On October 30, 2026, OpenAI released a document compilation titled “Fair use benefits everyone,” featuring excerpts from court briefs submitted by 12 independent entities, including library associations, disability rights groups, university law professors, economists, and independent creators. Their core argument was consistent: AI training, as represented by large language models, constitutes fair use under the U.S. copyright law framework and does not constitute infringement. The release coincided with the deadline for amicus briefs in the consolidated copyright case before the U.S. District Court for the Southern District of New York (SDNY), where Judge Sidney Stein is presiding.
The core plaintiffs in the lawsuit include The New York Times, which sued OpenAI and Microsoft in 2023, alleging that they used The New York Times’s copyrighted content to train large language models without authorization, directly violating copyright law. According to an analysis by cellcog.ai, the deadline for reply briefs in the case is November 20, 2026, and the court has not yet announced a ruling timetable. By publicly compiling excerpts from supporting briefs, OpenAI is making its final large-scale public-opinion push before a formal ruling.
The supporting lineup assembled by OpenAI includes the American Council of the Blind, library associations, the Consumer Technology Association, the Business Software Alliance, Authors Alliance, as well as economist Joshua Gans, writer Kevin Kelly, law professor Matthew Sag, musician Michael Wall, and others. Among them, accessibility advocates argue that tools such as AI reading assistance and speech-to-text can benefit people with visual impairments and dyslexia, and that these tools also rely on copyrighted content for training. According to tokenpost, a May 2025 report by the U.S. Copyright Office explicitly stated that “AI training can be transformative,” recognizing that such conduct may have room for fair use under certain conditions.
The supporters’ reasoning can be summarized in three layers: first, the purpose of using original works in AI training is fundamentally different from that of the original works, making it “transformative use”; second, the training process does not provide users with a substitute channel for accessing the original works; third, training itself does not constitute market-substitution harm recognized under copyright law. This logic is the standard framework for analyzing the fourth factor of U.S. copyright law, and courts have historically used it to uphold the legality of technologies such as full-text book search, image search engines, and digital reading tools for people with disabilities, precedents cited in the briefs.
The opposing camp is equally large. SAG-AFTRA, the Writers Guild of America (WGA), and the American Federation of Musicians (AFM) jointly submitted opposing briefs asking the court to reject a fair use exemption for AI training. On the publishers’ side, the Association of American Publishers (AAP), the International Association of Scientific, Technical and Medical Publishers (STM), and the Independent Book Publishers Association (IBPA) were among the organizations that co-signed briefs supporting the plaintiffs. Politically, Democratic members of the U.S. House Judiciary Committee Jamie Raskin, Jerry Nadler, and Hank Johnson submitted a brief opposing the Justice Department’s position—the DOJ had previously stated in a “statement of interest” on September 1, 2026, that the court should decline to find that LLM training violates copyright law.
The backdrop to this debate is two lines of judicial precedent that have diverged. In June 2025, Bartz v. Anthropic and Kadrey v. Meta both accepted fair use defenses for AI training under the specific facts of those cases—but neither created a nationally binding rule; according to an analysis reported by tokenpost, the two rulings “did not establish a uniform national rule.” On September 29, 2026, however, the Third Circuit in Thomson Reuters v. ROSS Intelligence expressly rejected a fair use defense invoked by a competing AI legal tool. This latest precedent is unfavorable to OpenAI because it shows that even in the AI field, fair use is not guaranteed and courts will review cases individually—especially when AI outputs directly compete in the market with the original copyrighted content.
OpenAI’s strategic intent is clear: in court, lawyers handle the legal arguments; outside court, OpenAI is trying to shape a narrative by compiling a list of “diverse supporters”—that opposing fair use for AI training is not protecting creators but harming accessibility groups, independent creators, and the technology ecosystem. Including creators and accessibility advocates together in the document is a deliberate move to counter the public-opinion frame that “tech companies are plundering cultural producers.” The document still releases excerpts from the briefs rather than full texts; independent analysis firm cellcog.ai noted that OpenAI also did not issue any standalone statement about the project through official channels, and that its spread has relied mainly on media reports.
For content creators and publishers, the direction of this lawsuit has real commercial significance: if the court formally establishes that “AI training constitutes fair use,” they will lose the legal leverage to demand licensing fees; conversely, if infringement is found, AI companies will face huge damages and forced licensing negotiations, and the training-data cost structure of the entire industry will be reshaped. For developers and enterprise users, the most direct impact at this stage is uncertainty itself—before a ruling is handed down, AI products built on copyrighted content always face retroactive legal risk, which is one underlying driver for some companies’ preference for licensed datasets or synthetic data.
From the structure of the litigation, the most likely outcome is that the court will enter substantive proceedings in the coming months, with the ruling focusing on “market substitution harm,” the fourth factor—the weakest link in the existing supportive precedents and the point most heavily attacked by opponents. Once the court finds that outputs from products such as ChatGPT are substitutive competitors to The New York Times’s content, the probability of a fair use defense succeeding will drop sharply. If the lawsuit ultimately ends in settlement, industry standardization of copyright licensing agreements will accelerate, and large content holders’ bargaining chips at the negotiating table will increase accordingly. Whether the court quickly schedules a trial after November 20, 2026, and how deeply the U.S. government intervenes in the case—the DOJ’s earlier “statement of interest” showed that the administration leaned toward supporting the legality of AI training, and whether that position is maintained under the new political landscape will profoundly influence the direction of the final ruling.
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