By Global Technology Desk
Published: September 2026
Main Facts
Newly unsealed court documents from the landmark copyright lawsuit between The New York Times, OpenAI, and Microsoft have brought to light internal communications that paint a damning picture of the tech giants’ approach to web scraping and copyright. The filings—brought to light via recent court disclosures analyzed extensively by outlets like Ars Technica and TechCrunch—reveal that high-ranking executives and lead researchers at both companies were acutely aware that their artificial intelligence models relied on ethically and legally dubious methods to acquire vast quantities of copyrighted journalistic and creative labor.
Most explosive among the revelations is a statement from Brent Hecht, Microsoft’s director of applied science. In an internal memorandum drafted in January 2023, Hecht characterized large-scale AI web scraping as "the largest theft of labor in human history." Furthermore, internal research data exposes the devastating impact of AI-driven answer engines on web publishers, showing steep declines in traffic ranging from 51% to upwards of 94% for prominent digital publishers, including The New York Times and Ziff Davis properties like IGN and Eurogamer.
The unsealed legal documents form a crucial part of The New York Times’ ongoing motion for sanctions against OpenAI, filed in December 2023. The newspaper initially alleged that OpenAI and its primary financial and infrastructural backer, Microsoft, misappropriated "lurid amounts" of copyrighted journalistic content to train large language models (LLMs) without permission or compensation. These new revelations strip away the corporate veneer of defensive legal arguments—such as fair use—revealing an internal acknowledgment that the current generative AI business model inherently cannibalizes its own "content supply chain."
Chronology of the Conflict
To fully understand the weight of these unsealed documents, it is necessary to retrace the timeline of the partnership, the development of generative AI tools, and the legal confrontation that followed.
Late 2022 to Early 2023: The Boom and the Internal Warnings
Following the public launch of OpenAI’s ChatGPT in November 2022, the race to integrate generative intelligence into search and productivity tools accelerated exponentially. Behind closed doors, however, technical leads were beginning to sound the alarm.
In January 2023, Microsoft’s Brent Hecht authored a critical internal memorandum. In it, Hecht warned that generative features like Copilot would simultaneously degrade the quality of Microsoft’s models and cripple the broader web ecosystem. Around the same time, technical discussions at OpenAI involved exploring methods to bypass digital barriers. Notably, internal chat logs show an OpenAI researcher, Nick Ryder, informing OpenAI President Greg Brockman about a "hack to get around [the] nytimes paywall" to facilitate data harvesting. Brockman’s response, according to the filing, was succinct: "ah nice."
December 2023: The New York Times Strikes Back
Frustrated by failed licensing negotiations and the rapid deployment of models trained on their archives, The New York Times filed a blockbuster copyright infringement lawsuit against OpenAI and Microsoft in the U.S. District Court for the Southern District of New York. The lawsuit did not name specific monetary damages initially, but demanded the destruction of models and checkpoints trained on Times journalism, arguing that the defendants sought to "free-ride on the Times’s massive investment in its journalism."
Early 2026: Depositions and Legal Maneuvers
As discovery progressed through 2024 and 2025, testimonies under oath began to complicate the corporate narratives presented by tech leadership. Earlier this year, Microsoft CEO Satya Nadella offered a deposition in which he admitted that had he known OpenAI was utilizing paywalled information for model training, he would have explicitly required OpenAI to retrain its models from scratch.
September 2026: The Unsealing
A federal court unsealed a massive cache of internal slides, memos, and chat logs. The release exposed the stark dichotomy between public legal defenses—which lean heavily on transformative fair use doctrines—and private corporate anxieties regarding labor theft, paywall circumvention, and the systematic destruction of publisher traffic.
Supporting Data: The Anatomy of the "Doom Loop"
The core economic grievance of modern digital publishing is laid bare in the newly unsealed data compiled by Microsoft’s own internal researchers. For decades, the implicit social contract of the internet was simple: search engines directed users to publisher websites via hyperlinks, generating ad revenue and subscription opportunities in exchange for indexing content. Generative AI fundamentally breaks this loop by providing direct answers extracted from scraped text, eliminating the need for users to click through to the source.
According to Microsoft’s internal metrics cited in the court filings:
- The New York Times: Click-through rates (CTRs) originating from Microsoft’s AI-enhanced search features plummeted by 87% to 93% compared to traditional, link-based Bing searches.
- Ziff Davis Network (IGN, Eurogamer, etc.): Traffic generation suffered similarly catastrophic blows, with click-through rates dropping between 51% and 94%.
Hecht memorably dubbed this phenomenon a "doom loop." In his presentation slides, he elaborated on the structural danger:
"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.’"
Put simply, Microsoft and OpenAI engineered a system that consumes high-value journalistic and creative labor to train models, deploys those models to answer user queries directly, and starves the original creators of the revenue required to sustain that labor in the first place. Without intervention, this dynamic threatens to dry up the very web of human knowledge upon which state-of-the-art LLMs depend for periodic updates and fine-tuning.
Official Responses and Legal Posture
The legal fallout from these disclosures has intensified pressure on both companies, forcing a delicate balancing act between public relations strategies and courtroom defenses.
OpenAI’s Defense and Leadership Complicity
OpenAI has consistently maintained that training AI models on publicly available internet data constitutes protected transformative use under copyright law, akin to human learning or data analysis. However, the revelation that senior leadership—including President Greg Brockman—was aware of, and seemingly encouraged, techniques to bypass paywalls like The New York Times’ complicates this argument. Under U.S. copyright law, willful circumvention of technological protection measures (TPMs) under the Digital Millennium Copyright Act (DMCA) carries separate, severe legal liabilities independent of standard copyright infringement.
Microsoft’s Internal Friction
The unsealed documents reveal a distinct cultural and strategic divide between Microsoft’s commercial imperatives and the warnings issued by its scientific personnel. While executives like Satya Nadella positioned Microsoft as a responsible enterprise partner adopting cutting-edge safety frameworks, applied scientists like Brent Hecht understood the existential threat posed to the information ecosystem. Nadella’s deposition testimony—stating he would have forced a total retraining of OpenAI models had he known about paywall violations—suggests potential friction or a lack of visibility into OpenAI’s data acquisition pipelines during the peak of the multi-billion-dollar partnership.
Broader Implications for the Tech and Publishing Industries
The unsealing of these documents transcends a single legal dispute between a historic newspaper and Silicon Valley giants; it represents a watershed moment for the entire digital economy.
1. The Future of Fair Use in the Age of Generative AI
For years, technology companies operated under a de facto "permissionless innovation" doctrine, assuming that text accessible via public internet protocols was fair game for machine learning. The admission by Microsoft’s lead scientists that this practice constitutes "the largest theft of labor in human history" provides plaintiffs with powerful rhetorical and evidentiary ammunition. Judges and lawmakers examining copyright reform will likely scrutinize whether scraping proprietary, paywalled data to build competing commercial products can truly be classified as fair use.
2. The Squeezing of the "Content Supply Chain"
As AI answer engines become the default interface for information retrieval, publishers face an existential crisis. If search traffic drops by upwards of 90%, digital advertising models collapse, and paywalls face increasing pressure from automated scraping tools. This raises a critical question for the future of AI development: Where will future models get their training data once the independent journalism and creative industries collapse under the weight of AI-driven traffic starvation?
3. Increased Regulatory Scrutiny and Sanctions
The motion for sanctions filed by The New York Times seeks severe penalties against OpenAI, and these unsealed documents significantly strengthen their case. Beyond the courtroom, antitrust regulators and intellectual property watchdogs in the European Union and the United States are expected to take renewed interest in how foundational models acquire their training data.
As the litigation proceeds, the mask has slipped from the early days of the generative AI boom. What was publicly framed as an inspiring march toward artificial general intelligence is revealed through internal records to have been recognized from the start as a reckless land grab—one built on the systematic extraction of human labor, acknowledged internally as unsustainable, and executed with full awareness of the economic devastation left in its wake.
