AI training

Pay-per-output? AI firms blindsided by beefed up robots.txt instructions.

AI, ai crawlers, ai scraping, AI training, Google, Meta, openai, Policy, really simply licensing, rsl standard, RSS, xAI / 9u50fv / September 10, 2025

“Really Simple Licensing” makes it easier for creators to get paid for AI scraping.

Logo for the “Really Simply Licensing” (RSL) standard. Credit: via RSL Collective

Leading Internet companies and publishers—including Reddit, Yahoo, Quora, Medium, The Daily Beast, Fastly, and more—think there may finally be a solution to end AI crawlers hammering websites to scrape content without permission or compensation.

Announced Wednesday morning, the “Really Simply Licensing” (RSL) standard evolves robots.txt instructions by adding an automated licensing layer that’s designed to block bots that don’t fairly compensate creators for content.

Free for any publisher to use starting today, the RSL standard is an open, decentralized protocol that makes clear to AI crawlers and agents the terms for licensing, usage, and compensation of any content used to train AI, a press release noted.

The standard was created by the RSL Collective, which was founded by Doug Leeds, former CEO of Ask.com, and Eckart Walther, a former Yahoo vice president of products and co-creator of the RSS standard, which made it easy to syndicate content across the web.

Based on the “Really Simply Syndication” (RSS) standard, RSL terms can be applied to protect any digital content, including webpages, books, videos, and datasets. The new standard supports “a range of licensing, usage, and royalty models, including free, attribution, subscription, pay-per-crawl (publishers get compensated every time an AI application crawls their content), and pay-per-inference (publishers get compensated every time an AI application uses their content to generate a response),” the press release said.

Leeds told Ars that the idea to use the RSS “playbook” to roll out the RSL standard arose after he invited Walther to speak to University of California, Berkeley students at the end of last year. That’s when the longtime friends with search backgrounds began pondering how AI had changed the search industry, as publishers today are forced to compete with AI outputs referencing their own content as search traffic nosedives.

Eckart had watched the RSS standard quickly become adopted by millions of sites, and he realized that RSS had actually always been a licensing standard, Leeds said. Essentially, by adopting the RSS standard, publishers agreed to let search engines license a “bit” of their content in exchange for search traffic, and Eckart realized that it could be just as straightforward to add AI licensing terms in the same way. That way, publishers could strive to recapture lost search revenue by agreeing to license all or some part of their content to train AI in return for payment each time AI outputs link to their content.

Leeds told Ars that the RSL standard doesn’t just benefit publishers, though. It also solves a problem for AI companies, which have complained in litigation over AI scraping that there is no effective way to license content across the web.

“We have listened to them, and what we’ve heard them say is… we need a new protocol,” Leeds said. With the RSL standard, AI firms get a “scalable way to get all the content” they want, while setting an incentive that they’ll only have to pay for the best content that their models actually reference.

“If they’re using it, they pay for it, and if they’re not using it, they don’t pay for it,” Leeds said.

No telling yet how AI firms will react to RSL

At this point, it’s hard to say if AI companies will embrace the RSL standard. Ars reached out to Google, Meta, OpenAI, and xAI—some of the big tech companies whose crawlers have drawn scrutiny—to see if it was technically feasible to pay publishers for every output referencing their content. xAI did not respond, and the other companies declined to comment without further detail about the standard, appearing to have not yet considered how a licensing layer beefing up robots.txt could impact their scraping.

Today will likely be the first chance for AI companies to wrap their heads around the idea of paying publishers per output. Leeds confirmed that the RSL Collective did not consult with AI companies when developing the RSL standard.

But AI companies know that they need a constant stream of fresh content to keep their tools relevant and to continually innovate, Leeds suggested. In that way, the RSL standard “supports what supports them,” Leeds said, “and it creates the appropriate incentive system” to create sustainable royalty streams for creators and ensure that human creativity doesn’t wane as AI evolves.

While we’ll have to wait to see how AI firms react to RSL, early adopters of the standard celebrated the launch today. That included Neil Vogel, CEO of People Inc., who said that “RSL moves the industry forward—evolving from simply blocking unauthorized crawlers, to setting our licensing terms, for all AI use cases, at global web scale.”

Simon Wistow, co-founder of Fastly, suggested the solution “is a timely and necessary response to the shifting economics of the web.”

“By making it easy for publishers to define and enforce licensing terms, RSL lays the foundation for a healthy content ecosystem—one where innovation and investment in original work are rewarded, and where collaboration between publishers and AI companies becomes frictionless and mutually beneficial,” Wistow said.

Leeds noted that a key benefit of the RSL standard is that even small creators will now have an opportunity to generate revenue for helping to train AI. Tony Stubblebine, CEO of Medium, did not mince words when explaining the battle that bloggers face as AI crawlers threaten to divert their traffic without compensating them.

“Right now, AI runs on stolen content,” Stubblebine said. “Adopting this RSL Standard is how we force those AI companies to either pay for what they use, stop using it, or shut down.”

How will the RSL standard be enforced?

On the RSL standard site, publishers can find common terms to add templated or customized text to their robots.txt files to adopt the RSL standard today and start protecting their content from unfettered AI scraping. Here’s an example of how machine-readable licensing terms could look, added directly to robots.txt files:

# NOTICE: all crawlers and bots are strictly prohibited from using this

# content for AI training without complying with the terms of the RSL

# Collective AI royalty license. Any use of this content for AI training

# without a license is a violation of our intellectual property rights.

License: https://rslcollective.org/royalty.xml

Through RSL terms, publishers can automate licensing, with the cloud company Fastly partnering with the collective to provide technical enforcement that Leeds described as tech that acts as a bouncer to keep unapproved bots away from valuable content. It seems likely that Cloudflare, which launched a pay-per-crawl program blocking greedy crawlers in July, could also help enforce the RSL standard.

For publishers, the standard “solves a business problem immediately,” Leeds told Ars, so the collective is hopeful that RSL will be rapidly and widely adopted. As further incentive, publishers can also rely on the RSL standard to “easily encrypt and license non-published, proprietary content to AI companies, including paywalled articles, books, videos, images, and data,” the RSL Collective site said, and that potentially could expand AI firms’ data pool.

On top of technical enforcement, Leeds said that publishers and content creators could legally enforce the terms, noting that the recent $1.5 billion Anthropic settlement suggests “there’s real money at stake” if you don’t train AI “legitimately.”

Should the industry adopt the standard, it could “establish fair market prices and strengthen negotiation leverage for all publishers,” the press release said. And Leeds noted that it’s very common for regulations to follow industry solutions (consider the Digital Millennium Copyright Act). Since the RSL Collective is already in talks with lawmakers, Leeds thinks “there’s good reason to believe” that AI companies will soon “be forced to acknowledge” the standard.

“But even better than that,” Leeds said, “it’s in their interest” to adopt the standard.

With RSL, AI firms can license content at scale “in a way that’s fair [and] preserves the content that they need to make their products continue to innovate.”

Additionally, the RSL standard may solve a problem that risks gutting trust and interest in AI at this early stage.

Leeds noted that currently, AI outputs don’t provide “the best answer” to prompts but instead rely on mashing up answers from different sources to avoid taking too much content from one site. That means that not only do AI companies “spend an enormous amount of money on compute costs to do that,” but AI tools may also be more prone to hallucination in the process of “mashing up” source material “to make something that’s not the best answer because they don’t have the rights to the best answer.”

“The best answer could exist somewhere,” Leeds said. But “they’re spending billions of dollars to create hallucinations, and we’re talking about: Let’s just solve that with a licensing scheme that allows you to use the actual content in a way that solves the user’s query best.”

By transforming the “ecosystem” with a standard that’s “actually sustainable and fair,” Leeds said that AI companies could also ensure that humanity never gets to the point where “humans stop producing” and “turn to AI to reproduce what humans can’t.”

Failing to adopt the RSL standard would be bad for AI innovation, Leeds suggested, perhaps paving the way for AI to replace search with a “sort of self-fulfilling swap of bad content that actually one doesn’t have any current information, doesn’t have any current thinking, because it’s all based on old training information.”

To Leeds, the RSL standard is ultimately “about creating the system that allows the open web to continue. And that happens when we get adoption from everybody,” he said, insisting that “literally the small guys are as important as the big guys” in pushing the entire industry to change and fairly compensate creators.

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

Pay-per-output? AI firms blindsided by beefed up robots.txt instructions. Read More »

Judge: Anthropic’s $1.5B settlement is being shoved “down the throat of authors”

AI, AI training, Anthropic, Artificial Intelligence, copyright, copyright act, copyright infringement, generative ai, libgen, piracy, Policy / Kelly Newman / September 9, 2025

At a hearing Monday, US district judge William Alsup blasted a proposed $1.5 billion settlement over Anthropic’s rampant piracy of books to train AI.

The proposed settlement comes in a case where Anthropic could have owed more than $1 trillion in damages after Alsup certified a class that included up to 7 million claimants whose works were illegally downloaded by the AI company.

Instead, critics fear Anthropic will get off cheaply, striking a deal with authors suing that covers less than 500,000 works and paying a small fraction of its total valuation (currently $183 billion) to get away with the massive theft. Defector noted that the settlement doesn’t even require Anthropic to admit wrongdoing, while the company continues raising billions based on models trained on authors’ works. Most recently, Anthropic raised $13 billion in a funding round, making back about 10 times the proposed settlement amount after announcing the deal.

Alsup expressed grave concerns that lawyers rushed the deal, which he said now risks being shoved “down the throat of authors,” Bloomberg Law reported.

In an order, Alsup clarified why he thought the proposed settlement was a chaotic mess. The judge said he was “disappointed that counsel have left important questions to be answered in the future,” seeking approval for the settlement despite the Works List, the Class List, the Claim Form, and the process for notification, allocation, and dispute resolution all remaining unresolved.

Denying preliminary approval of the settlement, Alsup suggested that the agreement is “nowhere close to complete,” forcing Anthropic and authors’ lawyers to “recalibrate” the largest publicly reported copyright class-action settlement ever inked, Bloomberg reported.

Of particular concern, the settlement failed to outline how disbursements would be managed for works with multiple claimants, Alsup noted. Until all these details are ironed out, Alsup intends to withhold approval, the order said.

One big change the judge wants to see is the addition of instructions requiring “anyone with copyright ownership” to opt in, with the consequence that the work won’t be covered if even one rights holder opts out, Bloomberg reported. There should also be instruction that any disputes over ownership or submitted claims should be settled in state court, Alsup said.

Judge: Anthropic’s $1.5B settlement is being shoved “down the throat of authors” Read More »

College student’s “time travel” AI experiment accidentally outputs real 1834 history

AI, AI development, AI research, AI training, Biz & IT, computational archaeology, digital archaeology, GitHub, historical AI, historical research, language models, large language models, LocalLLaMA, London history, machine learning, Open Source, reddit, TimeCapsuleLLM, Victorian era / Mike M. / August 23, 2025

A hobbyist developer building AI language models that speak Victorian-era English “just for fun” got an unexpected history lesson this week when his latest creation mentioned real protests from 1834 London—events the developer didn’t know had actually happened until he Googled them.

“I was interested to see if a protest had actually occurred in 1834 London and it really did happen,” wrote Reddit user Hayk Grigorian, who is a computer science student at Muhlenberg College in Pennsylvania.

For the past month, Grigorian has been developing what he calls TimeCapsuleLLM, a small AI language model (like a pint-sized distant cousin to ChatGPT) which has been trained entirely on texts from 1800–1875 London. Grigorian wants to capture an authentic Victorian voice in the AI model’s outputs. As a result, the AI model ends up spitting out text that’s heavy with biblical references and period-appropriate rhetorical excess.

Grigorian’s project joins a growing field of researchers exploring what some call “Historical Large Language Models” (HLLMs) if they feature a larger base model than the small one Grigorian is using. Similar projects include MonadGPT, which was trained on 11,000 texts from 1400 to 1700 CE that can discuss topics using 17th-century knowledge frameworks, and XunziALLM, which generates classical Chinese poetry following ancient formal rules. These models offer researchers a chance to interact with the linguistic patterns of past eras.

According to Grigorian, TimeCapsuleLLM’s most intriguing recent output emerged from a simple test. When he prompted it with “It was the year of our Lord 1834,” the AI model—which is trained to continue text from wherever a user leaves off—generated the following:

It was the year of our Lord 1834 and the streets of London were filled with protest and petition. The cause, as many re counted, was not bound in the way of private, but having taken up the same day in the day of Lord Palmerston, the public will receive a short statement of the difficulties under which the day of law has reached us. It is a matter of deep regret, that the present events in the history of the world are clear, and consequently will be’known. It is not true that the very men who first settled in the Gospel at Jerusalem should have so extensive and so interesting a record of the prosperity and prosperity

Curious about the accuracy, Grigorian did some fact-checking. “The output also brought up Lord Palmerston,” he wrote, “and after a google search I learned that his actions resulted in the 1834 protests.”

College student’s “time travel” AI experiment accidentally outputs real 1834 history Read More »

Reddit blocks Internet Archive to end sneaky AI scraping

AI, ai scraping, AI training, Artificial Intelligence, Google, Internet Archive, openai, Policy, reddit / DJ Henderson / August 12, 2025

“Until they’re able to defend their site and comply with platform policies (e.g., respecting user privacy, re: deleting removed content) we’re limiting some of their access to Reddit data to protect redditors,” Rathschmidt said.

A review of social media comments suggests that in the past, some Redditors have used the Wayback Machine to research deleted comments or threads. Those commenters noted that myriad other tools exist for surfacing deleted posts or researching a user’s activity, with some suggesting that the Wayback Machine was maybe not the easiest platform to navigate for that purpose.

Redditors have also turned to resources like IA during times when Reddit’s platform changes trigger content removals. Most recently in 2023, when changes to Reddit’s public API threatened to kill beloved subreddits, archives stepped in to preserve content before it was lost.

IA has not signaled whether it’s looking into fixes to get Reddit’s restrictions lifted and did not respond to Ars’ request to comment on how this change might impact the archive’s utility as an open web resource, given Reddit’s popularity.

The director of the Wayback Machine, Mark Graham, told Ars that IA has “a longstanding relationship with Reddit” and continues to have “ongoing discussions about this matter.”

It seems likely that Reddit is financially motivated to restrict AI firms from taking advantage of Wayback Machine archives, perhaps hoping to spur more lucrative licensing deals like Reddit struck with OpenAI and Google. The terms of the OpenAI deal were kept quiet, but the Google deal was reportedly worth $60 million. Over the next three years, Reddit expects to make more than $200 million off such licensing deals.

Disclosure: Advance Publications, which owns Ars Technica parent Condé Nast, is the largest shareholder in Reddit.

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Meta pirated and seeded porn for years to train AI, lawsuit says

adult content, adult sites, AI, ai porn, AI training, AI training data, Ai video generator, BItTorrent, copyright infringement, LLaMA, Meta, online piracy, Policy, porn, seeding, torrenting / Kelly Newman / July 28, 2025

Evidence may prove Meta seeded more content

Seeking evidence to back its own copyright infringement claims, Strike 3 Holdings searched “its archive of recorded infringement captured by its VXN Scan and Cross Reference tools” and found 47 “IP addresses identified as owned by Facebook infringing its copyright protected Works.”

The data allegedly demonstrates a “continued unauthorized distribution” over “several years.” And Meta allegedly did not stop its seeding after Strike 3 Holdings confronted the tech giant with this evidence—despite the IP data supposedly being verified through an industry-leading provider called Maxmind.

Strike 3 Holdings shared a screenshot of MaxMind’s findings. Credit: via Strike 3 Holdings’ complaint

Meta also allegedly attempted to “conceal its BitTorrent activities” through “six Virtual Private Clouds” that formed a “stealth network” of “hidden IP addresses,” the lawsuit alleged, which seemingly implicated a “major third-party data center provider” as a partner in Meta’s piracy.

An analysis of these IP addresses allegedly found “data patterns that matched infringement patterns seen on Meta’s corporate IP Addresses” and included “evidence of other activity on the BitTorrent network including ebooks, movies, television shows, music, and software.” The seemingly non-human patterns documented on both sets of IP addresses suggest the data was for AI training and not for personal use, Strike 3 Holdings alleged.

Perhaps most shockingly, considering that a Meta employee joked “torrenting from a corporate laptop doesn’t feel right,” Strike 3 Holdings further alleged that it found “at least one residential IP address of a Meta employee” infringing its copyrighted works. That suggests Meta may have directed an employee to torrent pirated data outside the office to obscure the data trail.

The adult site operator did not identify the employee or the major data center discussed in its complaint, noting in a subsequent filing that it recognized the risks to Meta’s business and its employees’ privacy of sharing sensitive information.

In total, the company alleged that evidence shows “well over 100,000 unauthorized distribution transactions” linked to Meta’s corporate IPs. Strike 3 Holdings is hoping the evidence will lead a jury to find Meta liable for direct copyright infringement or charge Meta with secondary and vicarious copyright infringement if the jury finds that Meta successfully distanced itself by using the third-party data center or an employee’s home IP address.

“Meta has the right and ability to supervise and/or control its own corporate IP addresses, as well as the IP addresses hosted in off-infra data centers, and the acts of its employees and agents infringing Plaintiffs’ Works through their residential IPs by using Meta’s AI script to obtain content through BitTorrent,” the complaint said.

Meta pirated and seeded porn for years to train AI, lawsuit says Read More »

Everything tech giants will hate about the EU’s new AI rules

AI, AI Act, AI risks, AI safety, AI training, Artificial Intelligence, copyright infringement, European Union, Google, Meta, microsoft, openai, piracy, Policy / Beth Washington / July 10, 2025

The code also details expectations for AI companies to respect paywalls, as well as robots.txt instructions restricting crawling, which could help confront a growing problem of AI crawlers hammering websites. It “encourages” online search giants to embrace a solution that Cloudflare is currently pushing: allowing content creators to protect copyrights by restricting AI crawling without impacting search indexing.

Additionally, companies are asked to disclose total energy consumption for both training and inference, allowing the EU to detect environmental concerns while companies race forward with AI innovation.

More substantially, the code’s safety guidance provides for additional monitoring for other harms. It makes recommendations to detect and avoid “serious incidents” with new AI models, which could include cybersecurity breaches, disruptions of critical infrastructure, “serious harm to a person’s health (mental and/or physical),” or “a death of a person.” It stipulates timelines of between five and 10 days to report serious incidents with the EU’s AI Office. And it requires companies to track all events, provide an “adequate level” of cybersecurity protection, prevent jailbreaking as best they can, and justify “any failures or circumventions of systemic risk mitigations.”

Ars reached out to tech companies for immediate reactions to the new rules. OpenAI, Meta, and Microsoft declined to comment. A Google spokesperson confirmed that the company is reviewing the code, which still must be approved by the European Commission and EU member states amid expected industry pushback.

“Europeans should have access to first-rate, secure AI models when they become available, and an environment that promotes innovation and investment,” Google’s spokesperson said. “We look forward to reviewing the code and sharing our views alongside other model providers and many others.”

These rules are just one part of the AI Act, which will start taking effect in a staggered approach over the next year or more, the NYT reported. Breaching the AI Act could result in AI models being yanked off the market or fines “of as much as 7 percent of a company’s annual sales or 3 percent for the companies developing advanced AI models,” Bloomberg noted.

Everything tech giants will hate about the EU’s new AI rules Read More »

Pay up or stop scraping: Cloudflare program charges bots for each crawl

AI, ai bots, ai crawler, ai scraping, AI training, Artificial Intelligence, cloudflare, Policy, robots.txt / Kelly Newman / July 1, 2025

“Imagine asking your favorite deep research program to help you synthesize the latest cancer research or a legal brief, or just help you find the best restaurant in Soho—and then giving that agent a budget to spend to acquire the best and most relevant content,” Cloudflare said, promising that “we enable a future where intelligent agents can programmatically negotiate access to digital resources.”

AI crawlers now blocked by default

Cloudflare’s announcement comes after rolling out a feature last September, allowing website owners to block AI crawlers in a single click. According to Cloudflare, over 1 million customers chose to block AI crawlers, signaling that people want more control over their content at a time when Cloudflare observed that writing instructions for AI crawlers in robots.txt files was widely “underutilized.”

To protect more customers moving forward, any new customers (including anyone on a free plan) who sign up for Cloudflare services will have their domains, by default, set to block all known AI crawlers.

This marks Cloudflare’s transition away from the dreaded opt-out models of AI scraping to a permission-based model, which a Cloudflare spokesperson told Ars is expected to “fundamentally change how AI companies access web content going forward.”

In a world where some website owners have grown sick and tired of attempting and failing to block AI scraping through robots.txt—including some trapping AI crawlers in tarpits to punish them for ignoring robots.txt—Cloudflare’s feature allows users to choose granular settings to prevent blocks on AI bots from impacting bots that drive search engine traffic. That’s critical for small content creators who want their sites to still be discoverable but not digested by AI bots.

“AI crawlers collect content like text, articles, and images to generate answers, without sending visitors to the original source—depriving content creators of revenue, and the satisfaction of knowing someone is reading their content,” Cloudflare’s blog said. “If the incentive to create original, quality content disappears, society ends up losing, and the future of the Internet is at risk.”

Disclosure: Condé Nast, which owns Ars Technica, is a partner involved in Cloudflare’s beta test.

This story was corrected on July 1 to remove publishers incorrectly listed as participating in Cloudflare’s pay-per-crawl beta.

Pay up or stop scraping: Cloudflare program charges bots for each crawl Read More »

Judge: Pirate libraries may have profited from Meta torrenting 80TB of books

AI, AI training, BItTorrent, copyright, copyright infringement, libgen, LLaMA, Meta, online piracy, Policy, shadow libraries, torrenting / Shannon Garcia / June 27, 2025

It could certainly look worse for Meta if authors manage to present evidence supporting the second way that torrenting could be relevant to the case, Chhabaria suggested.

“Meta downloading copyrighted material from shadow libraries” would also be relevant to the character of the use, “if it benefitted those who created the libraries and thus supported and perpetuated their unauthorized copying and distribution of copyrighted works,” Chhabria wrote.

Counting potential strikes against Meta, Chhabria pointed out that the “vast majority of cases” involving “this sort of peer-to-peer file-sharing” are found to “constitute copyright infringement.” And it likely doesn’t help Meta’s case that “some of the libraries Meta used have themselves been found liable for infringement.”

However, Meta may overcome this argument, too, since book authors “have not submitted any evidence” that potentially shows how Meta’s downloading may perhaps be “propping up” or financially benefiting pirate libraries.

Finally, Chhabria noted that the “last issue relating to the character of Meta’s use” of books in regards to its torrenting is “the relationship between Meta’s downloading of the plaintiffs’ books and Meta’s use of the books to train Llama.”

Authors had tried to argue that these elements were distinct. But Chhabria said there’s no separating the fact that Meta downloaded the books to serve the “highly transformative” purpose of training Llama.

“Because Meta’s ultimate use of the plaintiffs’ books was transformative, so too was Meta’s downloading of those books,” Chhabria wrote.

AI training rulings may get more authors paid

Authors only learned of Meta’s torrenting through discovery in the lawsuit, and because of that, Chhabria noted that “the record on Meta’s alleged distribution is incomplete.”

It’s possible that authors may be able to show evidence that Meta “contributed to the BitTorrent network” by providing significant computing power that could’ve meaningfully assisted shadow libraries, Chhabria said in a footnote.

Judge: Pirate libraries may have profited from Meta torrenting 80TB of books Read More »

Meta is making users who opted out of AI training opt out again, watchdog says

AI, AI training, Artificial Intelligence, facebook, Instagram, Meta, Online Privacy, Policy / Kelly Newman / May 14, 2025

Noyb has requested a response from Meta by May 21, but it seems unlikely that Meta will quickly cave in this fight.

In a blog post, Meta said that AI training on EU users was critical to building AI tools for Europeans that are informed by “everything from dialects and colloquialisms, to hyper-local knowledge and the distinct ways different countries use humor and sarcasm on our products.”

Meta argued that its AI training efforts in the EU are far more transparent than efforts from competitors Google and OpenAI, which, Meta noted, “have already used data from European users to train their AI models,” supposedly without taking the steps Meta has to inform users.

Also echoing a common refrain in the AI industry, another Meta blog warned that efforts to further delay Meta’s AI training in the EU could lead to “major setbacks,” pushing the EU behind rivals in the AI race.

“Without a reform and simplification of the European regulatory system, Europe threatens to fall further and further behind in the global AI race and lose ground compared to the USA and China,” Meta warned.

Noyb discredits this argument and noted that it can pursue injunctions in various jurisdictions to block Meta’s plan. The group said it’s currently evaluating options to seek injunctive relief and potentially even pursue a class action worth possibly “billions in damages” to ensure that 400 million monthly active EU users’ data rights are shielded from Meta’s perceived grab.

A Meta spokesperson reiterated to Ars that the company’s plan “follows extensive and ongoing engagement with the Irish Data Protection Commission,” while reiterating Meta’s statements in blogs that its AI training approach “reflects consensus among” EU Data Protection Authorities (DPAs).

But while Meta claims that EU regulators have greenlit its AI training plans, Noyb argues that national DPAs have “largely stayed silent on the legality of AI training without consent,” and Meta seems to have “simply moved ahead anyways.”

“This fight is essentially about whether to ask people for consent or simply take their data without it,” Schrems said, adding, “Meta’s absurd claims that stealing everyone’s personal data is necessary for AI training is laughable. Other AI providers do not use social network data—and generate even better models than Meta.”

Meta is making users who opted out of AI training opt out again, watchdog says Read More »

Judge on Meta’s AI training: “I just don’t understand how that can be fair use”

AI training, copyright, copyright infringement, fair use, leeching, LLaMA, Meta, piracy, Policy, torrenting / Beth Washington / May 3, 2025

Judge downplayed Meta’s “messed up” torrenting in lawsuit over AI training.

A judge who may be the first to rule on whether AI training data is fair use appeared skeptical Thursday at a hearing where Meta faced off with book authors over the social media company’s alleged copyright infringement.

Meta, like most AI companies, holds that training must be deemed fair use, or else the entire AI industry could face immense setbacks, wasting precious time negotiating data contracts while falling behind global rivals. Meta urged the court to rule that AI training is a transformative use that only references books to create an entirely new work that doesn’t replicate authors’ ideas or replace books in their markets.

At the hearing that followed after both sides requested summary judgment, however, Judge Vince Chhabria pushed back on Meta attorneys arguing that the company’s Llama AI models posed no threat to authors in their markets, Reuters reported.

“You have companies using copyright-protected material to create a product that is capable of producing an infinite number of competing products,” Chhabria said. “You are dramatically changing, you might even say obliterating, the market for that person’s work, and you’re saying that you don’t even have to pay a license to that person.”

Declaring, “I just don’t understand how that can be fair use,” the shrewd judge apparently stoked little response from Meta’s attorney, Kannon Shanmugam, apart from a suggestion that any alleged threat to authors’ livelihoods was “just speculation,” Wired reported.

Authors may need to sharpen their case, which Chhabria warned could be “taken away by fair use” if none of the authors suing, including Sarah Silverman, Ta-Nehisi Coates, and Richard Kadrey, can show “that the market for their actual copyrighted work is going to be dramatically affected.”

Determined to probe this key question, Chhabria pushed authors’ attorney, David Boies, to point to specific evidence of market harms that seemed noticeably missing from the record.

“It seems like you’re asking me to speculate that the market for Sarah Silverman’s memoir will be affected by the billions of things that Llama will ultimately be capable of producing,” Chhabria said. “And it’s just not obvious to me that that’s the case.”

But if authors can prove fears of market harms are real, Meta might struggle to win over Chhabria, and that could set a precedent impacting copyright cases challenging AI training on other kinds of content.

The judge repeatedly appeared to be sympathetic to authors, suggesting that Meta’s AI training may be a “highly unusual case” where even though “the copying is for a highly transformative purpose, the copying has the high likelihood of leading to the flooding of the markets for the copyrighted works.”

And when Shanmugam argued that copyright law doesn’t shield authors from “protection from competition in the marketplace of ideas,” Chhabria resisted the framing that authors weren’t potentially being robbed, Reuters reported.

“But if I’m going to steal things from the marketplace of ideas in order to develop my own ideas, that’s copyright infringement, right?” Chhabria responded.

Wired noted that he asked Meta’s lawyers, “What about the next Taylor Swift?” If AI made it easy to knock off a young singer’s sound, how could she ever compete if AI produced “a billion pop songs” in her style?

In a statement, Meta’s spokesperson reiterated the company’s defense that AI training is fair use.

“Meta has developed transformational open source AI models that are powering incredible innovation, productivity, and creativity for individuals and companies,” Meta’s spokesperson said. “Fair use of copyrighted materials is vital to this. We disagree with Plaintiffs’ assertions, and the full record tells a different story. We will continue to vigorously defend ourselves and to protect the development of GenAI for the benefit of all.”

Meta’s torrenting seems “messed up”

Some have pondered why Chhabria appeared so focused on market harms, instead of hammering Meta for admittedly illegally pirating books that it used for its AI training, which seems to be obvious copyright infringement. According to Wired, “Chhabria spoke emphatically about his belief that the big question is whether Meta’s AI tools will hurt book sales and otherwise cause the authors to lose money,” not whether Meta’s torrenting of books was illegal.

The torrenting “seems kind of messed up,” Chhabria said, but “the question, as the courts tell us over and over again, is not whether something is messed up but whether it’s copyright infringement.”

It’s possible that Chhabria dodged the question for procedural reasons. In a court filing, Meta argued that authors had moved for summary judgment on Meta’s alleged copying of their works, not on “unsubstantiated allegations that Meta distributed Plaintiffs’ works via torrent.”

In the court filing, Meta alleged that even if Chhabria agreed that the authors’ request for “summary judgment is warranted on the basis of Meta’s distribution, as well as Meta’s copying,” that the authors “lack evidence to show that Meta distributed any of their works.”

According to Meta, authors abandoned any claims that Meta’s seeding of the torrented files served to distribute works, leaving only claims about Meta’s leeching. Meta argued that the authors “admittedly lack evidence that Meta ever uploaded any of their works, or any identifiable part of those works, during the so-called ‘leeching’ phase,” relying instead on expert estimates based on how torrenting works.

It’s also possible that for Chhabria, the torrenting question seemed like an unnecessary distraction. Former Meta attorney Mark Lumley, who quit the case earlier this year, told Vanity Fair that the torrenting was “one of those things that sounds bad but actually shouldn’t matter at all in the law. Fair use is always about uses the plaintiff doesn’t approve of; that’s why there is a lawsuit.”

Lumley suggested that court cases mulling fair use at this current moment should focus on the outputs, rather than the training. Citing the ruling in a case where Google Books scanning books to share excerpts was deemed fair use, Lumley argued that “all search engines crawl the full Internet, including plenty of pirated content,” so there’s seemingly no reason to stop AI crawling.

But the Copyright Alliance, a nonprofit, non-partisan group supporting the authors in the case, in a court filing alleged that Meta, in its bid to get AI products viewed as transformative, is aiming to do the opposite. “When describing the purpose of generative AI,” Meta allegedly strives to convince the court to “isolate the ‘training’ process and ignore the output of generative AI,” because that’s seemingly the only way that Meta can convince the court that AI outputs serve “a manifestly different purpose from Plaintiffs’ books,” the Copyright Alliance argued.

“Meta’s motion ignores what comes after the initial ‘training’—most notably the generation of output that serves the same purpose of the ingested works,” the Copyright Alliance argued. And the torrenting question should matter, the group argued, because unlike in Google Books, Meta’s AI models are apparently training on pirated works, not “legitimate copies of books.”

Chhabria will not be making a snap decision in the case, planning to take his time and likely stressing not just Meta, but every AI company defending training as fair use the longer he delays. Understanding that the entire AI industry potentially has a stake in the ruling, Chhabria apparently sought to relieve some tension at the end of the hearing with a joke, Wired reported.

“I will issue a ruling later today,” Chhabria said. “Just kidding! I will take a lot longer to think about it.”

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

Judge on Meta’s AI training: “I just don’t understand how that can be fair use” Read More »

Judge calls out OpenAI’s “straw man” argument in New York Times copyright suit

AI training, chatgpt, copyright, copyright act, DMCA, new york times, openai, Policy / Kelly Newman / April 5, 2025

“Taken as true, these facts give rise to a plausible inference that defendants at a minimum had reason to investigate and uncover end-user infringement,” Stein wrote.

To Stein, the fact that OpenAI maintains an “ongoing relationship” with users by providing outputs that respond to users’ prompts also supports contributory infringement claims, despite OpenAI’s argument that ChatGPT’s “substantial noninfringing uses” are exonerative.

OpenAI defeated some claims

For OpenAI, Stein’s ruling likely disappoints, although Stein did drop some of NYT’s claims.

Likely upsetting to news publishers, that included a “free-riding” claim that ChatGPT unfairly profits off time-sensitive “hot news” items, including the NYT’s Wirecutter posts. Stein explained that news publishers failed to plausibly allege non-attribution (which is key to a free-riding claim) because, for example, ChatGPT cites the NYT when sharing information from Wirecutter posts. Those claims are pre-empted by the Copyright Act anyway, Stein wrote, granting OpenAI’s motion to dismiss.

Stein also dismissed a claim from the NYT regarding alleged removal of copyright management information (CMI), which Stein said cannot be proven simply because ChatGPT reproduces excerpts of NYT articles without CMI.

The Digital Millennium Copyright Act (DMCA) requires news publishers to show that ChatGPT’s outputs are “close to identical” to the original work, Stein said, and allowing publishers’ claims based on excerpts “would risk boundless DMCA liability”—including for any use of block quotes without CMI.

Asked for comment on the ruling, an OpenAI spokesperson declined to go into any specifics, instead repeating OpenAI’s long-held argument that AI training on copyrighted works is fair use. (Last month, OpenAI warned Donald Trump that the US would lose the AI race to China if courts ruled against that argument.)

“ChatGPT helps enhance human creativity, advance scientific discovery and medical research, and enable hundreds of millions of people to improve their daily lives,” OpenAI’s spokesperson said. “Our models empower innovation, and are trained on publicly available data and grounded in fair use.”

Judge calls out OpenAI’s “straw man” argument in New York Times copyright suit Read More »

Meta claims torrenting pirated books isn’t illegal without proof of seeding

AI copyright, AI training, copyright, leeching, Meta, online piracy, Policy, seeding, torrenting / DJ Henderson / February 21, 2025

Just because Meta admitted to torrenting a dataset of pirated books for AI training purposes, that doesn’t necessarily mean that Meta seeded the file after downloading it, the social media company claimed in a court filing this week.

Evidence instead shows that Meta “took precautions not to ‘seed’ any downloaded files,” Meta’s filing said. Seeding refers to sharing a torrented file after the download completes, and because there’s allegedly no proof of such “seeding,” Meta insisted that authors cannot prove Meta shared the pirated books with anyone during the torrenting process.

Whether or not Meta actually seeded the pirated books could make a difference in a copyright lawsuit from book authors including Richard Kadrey, Sarah Silverman, and Ta-Nehisi Coates. Authors had previously alleged that Meta unlawfully copied and distributed their works through AI outputs—an increasingly common complaint that so far has barely been litigated. But Meta’s admission to torrenting appears to add a more straightforward claim of unlawful distribution of copyrighted works through illegal torrenting, which has long been considered established case-law.

Authors have alleged that “Meta deliberately engaged in one of the largest data piracy campaigns in history to acquire text data for its LLM training datasets, torrenting and sharing dozens of terabytes of pirated data that altogether contain many millions of copyrighted works.” Separate from their copyright infringement claims opposing Meta’s AI training on pirated copies of their books, authors alleged that Meta torrenting the dataset was “independently illegal” under California’s Computer Data Access and Fraud Act (CDAFA), which allegedly “prevents the unauthorized taking of data, including copyrighted works.”

Meta, however, is hoping to convince the court that torrenting is not in and of itself illegal, but is, rather, a “widely-used protocol to download large files.” According to Meta, the decision to download the pirated books dataset from pirate libraries like LibGen and Z-Library was simply a move to access “data from a ‘well-known online repository’ that was publicly available via torrents.”

Meta claims torrenting pirated books isn’t illegal without proof of seeding Read More »