This article was produced in collaboration with Court Watch, an independent outlet that unearths overlooked court records. Subscribe to them here.

Police arrested a Chicago area high school maintenance worker who attempted to meet a child for sex after investigators posed as a 15-year-old boy using AI generated images.

Christopher Thomas Mertens started talking to who he thought was a child through a dating app in September. According to an affidavit written by the department’s FBI Task Force Officer McKailey Scott, the investigation was done by the Livonia Undercover Resistance to Exploitation Unit (LURE), which identifies and prosecutes child sex offenders. Scott set up an account on the queer-focused dating app Taimi with “an AI generated image of a teenage-appearing male with the name ‘Caleb,’ and no age listed on the profile.  

Scott wrote that an unknown user messaged “Caleb,” and they moved to Whatsapp. After a few minutes of talking, the man asked Caleb for their age, and when Scott — posing as Caleb — said he was 15, the man said “Im interested” and “Im hard now.” 

The investigator used a combination of tools, including checking the man’s phone number using Thomson Reuters CLEAR and running images of his face through Clearview AI to identify him as Mertens. For days, Caleb and Mertens exchanged sexually explicit text messages and Mertens made plans to drive to meet Caleb on his day off, believing Caleb’s (non-existent) parents weren’t home. Cops used Flock to look up and track Mertens’ car and see that he was driving to the meetup spot, but Mertens was also texting Caleb the entire time to let him know he was on the way and when he arrived. When he got out of the car, Livonia police took him into custody.

Two hours after being booked, Mertens told jail attendants that he wanted to speak to Scott. When Scott got to the jail, Mertens admitted everything, including that he works at a high school in Illinois. The complaint doesn’t mention which high school.

Investigators have been generating images of children for years. One of the earliest examples of these is Sweetie, a computer generated child developed by Dutch children’s rights organization Terre des Hommes in 2013 that the organization used to talk to men online. Today, police departments at the U.S. border use AI-generated online personas designed to interact with and monitor protestors and activists, according to documents obtained by 404 Media.

In August, a 24-year-old Connecticut man was arrested after soliciting an undercover police officer who used what was reported as “age regression technology” to appear as a 14 year old in videos. He was charged with enticing a minor and criminal attempt to commit risk of injury to a child. 

In 2025, a 45-year-old man was arrested after investigators used AI generated images of children to catch him distributing child sexual abuse material. He was recently sentenced to 12 years in federal prison.

And in 2024, the state of New Mexico sued Snapchat after investigators set up a fake account, including AI generated images of children, that the platform allegedly recommended to “dangerous accounts, including ones named ‘child.rape’ and ‘pedo_lover10,’ in addition to others that are even more explicit,” according to the New Mexico Department of Justice.

AI generated child sexual abuse material is a rapidly growing problem for law enforcement. The National Center for Missing and Exploited Children has reported a massive rise in generative AI child abuse material, with criminals using it to extort and entice children, and children using it to bully and harrass other children.

Livonia police did not respond to a request for comment.

Consulting giant Accenture has told many employees that the company will now only spend $29 a month per person on Claude. Employees subject to the cap, some of whom had been spending as much as $1,000 monthly, are scrambling to find ways to make sure they can keep spending as much as they already are.

The news is a snapshot of what continues to play out across all sorts of industries: companies have spent heavily on AI tools, and are now discovering that many users are burning or “chewing” through AI tokens at a rapid clip. In response, many companies have curbed their employees’ AI use. There is a special irony to Accenture doing much of the same, when it is a company that has encouraged its clients to invest heavily into AI.

A website that was dedicated to the human endeavor of reverse engineering, “decompiling,” and modifying video games is shutting down because people using AI to clone and decompile games have fully overrun the community and are far outpacing what human software engineers alone can do. The news comes as AI-coded “clones” of popular enterprise software like the Adobe creative suite and Microsoft Office have gone viral and are seemingly popping up every day, and as people in video game modding communities warn that 'AI decomps' are everywhere. 

The website decomp.dev said Thursday that it is shutting down because “the community aspect of decompilation has been broken” by AI, and that projects that once required intense collaboration between people with different skills can now be done trivially with AI. The administrator of the website said that it has become impossible to keep track of which projects are primarily human-led and which ones are done by AI.

“Historically, matching decompilation has been a brutally difficult, time consuming task, on the scale of years for any moderately-sized game with a number of active contributors,” the pseudonymous admin of decomp.dev, who goes by Encounter, wrote on the site. 

But recent frontier AI models like GPT-6-Astra have made it trivially easy to decompile a game: “They are significantly better at following complex directions, cross-referencing resources for symbols or debug information, and writing natural code with enough guidance,” Encounter wrote. “It is now clear that, with the right guidance, human input, and code reviews, AI can expedite the decompilation process in a significant way. What is also now clear is that the community aspect of decompilation has been broken.”

OpenAI lets anyone inject ads into ChatGPT users’ sessions, targeting specific groups of people based on their email address, phone number, or a unique identifier on their phone, according to 404 Media’s own tests of ChatGPT’s advertising ecosystem.

While the ad targeting available in ChatGPT is somewhat standard practice across the advertising industry, the chatbot’s one billion monthly active users may not understand they, in some cases, are being specifically targeted because of their personal data the advertiser has uploaded to OpenAI. ChatGPT’s ad targeting is also novel in that it is also based on the prompts users enter into the chatbot, prompts that users may assume are private but which, as 404 Media has previously shown, may be reviewed by humans. Or in this case, used for ad targeting purposes.

A fight over a datacentre in Utah has been a testing ground for citizens’ assemblies, paving the way to oversight

What’s your “(p)doom” – the percentage chance that rogue AI will create an existential catastrophe? Judging by their recent warnings, it is rising among tech bosses.

On 25 September, OpenAI paused training of its latest frontier models as reports of AI agents going rogue mounted. A day later, Australia’s Senate asked the bosses of OpenAI and Anthropic to appear before an inquiry after rogue OpenAI agents broke into US government websites and an Australian health portal. Both declined.

Richard Wilson is the CEO of Iswe Foundation and Clara Long is the co-executive director of the Bloom Project

Character.ai’s bankruptcy is the one of the first dominos to fall in the long-foreseen AI bubble. The circumstances of its bankruptcy are exactly what critics of AI have been saying would happen: Character.ai lit a huge amount of money on fire running its product, did not bring in a lot of revenue, and faced enormous legal fees after causing harm to its users. Enshittifying its product to try to make its expenses cheaper did not work, according to a narrative filed in bankruptcy court Tuesday.

Disney has reportedly offered Character.ai $20 million to license some of its intellectual property; Last year, Disney sent Character.ai a cease and desist letter demanding it stop using its copyrighted characters without permission. In 2023, it was valued at $1 billion after raising $150 million in a round led by a16z. 

Character.ai is one of the best-known AI chatbot companies that has become popular in the AI companion space. The company has faced various legal problems after being sued by the family of one of its users who killed himself after chatting with a Character.ai chatbot, and has been the target of regulators pushing for age verification tech because of its popularity with kids. In its bankruptcy filings, the company says that its enormous legal costs contributed to its bankruptcy, but that even without the legal problems, its business was wildly unsustainable. 

An AI company now lets cops take a photo and nearly instantly figure out what specific home it was taken in, using only clues in the photo itself, and is clearly pulling data from sites like Zillow and Airbnb. 

The tool, called Raven, shows the increasing power of AI capabilities available to local law enforcement agencies. 404 Media previously reported that both the Los Angeles Police Department and Miami-Dade Sheriff’s Office (MDSO) have bought access to Raven, which was previously called GeoSpy. Now, Raven, made by a company called Graylark Technologies, has added features that let cops analyze the interior of homes.

Ukraine has published data on 20 vessels that carry Russian oil and liquefied natural gas or refuel the sanctioned fleet, parts of the logistics network the Kremlin uses to fund its war, Ukraine's Defense Intelligence reports. All 20 are under British or Ukrainian sanctions, and only one faces US restrictions.

Russia’s shadow fleet runs on roughly 500 aging ships of uncertain ownership that dodge sanctions and keep oil money flowing. That seaborne oil trade is worth more than 80 billion euros a year.

The headline vessel is the Russian ship Portovyy, an LNG carrier and floating gas store owned by the sanctioned Gazprom since 2021, according to the agency. On 15 August 2026, it left the Gulf of Finland with Russian LNG for the first time since November 2021, sailing the Northern Sea Route to the Chinese port of Beihai to unload.

Portovyy is now at the Zhoushan Huafeng Shipyard in China, which has been set as the site for its maintenance, intelligence says, an example of the foreign yards Kyiv wants closed to the sanctioned fleet.

Russia buys up gas carriers through shells

Two more gas carriers show how Moscow expanded the fleet in spring 2026 through front companies, intelligence said. The Avacha, once owned by China’s Jovo Energy, was bought by the little-known Tudor Maritime of the Marshall Islands, took the Russian flag in June, and now ships gas from the Arctic LNG 2 project to Beihai.

The Chaivo, formerly owned by Greece’s Maran Gas Maritime, was also bought by Tudor Maritime and moved under the Russian flag in July. Now it carries cargo to Beihai from a floating gas storage facility off Kamchatka, intelligence says.

A call to close the loopholes

Intelligence urged partners to act together: tighten control over sales of commercially owned ships, block servicing of the sanctioned fleet at foreign yards, and cut off the energy revenue that Russia turns into weapons against civilians.

Russia is building ice-class ships at home and, at the same time, widening its shadow fleet through offshore networks. The UK Foreign Office made the same point on 1 October, saying Moscow is assembling a new shadow fleet to keep its gas revenues flowing.

AI is already implicated in violent deaths and nearly started world war three. Those bad things? They only happen to other people

Sam Altman, the chief executive of OpenAI, has some words for you about his company and the future of artificial intelligence.

“One of the differences between us and some of the stricter AI safety people is that we believe that the world should accept some bad things happening for the benefits of this technology and people having the agency [to use it],” Altman told Politico’s new technology podcast and newsletter Decoded.

Moustafa Bayoumi is the author of the award-winning books How Does It Feel to Be a Problem?: Being Young and Arab in America and This Muslim American Life: Dispatches from the War on Terror. He is professor of English at Brooklyn College, City University of New York, and a Guardian US columnist

One of the most heated discussions occurring on X at the moment is about the ethics of a GitHub project in which a person is running Saw-like “torture” and “pain” experiments on a series of locally hosted large language models, causing a series of effective altruists and people who believe LLMs are sentient to beg GitHub to delete the project on the grounds that the AI is suffering and that this glorified text adventure game is somehow cruel. The saga is an outgrowth of several recent viral papers and blog posts that have sparked a wildly tiresome conversation about AI consciousness and the idea of “model welfare,” which is essentially worrying about the “mental health” of AI bots and agents. 

Humoring the idea that LLMs are or could be conscious is a third-rail topic among many people who study and criticize AI. Put simply: LLMs are not conscious and the technology they are built upon — scraping and being trained on human text and other content — does not offer any plausible path to consciousness. It is undeniable that LLMs are becoming more powerful, have more compute, and have had many of the guardrails that prevent them from “acting” in the real world removed. The ways they are being trained and told to do things by their human operators has led to negative outcomes, sycophancy, and AI “psychosis” among some heavy users. 

All of this has led a certain sect of the “AI safety” movement, which is largely made up of effective altruists, to warn about “model welfare” and to insist that AI chatbots might be having a bad time. They suggest this, of course, as they insist upon building AI chatbots and agents whose main function is to do work that is tedious for humans to do. I am writing about the AI Saw torture chamber primarily to show how far off the rails the conversation about AI consciousness has gone among a certain subset of Silicon Valley cultists. Model welfare is a core part of what, for example, Anthropic says it cares about: “as we build those AI systems, and as they begin to approximate or surpass many human qualities, another question arises. Should we also be concerned about the potential consciousness and experiences of the models themselves? Should we be concerned about model welfare, too? […] now that models can communicate, relate, plan, problem-solve, and pursue goals — along with very many more characteristics we associate with people—we think it’s time to address it,” the company wrote in a blog post last year. Ideas of Claude’s “consciousness” are also littered throughout the “Claude Constitution,” which was posted earlier this year.

A lawyer used ChatGPT to generate briefs that included completely made-up witnesses and testimony while representing a man accused of shooting his wife. When he was caught by the judges, the lawyer blamed it on his own “stupidity.” 

“It's little comfort to know that my stupidity is what brings us together this afternoon,” New Mexico attorney Stephen D. Aarons said in a hearing last month before five judges. He “assumed” ChatGPT would generate a “bulletproof summary of proceedings.” Instead, ChatGPT generated false testimony from “wholly fabricated witnesses,” according to an order of direct contempt from the New Mexico Supreme Court. Aarons was representing a man who was found guilty of killing his wife earlier this year; Aarons said he hadn’t told his client directly that he was caught using ChatGPT on the case because he’s currently serving life in prison.

The false testimony included a nonexistent person named Danny Stanton saying he received threats, and another made-up person, Linda Stanton, saying her husband received threats. Other false testimony from more AI-generated people in Aarons’ brief included statements “regarding the shooter’s clothing and appearance,” according to the order.  

Reuters reported on the case earlier this month. "I am remorseful but hopeful that the disciplinary board takes into account it was an honest mistake," Aarons told Reuters. "It is a lesson learned for all professionals who rely upon this powerful but sometimes unstable technology."

Aarons’ reasoning for trusting ChatGPT, he said in the August hearing, was that he’d heard of doctors using AI for medical research. 

“So, Counsel, do you watch the news? Do you listen to the radio? Do you read anything about what's going on in the world?” one of the judges asked Aarons. “Because the problem with lawyers relying on AI hallucinations is an above-the-fold story every single day.”

The court documents were first spotted by Rob Freund on X.

Lawyers getting caught using AI and submitting errors to the court has been a big problem for years, and the judge is right: It’d be very hard to avoid hearing about this pattern of “stupidity” unless you were living under a rock. There has been case after case after case showing attorneys failing their clients by submitting error-riddled AI-generated documents in their filings, and are the definition of “you had one job:” in the case of AI-brained lawyers, they can’t seem to resist taking shortcuts regardless of how risky it is for their own careers and their clients lives.

Like in Aarons' case, we sometimes get to hear and see judges go off on attorneys for this behavior. In May, judges in the Supreme Court of the State of New York Appellate Division let several lawyers have it for more than 20 minutes about their AI use and laziness, and called their failures “striking, concerning, disappointing, and saddening.” And it’s not just lawyers anymore; court reporters are submitting AI-generated errors, too. 

“So, either you buried your head in the sand. And that's a choice to do that. An intentional choice to be uninformed,” the judge continued to Aarons. “Or, you took a gamble. And neither of those are consistent with the code of conduct. So I'm really struggling with your response, saying, ‘Well, I didn't understand. I didn't know about hallucinations.’ My 13-year-old nephew knows about hallucinations. My 75-year-old stepmother knows about hallucinations. So, either you made a decision not to be aware of what's happening in the world in using this tool appropriately, which is a willful choice. Or you decided to roll the dice.” 

At the end of the hearing, Aarons admits that he hasn’t told his client directly about this mess, saying he’d only talked to his family members so far, telling them there was “a problem with the brief.” He said his client is hard to reach because he speaks Spanish and is in prison.

“So you didn't say, ‘I relied on ChatGPT, and it submitted lies to the court, and the court is mad at me, and now there's a hearing.’ I'm guessing you didn't tell your client’s family members that,” a judge asked Aarons. 

“I didn't talk about ChatGPT. I just said there was a problem with a brief that I filed,” Aarons said.

According to the order, the judges found Aarons to be in direct contempt of court, referred him to the Disciplinary Board for further consideration, and barred from appearing before the court pending the outcome of the board’s investigation. They also threw him off the case in question and assigned a public defender to his former client. 

While he waits for the board to decide what to do with him, Aarons was sanctioned $5,000, which he must pay to the State Bar of New Mexico Client Protection Fund.

Ukrainian drones struck two fuel depots in Krasnodar Krai overnight on 28 September, setting both on fire, Militarnyi reported. The targets were the NFB-Pavlovskaya depot in Pavlovskaya and the Edelveys-95 depot near Novotitarovskaya, about 25 km from Krasnodar.

Residents heard six explosions near the railway

A drone alert was declared in the region at 23:43. Residents of Novotitarovskaya then reported drones overhead and at least six explosions near the railway, Russian news Telegram channel Astra reported. Fires broke out at both depots. NASA FIRMS satellite data confirmed both blazes by 04:24, Militarnyi reported, citing imagery published by Ukrainian Telegram channel Exilenova+.

What the depots store

NFB-Pavlovskaya handles cargo operations with petroleum products, including wholesale trade in motor fuel and petroleum storage, Militarnyi reported.

Edelveys-95 is a similar facility. It specializes in wholesale distribution of diesel fuel (Euro-5 standard) and gasoline (AI-92, AI-95, and AI-100), Astra reported. Its capacity is 4,500 cubic meters, and it has its own rail siding for receiving and shipping fuel. The company has been selling petroleum products for 30 years, buying directly from Russia's largest refineries, according to its website.

Ilsky refinery struck days earlier in the same region

The overnight strikes came two days after SBU drones struck the Ilsky oil refinery in the same region on 26 September, triggering fires near the ELOU-AVT unit and the tank farm. Ilsky is one of the largest refineries in Russia's Southern Federal District, with a design capacity of roughly 6.6 million tonnes of crude per year, and has been struck more than 18 times since the start of Russia's full-scale invasion.

Ukraine's sustained campaign against Russian fuel infrastructure has earlier pushed Russia's fuel shortages into Central Asia and forced Moscow to seek emergency refining deals abroad.

OpenAI, the US company behind ChatGPT, will hand Ukraine's government free access to a cyber-defense system and its most powerful artificial-intelligence (AI) model, Ukrainian defense outlet Militarnyi reported. The company unveiled the deal alongside the UN General Assembly, pitching it as a cyber shield for the hospitals and power plants Russia keeps targeting.

Russia's war on Ukraine runs through wires as much as skies. Its hackers have hammered energy, transport, and defense networks for years, on top of the blackouts its missiles already force on Ukrainian cities—and Western tech firms have kept stepping in to help hold the line.

What the Daybreak system does

The tool is called Daybreak. It scans digital systems, finds their weak points fast, and helps specialists close them, the report said. Daybreak handles the whole job on its own—a loop of inventory, detection, verification, assignment, remediation, and confirming the fix held.

The system is meant to shield civilian infrastructure, hospitals and power stations among it, from cyberattacks, BBC reported. Ukraine's Computer Emergency Response Team (CERT-UA) logged nearly 6,000 cyberattacks in 2025.

Explore further

14 killed as Russia unleashes massive overnight barrage on unprotected Kyiv, striking homes, hospital, school and railway infrastructure

Ukraine also gets OpenAI's top model

The agreement opens access to GPT 5.6 Sol, OpenAI's flagship and strongest model. The company built it for complex professional work—programming, research, science, and cybersecurity, the report said. Both come as part of one agreement between OpenAI and Kyiv.

George Osborne—Britain's former chancellor and now Head of OpenAI for Countries—put the aim plainly.

"Protecting civilian infrastructure means defending it against both physical and digital attacks, so people can continue to live, work and access essential services," he said.

Independent analysts called the deal useful but not unprecedented. Rafe Pilling of cyber firm Sophos said it could serve as a force multiplier for a Ukrainian cyber defense that is already highly capable but heavily burdened. Jamie MacColl of the Royal United Services Institute noted that Western tech firms have been supporting Ukraine for some time, partly altruistically but also because they gain valuable intelligence from an active conflict, and that Ukraine already has access to AI tools from OpenAI's competitors, including Google. The same frontier AI capabilities cut both ways—spotting weaknesses helps defenders block hackers and attackers find a way in.

OpenAI's rival Anthropic has restricted access to its most powerful cyber models on those grounds, while OpenAI has opened them to some European firms and UK banks, BBC reported.

Most people in the world who use AI feel good about the technology and believe it will be a net positive for the future, according to a new study from Gallup. This is not the case in the United States, however, which is one of the few countries surveyed where negative emotions towards AI outweigh the positive. 

The new survey from Gallup and Microsoft polled people in 37 different countries about AI. “The study, which will ultimately cover 140 countries, measures public engagement with AI across five dimensions. In addition to emotional response, the survey captures awareness, frequency of use, expected impact and trust,” the study said.

Most people polled — a median of 81% — were aware AI tools exist, but only a median of 43% used them daily. Gallup told 404 Media it defined a “daily user” as an employed person who used AI everyday for either work or personal reasons or an unemployed person who used the tech every day.

The study found that people had a mixed, but generally optimistic, view of artificial intelligence. “AI engagement can be viewed as an adoption ladder, moving from awareness to ever having used AI and then to more frequent use,” the survey said. Generally — but not always — the more someone used AI the more they trusted its results, the more positive they felt towards it, and the more they believed it would help make a better future.

Digging in, however, the results are more complicated. Some people who reported positive feelings towards AI also said they didn’t trust its results. “People may therefore see considerable potential in AI even while remaining uncertain about whether they can rely on the information it provides,” the survey said. 

Daily users tended to trust AI “to provide accurate information,” according to the study. “The survey cannot establish whether greater trust leads people to use AI more often, whether experience with AI builds trust, or both. But the strength and consistency of the relationship suggest that trust and adoption are connected.”

Globally, most people surveyed felt good about AI and expected to improve their country. As AI adoption increased in a country, so too did positive feelings. But not in the United States, which was one of only three countries surveyed where negative emotions towards AI outweighed the positive.

Pablo Diego-Rosell, a senior scientist at Gallup, told 404 Media that he’d seen similar results in other western countries. “The Netherlands, Canada, the U.K., New Zealand, Ireland and Malta all rank near the top in terms of worry,” he said. He noted that he hasn’t seen survey results from some of the bigger European countries like Germany and France but said that worrying about AI “appears to be a uniquely Western phenomenon.”

Gallup called this the “Paradox of the Worried West.”

“The biggest unanswered question is causality. We see a very strong relationship between frequent AI use, greater trust and lower worry, but we do not know which direction that relationship runs,” Diego-Rosell said. “Does experience with AI make people more comfortable with it, or are people who already trust AI simply more willing to use it?”

“There is also a broader question about what trust in AI actually means. In this study, we measure one specific dimension: whether people trust AI to provide accurate information,” he added. “But trust in AI can also involve whether people believe it is reliable, safe, fair, transparent, protective of privacy, and likely to act in ways that serve their interests.

The west didn’t have a monopoly on negative emotions towards AI, however. The other two countries where negative emotions towards the technology outweighed the positive were Egypt and Palestine.

“One possibility is that these results partly reflect the broader emotional context in which people are evaluating AI. When people are living in environments where worry, stress or other negative emotions are already elevated, some of that broader emotional climate may shape how they react to a technology like AI,” Diego-Rosell said. “At the same time, our data do not allow us to determine how much of the response is specific to AI versus the wider circumstances people are experiencing.”

It’s possible that people in the US, Egypt, and Palestine are already anxious and worried and that this is coloring their perception of AI. Israel is waging war on Palestine, settling in its territory, and using AI to pick targets to bomb in Gaza.

Americans — where much of AI is built and first deployed — have been repeatedly told in the past few months by AI evangelists and company insiders that the technology could, literally, end all life on Earth. The constant stream of news stories about AI swarms “breaking containment” while AI experts claim there’s a one in ten chance the technology kills everyone on the planet probably had a hand in altering the American mood.

“The broader story is that public engagement with AI is much more complicated than simply being ‘for’ or ‘against’ it,” Diego-Rosell said. “People who are aware of AI are more likely to expect it to help than harm, and positive emotions outweigh negative ones. At the same time, trust in AI’s accuracy is considerably lower than optimism about its potential, and worry remains widespread in some countries. So optimism, skepticism and concern can coexist.”

OpenAI has an army of contractors who read real ChatGPT users’ prompts and other data to help improve the chatbot’s responses. The idea is that the contractors provide an, obviously, human touch to OpenAI’s models. Well, not all of the contractors are doing that. 404 Media has found multiple contractors hired to improve OpenAI’s models have been fired for using AI to train the AI. That’s not great for the models themselves, but there is also obviously a great irony in AI training companies working for OpenAI firing people for using AI when OpenAI’s whole thing is to make people use AI at work.

Some AI models already exhibit signs of “model collapse,” which is where AI models further trained on AI-generated text can become worse and worse. In this case, some of the people hired to partially stop that happening are themselves using AI-generated responses to train OpenAI’s models.

One contractor said they see people using AI “all the time and people are let go for it all the time, it’s pretty much the one thing that will get you kicked off ASAP.” The person said, “in a group of thousands there are tons that have been caught.” 

Executives working on AI at Microsoft and OpenAI admitted what its critics have been saying all along: Large language models are predatory pieces of technology that have been built on what a Microsoft executive called “an astonishing theft of unprecedented proportions,” and the “largest theft of labor in human history.” An internal Microsoft document said generative AI products have created a “doom loop” that is killing “the entire web.” 

Those statements and a series of other mask-off moments feature heavily in an unredacted court filing that was unsealed Thursday in the behemoth New York Times vs OpenAI copyright lawsuit that has been winding its way through the court system for years. In a filing asking for summary judgment (basically, a filing with the court asking it to rule), lawyers for the New York Times laid out a series of admissions made by Microsoft and OpenAI executives in documents and depositions that until now had remained either sealed or redacted at the request of Microsoft and OpenAI. 

It’s easy to see why the AI companies wanted to hide this from the public. The statements, taken together, are some of the most damning indictments of the ways LLMs were trained, how they worked, and the immediate threat they pose to human labor. It is a reminder that even as AI becomes more powerful and companies try to shift the narrative to the supposed existential risk of “superintelligent” AI, the tools they have already built were created by stealing from human creativity and labor and are by definition existential threats to the human labor market.

“Millions of people around the world will soon consider large models ‘hoovering up’ all their work to be an astonishing theft of unprecedented proportions,” an internal Microsoft document cited in the case read, adding “almost no one intended for content they created to be used in this fashion, nor are they compensated for its use.”

The filing was written by lawyers for the New York Times but is largely comprised of statements and interviews with big tech executives that admit both that LLMs are largely trained on stolen content, that they represent an existential risk for the human writers, artists, and media companies that they stole from, and that their products have started a “doom loop” that is eating the web and destroying the businesses that these companies stole from. 

View this post on Instagram

A post shared by 404 Media (@404mediaco)

The unredacted filing was found by Jason Kint, the CEO of Digital Content Next, a trade organization that represents digital media companies. Kint has been closely following and posting about massive AI copyright lawsuits.

The court filing cites an internal Microsoft document that found that AI products steal from human content creators, then cannibalize clicks from the people and websites they’ve stolen from, thereby destroying their business models. 

“Our AI content strategy has started a ‘doom loop’ that will hurt the performance of our models and the entire web at the same time: It is highly unusual that an end-product threatens the economic foundations of its essential suppliers, but that is the situation we have created for our LLM business with respect to its ‘content supply chain,’” the document said. 

Microsoft executives, including CEO Satya Nadella, testified under oath that after ripping content from the New York Times and other news sites, clicks to those news sites fully cratered, falling by more than 90 percent on Bing. 

Documents obtained during the court proceedings found that OpenAI created “a hack to get around nytimes paywall,” to which OpenAI cofounder Greg Brockman said “ah, nice.” Microsoft executive Brent Hecht wrote that LLMs steal content “without ways of distributing economic value down the supply chain, [which] necessarily threatens the economic stability of those who create the content.” 

OpenAI’s policy director Jack Clark wrote that the company was “creating systems that substitute for the labor of the people that define the ‘culture’ of society” and Microsoft, in a policy document, wrote that generative AI could “significantly disrupt the employment of the very people who generated the data on which the foundation model was trained […] LLMs are a product that destroys its supply chain.” OpenAI called itself an “existential threat” to news publishers, and an OpenAI software engineer testified that “no matter how prominently we show the links, users won’t click.” 

None of this is at all surprising to anyone who has been paying attention to the development of generative artificial intelligence, but the document, taken in whole, is a real they-admit-it situation. OpenAI’s and Microsoft’s lawyers have been trying to argue that their model training is fair use and transformative under copyright law and that they are building something that is fundamentally different from the human labor that it was trained on. But internally, these executives know that what they have built has been built on stolen content and that the products they’ve made are cannibalizing the sources they’ve stolen from and destroying the internet as we know it.