The Metric Is Not the Mission is a ten-part examination of how Big Tech moved from building and expanding the open internet to increasingly shaping it around its own metrics, incentives and assumptions. Across the series, the argument follows the evolution of the platform economy—from the optimism of the early internet to the growing tensions around power, prediction, geopolitics, accountability and the future of digital life.
The series will be published in two parts each week over five weeks, with each installment building on the one before it. At the end of the series, the complete essay will be brought together in a single PDF edition, providing the full argument in one place.
Part II — When They Still Understood Us
Part I looked at the slow transformation taking place beneath the daily controversies surrounding Big Tech. This second part goes back to the beginning, asking what these companies originally understood about people and how the metrics that once measured their success gradually became the definition of it.
It has become fashionable to tell the story of Big Tech as though it were always destined to end here. In retrospect, it is easy to portray the rise of the major platforms as the inescapable march of surveillance capitalism, monopolistic ambition, and unchecked technological power. That narrative is emotionally satisfying because it offers clear villains and a comforting sense of inevitability. It also happens to be incomplete.
Cory Doctorow has given this deterioration a memorable name: “enshittification.” His argument is that platforms initially serve users well, then, once users and business customers are locked in, progressively shift value away from both toward shareholders, degrading the service in the process. It is a powerful account of how platforms become extractive. But it is not quite the argument here. The deeper problem is not simply that Big Tech has learned to extract more from us but that it has become increasingly convinced that because it can measure and predict our behavior, it understands us and, by extension, the societies it has come to mediate. The failure is therefore not only economic; it is also epistemic. The metric has become a substitute for the mission.
One cannot understand why these companies now appear increasingly disconnected from the societies they helped shape without first acknowledging that, for a remarkably long time, they understood those societies exceptionally well.
Technology succeeds when it solves technical problems. It changes the world when it solves human ones.
That was the genius of the first generation of internet platforms. Their founders did not invent friendship, curiosity, creativity or community. They simply recognized that the internet had reached a stage where these deeply human instincts required new forms of expression. The web of the late 1990s was exhilarating, but it was also fragmented, uneven and, for many people, intimidating. Finding information often required patience. Discovering interesting websites depended on chance as much as design. Publishing demanded a degree of technical literacy that excluded far more people than it empowered. The internet was open, but openness alone does not necessarily produce accessibility.
The great platforms emerged not because they sought to replace the internet but because they made it intelligible. Google transformed an expanding wilderness of information into something navigable. Wikipedia demonstrated that knowledge could be organized through collaboration rather than hierarchy. YouTube lowered the barriers to publishing so dramatically that expertise escaped universities, broadcasters and production studios. Facebook addressed an even more fundamental challenge. It recognized that the internet was no longer simply about information; it had become about people. Until then, maintaining relationships online had been surprisingly cumbersome. Email was too formal, instant messaging too ephemeral, personal websites too static. Facebook reduced social interaction to something almost frictionless. Its success lay not in technological sophistication but in psychological intuition.
This is easy to forget because the platforms that dominate our lives today bear only a partial resemblance to the ones that first captured our imagination. Facebook did not begin as an endless stream of algorithmically selected content. It was, in essence, a digital address book enriched by photographs, conversations, and the ordinary rituals of everyday life. It became valuable because it mirrored existing relationships rather than attempting to manufacture new ones. There was comfort in discovering former classmates, following the lives of distant relatives, or organizing gatherings that would otherwise have required dozens of emails and phone calls. The platform expanded social life without yet attempting to redefine it.
YouTube offered a similarly modest promise. It was not originally designed to maximize engagement or optimize watch time. It functioned more like an immense public archive whose value derived from its unpredictability. One could arrive searching for a lecture on astronomy and leave having discovered a forgotten jazz performance, a documentary on Greek history, or a repair manual for a washing machine. Recommendation existed, but it remained subordinate to curiosity. Users still felt as though they were exploring rather than being guided.
Even Twitter (now X), before it became a battleground for politics, culture wars, and performative outrage, captured something important about the changing nature of public conversation. It collapsed distance between journalists, academics, politicians, and ordinary citizens in ways that would have seemed extraordinary only a few years earlier. For all its imperfections, it suggested that expertise and authority might become more accessible rather than less.
Looking back, what united these companies was not simply technological innovation but a particular philosophy of the internet. They assumed that openness generated value. The more people connected, the richer the network became. Every new participant increased the possibilities for everyone else. Economists describe this as a network effect, but the phrase barely captures its cultural significance. Participation itself became the source of optimism. The internet appeared to be validating one of the oldest liberal ideas: that societies flourish when individuals are free to exchange ideas, collaborate voluntarily, and build institutions from the bottom up.
It is difficult to overstate how persuasive this vision became. Most governments celebrated the digital economy as an engine of innovation. Investors poured unprecedented sums into technology because the opportunities seemed limitless. Civil society organizations embraced online platforms as tools for democratic participation and global advocacy. Even critics of globalization often regarded the internet as an exception, a domain where openness appeared to distribute power rather than concentrate it.
For a brief historical moment, these interests aligned. What was good for technology companies often appeared to be good for users, for markets, and, in many respects, for the internet itself. The incentives reinforced one another. Companies grew by making the network more useful. Users benefited from larger communities. Developers built new services on open standards. The web expanded because success depended on drawing people further into its richness rather than confining them within a single destination.
History, however, has an inconvenient habit of changing the problems that institutions are asked to solve. The sociologist Robert K. Merton once observed that organizations often become prisoners of their own success. Practices that were rational under one set of conditions gradually harden into routines, and routines into orthodoxies. Institutions continue refining the solutions that once made them indispensable even as the environment around them evolves. Success breeds confidence; confidence breeds certainty; certainty eventually makes adaptation more difficult than persistence.
There is no reason to believe technology companies are exempt from this pattern. If anything, their extraordinary success may have accelerated it.
The platforms that once competed to help users navigate an open internet eventually found themselves managing ecosystems of unprecedented scale. Their priorities changed almost imperceptibly. The models they developed during the internet’s age of expansion proved astonishingly effective at connecting people, organizing information, and lowering the costs of participation. The metrics through which they evaluated success, such as growth, engagement, scale, and network effects, were not arbitrary inventions of venture capital. They reflected a period during which connecting more people genuinely created more value for everyone involved. The problem is that the world changed while the metrics remained stable. A measure that once indicated success gradually became the definition of success itself.
There is an obvious parallel here with Goodhart’s Law: when a measure becomes a target, it ceases to be a good measure. The principle, first articulated by economist Charles Goodhart in the context of monetary policy, describes what happens when an indicator that works as a proxy for an underlying objective is turned into the objective itself. But the problem here is slightly different. The issue is not simply that platforms began gaming their metrics, or that users learned to optimize for them. It is that the metrics gradually became so deeply embedded in the companies’ understanding of success that the distinction between the measure and the mission was lost. The metric did not merely distort the objective; it quietly became the objective.
None of this happened because a group of executives gathered in a boardroom and decided to undermine the open internet. Institutional change is rarely so theatrical. More often, it emerges from countless rational decisions made in pursuit of perfectly reasonable objectives: improve the user experience, reduce friction, personalize recommendations, increase safety, remove inconvenience. Each adjustment appears modest in isolation but collectively they alter the character of the system itself.
This is where history becomes quietly ironic. The companies that had once understood the internet better than anyone else slowly began to forget what had made the internet exceptional in the first place. They continued to believe they were connecting the world, even as they increasingly replaced the world with carefully curated representations of it. They accumulated unprecedented quantities of information about human behavior while becoming progressively less attentive to the human condition.
The distinction is subtle, but it may prove to be the defining story of this technological era. To observe behavior is not the same as understanding experience. A platform can know how long we hesitate before clicking a link, which videos hold our attention for an extra seven seconds, or what sequence of images is most likely to keep us scrolling late into the night. It can infer preferences with astonishing accuracy. It can predict patterns that would have been unimaginable a generation ago. Yet prediction, however sophisticated, remains an impoverished form of understanding. It reveals what people do. It says far less about why they do it, what they fear, what they hope for, or what kind of society they are trying to build together.
That difference, almost invisible at first, is where the story begins to change.
Konstantinos Komaitis, PhD, is a veteran of developing and analysing Internet policy to ensure an open and global Internet.
Our fun links this week include Jev, the super fast new AI classifier, and Persodex, the context layer for your Contacts (PS. hit Ben up if you’re in New York in mid-October).
A 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 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 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.
This filing 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.” 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.
To 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, 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.
As 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:
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.
That was a federal judge signalling to potential plaintiffs, if you’re bringing infringement cases like this, maybe find some evidence of dilution?
And… 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” 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.
A 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, 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:
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. 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.”
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).
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.
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.
Even 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.
A 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.” 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.
In 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.
Of 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,” or other full works, had some pretty blunt criticisms of the “whack-a-mole” paper:
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 aspecific memorization metric and elicitation methodologythat I don’t think hold up to scrutiny, anddon’t support the broad claimsthe 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.
That alone should be concerning, but the media — including the NY Times — really loved to report on these studies, even as their methodology seemed questionable to some experts, and despite the clear potential conflict of interest.
Now, 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.
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.
Now, 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.
Normally, 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:
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.” …
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. …
[…..]
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.”
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.
Got 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.
There’s also the bit about how the lawyers for OpenAI and Microsoft figure this out:
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:
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….
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...
That looks bad! This looks worse:
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:”
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.
OpenAI 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.
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.
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.
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].”
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).
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.
Once 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.
Literally everything about this bit of research — which is a key plank in the anti-fair use argument — comes out of this as suspect.
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On Monday we wrote about Donald Trump’s direct attack on the First Amendment and the free press by banning reporters from the White House. As we expected, a judge on Thursday morning issued a Temporary Restraining Order, blocking the White House from continuing this unconstitutional action, though (as happened the last time Trump tried this) the court relied on Fifth Amendment due process rather than reaching the First Amendment question.
Plaintiffs are also likely to succeed in showing that their hard passes were revoked without constitutionally adequate due process. The “general rule” is that “individuals must receive notice and an opportunity to be heard before the Government deprives them” of a constitutionally protected interest…. Indeed, the Supreme Court has “described the root requirement of the Due Process Clause as being that an individual be given an opportunity for a hearing before he is deprived of any significant property interest.” Cleveland Bd. of Educ. v. Loudermill, 470 U.S. 532, 542 (1985) (citation omitted). Karem also holds that, because of the substantial interests at stake, before the Government can revoke the White House-issued hard pass of a reporter it must promulgate rules or standards governing the conduct that would lead to such revocation. See 960 F.3d at 665. And the reporter must “receive fair notice not only of the conduct that would subject him to punishment, but also of the magnitude of the sanction that the White House might impose.”
Still, on this record, Defendants offer little to back up their asserted national security interest to justify revocation of Plaintiffs’ hard passes. So this interest does not tilt these factors in their favor, especially given that Plaintiffs have shown a likelihood of success on the merits.
For one thing, nothing in the record that predates this suit suggests that the revocation of Plaintiffs’ hard passes was motivated by national security concerns. Certainly, that is not what President Trump said when he announced that he was “banning” Plaintiffs from the White House—instead, he focused on the alleged lack of truthfulness and negativity of Plaintiffs’ reporting.3 And even the justifications provided to Plaintiffs after this case was filed are ambiguous about the true purpose of the revocations: while Defendants’ letters to Plaintiffs mention national security concerns, they purport to identify reporting that “threatened national security and/or spread falsehoods,” leaving open the possibility that all the stories fall into the later bucket, rather than the former.
Of course, it wouldn’t be the Trump presidency if his White House didn’t start out by ignoring the TRO. According to Politico (one of the banned outlets):
A POLITICO reporter was denied access to the White House Thursday and his press credentials confiscatedafter a judge orderedthe Trump administration overnight to immediately restore access for news organizations that President Donald Trump banned from the complex last week.
MS NOW and CNN said their reporters were also denied entry. The three outlets have been barred from the White House since Saturday, following an order from Trump to do so “as a result of their constant ‘reporting’ FAKE NEWS!”
And so, the news orgs rushed back to court to point out that the White House was violating the TRO, which judges generally don’t take kindly to:
Early this morning the Court issued a Temporary Restraining Order directing “that Defendants (except for President Trump) and their agents, representatives, and all persons or entities acting in concert with them shall immediately return, reinstate, and restore the White House ‘hard pass’ press credentials held by employees of CNN, MS NOW, and POLITICO that were revoked on or about September 18, 2026.” Dkt. 24 (the “Order”). This morning journalists from each of CNN, MS NOW, and POLITICO attempted to enter the White House and were turned away. A Secret Service agent confiscated the hard pass of journalists from all three organizations. And when Plaintiff Betsy Klein, whose hard pass was confiscated on Saturday, September 19, requested to have her hard pass returned, her request was denied and she was refused access to the White House complex.
The judge ordered the White House to respond to the non-compliance notice by 12:30pm, and quickly received a declaration from Micah Stopperich, the Director of White House Press Operations, that the passes had been restored as of 9:07am, and that previously confiscated badges had been dropped at the entry gate to return to the journalists they had been taken from. Yet reporters say they were still being turned away until around noon, well after that supposed 9:07am restoration. They eventually regained some access to the White House.
But hours later, journalists from two of the same outlets were turned away from the arrival ceremony for Trump’s state dinner with Xi Jinping. As MS NOW itself reported:
Hours after regaining access, MS NOW White House reporter Laura Barrón-López was denied entry Thursday evening to the arrival ceremony on the portico ahead of the White House state dinner for Chinese President Xi Jinping. MS NOW had requested credentials for the event but never received a response. A CNN producer and correspondent were also denied access. When Barrón-López asked why she was being turned away, a White House staffer told her to “talk to Steven,” seemingly referring to White House communications director Steven Cheung.
According to CNN, the White House told them that CNN could not send a reporter to cover Xi’s arrival, only a photojournalist and an audio technician. The White House will surely argue that credentials for a specific event aren’t the same as the hard passes covered by the TRO. But blocking the reporters while allowing only CNN’s camera crew (a restriction not imposed on any other network) is exactly the kind of petty gamesmanship that the pending preliminary injunction briefing will have to deal with.
It’s unclear how the White House thinks any of this helps. It’s unconstitutional, and it makes the administration look petty: An administration that insists it’s the champion of free speech can’t even manage to let reporters in the door after a judge orders it to.
I’ve written a lot this year about how Republicans hijacked the $42.5 billion Broadband, Equity, Access, and Deployment (BEAD) program (created by the 2021 infrastructure bill) and immediately set about weakening oversight standards, eliminating enforcement of stuff like broadband affordability, speed, and equitable deployment, and making it a priority to heavily subsidize Elon Musk for LEO satellite broadband networks he had already planned to deploy anyway.
All of the chaos and changes have resulted in endless delays, and a lot of promising providers backing out of the BEAD program entirely. That includes electric cooperatives, many of which have been pushing affordable fiber optics into their existing, very rural electrical footprints.
The Trump NTIA process has been so filled with cronyism, delays, changes, new pointless regulations and chaos, a third or more of U.S. cooperatives say they’ll no longer participate:
“63 electric cooperatives across 27 states received provisional BEAD awards to offer reliable high-speed broadband to some of the most challenging eligible locations in the country. But delayed implementation and shifting guidance have created a program defined by uncertainty and confusion. Instead of accelerating deployment, continual revisions to the program have discouraged participation,” said Matheson.
“To date, 20 of the 63 electric cooperatives originally slated to participate in BEAD have withdrawn from the program. Many others are considering withdrawal, citing concerns over the application of extra-statutory pole attachment requirements as a condition of participation,” he added.”
Cooperatives are annoyed, in part, about new pole-attachment regulations the NTIA applied that make installations much more time-consuming and complex. The Communications Act explicitly exempted electric cooperatives and municipal utilities from federal pole regulation because such providers serve the public interest and are often the only ones willing to connect rural Americans.
Many incumbent telecoms control local poles, and make pole fiber attachment extra annoying to forestall competition. I’d suspect the new restrictions — from an administration that generally demonizes corporate oversight and regulation — are at the direct request of companies like AT&T, worried that popular cooperatives might gobble up market share in markets they theoretically could serve in the future.
It’s worth reminding you: Republicans spent the entirety of the last few years insisting that BEAD was a giant government boondoggle, and that once in office they’d fix it. This claim was routinely propped up by the likes of Ezra Klein at the New York Times, who hasn’t had a single solitary thing to say about U.S. broadband access policy in the two-years since Trumpism retook control of the program.
Congress originally set aside $42.5 billion to improve U.S. broadband. The Trump administration effectively tried to cut the program in half, insisting that Elon Musk’s expensive, congested satellite service would be “good enough” for a lot of these locations. The Trump administration then very clearly tried to wander off with the remaining money, and continues to be very murky about when states will receive it.
Fixing U.S. broadband requires a coordinated array of solutions. Some communities are helped by municipally-owned broadband. Some are helped by the local electrical cooperative getting into fiber and expanding cheap fiber access to rural communities. Others are best served by public-private partnerships between local governments and private providers.
The Trump administration’s BEAD changes have worked tirelessly to redirect a lot of money away from these popular, highly localized solutions, and funnel as much money as possible into the back pocket of incumbent monopolies like AT&T and Comcast, or billionaires like Elon Musk.
Other smaller and mid-sized providers are increasingly backing away from participating in the program entirely, either because of new restrictions and delays, or because the cost of deployment is skyrocketing due to wars, tariffs, and other Trump bumbling. As more BEAD bidders back away from participation or existing awards, more and more money will be funneled to Musk for substandard service so Trump Republicans can pretend the problem of U.S. broadband access has been “fixed.”
In states like California, Trump officials are insisting that California won’t receive any of its already-scheduled $1.86 billion BEAD grant award if they do literally anything telecom monopolies don’t like, whether that’s holding big telecom affordable for high prices, or enforcing the state’s net neutrality law.
It’s a cronyistic mess that’s starting to see growing bipartisan anger even in states like Texas, and it’s poised to get much, much louder as the long-delayed money to states truly begins to flow next year. Right now, a lot of people in state broadband policy are hesitant to publicly comment because they’re worried the Trump administration will sever their grant awards entirely.
The velocity with which RFK Jr. continues to break the promises he made during his confirmation hearings is simply incredible. As we get further and further away from those hearings, which amazingly occurred only 21 months ago, we may lose sight of the assurances Kennedy gave directly to Congress about his plans if appointed to lead HHS. For the purposes of this post, here are two we’ll key in on.
Sen. Elizabeth Warren (D-Mass.) grilled Kennedy about the money he’s made in the private sector from lawsuits against vaccine makers and accused him of planning to profit from potential future policies making it easier to sue.
“Kennedy can kill off access to vaccines and make millions of dollars while he does it,” Warren said during the Senate Finance Committee hearing. “Kids might die, but Robert Kennedy can keep cashing in.”
Warren’s statement prompted an assurance by Kennedy.
“Senator, I support vaccines,” he said. “I support the childhood schedule. I will do that.”
Days later, Sen. Bill Cassidy of Louisiana, chair of the Senate Health, Education, Labor, and Pensions Committee, declared Kennedy had pledged to maintain existing vaccine recommendations if confirmed. Cassidy, a physician specializing in liver diseases and a vocal supporter of vaccination, had questioned Kennedy sharply in a hearing about his views on shots.
“If confirmed, he will maintain the Centers for Disease Control and Prevention’s Advisory Committee on Immunization Practices’ recommendations without changes,” Cassidy said during a speech on the Senate floor explaining his vote for Kennedy.
Kennedy was lying. He almost immediately went about violating those promises at HHS and its child agencies. He dismantled ACIP and rebuilt it with like-minded conspiracy theorists. He went about altering the childhood vaccine schedule. He has failed to actually support vaccines in America. He violated his pledge with the thoroughness of a completionist playing a video game. When hauled before Congress to ask just what the hell his problem was and why he did literally the opposite of what he’d promised, he yelled at Congress and lied some more.
And now he’s doing it all over again by disallowing states to get childhood COVID vaccines through the CDC’s Vaccine for Children program.
As respiratory virus season nears and fall vaccination drives get underway, more than half of US children are facing uncertainty over access to this year’s COVID-19 shot. The Centers for Disease Control and Prevention has unexpectedly delayed the distribution of the shots to a key federal program and some states.
Usually, the CDC would allow states to order the newly available seasonal COVID-19 vaccines through the federal Vaccine for Children (VFC) program, which provides vaccines at no cost to children who are uninsured, underinsured, Medicaid-eligible, or Indigenous people in the US. Approximately 52 percent of all US children are eligible for vaccines through the program.
“The delay in VFC means delays in these states’ ability to get vaccine for all children,” Demetre Daskalakis, former director of the CDC’s National Center for Immunization and Respiratory Diseases and chief medical officer at Callen-Lorde Community Health Center, told The Guardian.
Now, when the federal government blocks vaccines for the greatest pandemic in several generations to potentially half of the children in the entire country and American territories, you’d have to think they have a good reason for doing so. Your guess is as good as mine as to what that could be, because HHS ain’t talking.
In a statement, the Department of Health and Human Services told Ars Technica that “CDC has not yet finalized procurement decisions for COVID-19 vaccines through the Vaccines for Children and Section 317 programs.” The department—currently run by ardent anti-vaccine activist Robert F. Kennedy Jr.—declined to answer the question of why there was a delay in the decision. But the statement suggested that Trump officials were questioning whether children should get the vaccine.
“HHS and CDC are committed to … ensuring that vaccines purchased through federally funded programs are appropriate for the populations those programs serve,” the department said in the statement. It added that additional information about the decision will be released “soon.”
This is bullshit and it should result in congressional hearings. Kennedy must answer for this generally and explain yet another broken promise. He told senators, to their faces, that he would not be taking anyone’s ability to get vaccinated away from them. That was a promise made to the representatives of the American public and he lied about it. That must be answered for, or else there is no longer any point to having confirmation hearings, or perhaps to having oversight of the Executive Branch at all.
And Kennedy isn’t the only one who should be answering questions. Where the hell is Erica Schwartz in all of this? The new CDC Director was supposed to be one of the adults in the room. She was pitched as a bulwark against Kennedy’s insanity. Here, she appears to be completely out to lunch.
To the American Senate: do you all like being played for fools so publicly? Is this some sort of kink? If ever there was a cabinet secretary in the modern era worthy of being fired from his position, isn’t Kennedy it?
Over the last few years, it has become accepted knowledge that the internet — mainly social media and, lately, AI tools — was damaging the mental health of kids and increasing the suicide rate among that demographic. To hear the media and politicians talk about it, this was the biggest issue on the planet and we had to do basically everything possible to block social media (and AI) from kids.
Of course, the narrative was always bullshit. While there had been an uptick in suicide rates among teens between 2010 and 2020, they were way below the rates in the 80s and 90s. And by the time Jonathan Haidt’s “moral panic in a book” came out blaming social media for teen mental health problems, the data already didn’t support his claims, as I pointed out in my review of the book right after it came out.
In that review of the book, I highlighted that while suicide rates among teens had ticked up in the US, they had actually declined in many other countries — including France, Spain, New Zealand, and elsewhere — despite plenty of social media usage in those countries. Similarly, the data on mental health issues was clouded by (1) much more openness to talking about mental health, and (2) importantly, new guidance under the Affordable Care Act that mandated increased screening for depression in adolescent girls, while simultaneously instructing clinicians to record suicidal ideation differently than in the past, which resulted in a massive uptick in such numbers.
And now the narrative violation continues, as the latest CDC survey data shows that mental health concerns among teens have been declining since their 2021 peak (i.e., as we were coming out of the worst of the COVID crisis).
Continuing a trendfirst observedin 2023, teenagers surveyed at high schools across the country in 2025 reported improvements in several key measures, including persistent feelings of sadness or hopelessness, serious thoughts of suicide and attempting suicide in the last year.
Some might argue that this is due to the work of Haidt and politicians banning social media for kids, but the data doesn’t seem to show that at all.
Thirty-six percent of teenagers said that they used social media every hour or more, a similar percentage to what was seen in 2023, when the data was first reported.
This does not mean, of course, that we can declare victory. There are still, clearly, plenty of teens dealing with mental health challenges.
But the data show that many teenagers, especially girls and teenagers who identify as lesbian, gay or bisexual, are still struggling. Thirty-three percent of high school students reported persistent feelings of sadness or hopelessness in the last 12 months, down from a peak of 42 percent in 2021. Fourteen percent of teenagers reported that they had seriously considered attempting suicide, down from 22 percent in 2021.
As actual experts have been pointing out for years, the reality around mental health and suicidal ideation is extremely complicated and not fully understood. But, over and over again it seems that the approach recommended by actual experts is not blanket bans on technology or simply “blaming” anything, but rather better efforts at identifying those going through mental health challenges while simultaneously making more mental health resources available to all who need them.
But, the narrative is the narrative. Hell, it was just weeks ago that a judge in New Mexico took it as irrefutably proven that social media was damaging to kids’ mental health. Does anyone get to go back and show him the latest data suggesting that maybe something else was driving this? Or do we just keep treating the narrative as fact?
This is what I’ve been saying for years: when we misdiagnose the problem and blame the wrong thing, the “solutions” we get are not solutions at all. Indeed, they could be making the problem worse by not actually putting in place the tools and resources to help those in need while, simultaneously, doing real damage to groups that rely on internet communities for their own mental health support.
I’d like to think that as more data like this comes out, further debunking Haidt’s narrative, we could get back to a serious discussion about how to actually help kids who are struggling. But I fear the easy comfort of a moral panic is too strong a pull for people to give it up that quickly.
Meta’s settlement with the state attorneys general (currently awaiting court approval) has been touted as industry-redefining. Indeed, Meta desperately hopes it will be. Although Meta was the only industry player to negotiate its terms, the settlement agreement is structured to broadly reshape the social media industry. In addition to Meta’s guaranteed settlement payments of $12 billion, Meta will pay the state AGs a total of $5 billion in additional bonuses — if the state AGs restrict minors’ usage of Meta’s key competitors (and make comparable settlement payments).
The settlement’s quid-pro-quo effectively places a bounty on the heads of Meta’s competitors — and deputizes the state AGs as Meta’s bounty-hunters. Meta wants the government to hit Meta’s rivals. If state AGs deliver the results Meta wants, Meta pays them off. The quid-pro-quo is not subtle. It’s out in the open for everyone to see, but that doesn’t make it any less corrupt or corrosive.
It’s easy to understand why Meta dangled the bounty in front of the state AGs. For years, Meta has urged governments to increase their regulation of social media—but only so long as any new regulation doesn’t disadvantage Meta more than its rivals. By unilaterally entering into the settlement agreement, Meta has exposed itself to a risk that it ends up as the only major industry player hindered by the agreement’s restrictions.
This would put Meta in a precarious market position, especially given the settlement agreement’s time limits on use and the fact that Meta’s competitors are just a click away for consumers. The economic benefits of having its competitors equally restricted are surely worth far more than $5 billion to Meta. That’s why Meta will happily share a piece of its financial upside with the state AGs if they deliver their end of the bargain.
While it’s clearly in Meta’s interests to pay off the state AGs to impose the settlement terms on Meta’s rivals, why are state AGs so eager to become Meta’s bounty-hunters?
To be fair, the state AGs have plenty of motivation to prosecute Meta’s social media rivals without any additional bounties from Meta. Indeed, prior to the settlement, several state AGs had already initiated enforcement actions against some of Meta’s rivals. The state AGs might view the $5 billion bounty as a financial windfall for doing work they were willing to do for free.
Unfortunately, any windfall from Meta’s bounty arrangement comes at a high cost to the state AGs and their constituents.
First, the quid-pro-quo taints all further social media-related state AG enforcement efforts against Meta’s rivals. Going forward, judges, juries and Meta’s rivals will justifiably wonder: Are the state AGs bringing the enforcement action because they genuinely believe their constituents are being harmed, or because they hope to cash in Meta’s bounty?
Second, the state AGs have shown how justice is for sale in their offices. The state AGs will do the anticompetitive work of controlling the marketplace activities of a company’s rival — if enough money is on the table. Putting a price on justice this way degrades the rule of law.
In promoting the settlement, the state AGs have proudly claimed that they are working to protect the children in their states. Instead, Meta’s bounty demonstrates that the state AGs are actually working for Meta. This is a good reason for the courts to think carefully about whether the settlement should be approved.
Our society needs to have difficult and high-stakes conversations about how we can improve children’s welfare online. By selling out the integrity of their enforcement decisions, the state AGs have discredited themselves as contributors to those conversations.
Eric Goldman is a law professor and associate dean for research at Santa Clara University School of Law. He has been teaching and researching internet law for over 30 years.
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