed outcomes: a federal judge in New York allowed core copyright claims by The New York Times and other newspapers to proceed against OpenAI and Microsoft, while a prior legal decision suggested that some forms of training on copyrighted texts could qualify as fair use. These divergent judicial signals are already prompting plaintiffs and defendants to sharpen arguments over whether ingestion and transformation of copyrighted works constitute actionable copying or protected reuse. ^[3][5]

The case against Anthropic illustrates how stakes can translate into substantial settlements. Federal court documents show Anthropic agreed to a proposed $1.5 billion settlement with a class of authors who alleged the company trained its Claude model on nearly 465,000 books obtained from piracy sites; the agreement would pay authors roughly $3,000 per affected title. Industry reporting and court papers indicate that settlement negotiations can resolve some claims even as legal precedent remains unsettled. ^[5][7]

Newspaper plaintiffs are emphasising both economic and reputational harms. The Chicago Tribune’s recent suit against Perplexity, for example, alleges not only unauthorised redistribution of reporting and diversion of ad revenue but also the risk of AI “hallucinations” presenting false information under the newspaper’s name, potentially harming trust in its journalism. According to Axios, that complaint follows the Times’ approach in seeking redress for what publishers describe as systematic, uncompensated appropriation of their work. ^[6][1]

Defendants have presented a range of positions in other proceedings: some argue that training on publicly available text is lawful or transformative; others emphasise technical differences in how models process source material. In public statements and filings, AI companies have contested assertions that their systems simply copy or reproduce proprietary works at scale, and some firms have sought licences or begun talks with publishers as litigation and negotiation proceed. According to reporting, those commercial and legal strategies reflect an industry balancing product development with mounting pressure for transparency and accountability in dataset compilation. ^[1][4]

The litigation’s outcomes could set far-reaching norms for the AI sector. Legal experts say rulings that favour publishers may require clearer consent mechanisms, licensing frameworks and greater disclosure about training datasets,while decisions favouring defendants would leave broader latitude for using web-scraped content. Either path will influence how news organisations monetise digital reporting and how AI developers source training data, potentially prompting new commercial agreements or regulatory responses. Court watchers are therefore closely tracking forthcoming briefs, motions and any rulings that clarify whether model training is predominantly a matter of copyrighted copying or a legally protected form of transformation. ^[1][3][5]

For now, the suite of lawsuits, including the Times-led action brought by the reporter named in the OpenTools piece, author class actions settled with Anthropic, and multiple suits targeting OpenAI, Microsoft and Perplexity, illustrates the legal, commercial and ethical tensions that accompany generative AI’s rapid advance. Industry data and court filings show a landscape in flux: some disputes may be resolved through settlements and licensing deals,while others are likely to produce precedent-setting opinions that define the permissible scope of machine learning on third-party content. ^[1][5][2][6]

📌 Reference Map:

##Reference Map:

• ^[1] (OpenTools) – Paragraph 1, Paragraph 5, Paragraph 6, Paragraph 7, Paragraph 8
• ^[2] (AP) – Paragraph 2, Paragraph 8
• ^[3] (AP) – Paragraph 2, Paragraph 3, Paragraph 8
• ^[4] (AP) – Paragraph 2, Paragraph 6
• ^[5] (AP) – Paragraph 3, Paragraph 4, Paragraph 8
• ^[6] (Axios) – Paragraph 5, Paragraph 8
• ^[7] (Tom’s Hardware) – Paragraph 4

Source: Noah Wire Services

Noah Fact Check Pro

The draft above was created using the information available at the time the story first
emerged. We’ve since applied our fact-checking process to the final narrative, based on the criteria listed
below. The results are intended to help you assess the credibility of the piece and highlight any areas that may
warrant further investigation.

Freshness check

Score:
9

Notes:
The narrative is current, with the lawsuit filed on December 22, 2025. Similar reports from December 23, 2025, confirm the event’s recentness. ([thedailystar.net](https://www.thedailystar.net/tech-startup/news/new-york-times-reporter-sues-google-xai-openai-over-chatbot-training-4064756?utm_source=openai))

Quotes check

Score:
8

Notes:
Direct quotes from the lawsuit are consistent across multiple sources, indicating originality. No significant variations in wording were found.

Source reliability

Score:
7

Notes:
The narrative originates from OpenTools, a less established outlet. However, it references reputable sources like Reuters and AP, enhancing credibility.

Plausability check

Score:
8

Notes:
The claims align with ongoing legal actions against AI companies for unauthorized use of copyrighted material. The involvement of notable figures like John Carreyrou adds credibility.

Overall assessment

Verdict (FAIL, OPEN, PASS): PASS

Confidence (LOW, MEDIUM, HIGH): HIGH

Summary:
The narrative is fresh, with consistent quotes and plausible claims. While originating from a less established outlet, the use of reputable sources and the involvement of credible individuals support its authenticity.