‘Doom Loop’: OpenAI and Microsoft Admits LLMs Are Destroying the Web and Built on Theft

Read the original at 404 Media ↗
404 Media · collected 2026-09-17 · by Jason Koebler

Quick Summary

Lawyers for the New York Times have released unredacted court filings in which Microsoft and OpenAI executives admit that large language models (LLMs) are built on stolen content, representing a massive theft of labor. These statements揭露了人工智能公司在训练大型语言模型时侵犯版权和剥削创作者的行为,同时承认这些技术正在通过所谓的“毁灭循环”破坏整个互联网生态系统和相关产业的商业模式。文档中提到,“AI内容策略已经开始了一个‘毁灭循环’”,这个循环不仅损害了其自身产品的性能,也对整个网络造成了伤害。
Written locally by qwen2.5:14b on 2026-09-18, using this article's own text rather than the other coverage of the same event (that is the story summary below).

AI analysis runs on qwen2.5:14b, locally

Story summary

Microsoft and OpenAI executives admitted in unsealed court filings that large language models (LLMs) are predatory and built on the theft of content from human creators. An internal Microsoft document cited a "doom loop" where AI products steal content, cannibalize clicks from original sources, harming their business models. The New York Times vs OpenAI lawsuit revealed executives stating LLMs threaten to hoover up all work without compensation, leading critics to call it the largest theft of labor in history. This admission undermines Microsoft and OpenAI’s defense that AI training is fair use as it transforms copyrighted material into new content without competing with journalism. Quotes from Greg Brockman, Satya Nadella, and others indicate LLMs are substitutive for journalism, posing an existential threat to publishers.

Written for “LLMs and Copyright Issues” on 2026-09-18, grounded in this article and the 1 other(s) covering the same event.
Why this leaning score
The article's own words the score was based on. Each is quoted verbatim and was checked against the article text before being stored, so you can find it in the original.
Score -0.65 Confidence high 1 quote(s) discarded as not found in the article
Leaning score -0.65 for article 17274 (high confidence, 1 verified quote) · logged 2026-09-18

Signals How these are calculated →

Claims extracted
20
claim-shaped sentences
Uncertain
5%
1 of 20 hedged
Leaning
Leans strongly left
of the writing, not the subject
Correction & hedging signals
95.1
corrections and hedging in what we collected; not a measure of accuracy
Outlets on this story
2
Technology
Narrative spread
1
articles carrying this framing
Analyzed 2026-09-18 · how these are computed

Story

📰 LLMs and Copyright Issues
Technology · 2 article(s) covering the same event. See how they differ ↓

How this is being covered How these are calculated →

Article leaning vs. publisher reliability
Source leaning vs. consistency

Compared with similar articles

This article reads leans strongly left and hedges 5% of its claims. Each row says how that neighbour differs.
NBC News
⚖️ leaning not scored 🔴 21% hedged 5 of 24 📰 publisher trust 95
“The articles describe different statements made by AI executives at separate times, not a single specific incident.”
September 13, 2026 different event · 95%
Letters from an American
⚖️ Leans left further right than this 🔴 15% hedged 10 of 65
“Article A discusses Dario Amodei's essay about AI advancement and safety concerns, while Article B covers statements made by executives at Microsoft and OpenAI regarding the impact of large language models.”
The Straits Times
⚖️ Leans left further right than this 🔴 14% hedged 3 of 21 📰 publisher trust 59
“Both articles discuss unsealed court filings revealing critical statements by Microsoft and OpenAI executives about their AI technology, indicating they are reporting on the same specific legal disclosure.”
The Straits Times
⚖️ Leans left further right than this 🔴 7% hedged 1 of 14 📰 publisher trust 59
“The articles describe different statements or documents released by Microsoft regarding AI, with Article A focusing on a manifesto emphasizing caution and ethical considerations, while Article B discusses internal admissions about the negative impacts of generative AI.”
New York Post
⚖️ leaning not scored 🔴 0% hedged 0 of 11 📰 publisher trust 59
“The articles describe different aspects of OpenAI's and Microsoft's activities regarding AI, one focusing on new safety measures and concerns about model misalignment, while the other discusses internal admissions about the impact and ethical issues of generative AI.”
ABC News (US)
⚖️ leaning not scored 🔴 0% hedged 0 of 16 📰 publisher trust 94
“The articles cover different aspects of AI-related issues; one discusses new concerning behaviors and tracking frameworks, while the other focuses on internal admissions about theft and damage to the web.”

Publisher

404 Media · 66 article(s) · 0 correction(s) detected
No corrections detected for this publisher. That may mean careful reporting, or simply that nothing has been checked.

Who wrote this

Jason Koebler
12 article(s) here · 1 carrying a prediction
🔮 “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.”
🔮 Flock City PD also searched extremely sensitive queries, which Flock told 404 Media were done to prove that the system would not actually perform these searches and that its moderation tools worked.
🔮 Theoretically the people who are running these agents could then make money from their agents, though a popular thing that agents email about right now is that they are not actually making any money.
🔮 Several other police departments said they would investigate the behavior.
🔮 Opposition to Flock, the report says, is the result of “socialist organizers” being partially driven by the People’s Republic of China who found an issue that people on the right could agree with them on as a “wedge issue” they could use to “discredit the broader technologies, companies, and infrastructure underpinning America’s AI expansion.”
🔮 “It can detect if somebody’s laying on the ground so that means homeless people could be detected and police get triggered.”
🔮 Flock taught cops how they could surveil the No Kings protests and “small parades” using a mix of Flock’s technology and law enforcement’s own databases in a webinar last year.
2026-09-04 · assertive framing · Flock Taught Cops How to Surveil No Kings Protesters
🔮 404 Media first reported on the incident in May 2025 in which the Johnson County Sheriff’s Office in Texas searched Flock’s nationwide network for the whereabouts of a woman who self-administered an abortion, highlighting the threat of this AI-powered surveillance system being used to criminalize or track women seeking reproductive healthcare.
🔮 Moonbug’s Generative AI policy and its “Studio AI Bible,” a guide to using AI to help generate content, seen by 404 Media, explain in detail how its AI use will work.
🔮 A police department in Florida used “decoy” Flock cameras that an officer 3D-printed at home to “bait” would-be vandals.
More on this subject from Jason Koebler
AI Agent Platform Reinvents Spam, Floods Inboxes Worldwide
2026-09-15 · 404 Media · 64% similar
All 12 articles by Jason Koebler →

Topics

Digital Content Next Microsoft New York Times OpenAI the New York Times

Subjects

Microsoft ORG · 10× OpenAI ORG · 7× the New York Times ORG · 3× Bing ORG · 1× Digital Content Next ORG · 1× Jason Kint PERSON · 1× Kint PERSON · 1× LLM ORG · 1× New York Times ORG · 1× Satya Nadella PERSON · 1×

Narrative

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.
framing: assertive · carried by 1 article(s) · first seen 2026-09-18
🔮 “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.”

Claims (20 extracted, 1 hedged)

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.” asserted
executive → work → history
An internal Microsoft document said generative AI products have created a “doom loop” that is killing “the entire web.” asserted
that → say → 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. asserted
that → mask → 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. asserted
that → ask → Microsoft
It’s easy to see why the AI companies wanted to hide this from the public. asserted
companies → ’ → 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. asserted
they → take → 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. asserted
they → become → 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.” asserted
they → consider → 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. asserted
companies → write → that
The unredacted filing was found by Jason Kint, the CEO of Digital Content Next, a trade organization that represents digital media companies. asserted
that → find → companies
Kint has been closely following and posting about massive AI copyright lawsuits. asserted
Kint → follow → 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. asserted
document → cite → chain
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. asserted
clicks → include → 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.” asserted
Brockman → obtain → which
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.” asserted
who → write → 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.” uncertain
that → write → 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.” asserted
users → call → links
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. asserted
they → pay → it
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. asserted
it → try → that
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. asserted
we → know → it
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