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If you just happened to notice, left out is any acknowledgement of the reality that there are exactly two countries on the AI frontier, the United States and China. They seemingly want the American government to both unilaterally negotiate its own technological restraint and sign an accord with the Chinese Communist Party. Then we will have to trust Beijing to honor these vague, subjective terms. Given that AI doomerism has not proliferated in China in the fashion it has here, this would amount to unilateral technological disarmament.

The “Pacing the Frontier” letter is rife with valuable signatures, and they don’t just come from the hyper wokes within the “trust and safety” teams. Anthropic’s CEO, OpenAI’s chief scientist, Meta’s chief scientist, Google DeepMind’s chief strategy officer, and a long roster of the people who build these systems are signatories to the document.

I can’t help but to point out again that everything hinges on one word in that last sentence: International.

Europe is not in this race or really, any race that involves innovation these days. Mistral, in France, is the one European lab that is kind of sort of doing something interesting, but it’s still rather inconsequential. The continent has built a regulatory apparatus so hostile to building things that its best founders almost always relocate to the United States and incorporate here.

We have seen this appeasing China movie before and we know how it ends.

Take the Paris climate framework as an example. Both the U.S. and China signed the same document, but only the U.S. was baited into action. The United States pledged, in an agreement signed by former President Barack Obama, to drastically cut emissions immediately. This was a hard, near-term number, and the U.S. proceeded to wire billions of dollars into sketchy international climate funds and NGOs. China pledged to let its emissions keep climbing until roughly 2030 and then, at its leisure, to peak. The U.S. bound itself to self destruction while China bought fifteen years of runway and did absolutely nothing to achieve any stated objectives.

How exactly would this committe inspect a frontier AI system’s progress in China? It does not exactly emit gasses that can be picked up by satellite observation. There are no physical inspectors who could verify the compliance of companies within an authoritarian government that presides over a giant land mass and 1.5 billion citizens. A pacing agreement with China would be unverifiable by its nature, which means in practice it slows down exactly one country: ours.

And what exactly are we pacing?

Everyone has a different definition of AI. I think of it as a new technology that encompasses a general-purpose capability and a human productivity tool. If we slow down the frontier and you slow down whatever the frontier was about to produce. Do we tell a man with advanced cancer the bad news that his treatment is now banned because it is violating a subjective “pace” determined by an international committee?

There is no magical dial we can pinpoint that we can command to “slow down only the parts we determine as extra scary.”

Also, who would staff the committee(s)? Presumably, this would mean the signatories themselves, because they are some of the most knowledgeable people in the field, and their contemporaries who disagree with the proposal would not want to join such a committee. They would be handed discretionary power to decide, subjectively, like Soviet commissars, what rate of human progress we are permitted.

Frontier AI companies are raising hundreds of billions of dollars on the promise of the very technological breakthroughs they have achieved in recent months and years. It’s always been a bit paradoxical that these are the same people who are virtue signaling about the need to roll back AI progress. And it seems destined that whatever proposed mechanism gets built will almost certainly determine something that the incumbents can reach and their competitors cannot. Suddenly, the “safeguard” becomes a regulatory moat. Funny how that works out.

The expected rejoinder is that the letter deserves deference because very smart and successful (San Francisco-based liberals) leadership signed it.

But that just proves we have a massive bubble problem in West Coast tech circles. It does not prove that they know the first thing about governing a country, as proven by their historically awful proposal to have an international body usurp the authority of the United States government and our systems of laws and justice.

Being the best in the world at training an AI system confers no expertise in statecraft, treaty enforcement, morality, or constitutional design. And rarely will you be able to acquire the wisdom of the American founding principles by interacting with chatbots. Given their backgrounds, it’s not surprising that they imagine governance as an engineering problem that involves finding the right mechanism, tuning the particular incentives, and voila! Global compliance is achieved. But that’s entirely detached from human nature and the nation state system that governs our politics.

Much of this worldview traces to effective altruism, the movement that has colonized the very loud and intimidating “safety” wings of these companies. Their ideas have very little grounding in the American founding principles that allowed for the flourishing of their respective companies.

What Silicon Valley needs is not a new international body, but an infusion of certain principles that make rational Americans come to the obvious conclusion that self-governing people can handle a powerful technology better than a supranational committee ever can.

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Yet it’s not the lab-leak question and the real, widespread confusion surrounding those early days of hysteria that is the scandal here. What we lived through was a seasonal respiratory outbreak converted by an unaccountable bureaucracy and a compliant press into the largest episode of mass hysteria in modern American history. The pathogen was not a significant part of the covid story. The panic and hysteria that resulted in civilizational disruption is.

Agree with my premise or not, but on top of that, Fauci’s “mitigation” record is still indefensible, and Fauci has already admitted it under oath.

In January 2024, in a closed-door transcribed interview with the House Select Subcommittee on the Coronavirus Pandemic, Fauci was asked where the six-foot rule came from. His answer, released in full that May: “I don’t recall. It sort of just appeared. I don’t recall, like, a discussion of whether it should be 5 or 6 or whatever.” Asked whether he had seen any studies supporting six feet, he said he was not aware of any, and that such a study would be very difficult to do. He called it an empiric decision that wasn’t based on data, or even on data that could be gathered. Asked whether he recalled reviewing any studies on masking young children, he could not.

Now remember what six feet actually did.

That number, pulled out of thin air by government bureacurats, was the load-bearing number of the entire American shutdown apparatus. Six feet set restaurant capacity. Six feet determined whether a gym, a salon, a bar, or a church could open at all, and at what fraction of full capacity. These catastrophic government edicts dictated classroom layouts. A number that “sort of just appeared” was used to reorganize the economic, educational, and social life of 330 million people.

Then the masks. In January 2023, Cochrane published an updated review of physical interventions against respiratory viruses, pooling 78 randomized trials. On community masking it found little or no difference in influenza-like or COVID-like illness across nine trials and some 277,000 participants. Masks never work, but Fauci didn’t care. He found them a useful mechanism to control his sycophantic followers, like a cult leader insisting upon uniforms to showcase compliance.

Quite infamously, in November 2021, Fauci told CBS that his critics were really criticizing science itself, “because I represent science.” Four days after three courageous epidemiologists from Harvard, Oxford, and Stanford published the Great Barrington Declaration, Fauci and high level government health bureaucrats waged a smear campaign against the truth tellers. NIH Director Francis Collins emailed Fauci demanding “a quick and devastating published takedown” of what he called “three fringe epidemiologists.” No, not a rebuttal. A “takedown.” The federal government’s two most powerful “public health” officials used their authority to discredit the people asking questions about the legitimacy of their policies.

Between February and April 2020, the number of working business owners in America fell from 15.0 million to 11.7 million. That’s a loss of 3.3 million, 22 percent, the largest drop ever recorded. Many of those businesses never recovrered. The Great Recession, by comparison, took 730,000 over its entire span. Yelp alone logged 163,735 closures by that August, and roughly 60 percent of them became permanent. Peer-reviewed work using California’s full sales-tax filing universe found permanent-closure rates spiking, with small firms hit far harder than large ones.

There were also devastating results for America’s youth. After decades of sustained progress in math and reading, The Nation’s Report Card recorded the largest math decline in its history. Twelfth graders tested in 2024, which is the first cohort to spend all four high school years after the closures, were still way below normal levels. Despite tens of billions in federal dollars infused into the system, the money did not close the gap. Studies showed that the schools that stayed remote longest lost the most.

The hysteria was infinitely worse than the claimed disease itself. From April 2020 through the end of 2021, Americans died of non-covid causes at an annual rate 97,000 above trend. Heart disease, diabetes, drug overdoses, alcohol, homicide, car crashes, etc all went way up. All-cause mortality rose 26 percent among working-age adults versus 18 percent among the elderly. Among children, who were never threatened by a mild respiratory virus, there were essentially no aggregate excess deaths at all. We shut the schools for a supposed viral threat that was not impacting the students whatsoever.

In a just world, Anthony Fauci would spend the rest of his life behind bars. Not because of some massive, hard to track, intelligence agency sourced foreign conspiracy involving Wuhan, China. But because he used his credentials to insist again and again that his devastating authoritarian dictates were absolutely necesssary, and backed by real science. Fauci is a negligent and despotic criminal of the highest order, and it would be a shame if he got away with it. I do hope that he will face some type of real criminal prosecution in the coming days and months while Republicans are still in power.

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The Iranian regime has spent this war firing thousands of low cost drones and rockets at U.S. military bases, along with virtually every one of our regional allies. They’ve hit airports, oil facilities, and power plants, while striking American installations including Al Udeid in Qatar, Al Dhafra in the Emirates, Ali Al Salem in Kuwait, and a base in Jordan where American soldiers were killed. Iran has done its most destructive work with cheap drones and ballistics weapons bought in bulk. While its most advanced and costly ballistics have been defeated by American and Israeli long range defense systems, the “junk” is functioning to deplete our arsenals and wage a costly defense.

The counts our partners published tell the story. In the opening days the United Arab Emirates (UAE) reported detecting 174 ballistic missiles and 689 drones. Kuwait reported shooting down 97 ballistic missiles and 283 drones. Of course, months later, Iran has launched thousands more drones and thousands of additional ballistics at allied targets. It’s clear that the American defense establishment has not succeeded in accurately assessing the full quantity of Iran’s ballistics and drones.

Now, all too often, America and its allies have taken to stopping drones and low grade ballistics with very expensive weapons that we don’t have the ability to manufacture rapid fashion. A Shahed-class Iranian attack drone costs Tehran between $20,000 and $50,000. The Patriot missile system’s current round, the Patriot Advanced Capability-3 Missile Segment Enhancement (PAC-3 MSE), costs about $4 million, and a Terminal High Altitude Area Defense (THAAD) interceptor roughly $13 million. Sometimes we will fire two or three at a target to be sure of a “kill.”

Everyone in the coalition is in a less than optimal position, which is leading us to the dilemma the White House faces today.

On Friday night, reports surfaced that the Trump Administration paused a two-week bombing campaign after top officials, including General Dan Caine, raised concerns about the ammunition supply.

Nothing in the American arsenal was built to shoot down anything cheap. The Patriot program began with a 1961 Army requirement. THAAD was proposed in 1987 and did not field a unit until 2008. The whole system was designed many decades ago to stop Soviet bombers and Scud missiles. These are targets so expensive that nobody was worried about trading a million-dollar interceptor for what was on the receiving end of the warhead. Of course, nobody wants to see the United States suffer casualties merely because expensive missiles shouldn’t be used against inexpensive attack vehicles. Yet it’s clear that America does not have the manufacturing capacity to continue this status quo for a significant amount of time.

Throughout America’s Global War On Terror (GWOT), the threat of a non state or state actor with a massive drone fleet and/or cheap long range ballistics was rather inconsequential. Only until recent years did that threat mass proliferate on the battlefield. Unfortunately, tools that can be much more efficient for these defenses, like lasers and microwave weapons, are not quite ready for primetime.

The deeper problem is not the missile. It is what goes inside it. Every missile needs an explosive and a fuel, and America’s manufacturing capacity has lagged on this front.

America last made its own trinitrotoluene, the standard military explosive better known as TNT, in 1986. We now buy it from a single European supplier, with a replacement plant only now going up in Kentucky. The Radford Army Ammunition Plant in Virginia is the only place in the country making nitrocellulose, the base ingredient of gunpowder and artillery propellant. It was built in 1941. Essentially one company is certified to supply the chemical that makes solid rocket fuel burn, and a new plant takes about a year to permit and close to a decade to build. The number of American firms making solid rocket motors fell from six to two between 2000 and 2015.

While American plants closed and were never rebuilt, the work went overseas because much of it is unprofitable when America is not on a wartime footing. It seems like Pentagon officials just assumed private industry would keep idle capacity that no one was paying it to keep, as if a functional factory were something the market provides for free without any incentives. Plenty of money goes into dazzling technological applications, as evidenced by our $1 trillion annual defense budget, but not enough goes into the hardware and the unglamorous plants underneath.

America builds roughly 600 Patriot interceptors a year, and half are already promised to the eighteen other countries using Patriot. Boeing makes the seeker, the small radar in the nose that finds the target, for every one at a single plant in Huntsville, Alabama. It takes 24 months to build the missile and 30 to build its motor.

The regime in Tehran does not have to defeat our air defenses through qualitative power. It only has to keep sending cheap drones at Dubai, Kuwait, and American bases abroad to deplete our arsenal to the point that our reserves become critically low. Since America doe not have the capacity to produce these defense systems in rapid fashion, it’s time to consider the possibility that our current Cold War-era shoot down policy needs to be revised significantly until new technology arrives or faster production is possible.

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Heffernan wrote a column celebrating the supposed arrival of MAGA into the anti-data center movement. Of course, for those who have followed our reporting, that’s not at all what is happening, but let’s put that aside for a moment.

Somewhere in the middle of it, I turn up as “an AI zealot,” which is an interesting label. Imagine if thirty years ago, an early internet supporter was considered an internet zealot. Yeah, it just seems a bit much.

Credit where it’s due: she linked to The Dossier. That’s more journalistic courtesy than I get from most outlets, some of which prefer to just rip off my work and claim it as their own. I think that’s because they’re somewhat embarrassed to acknowledge that my reporting is better sourced and more influential than their well funded but unimpactful and dull establishment publications.

But here’s the part worth your attention, because I don’t really care about labels from the media.

She concedes that our narrative is factually accurate.

The piece she’s responding to is our March investigation into Humans First, the “America First” outfit that just staged a national day of protest against data centers. My reporting found that the group was conceived, funded, and stood up by a small network of leftist Effective Altruism operatives in San Francisco, who then installed conservative frontmen, but still maintain operational control over the organization.

Heffernan does not dispute a single fact, but she does claim that EAs are not lefties, which is inaccurate. They very much are lefties. Additionally, she doesn’t argue that I made any misteps about the facts, the funding, or the people. Her rebuttal, in full, is that EA activists fostered the group to engage conservatives, then handed it off to them, and that this is wholesome coalition-building rather than deceit. Sure, Virginia. Sure.

An entity can only be handed off if somebody else built it first. You cannot describe an organic uprising of heartland conservatives as having been “fostered” and then transferred. A grassroots movement, by design cannot be handed off to anyone. Basically, Heffernan is saying that an astroturf allegation is not important because the astroturf was laid with good intentions by her fellow liberals who sincerely believe that AI is bad for humanity.

So we agree on the facts and disagree on the intentions of the people who founded the outfit. That’s fine. I’m content to let sober minded readers sort that out for themselves.

A zealot is a person of fanatical and uncritical devotion. What, precisely, was my act of fanaticism? I broke the story on who is paying for a hyper political astroturf campaign that has major implifications for the future of the United States. Okay, guilty as charged.

In the 90s, was the reporter who thought the internet would be good for ordinary people, and who noticed that some of the loudest opposition was underwritten by interested parties, an internet zealot? Was there an electricity zealot beat back in the day? I am not a zealot to notice an emerging technology working and declining to panic about it in public.

One thing I’ll happily reaffirm is that plenty of conservative AI skepticism is entirely genuine, rooted in years of real concerns about transhumanism and civilizational risk. My reporting was never about whether people have sincere concerns, though I think it’s important to deal only in facts and not in narratives that people got psyopped into promoting. It was about who built the organization and who decided the messengers should wear red MAGA hats.

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From there the conversation turns to the economics and politics of the buildout itself: the tens of thousands of construction jobs tied to a single facility, the comparison to 1950s interstate highway spending, and why so much of this investment is landing in rural Virginia, Ohio, Texas, and Florida rather than Silicon Valley. We also work through why skepticism of AI runs deep on the right — from distrust of Big Tech’s politics to fears of a surveillance state — while arguing the “AI will destroy jobs” narrative keeps failing to materialize, pointing to a fresh wave of American entrepreneurship instead.

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With dozens of events planned across more than 20 states, the protests tap into genuine, widespread public concern. Gallup polling has shown roughly 70% of Americans oppose data centers in their own communities, thanks to the efforts of domestic and foreign groups that are trying to thwart the buildout of American technological infrastructure. Local pushback has already delayed or blocked projects worth billions of dollars in American jobs and local tax revenue in the first quarter of 2026 alone.

A closer examination of the individuals actually organizing these protests on the ground tells a very different story. While the national Humans First branding is conservative, many of the boots-on-the-ground leaders driving local events are drawn from the political revolutionary far-left.

In Gilroy, California, the key organizer is a man named Robert Bentson. On the day Charlie Kirk was assassinated, Bentson posted on Facebook celebrating the killing. He described Kirk as a “Nazi piece of trash,” a “white Christian nationalist Nazi,” and someone who engaged in “blatant shit and hateful speech and racism and homophobia.” Bentson wrote that Kirk was “in the fuck around phase and I guess he found out finally,” adding “Good riddance sorry not sorry” and calling it one less “pathetic hate spewing Nazi.” Bentson has also been involved in organizing “No Kings” protests. This is the type of activist Humans First is involving in its coalition.

In New York, the protest in Ticonderoga is being organized by a woman who has publicly stated that women’s “lives…depend on” MAGA supporters not gaining power.

In Nevada, a Biden donor and supporter is handling organization for at least one event. These are not isolated cases or fringe participants. They are the people Humans First is relying on to turn out crowds and execute the “grassroots” day of action it claims represents conservative America.

The contrast is stark. Nationally, Humans First presents itself as a patriotic pushback against AI infrastructure that they cllaim prioritizes corporate profits over American communities. Locally, the faces and voices leading many events belong to activists with clear records of hostility toward conservatives and Trump supporters.

Sure, legitimate questions about infrastructure buildouts exist across the political spectrum. Yet the pattern revealed here raises serious doubts about the authenticity of the “conservative” framing at the organizational level. If the movement were truly driven by conservatives concerned about sovereignty, energy independence, and community self-determination, one would expect local leadership to reflect those values. Instead, key organizers include individuals who openly celebrated the assassination of a prominent conservative voice and who have histories of anti-Trump activism.

This raises the obvious question: Is Humans First building a genuine conservative coalition, or is it deliberately providing cover for left-wing activists to shape the narrative around one of the most consequential technological buildouts in American history? The group’s national messaging may appeal to conservatives worried about Big Tech power, but the personnel executing the protests on the ground remind us of the reality that this astroturf movement is being steered by people whose politics are far detached from the average patriotic American.

Americans have every right to demand transparency, local input, and accountability from developers. They also have a right to know who is really leading the opposition to the reindustrialization of America.

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From hidden ties to the far-left Action Network, to a UK-based X account and articles of incorporation linking straight back to the Center for AI Safety, the operation is a textbook case of influence laundering designed to manufacture opposition to critical American infrastructure.

We also dive deeper into the broader ecosystem of astroturf “local news” outfits like Courier Newsroom, the parallels to decades of anti-nuclear fearmongering, and how bad information is being funneled into populist circles to stall progress on AI, energy, and national competitiveness. Parker shares sharp insights on how to uncover these networks and why conservatives must stay vigilant against foreign and domestic actors hijacking legitimate concerns. A must-listen for anyone serious about separating real grassroots sentiment from coordinated deception.

Check out the Capital Research Center here

Find Parker on X at @ParkerThayer

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I didn’t fight for my place in this country. I didn’t cross a vast continent or an entire ocean for it (though my ancestors did). I didn’t wait in a line or fill out a form. I was simply born here. Simple geographic happenstance can turn out to be the single greatest stroke of luck one has in his life.

It’s easy to forget that, living inside this great and vast nation. Our place in America starts to feel like weather: just the condition you exist in, barely worth noticing. But step back for a second. There are roughly 200 countries on this planet, and a staggering number of them are run by regimes that don’t let you speak freely, grossly mismanage their economies, and end up starving their citizens. Or simply, they offer their people some corrupt concoction that results in nothing to build a life around. Ask someone in one of those places what they’re proud of, and you’ll often get silence. It’s not because they lack character, but because patriotism needs something to be patriotic about. You can’t be patriotic about a country that gives you nothing and asks for a lot in return.

That’s what makes America strange, and rare, and always worth defending. Here, patriotism is often something American arrive at on their own, because the deal, despite our faults, is actually good. In America, we have free speech, the freedom to worship, the right to build something, fail, try again, fail again, and finally succeed. We have the right to say, with almost infinite ferocity, that our government is wrong. None of that is guaranteed in a state of nature. Throughout most of human history, and for those who live outside of our borders, the experience has been quite different.

So on this Independence Day, I’m thinking about the draw of a lifetime. I think about the version of me born somewhere else, somewhere with no rule of law, no ballot that means anything, no door open for someone who wants to find their passion in life and throw all of my weight behind it.

Gratitude isn’t the same as blindness. This country has plenty to fix, and loving it doesn’t mean pretending otherwise. But gratitude is the right starting point, because before we can improve something, we have to recognize what we were given. I was given a lot. A LOT. Not because I deserved it more than anyone else born this year, but because my ancestors fought to get here. I was simply lucky to be born here.

Happy Independence Day. Don’t waste the draw of a lifetime.

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From there, the conversation ranges widely. We both make the case that the real global contest isn’t left vs. right but the American model vs. the Chinese model, with Europe cast as a cautionary tale of a continent too regulation-happy and risk-averse to compete.

China has about a million people working on AI around the clock, while America has a fraction of that number, and yet, in D.C., some remain insistent on a plan to wall off China, which again, is not stopping China from catching up. Instead of just coping and banning, we can wake up and compete. America has the most robust markets and the best tech companies, and D.C. needs to focus on what makes us the best instead of deploying a strategy entirely based on botched attempts to handicap our adversary.

Why is this “stolen AI” story so popular in D.C.? Because it does two jobs at once. The first is to make Chinese AI look like stolen subpar junk, similar to a piece of military hardware or a knockoff EV, so that America can ban it instead of building something better. The second is to let us cognitively relax, because a country or company that only ever copies can never get ahead of the one making the real thing.

Start with the chips, because that is where the “they smuggled everything” idea is supposed to live. To train an AI model, you normally need thousands of specialized chips working together. The most powerful ones are American, and the U.S. has banned selling them to China, so the accusation from D.C. is that China just sneaks ours in in droves. But now, China says its newest AI models were trained on chips it built itself, made mostly by Huawei. That is believable to the honest observer, because Beijing has been prioritizing it as a national goal for years. One Chinese model that is getting a lot of hype in Silicon Valley, GLM-5.2, which is fast becoming good enough to rival the best American ones at writing code, was reportedly trained on about a hundred thousand Huawei chips with few if any American components involved. Another popular Chinese model, DeepSeek’s V4, was built from the start to run on Huawei chips too.

This doesn’t mean that China is engaged in zero nefarious behavior in the AI race. There are notable the criminal cases, and here the Department of Justice has indeed been busy, shutting down a $160 million smuggling network and separately charging a group that moved roughly $3.89 million worth of gear amounting to a few hundred chips. These are real prosecutions and real crimes, and yet when you set them against the global AI market, they amount to a rounding error. These reports amount to not even a small fraction of what it takes to build a tier one national AI program.

Now the “they stole our ideas” part. The main accusation is via distillation. Basically, an AI system learns by pulling the data from the answers of a smarter AI. In this scenario, we are talking about models like Anthropic’s Claude or OpenAI’s ChatGPT. It’s akin to a student studying a smarter classmate’s work to learn how they think. Yet in AI, this is an everyday practice among rival American and foreign companies. Anthropic admits, in the same report where it accuses China of bootlegging their product, that distillation is legitimate and used all over the industry.

The biggest hole in the “they just copy us” idea is what it forces you to believe about people. China produces close to half of the world’s very best AI engineers. To say all they can do is copy is to claim that hundreds of thousands of engineers, some of whom were trained in America, are mere robots who cannot think for themselves. We are just feeling good and coping more by disrespecting our rivals as stupid and incapable of original innovation.

And the plan built on that mistake, which was mostly spawned out of the Biden White House, is failing right in front of us. The export bans were supposed to choke off China. Instead, China is now turning American chips away at its own border on purpose, to push its companies onto Chinese chips and get better at making them. A recent Brookings report shows says the bans are speeding up China’s chip industry in the long run. The Biden Administration swung the ban hammer expecting China to come begging, and it instead walked away. Chinese companies that were hooked on American technology are becoming self sufficient.

Historically speaking, you never win a technology race by hiding the technology and banning your way to victory. You win by making your technology the thing the whole world uses, so that even your rivals build on top of it and speak your language. We should want the whole world built on American technology because it allows U.S. companies to become extensions of American power and influence.

The AI race with China presents a pretty simple binary, given that the U.S. and China are the only major players in the race: A foreign AI company that runs on American AI components is a win for America. A foreign AI company that runs on Chinese AI components is a loss for America. American tech companies, albeit imperfect instruments of American power, are one of the most powerful weapons this country has, and we are blunting them out of fear. America needs to stop coping and pretending, and start competing. Our Chinese rival is real and capable, their engineers are real and capable, and the way to win is to out compete China instead of spinning tales about how theyr’e just stealing all of our stuff.

We are watching some regulatory delays play out from the White House with Anthropic's Mythos and now OpenAI's GPT-5.6. The instinct is sound, and a brief, serious cybersecurity check before making them public is a matter of simple prudence. But prudence has a clock on it and a review that drags on can fast transform into the ban hammer again. The longer an American model waits in a government queue gives Chinese models extra time to ship to the world without delay. We can proceed with righteous caution, but this shouldn’t turn into an exercise involving overwhelming bureaucratic red tape.

Of course, none of this would matter so much if America and China were just two teams trading places on a leaderboard. The stakes here are about what kind of world the most powerful technology of our time gets built to serve. China is a totalitarian state which has created a system that exists to preserve the Party. The individual exists to serve the state, and an AI shaped by that worldview will carry its fingerprints into everything it touches. Our system is surely imperfect, but in America, many of us still believe that ordinary people are capable of governing themselves and deserve the freedom to flourish on their own terms, and American technology has a much better chance of continuing to represent those values.

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Soffer traces the company's origins to the aftermath of October 7th, when he teamed up with co-founder Asher Katz—a founding member of the IDF's tunnel-detection unit—and an ex–SpaceX and Boring Company engineer to tackle a domain the West has long treated as an afterthought. Underground warfare, the most ancient form of combat, has become one of the most neglected and consequential frontiers in modern defense: as drones turn the skies and surface into contested, lethal environments, adversaries from Iran to China are burrowing their most critical assets deeper than ever, and the recent B-2 strikes on Iran's nuclear facilities exposed just how hard those targets are to reach. Soffer walks through Traysar’s two newly unveiled systems, while arguing that the U.S. needs to treat "sub-T" as its own warfighting domain, complete with dedicated budgets, before its rivals seize the advantage beneath our feet.

The pattern it lays bare is comically consistent, because every transformative technology arrives wrapped in dread, and that dread sounds the same every single time. Consider nine of them:

1. Writing. Yes, writing. In Plato’s Phaedrus, Socrates feared the written word would hollow out memory and leave us with the mere appearance of wisdom.

2. The printing press. Scholars warned cheap books would drown Europe in information and corrupt morals, when what followed was the Reformation, mass literacy, and modern science.

3. The bicycle. The 1890s warned of a disfiguring “bicycle face” and feared mobility would ruin our physical form.

4. The telegraph. Critics swore instant news would destroy leisure.

5. The Kodak camera. Eastman’s 1888 camera triggered a privacy panic over roving “Kodak fiends,” and yet photography did not end civilization.

6. Radio. A 1941 study found most surveyed children addicted to crime dramas, while moralists feared degenerate music was pouring into the family home.

7. Television. The same anxieties were rerun a generation later, certain the glowing box would dissolve the family altogether.

8. Video games. For decades the conventional wisdom held that consoles were breeding violent delinquents, a thesis the research has refused to confirm.

9. The internet and social media. Every prior fear bundled into one grand apocalypse, and yet here we all are.

Nine major panics, every one now so woven into ordinary life that the fear once attached to it reads as moderately to completely unhinged.

Which brings us to artificial intelligence and to the newest front in this very old war, the data center. The objections are familiar in shape, because we are told that AI will swallow every job, bury the culture in synthetic slop, and drink the rivers dry to feed its server farms. These worries are not nothing, but then neither were any of the others.

Take the data center anxiety on its own terms. Training large models does consume real electricity and water, and the build-out is straining some local grids, but the history of computing has been the story of doing exponentially more with exponentially less, and the room-sized machines of the 1950s burned far more power than the phone in your pocket that now outclasses them entirely. The firms with the most to lose from runaway energy bills are precisely the ones pouring fortunes into efficiency and new power, which is why efficiency here is not a pious hope but the most reliable trend the business has.

Then comes the oldest fear of all, that the machines will simply take our jobs. They may take some, because every general-purpose technology reshuffles the labor market, and that is genuinely painful for whoever is standing in the wrong place when it lands, but reshuffle is the operative word. The sewing machine was supposed to throw seamstresses into the gutter and instead built a garment industry that employed far more of them, while the automated teller machine was supposed to end the bank teller, yet teller numbers rose for decades as cheaper branches multiplied. The destruction is vivid and immediate while the creation is diffuse and slow, which is why the panic always reaches the masses first.

So could this time genuinely be different? Sure. But if we are placing bets, the historical ledger is lopsided to the point of being nearly one-sided. Each technology that was supposedly going to doom us instead quietly integrated into our lives and society moved on, and the fears were not so much crazy as badly aimed, fixed on the technology rather than on the temporary disruption it caused on its way to becoming ordinary.

A panic is not a signal that something has gone terribly wrong, but rather that the world is changing, and that we are once again doing what our species always does, which is to worry loudly, adapt quietly, and end up considerably better off than the worrying ever assumed. Artificial Intelligence may yet surprise us, and we should hold that with humility, but if you want to know how this kind of story tends to end, the past two thousand years have been about as consistent as history gets.

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In Ayn Rand’s 1938 novella Anthem, a young man rediscovers electricity. He has spent years working in secret, alone in a forgotten tunnel beneath a dystopian collectivist city, where all forms of once common knowledge have disappeared. Equality 7-2521, a young man in the collectivist future society, possesses great intelligence and curiosity, but he lives in a society that punishes such attributes, and he's been assigned by the Council of Vocations to be a Street Sweeper despite longing to be a Scholar.

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Nonetheless, he builds this miraculous glass box that turns darkness into light. He believes he has given his society a gift unlike any in living memory. So he carries it to the World Council of Scholars, the body that governs all knowledge. He assumes that certainly, they will rejoice.

Not the case. Instead, they want to crush his discovery.

It’s not because of any kind of functional issue. Rather, because he made it alone, without their permission, and because his light threatens the Department of Candles. What is not done collectively cannot be good, they tell him. It took fifty years and the agreement of every council just to approve the candle. A single man with a better idea isn’t progress in their eyes. He is a danger to not just the plan, but society as a whole, they’ve determined.

That scene is a cautionary tale for a future ruling class that fully centralizes control. And today, we are at a crossroads when it comes to the future of artificial intelligence. We hear a lot these days about “responsible deployment,” and this notion that such powerful tools need to be managed by an elite hierarchy that knows what’s best for us. The question in AI was never really about capability. Instead, it is about access. Who gets to determine access to innovation?

One vision says the answer is a small, credentialed priesthood. They’ve determined that we need a hand-picked set of “trusted parties” granted something close to moral authority by a cluster of Effective Altruist and liberal internationalist Davos class-aligned ideologues on the West Coast, who have appointed themselves the stewards of what the rest of us are permitted to use. The other vision says the answer is the whole of American society. On AI, this means literally everyone with an internet connection. The kid in rural Appalachia, the suburban shopkeeper running a small business on main street, and the eighteen-year-old urbanite who can’t afford college but can now summon, in his pocket, the world’s best tutor, coder, and strategist on demand.

Such easy access to knowledge and capability has never existed before in human history. We are watching the cost of expertise collapse toward zero, and with it the oldest barrier is being torn down. This is not a job-killer, though the professional doomer class insists otherwise. It is the opposite, as the most powerful distributor of knowledge, leverage, and opportunity ever invented. AI is bringing us the fairest and freest playing field in American history.

So why the alarm? Why the urgent push for licensing regimes, “safety” bureaucracies, and deployment gatekeeping?

Anthem answers that, too, and it is worth remembering that Rand was not writing fantasy. She was born in St. Petersburg, watched the Bolsheviks seize her father’s pharmacy in the name of the people, and escaped to America in 1926 with a firsthand education in what centralized control of everything actually produces. The society in her novella is the logical end of that experience. It is a world where knowledge has been captured, catalogued, and rationed by committee, and the result is not a glittering scientific utopia by any means. It is a place lit by candles, one that has forgotten electricity, that recoils from the new because the new was not authorized by the trusted moral authorities. When you put bureaucrats or some kind of public-private fusion committee in charge of who may know what, you do not get safety. You get stagnation, impoverishment, and authoritarianism. Technology doesn’t advance under that arrangement. Innovation stalls out (which is the overt goal of “pause/stop AI” groups), gets gatekept, and remains inaccessible to the masses.

The AI gatekeepers speak as if the danger is too much capability in too many hands, when history’s far more reliable catastrophe is the reverse: capability concentrated in too few.

There is a name for an AI architecture built around central control, mandatory permission, and a managed hierarchy of who counts as trustworthy. We see it in China, and it’s called the CCP model. It is surveillance and compliance and a populace kept on the receiving end of tools that some will never be able to wield in order to try to make something of themselves. We should want no part of it, and we should be honest that some of the loudest voices calling for the centralization of AI are, intentionally or not, building the American version of exactly that.

There is no legitimate ethical or security reason to gatekeep this technology indefinitely. The case for doing so always seems to arrive wrapped in the language of caution, but the structure underneath it has so many historical examples that results poorly. We end up with a small group deciding it alone can be trusted with things as simple as a candle, and everyone else should be grateful for the candle.

America does not win by managing AI into an elite ladder of privilege. America wins by leaning into the thing that made it exceptional in the first place: distributed power, open access, faith in ordinary people to do the right thing when you stop standing between them and the tools they need to succeed.

America wins when we distribute knowledge and unleash innovation.

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There is a familiar rhythm to the way the corporate media and liberal politicians in D.C. talk about AI, and if you lived through two decades of climate narrative politics, you already know the beat. First comes the prophecy of imminent catastrophe. Then comes the insistence that only sweeping government action can save us. Then comes the curious detail that the catastrophe keeps failing to arrive on schedule, even as the demands for control grow louder. We have seen this movie before, and the only thing that has changed is the main character in the script.

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Consider Bernie Sanders, who has become the loudest political voice on AI’s supposed jobs apocalypse. In October, the senator’s HELP Committee released a report carrying the subtle title warning that AI and automation “could destroy nearly 100 million U.S. jobs in a decade.” He has since called for breaking up OpenAI, told an interviewer the technology is “like a meteor coming,” and alongside Rep. Alexandria Ocasio-Cortez (D-NY), introduced legislation for a federal moratorium on new AI data centers until the government can install the proper “safeguards.” The policy wishlist arrived fully formed with demands such as a robot tax and a moratorium on technological innovation all citing a potential crisis, but no actual data-backed causes.

AI doomerism is the climate template, reproduced almost line for line. Even decades before I was born, Americans were told that catastrophe was always ten years out, that the science was settled, that the only debate left was how much state power to hand over, and how quickly. The predictions, like ice-free Arctics, drowned coastal cities, climate refugees by the hundreds of millions—came with confident dates attached. Notably, the dates passed, but the demands did not recede. The alarmists simply found more nonsensical narratives and more new deadlines.

Consider Bill McKibben, who wrote The End of Nature in 1989, arguably the founding text of modern climate alarm, and who in 2023 signed the Center for AI Safety’s statement declaring that “mitigating the risk of extinction from AI should be a global priority.” McKibben didn’t so much change subjects as expand his catalog of apocalypses, explicitly citing climate as the precedent: “Given our failure to heed the early warnings about climate change 35 years ago, it feels to me as if it would be smart to actually think this one through,” he said of AI. Yuval Noah Harari, the Davos circuit’s favorite prophet, has likewise spent years warning of ecological collapse and now insists AI is as threatening as climate change and nuclear war, an “alien species” that could end us.

The institutional overlap is not exactly subtle. The Bulletin of the Atomic Scientists, keeper of the Doomsday Clock, spent years citing climate change as a primary reason humanity was creeping toward midnight. In January it set the clock at 85 seconds to midnight, its closest ever, and folded artificial intelligence directly into the same basket of “existential threats” alongside nuclear war and climate change. The same body, the same apocalyptic framing, the same call for “international guidelines” and “multilateral agreements.” The Bulletin’s own writers have made the connection explicit, arguing that the world’s “collective failure to heed climate warnings” is a lesson that must now be applied to AI. The threat is interchangeable and the remedy is always centralized control over society.

What makes the AI version especially worth scrutinizing is that, unlike long-range climate modeling, the central claim is testable right now. Sanders says AI is throwing millions onto the street. So is it? The data says no.

The Yale Budget Lab, hardly a den of right-wing skeptics, has been tracking AI’s labor-market footprint since the first version of ChatGPT’s release. Its current conclusion: while anxiety is widespread, the effect on today’s labor market “remains largely speculative.” The picture that emerges, the researchers wrote, “is one that largely reflects stability, not major disruption at an economy-wide level.” They found no clear rise in AI-task exposure among the unemployed and no lengthening of joblessness in the most exposed occupations.

Anthropic, which nobody in their right mind can claim as a hyper accelerationist outfit, published research in March finding “no systematic increase in unemployment for highly exposed workers since late 2022.” Goldman Sachs projects that any AI unemployment effect will be transitory and no larger than half a percentage point above trend. Every major institutional forecast, from the IMF, to McKinsey, to the BLS shows net positive job creation at the macro level over the medium term. When Amazon cut tens of thousands of corporate roles, even Amazon attributed the move to slashing bureaucracy, not robots or AI. The Yale researchers raised the pointed question of “AI-washing,” which amounts to companies blaming innovation to justify necessary cost-cutting from overhiring in the post covid era.

None of this means AI and the sweeping technological innovation that will come with it is consequence-free. Entry-level hiring in some fields, like junior software roles, has clearly softened. But the most plausible explanation is not that the machines have already replaced those workers; it is that hiring managers are making decisions based on the very narrative that politicians like Bernie Sanders are selling. A Reuters/Ipsos poll found 71 percent of Americans fear permanent job loss to AI, and firms are responding to that expectation rather than to a measured productivity reality. Goldman Sachs describes employers “integrating AI to avoid adding headcount” rather than firing anyone. The AI doomer prophecy is self-fulfilling: the alarm itself, like the climate narrative, creates a certain corporate standard even if it’s vidence free, and it results in the cooling of the hiring pipeline. The scale back then gets cited as proof the alarm was warranted.

AI doomerism is a powerful narrative, and pursuing some kind of sweeping federal moratorium based on a narrative, and not evidence, would entrench that narrative and make the prophecy come to life.

The alarmist method does not actually require evidence, because the prophecy is structured to be unfalsifiable. If layoffs come, that proves the danger. If they don’t, that proves we caught it just in time, or that the catastrophe is merely delayed, lurking past the next horizon. The climate narrative skirmishes taught the activist class that a sufficiently frightening and sufficiently distant prediction can power an entire political program indefinitely, immune to the inconvenience of being checked against reality.

AI may well reshape the economy. But “take it seriously” and “grant the government emergency powers over a multi trillion-dollar industry on the strength of predictions data already contradict” are two very separate paths forward.

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And it is generous indeed. By its own public accounting, the Tarbell Center is paying working journalists an average of better than $7,600 for every single article it bankrolls, with individual grants running as high as twenty thousand dollars a story. That kind of money buys the sort of artificial intelligence coverage that treats the most promising technology of our lifetimes as a slow-motion apocalypse. If you have ever wondered why so much of the corporate press covers AI like a horror film rather than an industrial revolution, the Tarbell-media stenographer pipeline makes sense of that dilemma.

This is no one-off arrangement. Tarbell runs an ongoing fellowship that embeds its hand-picked, salary-funded reporters directly inside the nation's most influential newsrooms, where they work the AI beat from the inside for up to two years. Its fellows have been placed at the Los Angeles Times, NBC News, Bloomberg, TIME, The Guardian, The Verge, MIT Technology Review, The Information, the South China Morning Post, among others.

So who is signing those checks? Follow the money up the chain and you arrive at a left-wing tech billionaire. Surprise! Tarbell’s funding flows in significant part from Open Philanthropy, the sprawling Effective Altruist-aligned grantmaking machine recently rebranded as Coefficient Giving, which exists to deploy the fortune of Facebook co-founder Dustin Moskovitz and his wife Cari Tuna. Moskovitz is no quiet, apolitical philanthropist tinkering at the margins of public life. He is one of the largest Democratic megadonors in the entire country, a man who poured around twenty million dollars into electing Hillary Clinton, tens of millions more into defeating Donald Trump and installing Joe Biden, and who by 2022 had routed better than seventy million dollars into Democrat-aligned political machinery. In 2024 he was reported to be the single biggest tech-founder donor to Kamala Harris. This is the man whose philanthropic empire quietly underwrites a meaningful share of what your morning paper tells you about artificial intelligence.

The worldview that empire is buying is not the neutral, public-spirited “AI safety” that Tarbell advertises. Strip away the language about supposedly helping society “navigate advanced AI” and what you are left with is pure doomerism. We are left with the conviction that AI is less an engine of prosperity than an existential menace that must be slowed, regulated to death, and consumed by the state, with a policy emphasis on the latter two objectives, given that Moskowitz is a major shareholder in Anthropic, which seeks an impenetrable regulatory moat in D.C. This is a degrowth and anti-competitive ideology aimed squarely at a single industry, the insistence that AI is a thing to be feared and contained rather than unleashed broadly and fairly for the benefit of ordinary Americans.

Moskovitz related entitites bankroll several of the think tanks that draft the regulations and the policy shops that lobby for control, and it now helps fund the journalists who cover the whole apparatus.

Tarbell insists that none of this money touches the journalism itself. Its favorite phrase on its website is editorial independence. The donors have no involvement, it assures us. An independent panel of judges scores the applications. Staff never see or shape a story before publication, and every funded piece carries a tidy little disclosure line buried at the bottom.

But notice what that very defense quietly concedes. There is a committee. Tarbell says so itself, in plain language: applications are judged by a panel, and when the judges disagree, Tarbell’s own staff make the final call on who gets paid and who walks away empty-handed. An organization that decides which pitches are worth thousands of dollars and which are worth nothing is exercising editorial power of the most consequential sort, and it is doing so before a single word has been published. You never have to editorialize a reporter’s copy when you get to choose which reporters are funded to file in the first place. The selection bias and the selection criteria sit in plain view on Tarbell’s own website, nudging applicants toward the safety pledges, the “dangerous capabilities,” and the corporate villainy that the doomer movement is most eager to see splashed across the internet.

This is how narrative engineering operates in the current era.. There is no public online memo that sleuths can dig up to show specific orders to the reporters Tarbell supports. Yet there is a grant program, a prestigious fellowship, a generous stipend, and an assignment desk with charity window dressing. All of it is purposed with steering some of the nation’s most influential newsrooms in a direction chosen by a handful of ideologically committed individuals. The reader who sees an LA Times, NBC News, Bloomberg, Guardian or WIRED byline has no way of knowing that the story exists at all because a Democratic megadonor’s foundation decided it was worth paying for.

None of this involves a smoke-filled room or a secret handshake. It requires only money, groups of deployed ideologues, and a firm editorial sense of which stories advance the cause. He who pays for the beat will, given enough time, shape the beat. This is not an act of charity. It’s an influence operation designed to achieve the objectives of the AI panic camp.

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The Party for Socialism and Liberation (PSL) has quietly become one of the most visible forces in the rapidly escalating war on American AI infrastructure. By a conservative count, PSL chapters have led or organized anti-data center protests in at least nine to ten distinct campaigns since late 2025. The Dossier found a significant presence in Prince George’s County, Maryland; East Charlotte, North Carolina; Tucson; Springfield, Illinois; Madison and Milwaukee; St. Louis; the Puente Hills; Atlanta’s DeKalb County; and northern Minnesota, among others.

In Landover, Maryland, PSL helped force a temporary moratorium after a string of rallies and press conferences. In Springfield, Illinois, the party turned out hundreds for a county board meeting that ultimately paused a major project. In Wisconsin, PSL co-led a “Beating the Data Centers Statewide Day of Action” that hit the Capitol and Milwaukee on the same day. The chants are nearly identical from one coast to the other: “Hey hey, ho ho, these data centers have got to go.”

This is the kind of grassroots-looking, professionally coordinated activism that gets results. It’s also worth asking who is paying for all of this.

Let’s follow the money to Shanghai.

PSL’s largest documented benefactor is Neville Roy Singham, a billionaire American-born far-left tech magnate who sold his consulting firm and now lives in Shanghai. The New York Times has reported that Singham operates from a shared workspace with a Chinese Communist Party propaganda outfit and has funneled enormous sums into a global network of nonprofits and media properties that consistently echo Beijing’s foreign policy line, from discrediting China’s cultural genocide against the Uyghurs, to anti-Taiwan talking points to anti-American framings of nearly every geopolitical contest.

PSL isn't exactly hiding the ball. In an April 28 manifesto on its flagship outlet Liberation News, the Singham-funded group demands what it calls "popular control of AI" (a euphemism for state control) and warns that the window to act is closing because once a technology gets entrenched under capitalism, the chance to dismantle it is gone. The piece declares America is captured by tech billionaires and casts data centers themselves as instruments of surveillance and extraction against working-class communities. The policy goal is straightforward: freeze, dismantle, or nationalize American compute infrastructure.

The Singham network has poured money into the People’s Forum in New York, BreakThrough News, Code Pink, and Tricontinental, organizations whose orbits substantially overlap with PSL’s leadership and messaging. PSL itself does not publish detailed donor disclosures, but congressional investigators have flagged the Singham network for possible Foreign Agents Registration Act violations, and House committees have been examining whether the relationship constitutes undisclosed foreign influence. House Ways and Means Chairman Jason Smith has set a May 18, 2026 deadline for the People’s Forum, BreakThrough News, and Tricontinental to turn over records on their funding sources, or face subpoenas.

Efforts to thwart American innovation are being pursued via a funding pipeline through a billionaire who now spends his days in Shanghai spearheading CCP propagandist efforts, and unsurprisingly, the organizations that he funds have positions on issues that perfectly align with the Chinese government. On Taiwan, AI competition, semiconductor policy, and now American data infrastructure, the Singham network converges perfectly with Beijing’s foreign policy. The House Oversight Committee has recently named PSL among the organizations it is examining in connection with Singham’s network.

Data centers are not just warehouses full of servers. They are the physical substrate of American technological development. In the view of both U.S. and Chinese policymakers, this buildout will help determine which superpower wins the next decade. The Chinese government has made AI dominance an explicit national priority. American hyperscalers (albeit imperfect vessels of American power) spending hundreds of billions on domestic data centers are an essential component of that competition.

Slowing these infrastructure projects down, through moratoriums, zoning fights, environmental challenges, and community pressure campaigns, has obvious strategic value to a geopolitical rival. The far-left’s framing wraps that delay in the language of anti-capitalism, anti-tech-billionaire populism (ironic, given their funding), and conservationist environmentalism. It is a flexible message that picks up genuine local concerns and channels them toward an outcome that would advantage the country where the party’s biggest funder lives.

None of this means homeowners worried about a substation in their backyard are foreign agents. Many of those concerns are entirely legitimate and they deserve a fair hearing. But the people who show up with the megaphones are quite often entirely disinterested in local priorities, and Americans have a right to know whose dollars are advancing those campaigns.

Congress has already opened the door. The FARA inquiries into the Singham network should proceed on the merits, with the same seriousness applied to any other foreign-influence investigation. Local journalists covering data center fights need to start asking tougher questions about who is organizing the rallies, and state legislatures considering moratoriums spurred by these campaigns should understand whose strategic interests they may be inadvertently serving.

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This is being marketed as compassionate foresight. It’s not. A UBI social welfare program would be the most costly and most destructive economic and societal initiative in American history, and one we should refuse on principle long before Congress could potentially entertain this path of ruin.

Let’s start with the foundational claim, that AI will produce permanent mass unemployment requiring permanent income replacement. There is no serious evidence this is happening. Anthropic’s own labor-market research has found no increase in unemployment in the occupations most exposed to AI. National unemployment sits at 4.3 percent. Software engineering job listings recently hit a three-year high. The Doomer narrative is rhetorical, not empirical, and notably, it is being pushed hardest by the people who stand to gain most from convincing the public that they need a massive regulatory and competitive moat to protect their technology.

History demolishes the displacement thesis. In 1900, roughly 40 percent of American workers were employed on farms. By 1980, that figure was 3.4 percent. Tractors, fertilizers, and irrigation collapsed agricultural labor demand by an order of magnitude. The result was not mass destitution. There was a rise of entire industries that the visionaries of 1900 could not have named: aviation, electronics, software, telecommunications, biotech. Each new wave of automation freed human capital to flow toward problems we had not previously had the bandwidth to solve. The Luddite fallacy is baed on a left wing assumption that the quantity of labor demanded is fixed, and it has been refuted in every generation. Somehow, every generation of central planners forgets this lesson.

Even granting the Doomers and Effective Altruists their worst-case scenario, a rough transitional decade in which displaced workers struggle to reskill, UBI is the worst available answer. It is not, as its boosters claim, a clever technocratic patch. It is straightforward socialist redistribution scheme. I know, UBI advocates get really upset when you properly label this idea as socialism. But yes, it’s socialism.

A mere $1,000 monthly payment to every American carries a price tag of roughly $4 trillion per year, equivalent to half the entire federal budget. There is no honest path to that revenue that does not involve a permanent and dramatic expansion of state power, federal taxation, and central economic planning. Once established, no such program has ever shrunk. UBI is not a bridge; it is a foundation, and the building that gets erected on top of it is bigger government in perpetuity. And it’s not like other government programs will be shut down to make up for the budget hole that UBI creates. It just never works that way.

The pilot data is incredibly damning. Trials in the United States have found that recipients work less and enjoy more leisure, but show little evidence of better entrepreneurship or lasting mental-health improvement. The promised burst of small-business creation and creative renaissance does not materialize. What materializes instead is that people consume the subsidy and reduce their economic output.

That last point should worry us most, and here is where Anthropic cofounder Olah’s framing should be turned back on him. The strongest case against UBI is not fiscal but moral. Work is not merely how people pay rent. It is so critical to how they build identity, structure time, form community, and compose a meaningful life. Of course, this doesn’t mean that people should engage in work for the sake of working. There needs to be a purpose to that work.

The Doomers’ UBI proposal takes the worst pathology of post-industrial America and offers it to everyone as policy, and it is being pushed by the very firms whose products will allegedly necessitate it. It is not a moral imperative, but a moral inversion of historic proportions.

Also, UBI lets frontier AI companies socialize the costs of their disruption while continuing to privatize the upside. The American taxpayer would be forced to absorb the workforce displacement. It is a remarkably tidy and economically beneficial arrangement for the people proposing it.

The honest response to AI’s potential labor-market effects is the opposite of what is being proposed. Instead of a UBI regime that fundamentally transforms America into a socialist nanny state, cut the regulations that block new industries from forming and get the federal boot off countless American industries. Free people and market forces will always adapt to change better than some massive, society immolating UBI program.

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We’re going to get into Sam’s new white paper, which traces a pretty alarming web of Chinese state media, CCP-aligned nonprofits like the Singham Network, and foreign billionaires who are pouring money into the campaign to slow down American AI and block data center build-out across the country. We’ll talk about how that influence is making its way into legislation (including the Bernie–AOC data center moratorium) what’s really at stake in the US-China AI race, and why Sam describes data centers as the “enriched uranium” of this generation’s defining technological competition.

Follow Sam Lyman on X: https://x.com/SamLyman33

The Bitcoin Policy Institute whitepaper: https://www.btcpolicy.org/articles/foreign-influence-in-the-campaign-against-american-ai

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In 2022, the Biden administration unveiled its signature tech policy: a sweeping set of export controls designed to choke off China’s access to advanced AI chips. The goal, at least on paper, was to preserve America’s qualitative advantage in Artificial Intelligence specifically by keeping the most powerful processors engineered by Nvidia, the indispensable flagship American AI company, out of Chinese data centers.

Four years later, the results are in.

Huawei, a key instrument for the Chinese Communist Party’s global tech ambitions, expects $12 billion in AI chip revenue this year, up from $7.5 billion in 2025. That’s a whopping 60-plus percent year-over-year growth, with orders already locked in from Chinese tech giants Alibaba, ByteDance, and Tencent. Nvidia’s market share in China? Its founder and longtime CEO Jensen Huang told an interviewer last month that it has fallen to zero. Yes, zero. “Nvidia had … 90-some odd percent of the world’s market share,” Huang said in the interview. “Today, in China, we have now dropped to zero.”

Another major American AI hardware and software company finds itself facing similar issues with global competitiveness. AMD makes a performance-capped chip designed specifically for the Chinese market because the chip is deliberately neutered to fall under export thresholds. AMD has been allowed to keep shipping into China, but the structure of the deal is itself is a mess. AMD is being permitted to occupy a small piece of the market that Beijing has not yet decided to close. It’s the same tier Nvidia briefly held with similar chips before Chinese regulators began pressuring buyers to refuse it.

And some members of Congress are making all of this worse. In April, a group of House lawmakers introduced the MATCH Act, which would follow the same aforementioned path to tightly control the export of chipmaking machines made by the Dutch firm ASML. The bill goes a step further than past rules: it would also stop ASML and big time American firms like Lam Research and Applied Materials from servicing the machines already installed in factories abroad. Some voices in Congress are not just trying to block new sales, but hoping to break down the supply chain entirely. Like its peers, ASML's China revenue has already collapsed from more than a third of its quarterly sales late last year to under a fifth this spring, and the MATCH Act would push it lower still. The MATCH Act, ostensibly written to slow China’s ambitions, will instead pay for it, and the bill will be paid by mostly American companies whose grip on Asia acted as a major piece of leverage against our adversaries.

So is America winning?

Unfortunately, the policies that are being promoted to handicap China’s AI ambitions instead handed Huawei the largest captive market in the world and forced some of the world’s most talented engineers to do exactly what Washington wanted to avoid most: China is building a credible domestic alternative to the American AI stack.

To understand why this matters, you have to understand how AI ecosystems work.

When a frontier AI model is built (think ChatGPT, Claude, Gemini, etc), its developers don’t just write code that runs on whatever hardware happens to be lying around. They optimize for a very specific, non swappable chip architecture. That optimization extends to the surrounding software, which involves the “stack” that turns metalloids into an entire AI system.

Nvidia’s edge over the past decade has not been chips alone. It has been CUDA, the software platform that hundreds of thousands of engineers know how to use and have built atop. Once your AI model is tuned for CUDA, every downstream piece of infrastructure comes with it. You cannot simply unplug any Nvidia GPU and replace it with a Huawei processor. The whole model has to be rebuilt and recalibrated for its engine. A switch would mean that the whole team has to be retrained and the whole ecosystem has to be migrated.

This is precisely what just happened in China, but in the wrong direction.

In April, the Chinese AI startup DeepSeek released its V4 model, an advanced system optimized not for CUDA but for Huawei’s CANN system. Their engineers worked directly with Huawei before launch, and reportedly, did not extend the same early access to Nvidia or AMD. Chinese tech giants Alibaba and Tencent deployed V4 services within hours of release.

Once Chinese cloud providers built their infrastructure around Huawei’s hardware and software, the cost of switching back to Nvidia became prohibitive. Huawei now reports more than four million developers on its CANN platform. Three years ago, that number was effectively zero.

Nvidia’s latest annual filing concedes what its founder has publicly stated, that the company is “effectively foreclosed from competing in China’s data center computing/compute market” and is booking no revenue from the broader region in its current outlook. Analysts project Nvidia’s share of China’s AI GPU market will settle around 8 percent or less in the coming years, down from 66 percent in 2024.

The AI race is a global contest. Every country is now trying to build serious AI capacity in some form. These countries now face a choice that did not meaningfully exist only two years ago. Huawei has been actively pitching Ascend chips and remote access to its CloudMatrix systems to Gulf states and Southeast Asia, while Washington’s tiered framework, which placed even close allies like Israel and India behind chip caps, pushed those governments to take the calls from our foremost adversary. If Riyadh’s national AI infrastructure or Jakarta’s data centers get built on Ascend silicon and CANN software, they will not be migrated back to American hardware in the next decade. Network territory generally works the same way everywhere: the tech stack that arrives first is usually the only one that stays, because swapping out and retraining is both cost prohibitive and burdensome on governments, bureaucracies, and private customers.

The strategic logic of America’s chip war assumed that China could not build its own alternative quickly enough to matter. That assumption is now being proven as incorrect. Huawei has rolled out its own high-bandwidth memory chips and Beijing is pushing for 70 percent domestic silicon wafer use. A fully integrated Chinese AI stack is no longer a hypothetical, but a very clear reality that we confront in our geopolitical decisionmaking today.

There is a lesson here that goes beyond one White House administration. America’s technological dominance is fueled by a system that leans into free enterprise and our founding ideals. It has never rested on what it forbids others from doing. It has rested on what its ecosystem makes irresistible to use. When the world’s developers build on American platforms, American influence compounds, not just commercially, but strategically. Of course, our most prestigious technology companies do not perfectly represent American domestic and national security interests, but they do so far more accurately than a Chinese counterpart ever will.

The Biden Administration’s export controls did the opposite of their intended effect. It spawned a domestic powerhouse industry within our adversary that will now seek to deploy its technology globally.

The Trump administration has signaled a willingness to revisit elements of Biden-era chip policy. It should. The question is no longer whether to slow China. Winning the AI race means allowing American companies, as mighty but imperfect extensions of American power, to be given the freedom to compete and win globally.

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Their headline policy ask, parked unobtrusively near the end of the piece, is the giveaway. “Congress should mandate audits of A.I. developers’ safety claims and processes,” they write, “requiring that they be conducted by independent expert bodies overseen by the government.”

That single sentence is the whole game.

Halfway through the column, a parenthetical notes that “Dr. Buchanan is an outside adviser to Anthropic,” which pretty much reveals that this “op-ed” is a corporate memo from Anthropic itself, given that Ball too has deployed rhetoric that is indistinguishable from the company’s policy posture (and works for the Foundation for American Innovation, which has become Anthropic’s chief defender in its battle with the Pentagon). The articles central piece of evidence (the case study the authors use to argue AI now threatens the homeland) is a product announcement from Anthropic itself. Claude Mythos, we are told, found “thousands of critical vulnerabilities” in foundational software, and “in the wrong hands” could be turned against power grids, hospitals, and banks. So one of the authors is paid by the company whose marketing material he is using as a national-security threat assessment to justify federal regulation that, conveniently, his client is already structured to comply with.

You don’t have to be cynical to notice that The New York Times published what amounts to paid advertising in op-ed form.

Ball and Buchanan would have you believe their proposed audit regime is a modest, common-sense guardrail. It is not. Mandatory third-party safety audits of AI developers, conducted by government-blessed “expert” bodies of political animals, are a textbook regulatory moat. They impose fixed compliance costs that scale beautifully for incumbents and crush everyone else. Anthropic, OpenAI, and Google can absorb a compliance bureaucracy without breaking a sweat. A team of seven engineers in Miami or Austin building a startup competitor cannot.

I’ve spend enough time in D.C. to know that this is how it always works. In finance, in tech, in pharmaceuticals, in energy, etc, the firms that lobby loudest for “responsible regulation” are the ones already sitting on top of the hill. Once you are the incumbent, the most valuable thing the government can sell you is a fence. This op-ed is a polite request for that fence, and the “national security” rhetoric is an attempt to scare the holdouts into submission.

And who, precisely, would staff these “independent expert bodies overseen by the government”? AI is still a small field. The pool of credentialed and somehow unaffiliated experts capable of evaluating frontier model safety lives almost entirely inside the same handful of companies the audits would govern, or in the academic and think-tank ecosystem those organizations underwrite. The revolving door would be in big time play here, similar to how pharmaceutical regulatory bodies are always staffed with individuals who were placed there to protect specific corporate interests. Anthropic in particular has spent years branding itself as the “safety-first” AI company, marketing its researchers as the responsible adults in the room. A federal audit regime would formalize that positioning into law. It would take the company’s existing internal practices, declaring them the federal standard, and forcing every competitor to either adopt them or exit the American market.

Notice also the asymmetry baked into the piece. Bioweapon risk and cyber catastrophe are described in vivid, urgent prose. They talk about power grids going down, hospitals breached, virologists outclassed by new LLMs. The threats (though they remain entirely hypothetical) that justify expanding the federal role are said to be concrete and imminent.

The “bipartisan” framing is the ultimate tell in Washington. Ball and Buchanan note, as if it were profound, that they served different presidents and still agree. Yet both have an overwhelming personal and professional interest in expanded federal involvement, because they ultimately answer to the same stakeholders. When two former White House staffers from opposing administrations converge on a policy, that is not some kind of automatic sign the policy is correct. Far from it.

Innovation does not happen because Congress mandates audits. It happens because builders are free to build, fail, iterate, and try again, without first having to be approved by a government-credentialed compliance body funded, staffed, and culturally captured by the firms it is supposedly overseeing. This domestic audit regime they recommend is a moat, dressed in safety language, written by men with a financial and professional interest in the moat being built.

Anthropic wants its AI moat, and I don’t blame them for playing the D.C. game of making their case through an endless series of Matryoshka doll cutouts. This is a company that could very well IPO at a valuation of well over a trillion dollars. Nonetheless, when it comes to probably the most important technological innovation category of today and the coming decades, allowing for competition and an open playing field in AI will be far more beneficial to the American people as a whole.

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