{"slug": "openai-accuses-plaintiffs-lawyers-of-paying-for-hiding-and-then-laundering-key", "title": "OpenAI Accuses Plaintiffs’ Lawyers Of Paying For, Hiding, And Then Laundering Sketchy Key Evidence In AI Copyright Case", "summary": "OpenAI and Microsoft filed a motion on Wednesday accusing plaintiffs' law firm Susman Godfrey of paying for research to supply evidence its clients lacked, hiding the payments from defendants, and introducing the research outside the normal expert process in the consolidated AI copyright class action. The filing targets an Arxiv preprint titled \"Generative AI floods and dilutes the market for books\" by four researchers including Jane Ginsburg, which OpenAI says was funded by Susman Godfrey and disclosed via a CV listing $100,000. Professor Ed Lee, who runs ChatGPT is Eating the World, called the motion \"explosive.", "body_md": "# OpenAI Accuses Plaintiffs’ Lawyers Of Paying For, Hiding, And Then Laundering Sketchy Key Evidence In AI Copyright Case\n\n### from the *laundering-evidence-is-a-bad-look* dept\n\nA ton of attention was paid recently to some offhand statements from OpenAI and Microsoft employees that surfaced in filings in the [NY Times’ ongoing case](https://www.techdirt.com/2023/12/28/the-ny-times-lawsuit-against-openai-would-open-up-the-ny-times-to-all-sorts-of-lawsuits-should-it-win/) against OpenAI, which has been consolidated into a much larger class action lawsuit. As I argued earlier, that struck me as something of a nothingburger of a story, because it [should have no impact](https://www.techdirt.com/2026/09/23/copyright-infringement-still-isnt-theft-even-when-a-microsoft-employee-says-it-is/) on the actual legal questions regarding copyright infringement and fair use. However, on Wednesday evening, OpenAI and Microsoft filed something far more stunning, accusing Susman Godfrey (which represents the plaintiffs in the consolidated case) of effectively end-running basic rules of discovery and evidence by (1) paying for research to supply evidence its clients lacked, (2) hiding from the defendants that it had paid for that research, and (3) sneaking the paid-for research into the case outside the normal expert process.\n\n[This filing](https://storage.courtlistener.com/recap/gov.uscourts.nysd.640396/gov.uscourts.nysd.640396.2046.0.pdf) should be seen as the massive bombshell (if not fraud on the court) that people tried to make out that earlier filing to be. Professor Ed Lee, who runs ChatGPT is Eating the World (which tracks all of the various AI lawsuits), has called this an “[explosive motion](https://chatgptiseatingtheworld.com/2026/09/23/openai-moves-to-strike-paper-generative-ai-floods-and-dilutes-the-market-for-books-by-prof-tuhin-chakrabarty-based-on-cvs-alleged-disclosure-of-100000-funding-by-susman-godfrey-law-firm-repre/).” But it’s a little bit complex to understand why, which is why it will not get nearly as much attention as some offhand comments by a Microsoft employee.\n\nTo understand why this is such a big deal, we need to take a few steps back to explain. There are a bunch of different cases going on in the US regarding whether or not AI training is “fair use” and therefore not a copyright infringement. There were two important rulings in California last year, [one after the other](https://www.techdirt.com/2025/06/26/two-judges-same-district-opposite-conclusions-the-messy-reality-of-ai-training-copyright-cases/), where one judge (William Alsup) found training to be somewhat obviously fair use, while the other judge (Vince Chhabria) found it to be somewhat obviously *not* fair use.\n\nAs often happens in fair use cases, a lot of time is spent on the “effect on the market” argument, and part of that is whether or not the new works “dilute” the market for earlier works. In the Anthropic case, Alsup didn’t buy the claims of dilution, which is maybe not surprising, since he found training to be fair use. But perhaps more interesting is that in the Meta case, Chhabria — even as he found against fair use — wasn’t persuaded about the “dilution” argument:\n\n*As for the potentially winning argument—that Meta has copied their works to create a product that will likely flood the market with similar works, causing market dilution—the plaintiffs barely give this issue lip service, and **they present no evidence** about how the current or expected outputs from Meta’s models would dilute the market for their own works.*\n\nThat was a federal judge signalling to potential plaintiffs, if you’re bringing infringement cases like this, *maybe* find some evidence of dilution?\n\nAnd… that happened. Earlier this year, a preprint came out on Arxiv seemingly providing evidence on that specific point, claiming that “[Generative AI floods and dilutes the market for books](https://arxiv.org/abs/2607.20349)” written by four researchers, most notably Jane Ginsburg, who is one of the most famous copyright scholars around (though is also well known as one of the most extreme copyright maximalists, not to mention a general hater on a broad interpretation of fair use). But the lead name on the paper is Tuhin Chakrabarty, a recent PhD. (2024) grad who is now a computer science professor at SUNY Stony Brook. Chakrabarty received his PhD. from Columbia University, where Ginsburg teaches.\n\nA friend had sent me that report when it came out and I found the analysis… perplexing. I had put it on my list of things to write about, but never got to it. Thankfully, Thad McIlroy, who runs “The Future of Publishing” and has been a long term contributing editor at Publishers Weekly, took it upon himself to examine the paper and [found it deeply problematic](https://thefutureofpublishing.com/2026/07/is-ai-flooding-the-market-for-books-and-diluting-their-value/), mainly because they relied on Kindle Unlimited to get copies of the books that they used for the analysis. But as McIlroy points out, that’s distortionary for many reasons regarding how KU works, and suggests that many of the underlying assumptions in the paper simply don’t hold up to scrutiny:\n\n*But the author earns income on KU solely on the number of actual pages of their book that are read by a subscriber. Just getting downloaded provides no income. The complex formula is [well-described here](https://kindlepreneur.com/kenp-calculator/). There is no method available to estimate the page reads for a book, nor the KU income. Chakrabarty writes, “We measure Kindle Unlimited as whether a title is available on the service, not as how much of it readers actually read. The panel does not tell us whether a given unit is a Kindle Unlimited borrow, a page read allocation, or an ordinary purchase.”*\n\n*An interesting aspect of KU is that a book’s income there may relate far more closely to quality than it does under royalty systems. If a reader downloads a low-quality AI-generated book on KU, starts to read it, and recognizes the low quality, they will stop reading and move onto another book. The author will earn an insignificant amount of money. On the other hand, if a reader buys the same book, the author receives their full royalty (unless the reader goes to the trouble of returning the book and seeking a refund).*\n\n*An AI-generated book on KU will only earn significant page revenue if readers find it to be of quality sufficient to match the genre books they are used to reading on the platform.*\n\n*With these factors in mind, the prevalence of Kindle Unlimited titles in this study appears to be a distorting influence. First, AI-generated books are more likely to appear on Kindle Unlimited than they are more broadly on the Amazon Kindle platform. Second, there is no clear method available to estimate a book’s actual KU income.*\n\nEven more bizarre, when McIlroy shared a copy of his critique with Chakrabarty, he was dismissed *on moral grounds*, because McIlroy has argued for ethical ways to use AI in publishing, which Chakrabarty claims is “morally not okay with me.” That alone should raise some serious red flags about the objectiveness of Chakrabarty in this research. He did not come to this with an open mind. He came bearing a grudge.\n\nA few months earlier, Chakrabarty and Ginsburg (along with Xinyue Liu, who was also an author of the paper above, and who appears to be a first or second year PhD. student working for Charkrabarty) put out another paper called “[Alignment Whack-A-Mole: Finetuning Activates Verbatim Recall of Copyrighted Books in Large Language Models](https://arxiv.org/abs/2603.20957).” That piece claimed there was evidence that AI models “store copies of copyrighted works” and even pointed out that this “undermine[s] a key premise of recent fair use rulings.” Indeed, it calls out the Alsup and Chhabria rulings in the paper itself, and effectively notes that they’re responding to the judge’s concerns regarding the effect on the market.\n\nIn short, Chakrabarty, Liu, and Ginsburg have been publishing research that attempts to fill in the gaps that multiple judges had called out, and to help plaintiffs argue that training is not fair use. This was especially important because if such evidence was widely available, other plaintiffs would have brought it up. But they have not. Likely because it doesn’t *really* exist unless you stretch your methodology to its breaking point.\n\nOf course, my biases are known: I’m quite convinced that training AI on copyrighted works is fair use, and I find the argument that slop books “dilute” non-slop books to be beyond nonsensical. Similarly, knowing a little bit (just enough to be dangerous) about how LLM training works, makes it difficult for me to believe that models are, in fact, holding full copies of works they are trained on. That’s just not how they work. But you don’t have to take my word for it. A. Feder Cooper, a well-known computer science professor at Yale who has (somewhat famously) done research on getting LLM’s to spit out “[memorized books](https://books-memorization.github.io/),” or other full works, had some [pretty blunt criticisms](https://afedercooper.info/whack-a-mole/) of the “whack-a-mole” paper:\n\n*As will become clear soon, I think the paper has significant methodological and presentation problems. I’ve spent considerable time reviewing and re-reviewing the paper, and have consulted with two trusted senior colleagues who are experts on memorization to gut-check my reading. And, in brief, I’m confident that Alignment Whack-a-Mole’s headline claims are incorrect. These results rest on a* *specific memorization metric and elicitation methodology**that I don’t think hold up to scrutiny, and* *don’t support the broad claims**the paper makes. At best, I think the claims are seriously overstated; at worst, the large majority are wrong. I can’t tell which because the paper doesn’t report enough detail to distinguish the two.*\n\nThat alone should be concerning, but the media — including the NY Times — [really loved to report on these studies](https://www.nytimes.com/2026/07/28/books/ai-bookselling-amazon.html), even as their methodology seemed questionable to some experts, and despite the clear potential conflict of interest.\n\nNow, that takes us to the claims in the OpenAI filing from earlier this week: it’s that the plaintiffs’ lawyers at Susman Godfrey secretly paid at least Chakrabarty to do these studies, hid that fact, and then took further steps to launder the studies as non-biased expertise. It appears this wasn’t just a conflict of interest at work, it was a conflict piled upon a conflict, and then potential fraud on the court.\n\n*Unable to muster any evidence of harm after years of discovery, Class Plaintiffs’ counsel Susman Godfrey L.L.P. (“Class Counsel” or “Susman”) paid Stony Brook University professor Dr. Tuhin Chakrabarty to research “[h]ow AI generated books dilute the market for human authors.” Declaration of Victor Chiu ISO Motion to Strike (“Chiu Decl.”), Ex. A. Dr. Chakrabarty then coauthored a working, non-peer-reviewed paper purporting to show exactly that (the “Chakrabarty Paper”). The paper was initially self-published on July 22, 2026. Susman had disclosed Dr. Chakrabarty and one of his co-authors as retained experts months earlier—but the resumes Susman provided omitted that Susman had funded Dr. Chakrabarty’s research. Neither Dr. Chakrabarty nor the other disclosed expert ever served an expert report in this case. And after Defendants specifically objected that Dr. Chakrabarty’s resume was incomplete, Susman provided what it represented was an “updated resume” that still omitted Susman’s own funding of his market-dilution research.*\n\nNow, some people will point out that it’s not uncommon for companies to pay for research and then use that research elsewhere in ways that are beneficial to them. That’s absolutely true. The problem here isn’t who paid for the research, but the lengths the plaintiffs’ lawyers went to in hiding who paid for it from the court (and from OpenAI and Microsoft)… and how the evidence was laundered into the case long past the normal deadline where it could have been challenged.\n\nNormally, if you bring expert witnesses into a case, the other side gets to challenge their expertise and any research findings that they’re providing. But here, the class plaintiffs’ lawyers took a bunch of steps that at least suggest they deliberately sought to make that effectively impossible with this bit of research. They had named Chakrabarty as a *potential* witness, providing an incomplete resume for him, but then didn’t use him as such. Instead, they did a kind of evidence two step to get it into the case in a way that would make it harder to challenge:\n\n*On July 22, 2026—after the deadlines for all expert reports had passed—Dr. Chakrabarty, Dr. Dhillon, Xinyue Liu, and Professor Jane Ginsburg uploaded to the internet a working paper titled “Generative AI floods and dilutes the market for books.”… They then uploaded two subsequent versions of the paper on July 26, 2026 and August 3, 2026, respectively…. The paper remains identified as a “Working Paper Under Review.” …*\n\n*The Chakrabarty Paper purports to “measure[] how generative AI” impacts “a real book market once its output reache[s] the catalog and compete[s] for sales.” … Its abstract asserts that the research “bear[s] directly on the market-effect question at the center of the fair use defense to copyright infringement.” … The July 22 and July 26 versions of the Chakrabarty Paper did not disclose that it was funded by Susman and did not make any of its underlying data available. … The August 3 version of the Chakrabarty Paper again did not disclose its funding source. …*\n\n*[…..]*\n\n*On Sunday, August 2, 2026, the afternoon before Mr. Lasinski’s deposition, Class Plaintiffs served a supplemental report devoted entirely to the Chakrabarty Paper and which cited the July 26, 2026 version. … At his deposition the next day, Mr. Lasinski testified that he did not analyze any of the data underlying the Chakrabarty Paper…. Mr. Lasinski also testified that he had never spoken with Dr. Chakrabarty or any of his co-authors “about this paper or any other matters related to this litigation.” … When Mr. Lasinski was asked whether he understood that Dr. Chakrabarty and Dr. Dhillon “were retained as experts by Plaintiffs in this matter,” counsel from Susman objected: “I’m not sure why this is appropriate to ask Mr. Lasinski about.” … Mr. Lasinski ultimately testified that he did not “know that this means that [Dr. Chakrabarty and Dr. Dhillon] were retained.”*\n\n*Mr. Lasinski likewise did not know who had funded the research he was relying upon. When asked whether “the study was funded by Plaintiffs in this case or the Susman Godfrey firm,” Mr. Lasinski testified: “I don’t know the funding sources,” but “to be clear . . . **funding something like this would be inconsistent with what I’ve known the Susman Godfrey firm to do**.” … Counsel from Susman, who was defending the deposition, did not correct the record or comment on the issue of funding.*\n\nGot that? After the deadlines for expert reports were past, the Susman lawyers filed a “supplemental report” from a *different* expert, Lasinski, which was all about this report that Chakrabarty et al had only just published, effectively getting it into evidence after the deadline passed, and through a non-author of the paper, who had little actual knowledge of the paper’s methodology or data. And, yes, it’s notable that Lasinski said it would be “inconsistent” with what he knew of Susman Godfrey for the firm to fund something like this. Meanwhile, the Susman lawyers in the room objected to questions about whether the paper’s authors were retained experts, and then said *nothing at all* when Lasinski vouched that the firm wouldn’t fund such research. How… interesting.\n\nThere’s also the bit about how the lawyers for OpenAI and Microsoft figure this out:\n\n*After Mr. Lasinski’s deposition, OpenAI independently located a substantially similar version of Dr. Chakrabarty’s resume on his website…. Unlike the “updated” resume Susman provided in February, however, the version OpenAI found contains a section specifying $100,000 in “Funding” from Susman in December 2025:*\n\n*The resume identifies the $100,000 as an “Unrestricted Gift for sponsored research” on “How AI generated books dilutes the market for human authors?”—the same subject covered in the Chakrabarty Paper and in Mr. Lasinski’s supplemental report….*\n\n*Thus, according to Dr. Chakrabarty’s own resume, Susman’s funding had begun approximately two months before Susman provided Defendants with his supposedly “updated” resume, and the stated subject of that funding was the same market-dilution issue addressed by the Chakrabarty Paper and Mr. Lasinski’s supplemental report. Neither of the resumes Class Plaintiffs provided in February disclosed that the research was sponsored or the source of funding..*.\n\nThat looks bad! This looks worse:\n\n*Two days later, on August 27, 2026, Dr. Chakrabarty changed the resume on his public-facing website and removed the reference to Susman’s $100,000 gift. Chiu Decl. ¶ 15, Ex. M. The revised resume now states, in fine print and barely legible font, that “[a] previous version of [Dr. Chakrabarty’s] resume stated that [he] received an unrestricted gift for sponsored research from Susman Godfrey LLP in the amount of $100,000. This was incorrect as the research was done for In re Mosaic LLM litigation for which [his] institution was compensated in a lesser amount:”*\n\n*Even taken at face value, the revised resume does not deny that Susman funding facilitated the research presented in the Chakrabarty Paper. Whether the money was nominally earmarked for this MDL or the In re Mosaic LLM Litigation case, it supported the same researcher investigating the same market dilution question that is the subject of the Chakrabarty Paper, which in turn is the subject of Mr. Lasinski’s supplemental report.*\n\nOpenAI and Microsoft have asked the court to toss the paper entirely, and it’s the plaintiffs’ key evidence on dilution, the exact thing Chhabria said was missing in the Meta case. But also, they point out that this appears to be an attempted fraud on the court.\n\n*The Lasinski Supplement is not just late; it instead appears to be a deliberate effort to gain an advantage by evading Rule 26. “It is troublesome, to say the least, for a party to engage a consulting, non-testifying expert; pay for that individual to conduct and publish a study, or otherwise affect or influence the study; engage a testifying expert who relies upon the study; and then cloak the details of the arrangement with the consulting expert . . . in order to conceal it from a party opponent and the Court.” … To make matters worse, Susman appears to have concealed its funding of the Chakrabarty Paper from Class Plaintiffs’ own expert, Mr. Lasinski, despite asking him to rely on it. Dr. Chakrabarty himself was also apparently ignorant of the fact that the tens of thousands of dollars Susman was funneling his way to conduct market-dilution research and publish papers was tied to a specific litigation, much less which one. And Class Plaintiffs have now completed the maneuver: their summary judgment submissions rely extensively on the Chakrabarty Paper and describe it to the Court simply as an “academic stud[y],” without disclosing that their own counsel funded the underlying research.*\n\n*This maneuver deprived Defendants of the opportunity to fully analyze and rebut the Chakrabarty Paper—and the Court of the ability to properly assess its reliability. Had Class Plaintiffs properly disclosed the Chakrabarty Paper and underlying data and materials, Defendants would have evaluated the data on which the study is based, deposed Dr. Chakrabarty and his co-authors, and tested the study’s methodology and conclusions through the ordinary discovery process. Instead, Defendants were only able to depose Mr. Lasinski, who knew nothing about Dr. Chakrabarty’s underlying data and who mistook the Chakrabarty Paper to reflect neutral, independent research.*\n\n*Courts recognize that it is “fundamentally unfair” for a party “to supplement the record with reports of alleged ‘consulting experts’”—like Dr. Chakrabarty here—“whose identity and opinions have been shielded [from disclosure].”*\n\nAnd this kind of sketchy behavior has been [deemed to be fraud on the court](https://supreme.justia.com/cases/federal/us/322/238/) before.\n\n*The Court also has the inherent authority to preclude the Lasinski Supplement and Chakrabarty Paper to “prevent [Class Plaintiffs] from perpetrating a fraud on the court,” Yukos Capital S.A.R.L. v. Feldman, 977 F.3d 216, 235 (2d Cir. 2020), or interfering with the judicial system’s ability to impartially adjudicate this action. Such interference includes concealing counsel’s role in creating purportedly neutral scientific evidence. See Hazel-Atlas Glass Co. v. Hartford-Empire Co., 322 U.S. 238, 251 (1944) (vacating judgment obtained using an article ghostwritten by counsel but presented as the work of a disinterested expert).*\n\n*That is what Susman did here. When disclosing Dr. Chakrabarty as an expert, Susman omitted that it funded the research subject of the Chakrabarty Paper, continued to omit that funding even after providing what it represented was an “updated resume,” and allowed Mr. Lasinski to testify at his deposition that Susman would not provide such funding. And even since its funding of the research has come to light, Susman has refused to answer straightforward questions about the nature of its relationship with Dr. Chakrabarty and his co-authors. As Mr. Lasinski himself acknowledges, it would be “inconsistent” for a law firm to fund a study for litigation and then present it through an expert as neutral academic literature.*\n\nOnce again, the issue isn’t even that the research is sketchy (although… it is). Nor is it that the research was paid for by an interested party (though… it was). The main issue is that the funding appears to have been deliberately hidden from the defendants, and then the sketchy, paid-for research was laundered into the case through a different expert after the deadline for expert reports had passed.\n\nLiterally everything about this bit of research — which is a key plank in the anti-fair use argument — comes out of this as suspect.\n\n\tFiled Under: [ai](https://www.techdirt.com/tag/ai/), [copyright](https://www.techdirt.com/tag/copyright/), [dilution](https://www.techdirt.com/tag/dilution/), [effect on the market](https://www.techdirt.com/tag/effect-on-the-market/), [evidence](https://www.techdirt.com/tag/evidence/), [experts](https://www.techdirt.com/tag/experts/), [fair use](https://www.techdirt.com/tag/fair-use/), [jane ginsburg](https://www.techdirt.com/tag/jane-ginsburg/), [training](https://www.techdirt.com/tag/training/), [tuhin chakrabarty](https://www.techdirt.com/tag/tuhin-chakrabarty/), [vince chhabria](https://www.techdirt.com/tag/vince-chhabria/), [william alsup](https://www.techdirt.com/tag/william-alsup/)\n\n\tCompanies: [microsoft](https://www.techdirt.com/company/microsoft/), [ny times](https://www.techdirt.com/company/ny-times/), [openai](https://www.techdirt.com/company/openai/), [susman godfrey](https://www.techdirt.com/company/susman-godfrey/)", "url": "https://wpnews.pro/news/openai-accuses-plaintiffs-lawyers-of-paying-for-hiding-and-then-laundering-key", "canonical_source": "https://www.techdirt.com/2026/09/25/openai-accuses-plaintiffs-lawyers-of-paying-for-hiding-and-then-laundering-sketchy-key-evidence-in-ai-copyright-case/", "published_at": "2026-09-25 17:55:47+00:00", "updated_at": "2026-09-25 18:00:56.432733+00:00", "lang": "en", "topics": ["ai-policy", "artificial-intelligence", "generative-ai"], "entities": ["OpenAI", "Microsoft", "Susman Godfrey", "Ed Lee", "ChatGPT is Eating the World", "Jane Ginsburg", "Arxiv", "William Alsup"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/openai-accuses-plaintiffs-lawyers-of-paying-for-hiding-and-then-laundering-key", "markdown": "https://wpnews.pro/news/openai-accuses-plaintiffs-lawyers-of-paying-for-hiding-and-then-laundering-key.md", "text": "https://wpnews.pro/news/openai-accuses-plaintiffs-lawyers-of-paying-for-hiding-and-then-laundering-key.txt", "jsonld": "https://wpnews.pro/news/openai-accuses-plaintiffs-lawyers-of-paying-for-hiding-and-then-laundering-key.jsonld"}}