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All too often, we treat reliable electricity as something that will magically appear as a result of investors piling money into super intelligence chips and data centers.

To achieve President Trump’s vision of American energy and American SI dominance, we need to achieve an enormous expansion of reliable electricity generation. Our chief rival in China has no shortage of power. Nuclear power should be central to the effort to bridge the gap.

Scrolling through X today, I discovered a startup’s promising new proposal in eastern Kentucky, and it offers a powerful glimpse of what building at the necessary scale could mean for America’s future.

The Nuclear Company has announced Prosperity One, a proposed campus along the Ohio River in Lewis County, Kentucky that could accommodate six Westinghouse AP1000 reactors, producing approximately 6.6 gigawatts of electricity. If it comes to fruition, the campus would serve as the largest nuclear site in the United States. The U.S. nuclear fleet currently has a total net generating capacity of about 97 gigawatts, according to the U.S. Energy Information Administration.

America needs an energy policy that makes projects of this size possible, and the president has already established that he has bold plans for nuclear energy. His nuclear executive orders call for expanding American nuclear capacity from roughly 100 gigawatts to 400 gigawatts by 2050, alongside a goal of having ten new large reactors under construction by 2030.

Meeting these targets will require more than just booting back up outdated shuttered plants or improving the current fleet. We need to build new reactors at industrial scale, and unsurprisingly, nuclear has become one of the hottest spaces in American entrepreneurism today.

Prosperity One is especially interesting because it proposes using an established reactor technology rather than waiting for a future breakthrough. While theoretical future nuclear ambitions generate lots of intrigue from venture capitalists in the Bay Area, America can’t base our nuclear strategy on theoretical prospects. Seventeen AP1000 reactors are already operating or under construction across the world. The Nuclear Company’s broader strategy emphasizes standardized engineering and repeat construction: design once, build many.

For super intelligence, the case is rather straightforward. American technological infrastructure needs dependable electricity right now. Nuclear delivers enormous quantities of power around the clock without depending on whether the sun is shining or the wind is blowing. And it mitigates many of the concerns that arise when data centers are forced to install turbines to supply power to hyperscale data centers.

The White House has made clear that Americans should not be asked to accept higher household bills as the price of innovation. We just need to meet the demand with more supply.

What I like about the new proposal is that it wants to deploy the campus deep in coal country. It’s a place where solid jobs are often in short supply. The employment potential is substantial. Georgia Power reported that construction of two new reactors employed some 9,000 people. These large-reactor projects can significantly bolster economic value to distressed regions throughout the country.

For too long, the nuclear industry has been in a permanent state of paralysis. Despite the technology being both safe and incredibly efficient, Washington hasn’t done its part to let American builders strengthen our innovative capacity in the 21st century.

The significance of this project goes well beyond just The Nuclear Company but it serves as perhaps the largest manifestation of President Trump’s energy and super intelligence agenda. If we want to lead the super intelligence era, we need to deploy the buildout necessary to scale it.

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This time, however, leftist organizers are not pressuring social media companies like Meta and X. They’ve pivoted to “AI-safety.”

“AI-safety” as a whole is becoming a major political enterprise, having attracted countless millions from motivated ideologues who seek the reimposition of the authoritarian censorship apparatus that was on display during the coronavirus era.

Axios reports that “AI-safety” groups have spent $48 million thus far across Democratic and Republican races. One organization, called the Guardrails Alliance, is positioning itself as the voice for tech workers. It has already raised $11.7 million between its super PAC and its associated nonprofit.

Guardrails is just one of several pro-censorship organizations seeking to dominate the AI/SI policy space. These groups’ efforts highlight the true nature of these outfits.

Nonprofit filings identify Shaunna Thomas as its executive director. Thomas is a longtime ultra-progressive organizer who openly advocates for the reimposition of Trust and Safety. In her June announcement of Guardrails, Thomas identified Leah Hunt-Hendrix as her co-founder and board chair. Hunt-Hendrix is an heiress to the Hunt family oil dynasty. She has deployed much of her inherited wealth into progressive causes.

Thomas has a Substack that she uses to advocate for her preferred AI/SI policy ideas.

In a November 2025 Substack post, she explicitly laments that “Trust and safety teams” have been “dismantled” by “oligarchs” like Peter Thiel and Elon Musk.

She immediately called for “democratic government regulation” in the form of her preferred censorship apparatus. Her essay praises Europe’s regulatory approach and explicitly prioritizes “governance over growth.”

Thomas and her comrades are demanding government intervention in the AI/SI economy, which, of course, will cripple innovation but also has huge implications for speech in America. She and like-minded allies in the “AI-safety” movement want legally enforceable authority over dissidents.

Who could forget that we have already experienced this arrangement? It wasn’t even that long ago.

During the coronavirus-hysteria era, Jack Dorsey’s Twitter adopted rules requiring the removal of certain posts that contradicted “expert” guidance. An infamous March 2020 policyencompassed denial of that guidance from all-knowing health authorities like Anthony Fauci as grounds for suspension.

It’s not hard to foresee a future in which denying that Claude exists as a real person or denying adherence to certain progressive tenets about gender and morality could end in one being banished from the social media town square.

The AI-safety coalition wants to bring back an environment that saw the elevation of credentialed government authorities as arbiters of permissible speech.

During the coronavirus era, we witnessed Biden administration officials pressuring platforms over coronavirus content and eventually expanding their purview into election-related content. The AI-safety coalition is just the latest vehicle for consolidating power and clamping down on dissent.

The AI-safety movement is a political project masquerading as a mere request that engineers improve the safety of their products.

Preventing fraud in AI/SI, prosecuting abuse, and protecting people from unlawful discrimination are appropriate objectives. But those objectives are being manipulated to justify empowering an activist-regulatory apparatus to supervise a massive leap forward in technological progress.

Who decides whether a super intelligence model sufficiently advances the “common good”? Does an entrepreneur get to release a useful product, or must he first satisfy a Democratic Party bureaucracy’s preferred conception of social justice?

Those questions become especially important when the advocates seeking authority regard technological development as subordinate to their broader economic and ideological agenda.

In June, Thomas wrote that there should be no place for pro-innovation AI money in the Democratic Party.

Should a blue wave materialize, this movement will have big leverage over the winners.

The Trust and Safety movement is seeking renewed influence through the ballot box in November, and the regulatory-capture risk is obvious. Should Democrats come to power, they will employ a regulatory regime full of costly assessments, compliance obligations, and deployment restrictions that will favor frontier firms while crushing the upstarts.

Being pro-innovation doesn’t mean you have to blindly trust major technology executives. It means recognizing that innovation, competition, and widespread access offer a better path to American prosperity than permanent permission-seeking from political gatekeepers who want to impose a Trust and Safety political censorship regime upon the American people.

Originally published at American Greatness.

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There are enormous consequences for who wins this rhetorical match, as the victor will have great influence over the most consequential innovation since the internet.

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In the policy and politics world, these two respective universes fundamentally disagree about what kind of problem SI can pose to the world.

The SI doomers witness the development of increasingly capable SI models and chalk it up as evidence of increasingly sentient intelligence that will eventually become an uncontrollable monster. Essentially, what amounts to Frankenstein’s monster. They understand the real limitations in today’s systems and extrapolate to scenarios in which future systems are actively trying to deceive their operators without instructions, go “rogue,” and eventually threaten the whole of humanity.

On the other side, there are those who accept the reality that we are dealing with an incredibly potent and powerful technological breakthrough. And yes, it must be tested, monitored, and even restricted at times if engineers aren’t confident about their controls.

The former narrative dominates the discourse in Washington and the Bay Area.

The latter, however, is a real solution to a real problem instead of a theoretical development involving a future unknown.

The doomer worldview has influential advocates in Effective Altruist (EA) circles and among people associated with frontier SI companies, especially within the ranks of Anthropic and OpenAI and “third-party” like-minded evaluators like METR and Redwood Research. The humanizing rhetoric surrounding “rogue” models invites the public to imagine something closer to an emerging will than a system operating within the confines of engineering reality. The SI doomers are diverting from a problem we can solve—what did the system have access to?—to a sentient SI story about the wants and needs of an SI model.

I recently examined reports of SI models that had allegedly escaped test environments and reached real-world systems. If you are to absorb the corporate media take, the models had “broken containment” as if they had their own interests. But in our grounded reality, the concrete explanation was that testing environments were horribly misconfigured and allowed these advanced SI systems to acquire internet access. In every publicly examined incident of “rogue SI” breakouts, the cause was attributed to an improperly secured evaluation environment and not a conscious SI system. Software does not have an independent desire for freedom, but these kinds of stories are much more interesting to a corporate media that is all too happy to advance these nonsensical doomer talking points.

SI doomers have built an entire lexicon with incredibly loaded terms that are meant to advance their objectives. Consider the term “alignment.” To the uninitiated, it sounds like straightforward, innocent, uncomplicated language. Yet within the doomer discourse, alignment is the most loaded premise of all time. Doomers say that SI models are potentially capable of developing independent objectives akin to those of a sentient being. Alignment isn’t about software design. Instead, it focuses on whether humanity itself can retain control over a new form of intelligence.

SI “risk” is another severely loaded term in the doomer lexicon. Indeed, every novel technology has risks if the innovation leaps far ahead of our understanding of tackling the security parameters. But when SI doomers invoke “Risk,” they are often smuggling the notion of a hypothetical sentient SI that seeks human extinction into the conversation. Then SI “Safety” becomes the answer for this hypothetical “risk” event without any of the core premises being grounded in reality. If we take the bait and accept the doomers’ terms, they come to us with preferred solutions that are now “common sense” in the policy and politics world. This quickly turns into advocacy for restricting access to like-minded ideologues and delegating authority to a small circle of approved experts for the sake of humanity.

So often in these “breakout” scenarios breathlessly reported in the media, we find a not-so-subtle hint that can only be interpreted as a glimpse into the future of an autonomous adversary. Of course, it’s just not true. And by the time anyone more sober-minded can explain the prompts, permissions, tools, etc. that these systems involve, the public is manipulated into the sense that SI “went rogue” again. Policymakers in D.C. and doomer corporations in California then declare that ordinary technical controls are inadequate, and it must be solved with regulation, legislation, and the like. The conclusions are continually outrunning the evidence in front of us.

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Meanwhile, there are some great American companies building SI solutions for real SI risks and SI safety problems without the loaded doomer lexicon insinuations.

Palantir is innovating on an SI platform built around access controls, monitoring, controlled deployment, and human approval in consequential workflows. NVIDIA offers guardrail tools for detecting jailbreak attempts, restricting topics, and controlling the potential diversity of outputs.

We can’t guarantee that every future SI system will be perfectly safe. But there are real controls being built to handle the reality in front of us when models are becoming increasingly more capable. SI risk and SI safety are fundamentally engineering problems that require engineering solutions.

There is nothing wrong with working together freely and openly to tackle the problems of today and tomorrow. It’s a much better course than surrendering the future to a particular group of experts and delivering authority to dictate the pace and terms of the SI industry as a whole.

I don’t doubt that many of these doomer advocates are entirely sincere. Nonetheless, they are entirely delusional about SI sentience. And of course, sincerity does not erase incentives. A regulatory system built around elaborate safety mechanisms and approval regimes would protect incumbents like Anthropic and OpenSI while making it harder, if not impossible, for competitors to challenge them. Legislators and media observers should ask “who benefits?” from all of these proposals before simply accepting the fearmongering at face value.

The United States should not have to choose between a deployment free-for-all and a mutually credentialed cabal of SI doomers who believe innovation itself is a problem that needs to be thwarted.

With so much at stake, people in positions of power and influence have a responsibility to use terms much more precisely. Describing engineering failures as evidence of awakening Frankenstein’s monster does not make us safer, and it does nothing but obscure developing solutions that will allow us to advance human flourishing safely and securely.

Originally published at American Greatness

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AI Doomers are split over what the future looks like, and they surely have internal squabbles about how to navigate the narrative war, but they fundamentally agree about the idea that they should be the ones in charge.

There are two prominent AI Doomer camps. The first is the more hardcore ideological camp, which is heavily associated with effective altruists (EAs) in the San Francisco Bay Area. Its fiercest ideologues can be found on social media doing the Chicken Little act day in and day out about how AI will eventually wipe out humanity. To them, the “AI race” is a competition that creates unacceptable risk. So open research, open debate, and open AI models need to be counteracted by an authoritarian cabal of like-minded EAs.

In short, they believe that the values that made America the most prosperous and most exceptional nation to ever exist should not be extended to AI.

People whose values do not align are unacceptable risks to the future of humanity. If they can’t have AI progress halted entirely, they default to a tiny number of approved comrades who will be sanctioned to operate under extraordinary third-party supervision.

These are true believers who think that AI is an existential threat to humanity, and they’ve created a public policy and “alignment” ecosystem that defines moral behavior and what value systems can be embedded into AI models.

The second group of AI Doomers is much more corporate. They’re represented by AI frontier megacorps like Anthropic and its CEO Dario Amodei. They offer a commercially useful version of AI Doomerism, one that can help to hype a reportedly $2 trillion IPO. They also say that AI development presents existential risks, but luckily for us, those risks can be managed through their network and collaboration on a Trust and Safety regime.

Both camps of prominent AI Doomers come together on the notion that the right people need to be the ones in charge of our AI future.

I would argue that most AI Doomers in the field are genuinely sincere about the conclusions they’ve made about “AI risk.” They believe we are navigating through a high-stakes emergency, and they believe that only they are the responsible stewards of such a powerful technology.

The hardcore AI Doomers say the AI buildout should be halted entirely, but if this thing is truly inevitable, short of resorting to terrorist-like behavior (plenty of AI Doomers have advocated for such things), they concede that their friends in San Francisco are best suited to be the ones in charge. The Anthropic-style corporate narrative agrees that the frontier is dangerous, but “careful” institutions of “enlightened” like-minded individuals should “pace” it accordingly.

These two lanes are in complete and total agreement when they declare war on independent, open-source developers, smaller upstart AI companies, auditing shops that disagree with their premises, and the broader public that hasn’t bought into Doomer narratives wholesale.

The AI Doomers want to install a public-private class of permanent gatekeepers. Yes, the Doomer camps arrive at that conclusion by different routes, but both have singled out a free and open ecosystem, along with robust intellectual diversity and competition in the AI space as the problem.

Notable AI executives have called for an expanding “alignment” and “safety” apparatus to deal with AI risk. Some of this work indeed addresses genuine concerns, but “safety” is an exceptionally elastic label and we’ve seen it recklessly abused during the COVID panic era. “Safety” can cover preventing real and clear harms, but it can also cover deciding which opinions are valid for an AI model to train on and express.

Again, we have seen this pattern before. Who can forget how Big Tech’s Trust and Safety mechanisms began with concerns about “misinformation” only to turn into a Biden administration-endorsed censorship regime? We witnessed a small group of tech oligarchs who had the power to make sweeping, often opaque decisions about what users were allowed to see and express.

AI could take Trust and Safety to a whole new level if the AI Doomers get their way. These aspiring AI gatekeepers want the power to predetermine acceptable ways to research, write, code, and think.

The American public should be very wary of any proposals to further concentrate power into the hands of one or two AI companies and their preferred “third-party” expert associates. Once these institutions are empowered to write the rules, they can set up a regulatory capture mechanism to make it impossible to compete in the space. Then their models suddenly become essential infrastructure that is fused with the government.

We aren’t witnessing a secret conspiracy to centralize and control the future. The debate is playing out right before our eyes. By arguing that catastrophe is possible but manageable under their stewardship, the Doomers are laying the groundwork for a capture-and-control play.

AI is the most consequential technological innovation since the internet. The stakes of America’s future are too high to let Doomer cult members in San Francisco get their way in the form of a permissioned Trust and Safety apparatus.

AI undoubtedly has risks, and those risks can be solved by engineering, dialogue, open debate, and policy that incentivizes lawful action. We cannot let fear of the unknown be the justification for deciding to grant unlimited power to ideological fanatics in San Francisco.

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Originally Published in American Greatness

In a series of sprawling essays on his website, Amodei has outlined his expectations for a world transformed by powerful AI. His forecasts range from curing diseases and accelerating economic growth to creating catastrophic biological threats and destabilizing the balance of power between the United States and China.

These essays are presented as the work of a sober-minded technologist trying to navigate humanity through an unprecedented transition.

In the acknowledgments section, Amodei inadvertently reveals insight into the ideas forming his worldview.

Across four of his major essays—”Machines of Loving Grace,” “The Urgency of Interpretability,” “The Adolescence of Technology,” and “Policy on the AI Exponential”—Amodei thanks a recurring cast of advisers and intellectual collaborators. The list includes Tom McGrath, Martin Wattenberg, Chris Olah, Ben Buchanan, Kevin Esvelt, Parag Mallick, Stuart Ritchie, Matt Yglesias, Erik Brynjolfsson, Jim McClave, Allan Dafoe, Mariano-Florentino Cuéllar, Richard Fontaine, Buddy Shah, Vas Narasimhan, Nick Beckstead, Jason Matheny, and Brad Carson.

Amodei thanks this group for their contributions to his ideas, comments on his drafts, and help to strengthen his thinking.

Of course, these acknowledgments do not prove some kind of uniformity of worldview. However, they help us map his intellectual world.

And that world is remarkably homogeneous.

It includes, unsurprisingly, Anthropic insiders but also establishment academics, liberal policy experts, national-security think tankers, NGO executives, and prominent figures intertwined with the Effective Altruism (EA) movement.

Here are some of the more notable characters Dario Amodei has cited:

• Matt Yglesias is a high-profile liberal journalist.

• Ben Buchanan, an Anthropic adviser, served as a special adviser for AI at the Biden White House.

• Allan Dafoe is a prominent name in the Effective Altruism community, and he established one of its AI academic centers at Oxford.

• Nick Beckstead is a high-profile figure in the Effective Altruism network.

• Jason Matheny has deep, longstanding ties to the EA world, and he’s now president of the RAND Corporation.

• Richard Fontaine runs the left-leaning Center for a New American Security (CNAS), a major Democratic Party policymaker incubator in D.C.

• Mariano-Florentino Cuéllar is the chief global affairs official at Anthropic and has long been a staple in the Democratic Party legal world.

• Chris Olah is an Anthropic cofounder.

• Stuart Ritchie is the research communications lead at Anthropic.

• James “Jim” McClave is an early Anthropic investor who has long been embedded in the EA community. McClave reportedly made one of the largest 2022 contributions to Future Forward, a super PAC that supported Joe Biden.

• Neil “Buddy” Shah is the CEO of the Clinton Health Access Initiative.

• Brad Carson is a former Democratic congressman who served in senior positions in the Obama administration.

What is missing from this collection of contributors?

First and most obvious, there is no identifiable right-leaning intellectual, academic, or policymaker in the mix. Dario Amodei does not appear to consult with any White House-aligned voices, and few, if any, critics of centralized power or anyone skeptical of unverifiable international agreements with China.

We can’t find anyone publicly mentioned within Amodei’s brain trust who seems to recognize that global, U.N.-like institutions frequently fail or become quickly corrupted by a group of credentialed “experts” who inevitably just seek to increase their own power and status.

His brain trust is indeed diverse in professional specialization, but it’s painfully narrow in ideological diversity.

That likely explains the liberal-internationalist-meets-Effective-Altruist blend that runs through his writing and media appearances. Amodei combines the Effective Altruist obsession with extinction-level AI risks with the liberal internationalist worldview, which posits that an “expert” class can design more useful international institutions outside of America’s sovereign borders.

In “Machines of Loving Grace,” putting aside the hyper-pagan notion of a machine God, Amodei is quite optimistic about AI being used to advance a variety of fields that can result in human flourishing. The essay considers a near future in which powerful AI systems are making decades of scientific progress in just months or years.

In “The Adolescence of Technology,” however, Amodei concentrates on the darker side of the same exponential curve. He discusses autonomous AI, bioweapons, economic displacement, and authoritarian inputs that could threaten much of humanity. Consulting with his brain trust, Amodei is determined to construct systems capable of guiding us through this dangerous period of “adolescence.”

In “The Urgency of Interpretability,” he calls for transparency laws and strict export controls on AI chips to China. He argues, in consultation with his brain trust, that America could create enough breathing room to make powerful systems more understandable before geopolitical competition makes caution impossible.

Amodei isn’t wrong to point out that AI companies should definitely test their systems before public release. And it’s wise to continue dedicating resources to researching how to understand these novel systems.

Yet Amodei’s institutional reflex is visible throughout his writing. When he encounters something that is determined by his West Coast bubble as a risk, the “expert” brain trust fills in the gaps on policy and morality.

In his latest proposals, Amodei has floated something of a U.N.-style AI standards body and a Paris Climate Deal 2.0 with China.

Amodei told CBS, “The worry I have—I am concerned that one single government could abuse this technology just as easily as a single company could.”

He added, “But I think a combination of democratically elected governments—I don’t know about handing over, but some kind of oversight, some kind of joint governance.”

As for the China deal, he says the agreement must be verifiable. He even concedes that an AI pause is unlikely because the incentive to cheat would be enormous. Yet he still presses as if this is the best option. If that sounds like Hillary Clinton and Barack Obama, it’s not some accident of interpretation. He is using the liberal internationalist playbook.

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As the Paris climate agreement already showed, the Chinese Communist Party is not a good-faith participant in international agreements. It is an adversarial regime seeking technological, military, and geopolitical supremacy over the United States.

A climate change-style agreement is hard enough to verify. With AI, it’s even more difficult. Do we really think China is going to hand American inspectors a list of its most capable data centers, military facilities, intelligence-gathering sites, and a whole variety of other secret networks that are critical to its national AI program?

Amodei can see the problem, as evidenced in his writing, but his narrow intellectual brain trust prevents him from following it to its logical conclusion. He recognizes the behavior of adversarial states while retaining faith in the institutions that assume cooperation among them. And he wants to create new global government institutions that will supposedly solve these problems.

This is the reality of living and operating in the San Francisco tech bubble. Dario Amodei and his ideologically narrow group have introduced a series of highly elaborate ideas that have not been stress-tested by reality and history.

Everyone helping him answer complex questions comes from the same constellation of institutions, liberal policy shops, Effective Altruist-connected organizations, and technocratic philanthropy. His U.N. for AI and Paris 2.0 “solutions” reflect the blind spots in his thought process.

Before determining that he has all of the firepower to solve all of the big problems in AI, Dario Amodei should first consider expanding his own context window.

Originally published at American Greatness

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These forces operate within a network of high profile technology founders, employees, and activists. In order to appeal to the masses, they’ve historically presented themselves as mere neutral experts on AI, and simple dispassionate voices who were concerned about humanity and want to protect it from a supposed imminent apocalyptic scenario.

In reality, the AI doomers were quietly advancing a hyper political project with specific objectives. They want to act as gatekeepers of the AI future, while empowering a mutually credentialed set of approved individuals, corporations, and constructed international regulatory bodies, with the goal of harvesting complete control over perhaps the most important innovation of our time.

But they’ve overplayed their hand, badly.

The ongoing blitz campaign to “pace the frontier” of AI has exposed the doomers’ agenda. And it has awakened a powerful coalition of Americans that recognize everything that’s on the line if their gambit succeeds. What’s at stake? Just the future of economic abundance, American sovereignty, and the freedom to build out great ideas without permission of an unaccountable group of supposed experts.

Jacob Coxon, an AI researcher who had a remarkably short stint at Anthropic, helped trigger the latest panic by declaring that “the people building AI earnestly believe that it could kill us all by the end of the decade”. Coxon’s doomsaying has sparked tons of interest from primetime television, where he has laundered doomer narratives to the masses.

Suspiciously, Anthropic CEO Dario Amodei did not condemn Coxon. No, he subsequently said he agreed with Coxon.

Amodei’s recently published “pace the frontier” essay calls for deliberately slowing the development of AI through third-party monitors, blanket restrictions, government intervention, and eventually international coordination that would include China.

Amodei and his collaborators are clearly gunning for the creation of an AI cartel, one which would deliver incredible power to his ideological bubble.

Should his plan succeed, smaller competitors would face impossibly high compliance costs and it would freeze them out of the AI market. The incumbents that raced ahead (and now want to “pace”) in an open business environment want to pull the ladder up behind them.

Sam Altman, the founder of OpenAI, quickly endorsed Amodei’s ideas, writing that he agreed with Amodei about pacing the frontier and supported this notion of delivering access to third party evaluators (who just happen to be likeminded members of the San Francisco AI safety gang). Surprise!

Altman has also spent years advocating an international AI regulator modeled on the International Atomic Energy Agency, before backtracking on the idea after some considerable pushback. Now, apparently, he’s back on board and trying to help Amodei install this duopoly.

The duopoly seekers and their allies in the AI doomer world want what amounts to a U.N. for AI.

And because their supranational institution would be an international outfit, it would inevitably require negotiation with China over a global AI deal.

So the doomers now want both a U.N. for AI and a Paris Climate Deal 2.0 with China.

They want unilateral disarmament, and we’re supposed to just go along with it.

The doomers apparently expected the Trump Administration to just fall in line. Instead, they provoked a backlash from some of the most powerful political figures and influential pro AI voices in the country.

President Donald Trump told the nerds to go back to work. He responded with defiance by pushing for a faster American tempo in the AI race, directly rejecting demands for a slowdown.

Vice President JD Vance found a series of holes in the doomer play. He asked why the largest frontier companies are now begging the government to regulate them, likening the campaign to a possible “Trojan horse” that would protect incumbents under the guise of safety.

The U.S. Department of War (DOW) is pushing back too, with Pentagon CTO Emil Michael directly naming the Effective Altriusm ideology that poisons so much of the conversation in Tech. A military does not win by intentionally slowing its own technological development while hoping the adversary reciprocates.

Some of the most influential forces in America’s technology sector are pushing back too.

Nvidia CEO Jensen Huang has taken up the mantle as the tech world’s most fearless voice for sanity and human flourishing. At the All-In Summit, he described the fearmongering doomer campaign as “made up” nonsense. It’s worth watching the video below in its entirety:

Palantir is stepping up to the plate too and making the case for American AI sovereignty. Alex Karp and his company have boldly led on this front, rejecting the doomsday hypothesis about theoretical sentient AI systems while encouraging open source development and localized AI systems.

In recent months, these companies joined with major American technology corporations like Microsoft, Meta, IBM, Salesforce, and others in a call for keeping the AI industry open. They warned Congress against blanket restrictions on open-weight frontier models, arguing it would roll back human progress and it would create an unfair, lopsided playing field.

The ongoing doomer assault has unwittingly exposed the ugly side of the Effective Altruism/AI Doomer movement to the masses. As we’ve reported here in the Dossier, EA outfits have built an influential network in America around the notion of “existential risk” from AI. Their biggest donors, such as Kamala Harris megadonor Dustin Moskovitz (who also happens to be an early Anthropic investor), have directed untold millions (maybe billions at this point) toward AI-doom institutions.

The doomers hoped their targets would simply bend the knee and submit to their demands. But their campaign has backfired, and you can witness on social media and in official statements that it is producing robust organized opposition.

The doomers have awakened a sleeping giant. Many are discovering these nefarious, anticompetitive, and authoritarian actors in the AI space for the first time. Thankfully, we are now witnessing the creation of a continually expanding coalition that unites the Trump administration, America’s best thinkers and entrepreneurs, and citizens who believe America must be protected from those who would surrender our sovereignty to international committees and Chinese government bureaucrats.

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The more I learn about how AI works, the more I’ve come to prize the value of human creativity in the AI era, especially when it comes to writing.

AI is a revolutionary productivity tool, but it is not a replacement for human knowledge or input. The software can only go as far as the human behind the machine.

AI has many incredible applications, but AI writing is mediocre by design. It’s fine. Not great. Just fine.

It’s suitable for the vast majority of the population, especially since most people currently can’t identify the difference between AI writing, AI-assisted writing, and purely human, unassisted writing. Undoubtedly, there’s a place for all of these calibrations.

But there are a few reasons why AI models can’t, on their own, produce uniquely outstanding literature.

Let me explain:

Think of your favorite chatbot as a student who has read every book in circulation. That’s incredibly impressive. Your student is an encyclopedia of knowledge! You ask him a question, and his default job is simply to guess the next word. He’s very good at guessing, but that’s because, despite his wealth of knowledge, he’s inclined to be probabilistic and not unique. Sad! He knows that among a million writers, there is a significant chunk that will finish a sentence the same way, and that’s the decision he will use in his writing. So by default, he is brilliant but seeks to optimize an average. And he can’t, by design, break out of this mediocrity shell.

Major AI companies, like Anthropic, SpaceXAI, OpenAI, and the like, have hired thousands of people to train AI models and evaluate their answers. Whether they intend to or not, they are eliminating unique answers because they are seeking to install a reward mechanism that encourages the models to play it safe. AI is trained to be a teacher’s pet, one who calculates what the “teacher” (AI model trainer) prefers and decides to write that way to achieve the reward. AI writing is habitually mediocre because of this.

Moreover, all of the major American AI companies (and foreign ones, because they distill information from American labs) train their models using the same internet with similar processes. And when smaller upstarts build their own models, they train them on behemoths like ChatGPT, Claude, and Grok, which is much more cost-efficient, but it leads to the same problem. So their habits become everyone else’s habits. Despite the mess they’ve created, none of the big dogs in AI seem to want to hire great writers and editors to fix that institutional headache, probably because there isn’t much ROI involved. You can’t tell chatbots apart by their prose because it’s one big circular learning environment.

When a human being writes an article without assistance from AI, they inject creativity from their own life experience or imagination into the piece. If you tell an AI to “write an article” about something, it does not have an independent perspective, so it fills the space with pieces of information that have been spliced together from a variety of places. Despite the claims of delusional tech bros on the West Coast, AI models do not have the ability to think independently. AI models are very advanced software projects that operate under a very impressive but very non-human paradigm.

Fixing this problem is mostly above my pay grade. More and more content online is now written entirely by AI, so AI models are now training on AI writing at an increasing rate, which likely means that this mediocre writing problem will get worse before innovation arrives to make it better.

Due to the aforementioned institutional hurdles to creativity, it’s become clear to me that great human writing (with or without AI assistance) is needed now more than ever.

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Bill Gates, the guy who tried to destroy the world over the Wuhan sniffles, says it’s time to panic about AI. Should we?

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The billionaire Microsoft founder is very concerned about AI. He is concerned about our jobs, our families, our ability to think and reason about the issue, and of course, how AI impacts his precious climate change narrative. What he is not concerned about, apparently, is his own track record as a nanny state catastrophist.

In a several-thousand-word essay on his website, Gates tells us that the time to act on AI is now, well before any of his predictions come to fruition or go bust.

We have seen this movie. Gates was one of the chief antagonists for a national shutdown and forced compliance with vax mandates over the COVID-hysteria years. As someone who covered this beat closely, it’s easy to recall the Gates-funded Imperial College model that tried to panic the masses by projecting millions of American deaths in the absence of sweeping lockdowns. Gates and his underlings went on TV and demanded sweeping shutdowns. He got his way, and it resulted in millions of American businesses destroyed and American families torn apart, for no reason whatsoever. He has shown no remorse and has simply moved on to the next current thing, AI, which apparently demands his infinite wisdom.

The bill came due in tragic fashion. The average American student remains significantly behind pre-COVID achievement levels in math and reading, with the gap widest in the poorest places in the country. Some student metrics fell to their lowest point in decades. The policies that Gates demanded hit hardest on the people who could least afford it.

Not everyone was hurt during the COVID years. Gates, for his part, made a massive windfall on his early investments in mRNA vaccines. Once an mRNA hype man, he later conceded that his “miracle cure” shots weren’t actually useful, and he simply moved on to the next issue.

Now, in 2026, the AI era is here, and Bill Gates is back demanding a centrally planned response to AI innovation. For Gates watchers, it’s easy to notice that the policy structure of his arguments hasn’t changed.

Another new threat that is “unprecedented.” The public is “underestimating” it. Existing institutions are inadequate. New institutions must be built. Humiliating ourselves before China is again necessary. And time is of the essence. We must act right now before it’s too late. We can’t wait for this apparent catastrophe. We must preempt it like the Bush Doctrine in Iraq.

In his essay, Gates says that he wants a sweeping domestic apparatus with authority spanning employment, education, taxation, energy, elections, public health, finance, law enforcement, transportation, and public lands. But that’s still not enough. He also wants to install a new national and global regulatory body. He offers the post-9/11 government reorganization as his benchmark. Who knew the TSA was so popular? Well, Gates apparently wants the equivalent of a Patriot Act and TSA for AI. Hold his vegan, non-GMO, toxic sludge beer, Dario Amodei.

In his infinite central planning wisdom, Gates says it’s time to have jobs reserved by government decree. He calls them “Human Reserved” jobs. To his credit, Gates lists some objections himself but doesn’t really answer his own critiques. He moves forward with the proposal anyway, declaring it “will need to be worked out in public” after it’s implemented. It’s similar to the Pelosi-ism of “pass it so you can find out what’s in it.”

Next, Gates wants to tax AI tokens and robots. He concedes it isn’t economically efficient, but the man with a $100 billion-plus net worth argues “we” can afford the inefficiency because innovation will make up for it. It would “slow the rush away from human labor a little,” he says. The flaw with this argument is that the government would somehow be expected to devote that new tax revenue to something worthwhile. In reality, he is just arguing that America should slow down innovation because he feels bad vibes about human progress right now.

Then there is the China appeal. Gates writes that “some cooperation between the U.S. and China will be required” and holds up Beijing’s AI rules as the world’s most advanced. This is the same guy who argued that America should embrace the ruthless Wuhan lockdowns. Gates has repeatedly praised the Chinese Communist Party’s governance, which he seems to love because of the iron grip the Central Party maintains over the population. We have run “cooperation” experiments with China before, and it has resulted in America being bamboozed by Beijing. Under the Obama-era Paris Agreement, China pledged to curb emissions before 2030 (China never made any concessions), while the United States accepted immediate costs and paid out billions to meet the new standards. The Gates framework will be more of the same.

Gates does concede that AI will bring us great things for humanity, such as cheaper medicine, more accurate diagnostics, productivity for farmers, competent legal and financial help for people who could never afford either, and more. But he says it’s more important to adhere to his nanny state agenda, because the catastrophist has strong feelings about the trajectory it is on. Those positive outcomes he lists are only possible through open markets and free competition, not through a global authority chaired by men like Bill Gates, who were catastrophically wrong the last time they wielded enormous authority and paid no price for it.

The choices we make now are indeed critical. Our first choice should be to stop listening to Bill Gates.

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Not so long after the piece was published, journalists ran the column through Pangram, an AI-detection tool (which is also now embedded in Substack). The article received a 100% AI generated score.

When reached for comment, Druckenmiller doubled down on his use of AI. [Though I suppose he didn’t double down because he didn’t acknowledge it when the piece was published.] “Of course I used AI,” he said, adding that he’s “not embarrassed by it,” and that he now writes with AI “for the same reason I use a calculator when I do math problems.”

“My name is on the piece. It’s my message,” he declared.

Wall Street Journal opinion editor Paul Gigot, clearly put in an awkward position by editors who grossly failed him (given that the article was so clearly identifiable as AI), defended the piece. In a statement to the media, Gigot said “AI is a fact of modern life” and “nobody can doubt that his op-ed is his genuine opinion.”

The problem isn’t the use of AI. It’s that an S-tier media publication would have such low standards for the use of AI. I have no objection to writers using AI. I think it’s an excellent research assistant and productivity tool. It’s an even better editor for grammar, content, clarity, etc. If Druckenmiller had fed an initial prompt into Claude or GPT to start making his case, and then had his team do a little back and forth to tighten up his argument, I wouldn’t have much of a problem with what he did here.

Druckenmiller basically one-shotted the whole thing, as evidenced by his 100 percent AI score on Pangram and my understanding of what AI writing looks like. This thing wasn’t ever even touched by a human. This wasn’t even an “AI-assisted” piece. A prompt went in and the essay came out. There was no effort or energy dedicated to such a high-stakes op-ed.

Druckenmiller’s calculator analogy is clever but wrong. A calculator does not make an argument for you. It just computes math problems that would remain identical to the product that you would do by hand, just with a faster output through technology.

The op-ed blunder is the exact opposite of the calculator analogy. He basically licensed his name to a large language model and signed off on the result. Druckenmiller outsourced his own thinking to AI, but tried to keep the credit to himself.

I had an interesing back and forth with the chief economics correspondent of the Journal here:

I’m sure Druckenmiller really does believe that Bessent is wrong about bond buybacks and the like. He’s on CNBC all the time delivering similar sentiments, but it’s not an issue I’m super familiar with and the point of this discussion has nothing to do with the merits of the case. Nobody subscribes to the Wall Street Journal to read op-eds that kind of sort of capture the rudimentary sentiments of influential people. They read it because they want to absorb, digest, and distribute the high-level reasoning that makes its way to print.

The Wall Street Journal is making a mistake by legitimizing low-effort slop from high-status people who are trying to shape the public debate. This is the paper of record for American markets. Its editorial page should be a place where ideas are buttoned up and independent of an overreliance on software. Gigot shouldn’t accept a new standard that allows for influential people and organizations to deliver minimal effort, especially when they have incredible resources at their disposal to dedicate time and energy to the process of publishing an op-ed.

AI is a tool that when used well, can very much elevate published work and make it just as authentic as before. Used the way it was used here, it produces nothing more than slop.

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Originally I believe I was supposed to debate Glenn Greenwald on these issues. My opponent later became Harrison Smith, a popular commentator in the right leaning conspiracist/dissident right space. It was moderated by popular Rumble podcaster Viva Frei.

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It became apparent early on that Harrison had very few facts to work with so he began by trying to smear me as a foreign agent for Israel and then proceeded to use vague language about all of this being a plot to impose a global surveillance state. It was clear that he didn’t really have any good information other than a couple anecdotal pieces of news. It was akin to debating the horseshoe right version of AOC. It was a good reminder that are not purely about facts, but convincing people that my side of the argument is also reasonable and morally sound.

I thought it was important to debate these issues because so many have become consumed by a hysteria that is entirely detached from reality. And I’m happy to take the unpopular position (which is currently the case on a lot of these topics) as long as I believe it is truthful and the right thing to do.

I’d love to participate in more debates, but take it easy on me because I don’t do it often! Would love to know what you all think, and feel free to drop any recs for who I should debate next. I appreciate your thoughts and value your opinions, whether you agree or disagree with my views.

Here’s a YouTube link to the debate in full:

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Surprise surprise. There’s another AI panic sweeping through Washington this month, and it is not holding up to basic scrutiny. Headline after headline has declared that AI models have “escaped” their test environments, gone rogue, and hacked real companies without the consent of their operators. Endless cable news and web-based tech media segments have leaned into the panic narratives, which basically amounts to the idea that the AI software is becoming sentient and betraying its human masters. If it was remotely true, it would make for quite a tale, and it would be sure to create lots of hysteria and demands from lawmakers to regulate AI. However, once you scrutinize the sources of these claims, it boils down to the simple fact that a single partner firm made the same error over and over again.

There were five “incidents” in question over the past month or so.

Anthropic says it reviewed 141,006 interactions in which its Claude models could have reached the open internet during cybersecurity testing, and found three cases where a model supposedly wandered outside its simulated environment and broke out of the sandbox to target real infrastructure belonging to three separate organizations. However, what we really find is that the model did exactly what it was told to do in the exercise. The exercise just was not actually contained in the way it was supposed to be.

Another case from August involved an OpenAI model connecting to the internet during an evaluation and compromising the website of an outside institution. As with Anthropic, it comes down to the same root cause: a misconfigured testing environment that let the model reach the internet, because internet access was available to it.

Meta’s Muse Spark 1.1 model broke into an outside company’s systems during a cybersecurity evaluation. In a recent statement, Meta said it was “a misconfiguration” that “inadvertently allowed one of our models access to the internet during evaluation.”

All five “incidents” were the fault of the same partner, a startup cybersecurity testing firm called Irregular.

For whatever reason, all three companies are using the same contractor to test their frontier models. I don’t have the cybersecurity expertise or knowledge to explain why that is. Perhaps they have a unique technological advantage.

An Irregular spokesperson has already made clear that these non-incident incidents “did not involve a sandbox escape or a sophisticated cyber action.”

So no, AI software did not independently think its way out of supermax confinement, as the media has continued breathlessly reporting.

“A contractor screwed up” and “an AI decided to break free and pursue its own agenda” are two entirely different stories with massive implications for the latter, and only the former is actually supported by evidence. Yet the impression that the latter has occurred has caused all kinds of panic in the halls of power.

Some prominent voices in the cybersecurity world have already expressed skepticism about the new AI panic. Ledger CTO Charles Guillemet described the ongoing news cycle as “marketing theatre,” arguing that having a model “go rogue” has become akin to a test of whether you remain on the frontier. Sorry, Google!

This comes on the heels of the new push from some of these forces to “pace the frontier” and convince lawmakers to grant them unprecedented power to create something of an AI “expert” cartel.

We shouldn’t rule out that self-directed system are possible down the road. Yet a hypothetical situation has been narrative-laundered into a concocted real-life scenario. All these “incidents” prove is that Irregular should probably fix its repeatedly broken testing infrastructure.

Anthropic and OpenAI are two of the fastest-growing companies in American history. They don’t need the White House and Congress to protect them. If Anthropic and OpenAI genuinely believe that they are going too fast and unleashing some mythical monster, they have every resource in the world to tackle it themselves or simply slow their own pace. The fact that they would rather lobby the government to write new rules for them should tell us a lot about what they’re trying to accomplish in D.C.

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The United States is in the early innings of an AI-powered economic boom, but if we embrace the degrowth doomers and stop building, the boom stops with us, and Beijing is more than happy to take our place.

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Here’s the state of play in 2026:

AI-adjacent companies accounted for more than 80 percent of the S&P 500’s gains this year, leaving the index with virtually zero gains without them. Over the course of President Trump’s second term, the trend becomes even clearer. From May 2024 to June 2026, the S&P 500 gained 142 percent.

Now, if we remove the AI stocks from the equation, that number collapses to just 16 percent, which is just about on par with the pace of inflation, or even lower, depending on who you ask. AI-linked companies now make up almost half of the entire index. And that’s not because the market is driven by pure hype and a lack of fundamentals. The AI sector is producing at an unprecedented pace of innovation, and markets are rewarding companies participating in that reality.

Chip companies, data center hosts and builders, energy providers, and software corporations are among the dominant categories turning AI into real products and services. They are the ones putting the American economy and Americans’ retirement accounts on their backs. At the same time, the non-AI-associated economy is struggling, through a combination of inflation, rapidly increasing debt, an insecure housing market, among other factors

America’s AI engine is giving us the potential to elevate human flourishing to new heights. Without it, we could very well be staring down the potential of a long, crippling downturn.

The pace of innovation is unlike anything we’ve ever seen, and it’s worth digging into the numbers to make that clear.

The five biggest American tech companies alone plan to spend over $600 billion on infrastructure by the end of 2026. That is more than the annual GDP of the vast majority of countries, deployed in a single year, by a handful of American companies. While AI doomers and populist degrowthers want to merely chalk it up as some kind of giant scam, the exact opposite is true. This is the result of market demand, and additionally, real, exponential consumer demand. Despite wavering public opinion on AI, take a look at your app store, and you’ll see that the public wants to use these tools, and it finds them greatly useful to their personal and professional endeavors.

According to a McKinsey study, companies using AI are slashing logistics costs by 5 to 20 percent, inventory by 20 to 30 percent, and procurement spending by 5 to 15 percent. Additionally, a June 2026 AI Adoption Study surveyed supply chain leaders across North America and Europe and found that supplementing with AI-driven decisions represents roughly a $55 million opportunity for a $1 billion company. Thanks to AI, it will cost increasingly less to make things and to move things. This matters greatly in an era when families are battling inflation and a mixed bag of policy coming from D.C. Cheaper logistics means cheaper groceries, cheaper shipping, and cheaper everything, really.

Health care and medicine applications in AI are just starting to take off, and they’re already showing great promise. There are now more than 170 AI-discovered drug programs in human clinical trials, with 15 to 20 expected to enter final-stage trials this year alone. Moreover, AI-discovered drugs are currently passing Phase I safety trials at twice the rate of traditionally discovered processes. Health care costs have been a major political and policy issue in the post-Obamacare era, and tragically, these struggles have been making life incredibly difficult for many American families. AI has the technological capacity to reduce the harm of bad economic policy that limits choice and stifles innovation.

On the “solopreneur” front, AI is making it possible for individual Americans to have virtually unlimited productivity and efficiency tools at their disposal.

In May 2026, American “solopreneurs” filed around half a million new business applications. There are now almost 30 million nonemployer businesses in America generating trillions in business. A study conducted by Stripe found that AI is chiefly responsible for the solopreneurboom.

All you need is a laptop and an internet connection, and anyone in America can weaponize AI to do work that once required entire departments. With a little AI assist, you can now do your own marketing, design your own products, and “vibe code” your own website. Millions of Americans are building small businesses with tools that used to cost a fortune and/or were not accessible to the masses.

We don’t appreciate data centers enough. More politicians and policymakers should understand that we need to have robust physical infrastructure in place to ensure the viability of our economic system. Data centers are, without question, the heart of the modern American technological economy in 2026. I call it American technological infrastructure, because these are literally the physical factories of the intelligence age.

If we do not build them, the consequences are immediately apparent. Without AI compute infrastructure, America cannot scale an AI economy. Without an AI economy, the one engine pulling the U.S. market forward will stall out, and it doesn’t take Milton Friedman to figure out that we will almost certainly face the real prospect of a debilitating recession.

China is not waiting for us to figure out how to stay on top here. Beijing has made data centers a national strategic priority, and its capacity is on track to nearly double to 60 gigawatts by 2030. China is electricity-rich, and its data centers pay less than half what American facilities pay for electricity. The AI race will be won by whoever capitalizes on the opportunity to scale compute and generate power for the physical infrastructure of the AI age. If America loses this race, we lose the commanding heights of the global economy to our fiercest competitor, which, of course, happens to be an authoritarian one-party state with polar opposite founding principles to those of the United States.

Lawmakers in D.C. do not need to subsidize this revolution with infinite loopholes and pork legislation and the like. They need to just stop strangling innovation and let markets work.

Our best and brightest business leaders want to build the infrastructure necessary to keep America atop the global hierarchy. We should just let them cook.

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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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