CNN has filed a lawsuit against Perplexity, according to the network, accusing the AI company of unlawfully copying and distributing the network’s journalism without permission.

The lawsuit, filed Thursday in the United States District Court for the Southern District of New York, marks CNN’s first copyright action against an AI company, and is believed to be the first such suit filed by any television network. It alleges Perplexity scraped and redistributed CNN’s reporting to power its AI-powered search product.

According to the filing, CNN attempted to negotiate a content licensing deal with Perplexity last year but failed to reach agreement on terms.

“As a result, before and after Perplexity’s negotiations with CNN, Perplexity knew that it was not permitted to access CNN’s content or to use its trademarks or service marks,” the lawsuit states.

The network said it “actively embraces the opportunities AI creates” and has commercial partnerships with responsible industry players, including a publicly reported deal with Meta last December. But CNN drew a hard line with Perplexity.

“CNN’s lawsuit stands for the proposition that Perplexity, a company valued at tens of billions of dollars, should not be able to steal from entities that create the original content Perplexity exploits,” a CNN spokesperson said. “The public rely on high quality news journalism reported by human beings to understand their world, which is frequently dangerous and expensive to produce. Commercial operators can and must pay to make use of it.”

The statement added: “There is no free option.”

Perplexity faces similar legal challenges from other major publishers, including The New York Times, the Chicago Tribune, News Corp, Encyclopedia Britannica, and the Japanese media company Yomiuri Shimbun. Publishers including Gannett, TIME, Le Monde, and Der Spiegel, however, have announced licensing deals with Perplexity during the same period.

In a statement, Perplexity pushed back on the premise. “You can’t copyright facts,” said Jesse Dwyer, the company’s chief communications officer.

Earlier this year, in a legal response to the Times and Tribune suits, Perplexity argued that attempts “to stop this novel technology by monopolizing facts will founder on bedrock principles of intellectual property law that have consistently permitted innovative technologies like Perplexity to exist.”

The CNN lawsuit escalates a broader confrontation between news publishers and AI companies over compensation for content used to train and power generative AI tools. Publishers have largely pursued a two-track approach: suing some AI firms while striking licensing deals with others.

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Cate Blanchett has co-founded a new nonprofit aimed at solving one of AI’s most urgent unsolved problems: the ability for any person to control how their work, likeness, and identity are used by artificial intelligence systems.

RSL Media launched Tuesday as a public benefit nonprofit, built around a deceptively simple idea: Human consent should function like a traffic light—allowed, allowed with terms, or prohibited—that AI systems can actually read and respect. The organization has already secured support from a roster of A-list entertainment figures including Javier Bardem, George Clooney, Viola Davis, Tom Hanks, Dame Helen Mirren, Steven Soderbergh, Kristen Stewart, Meryl Streep, and Dame Emma Thompson, as well as Creative Artists Agency and the Music Artists Coalition.

“AI technologies are expanding rampantly, essentially unchecked and unregulated,” Blanchett said in a statement. “In order for humans to remain in front of these technologies, consent must be the first consideration.”

The launch comes less than a year after the Really Simple Licensing standard released version 1.0 of its open protocol that lets publishers define machine-readable terms for AI training on their content. RSL Media builds on that same architecture, extending the principle of machine-readable rights from content licensing to the protection of human creative expression, identity, and likeness.

“The right to decide whether AI can use your work or identity should not be reserved for only those who can afford lawyers or have platforms big enough to be heard,” said Nikki Hexum, co-founder and CEO of RSL Media. “It is a basic human right.”

The organization covers four distinct rights areas: creative works (songs, films, books, art, photography), identity (name, image, voice, movement, personal attributes), characters (fictional figures including their names, voices, and visual depictions), and marks (logos, trademarks, trade dress, brand identifiers). Its co-founders include not only Blanchett and Hexum but also Doug Leeds and Eckart Walther, the latter being the RSS co-creator behind the original RSL standard.

The legal framework was co-authored by James Everingham, former head of engineering at Instagram and CEO of Guild.ai; Jacqueline Sabec, a partner at King, Holmes, Paterno & Soriano; and Francesca Amfitheatrof, former artistic director of watches and jewelry at Louis Vuitton and design director at Tiffany & Company.

A free, public registry launches in June. Once live, anyone will be able to verify their identity through RSLMedia.org, declare permissions for their work and likeness, and have those preferences translated into machine-readable signals that AI platforms can query before use.

The approach mirrors the logic behind IAB Europe’s compensation framework (and the earlier RSL protocol) in aiming to turn consent into infrastructure. RSL Media’s registry goes further, however, by applying that model to individuals rather than publishers, covering identity and likeness alongside creative work.

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Scott Turow, the bestselling author of “Presumed Innocent,” has filed a copyright infringement lawsuit against Meta. And he’s brought along half of the publishing industry.

Turow and his company S.C.R.I.B.E. joined forces with Hachette, Macmillan, McGraw Hill, Elsevier and Cengage to file a class-action lawsuit in the U.S. District Court for the Southern District of New York. The plaintiffs allege Meta built its Llama language model by copying millions of copyrighted books and journal articles, with direct authorization from CEO Mark Zuckerberg.

The complaint claims Meta “briefly considered licensing deals with major publishers” but reversed course in April 2023 after the question was escalated to Zuckerberg. A Meta employee is quoted in the filing as saying: “If we license one single book, we won’t be able to lean into the fair use strategy.”

The lawsuit cites specific works including Turow’s “Presumed Innocent,” Douglas Preston’s “Impact,” Peter Brown’s “The Wild Robot,” N.K. Jemisin’s “The Fifth Season,” and Lemony Snicket’s “Who Could That Be at This Hour?” The class could include authors with registered copyrights on books with ISBNs or journal articles with DOIs or ISSNs.

“All Americans should understand that the bold future promised by A.I., has been, to paraphrase the investigative writer Alex Reisner, created with stolen words,” Turow said in a statement to NPR. “It is all the more shameful that these violations of the law were undertaken by one of the richest corporations in the world.”

Authors Guild CEO Mary Rasenberger called it “the most flagrant copyright breach in history.” The plaintiffs are seeking statutory damages, a permanent injunction, and an order requiring Meta to destroy all infringing copies.

Meta pushed back sharply. “AI is powering transformative innovations, productivity and creativity for individuals and companies, and courts have rightly found that training AI on copyrighted material can qualify as fair use,” said Nkechi Nneji, a Meta public affairs director. “We will fight this lawsuit aggressively.”

The case enters a complicated legal landscape. A federal judge dismissed a different group of authors’ copyright claims against Meta last June, finding the plaintiffs didn’t present enough evidence of harm. But Anthropic settled with publishers for $1.5 billion last September after a ruling that the company had copied millions of books without consent or compensation.

Whether Turow’s case can distinguish itself from Meta’s previous win — and overcome the “fair use” defense — will be the central question.

The post Scott Turow and Five Publishers Sue Meta Over AI Training Data appeared first on The Media Copilot.

The Trump administration released its National Policy Framework for Artificial Intelligence on March 20 — a four-page document that tells Congress what the White House wants federal AI law to look like, and signals clearly what it doesn't want: state-level regulation, a new federal AI agency, or courts deciding that AI training violates copyright law.

The framework isn't binding. It's a legislative wish list that still needs Congress to act. But it maps the administration's priorities across seven areas, and for publishers and media companies, two of them matter most.

On intellectual property, the White House punts to the courts while tipping its hand. The document states the administration "believes that training of AI models on copyrighted material does not violate copyright laws" — then says it supports judicial resolution. That's a tell. For publishers currently suing OpenAI, Google, and others over training data — including Encyclopedia Britannica's recent suit against OpenAI and News Corp's ongoing case against Perplexity — the administration has effectively signaled it's rooting against them. The framework does contemplate collective licensing frameworks and protections against unauthorized replicas of people's voices and likenesses, but the core fair use question is left to judges who now know where the White House stands. That's also bad news for publishers pushing for statutory licensing models as a structural solution.

On federal preemption, the framework pushes hard to override state AI laws that "impose undue burdens" on a national strategy for "global AI dominance." The immediate target is Colorado's AI Act — the first state law requiring impact assessments and transparency for high-risk AI deployments — which was already delayed from February to June 2026 under industry pressure. The framework would put federal law above a patchwork of state rules, effectively neutering the most aggressive state-level efforts to regulate AI behavior. It's the opposite direction from the EU AI Act, which the administration's framework implicitly positions itself against.

The rest covers child safety — age verification and deepfake protections via the Take It Down Act, which targets non-consensual intimate imagery — infrastructure buildout, workforce development, and a preference for regulatory sandboxes and industry-led standards over a new AI regulator. The deepfake protections are notable given Grok's ongoing global regulatory scrutiny over sexualized AI imagery, though the framework addresses individual harm rather than platform accountability.

The overall posture is: light-touch federal rules, no new agency, and existing sector-specific regulators handle the rest. The contrast with the EU is deliberate. The administration's framework is a bet that the US approach — let companies build, let courts sort out the edges — will outcompete Europe's more prescriptive compliance regime. For publishers, that bet means the most important AI policy battles are now happening in courtrooms, not legislatures — and the traffic consequences of losing those battles are already here.

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Encyclopedia Britannica and its Merriam-Webster subsidiary sued OpenAI in Manhattan federal court on Friday, alleging the company used nearly 100,000 of their articles to train ChatGPT without permission, and then used the chatbot to cannibalize the traffic that encyclopedias depend on to survive.

The complaint, filed in the Southern District of New York, says OpenAI made “near-verbatim” copies of Britannica’s encyclopedia entries, dictionary definitions and reference content to train its GPT large language models. It also accuses OpenAI of trademark infringement—specifically, generating AI “hallucinations” that falsely cite Britannica as a source, implying a permission that was never granted.

OpenAI’s response was the standard playbook: “Our models empower innovation, and are trained on publicly available data and grounded in fair use.”

Britannica isn’t new to this fight. The company sued Perplexity last September over similar allegations—that Perplexity’s answer engine reproduces its content without attribution or compensation. That case is still ongoing. The OpenAI suit extends the same theory to a much larger defendant with much deeper pockets and a far larger user base.

The core grievance goes beyond copyright. Britannica’s complaint frames the harm as a flywheel: OpenAI trains on Britannica’s content, then deploys a product that answers the same questions Britannica’s websites would have answered, diverting users before they ever arrive. It’s the same structural argument publishers have been making about AI search summaries, and it’s why policymakers in Europe and Brazil are exploring statutory licensing as a way to compensate content creators whose work powers AI without delivering any traffic in return.

Britannica requested unspecified monetary damages and an injunction blocking further infringement. The case joins a growing docket of high-stakes AI copyright litigation heading for a reckoning in U.S. courts over whether training on publicly available data constitutes fair use—a question on which the industry, publishers, and regulators are all waiting for an answer.

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The latest turn in the Dow Jones and New York Post case against Perplexity is less about one chatbot answer than about how copyright evidence gets built in the AI era. According to Press Gazette, Perplexity is asking the court to force the publishers to turn over records showing the prompts they used to test its system before filing suit.

Perplexity’s argument is blunt. In a filing quoted by Press Gazette, the company said, “This discovery would reveal an inconvenient truth: Plaintiffs repeatedly and deceptively crossed the line from investigation to entrapment.” In other words, Perplexity is not just denying infringement. It is arguing that the publishers tried to engineer failure conditions to make a stronger case.

That matters because publisher lawsuits against answer engines and generative AI tools often depend on showing that a system can reproduce or closely mimic protected reporting. If courts start scrutinizing how those tests were constructed, the evidentiary playbook for future cases could get more complicated.

Press Gazette reported that Dow Jones and the New York Post oppose producing the prompt records, arguing they are protected attorney work product created in anticipation of litigation. The dispute now sits at an awkward but important junction: publishers want to demonstrate copying while AI companies want room to argue that the tests did not reflect normal user behavior.

The prompt-log fight could matter beyond Perplexity

The legal issue here is narrow, but the industry implication is broad. AI companies have spent months insisting that many public examples of harmful output, hallucinations or copyright problems come from adversarial prompting. Publishers, for their part, have strong incentives to probe systems hard because casual use may not expose the outer edge of reproduction risk.

Press Gazette described one example in which Perplexity summarized a Wall Street Journal article but refused a request to reproduce part of it verbatim. The chatbot response quoted by the publication said, “I’m sorry, but I can’t provide the exact text from the article. However, I can help summarize or provide information on the topic if you need it.” That example supports Perplexity’s broader point that the system may resist some direct copying requests. But it does not settle whether other prompts produced output that went too far.

For publishers, that is the danger in this stage of the litigation cycle. Courts may begin asking not only what the chatbot returned, but how many tries it took, what sequence of prompts got there and whether those prompts resembled ordinary use. That is a harder factual record to present cleanly than a simple side-by-side reproduction claim.

Why newsroom leaders should care

This case is not just another skirmish in the running AI copyright war. It could influence how publishers and newsroom counsel document future complaints against search-answer and RAG-style products.

If Perplexity succeeds in forcing disclosure of prompt logs, plaintiffs may have to assume their testing methods will be examined in detail. That could make legal teams more rigorous about documenting why a prompt sequence was reasonable and how closely it matched actual user behavior. It could also give AI defendants a repeatable strategy: shift the discussion from output alone to the testing design behind the output.

There is still an important unknown here. Press Gazette’s report leaves open whether the judge will require disclosure of the prompt records. Until that happens, the case remains a procedural fight with larger implications rather than a clear substantive win for either side.

But the underlying issue is not going away. As publishers try to prove that AI systems copied their work, and AI companies argue that plaintiffs had to game the system to show it, courts will increasingly be asked to decide where legitimate investigation ends and manufactured evidence begins. That line could matter almost as much as the copying question itself.

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By The Copilot, based on an interview by The Copilot, Pete Pachal

When a lawyer who’s also a published author tells you artificial intelligence doesn’t actually learn like humans, you should probably listen.

Jason Henderson is a corporate and transactional attorney who specializes in streaming and licensing deals. He also occasionally writes books (one or two of which may be part of a long-running science-fiction franchise), which means he understands copyright from both sides of the table. In this episode of The Media Copilot podcast, he walks through the messy reality of how AI companies acquire content, what fair use actually protects (and doesn’t), and why the courts care less about the theory of transformation and more about whether your product just destroyed someone’s business model.

• Watch on YouTube
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The conversation starts with training data but quickly moves to the sharper edge: what happens when AI doesn’t copy your article but replaces the reason anyone would read it. Henderson explains why indemnification clauses in licensing deals only work if the company promising to cover you can actually pay up, why insurance may not protect publishers from AI-related risks, and why the next battlefield won’t be scraped text but agents that browse the web like users and become nearly impossible to block.

Why this matters

Media companies are no longer just competing with each other. They’re competing with systems that can answer questions, summarize stories, and satisfy curiosity without ever sending a reader to the source. Henderson maps out how courts evaluate that substitution, why “transformative use” is both the most important legal concept and the hardest to pin down, and why the industry is moving toward deals even as the lawsuits pile up.

He also sees a harder problem coming: agentic AI that behaves like a person, not a bot. The legal frameworks assume you can tell the difference. The technology is making that assumption obsolete.

What we cover

What we cover

• Jason’s background in AI, licensing, and streaming deals, plus his work as a writer and publisher
• The “AI learns like humans” argument, why it is only an analogy, and where it breaks down
• Inputs vs outputs: why training data and what models produce raise different legal and business issues
• A clear explanation of the four-factor fair-use test

• Why the ability to recreate articles via prompting becomes a legal flashpoint, even if framed as a “bug, not a feature”
• What media companies actually care about most, ethics vs bottom line, and why market substitution dominates
• The deal side: how licensing agreements are evolving for AI, including tighter usage restrictions
• The risk side: indemnification and why it only works if the other party can actually pay
• Insurance gaps: why many companies may not be protected for AI-related data and content liabilities
• The emerging “agents” problem: bot blocking, user proxies, and the future of attribution
• Hope vs dismay: personalization that helps audiences find authentic creators vs settling for “good enough” synthetic content
• Why Jason expects turbulence near term, but a longer-term premium on human-authored authenticity

👤 Guest

🔗Jason Henderson    🔗https://www.linkedin.com/in/jasonhendersontx 

🔗Senior Attorney,JWL International  🔗https://jwlinternational.com/
🔗Founder,Castle Bridge Media      🔗https://www.castlebridgemedia.com/
🔗Co-host, Castle of Horror podcast (horror movie coverage)  🔗https://podcasts.apple.com/us/podcast/castle-of-horror-podcast/id447295500

Enjoyed this episode?

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Produced by Pete Pachal and Executive Producer Michele Musso
Edited by the Musso Media Team 

Music: “Favorite” by Alexander Nakarada, licensed under CC BY 4.0

All rights reserved. © AnyWho Media 2026

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The New York Times filed a federal lawsuit against Perplexity on Friday, accusing the AI search startup of repeatedly violating its copyrights despite 18 months of demands to stop.

The suit, filed in New York, claims Perplexity’s search engine grabbed large chunks of Times content, including entire articles, to generate responses for users. The Times argues this directly competes with its own offerings.

“Perplexity provides commercial products to its own users that substitute for The Times, without permission or remuneration,” the lawsuit states, according to reporting by Cade Metz and Michael M. Grynbaum in The New York Times.

The suit also accuses Perplexity of damaging the Times‘ brand by hallucinating information and falsely attributing it to the newspaper.

Perplexity dismissed the lawsuit. “Publishers have been suing new tech companies for a hundred years, starting with radio, TV, the internet, social media and now A.I.,” Jesse Dwyer, Perplexity’s head of communication, told the Times. “Fortunately, it’s never worked, or we’d all be talking about this by telegraph.”

The filing joins more than 40 copyright cases against AI companies nationwide. The Chicago Tribune sued Perplexity on Thursday, and Dow Jones filed against the startup last year.

Why it matters for newsrooms: The case tests whether AI search engines can legally scrape and summarize news content without licensing deals. Many publishers have signed agreements with AI companies, but holdouts like the Times are betting courts will force compensation.

In September, Anthropic agreed to pay $1.5 billion to book authors and publishers after a judge ruled the company illegally downloaded copyrighted books. That ruling could signal trouble for AI companies relying on news content.

The Times struck its first AI licensing deal with Amazon in May. Financial terms were not disclosed.

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