Everyone—you, me, politicians, Wall Street, tech people, philosophers—is a little bit scared and dazzled by AI. This is natural. Nobody quite knows if it will kill humanity or cure cancer, destroy all jobs or create infinite prosperity, be a pivotal moment of planetary history or a glorified office assistant. All of the above? Finding out is the fun part!
Unfortunately, this very normal uncertainty about the technological future of AI has bled into some unnecessary political uncertainty about how to approach AI regulation. Some of this, of course, is the usual consequence of corporate influence-buying to insulate themselves from all restraint. But another factor is that the flashy unpredictability of AI seems to be convincing political leaders and a concerned public alike that our current tool set is not up to the task—that this exotic new industry will require an equally exotic new regulatory approach.
This is untrue. It is also damaging the public interest, because it causes a delay in getting some solid regulations on the books. That delay is not only wildly unsafe, but also allows AI companies to race ahead with little oversight, laying the groundwork for the classic “Well, we’ve already come this far, so we can’t go back” style of corporate regulation-dodging.
Perhaps the best example of this somewhat confused approach to AI oversight is Bernie Sanders’ proposal for the federal government to take a 50% stake in the biggest AI companies, and use the proceeds to create a sovereign wealth fund. I have written before about why this is not the best idea. I apologize for returning to the same topic again, but, shockingly, my last piece did not cause Bernie to drop his plan and rally to my side. It feels worth one more stab at clarity on this issue. If progressives genuinely want to get ahead of the dangerous consequences of unchecked AI—and I know that they do—it’s important for all of us to know that everything we need to do so is right there waiting for us.
In my lifetime, we have already witnessed the full arc of a powerful new industry growing up and taking over the world with insufficient regulation. That would be the tech industry. The failure of the US government and of organized labor to get ahead of the tech industry’s wild growth has produced: A crisis of economic inequality; an outright oligarchy with centibillionaire tech executives at the top of pyramid; a near-total absence of labor unions in the world’s richest industry; and massive psychological and societal damage as a result of unregulated social media and algorithms assaulting the overmatched human attention span. Collectively, it is safe to say that the way that the tech industry’s growth has played out this century is not something we want to repeat.
AI, for all of its novelty, is the latest iteration of the tech industry. It has the same explosive economic growth, creeping disruption of existing industries, and grandiose claims to being different from all that has come before. Now is the time for us to recognize that we have three tried and true tools at our disposal to prevent AI from becoming a socioeconomic rerun of the devastating example of the tech industry.
Taxes
Taxes. Yes! The government can levy taxes on companies. Are you afraid that unaccountable and soulless corporations are growing too powerful because they are making too much money? Tax them. This leaves them with less money. It leaves their potentially oligarchical owners with less money, too. Great.
Compare “raising corporate taxes” to “having the federal government take 50% of the equity of select large AI companies.” The first option has a number of advantages over the second. For one thing, taxes fall on all companies across the board, or of a certain size. There is no need to guess at which companies will be successful, or for the government to risk locking in the current dominance of a handful of companies by becoming shareholders in them. The companies can do what they do, and their position in the markets can rise and fall as it will. Don’t want ultra-powerful AI companies coming to dominate the economy? Tax their money away. Don’t want AI company CEOs becoming trillionaires? Tax their money away. Don’t want corrupt Trumpian administrations using their stakes in corporations as a slush fund? Don’t want to put the American public in the absurd position of saying, “Oh no, we must bail out OpenAI because we are all shareholders in it, and we want it to do well?” Don’t make the American public shareholders in these companies, then! Just tax them. And if you want to make a particular outcome like, for example, “automating all the customer service jobs” less economically attractive, you can tax that specific thing as well. It is a simpler, more direct, and more powerful way to accomplish what Bernie is trying to accomplish, without the potential pitfalls.
But, uh oh—what if taxes are not enough to stop these AI companies from doing bad horrible profitable things?
Laws
Laws. Yes! The government can pass laws that prevent the AI companies from doing things. Don’t want them releasing dangerous new models without government oversight? Don’t want them doing autonomous killer drones? Want to make sure there is disclosure if AI is used in media or entertainment? Want to keep AI slop out of public education? Pass a law. Taxes can change the economic incentive for companies to do things, and laws can stop them from doing things at all. Together, taxes and laws are what “regulation” means. I will not go on and on about this, because it is pretty straightforward. It is familiar. It is a regime that already exists.
When you realize that the federal government has the ability to levy taxes and pass laws, it becomes clear how misguided and unnecessary the idea of becoming an equity shareholder in AI companies is. If the government wants half of Anthropic’s money, it does not need to hold stock in the company; it can just tax it away. If the government wants to stop OpenAI from doing something bad, it does not need to go into the boardroom and say “you better listen to me because I’m a big shareholder!” No; it simply needs to pass a law. The federal government is not a person that needs to build up a big war chest of stock in order to throw its weight around with corporate America. The government is an entity charged with protecting the public good, that sits above corporations, and is empowered to take their money and set rules governing their conduct as it sees fit.
My argument is not that it is politically easy to regulate the AI industry; it is that we should pursue a method of regulation that is the best and most effective and has the least downsides. That method is taxes and laws. It is not “having the government go into the AI business.”
Unions
Unions. Yes! Labor unions. One woefully underdiscussed reason why the tech industry has created such profound economic inequality and has operated with such grotesque impunity is that virtually none of the major tech companies are unionized. This fact has allowed the company owners to hoover up bazillions in profits that would have otherwise been shared widely with hundreds of thousands of employees. It has allowed people like Mark Zuckerberg to pursue decisions that range from wasteful (the Metaverse) to morally horrific (enabling ethnic violence) with little effective internal pushback. The government clearly had no ability to or interest in preventing these and other bad tech company actions. Do you know what could have, though? A union.
Unions create a power center inside of companies that is separate from both the government and the management of those companies. Unions are not perfect, but they are the single most effective check on corporate power when they are strong. Had the tech industry been widely unionized, America’s economic inequality today would be drastically less, and the power of tech billionaires would be vastly reduced. Also, the labor movement itself, which has been weakening since the mid-20th century, would be significantly more influential both politically and economically, which would change our entire political landscape and could well have prevented the Trump era from happening altogether. It’s a big deal. I won’t go on about this forever, but there’s a book you can read that expands this argument.
Recognizing the potential of unions inside the major AI companies to mitigate some of the worst outcomes of the industry’s evolution, we can make reforms that make it easier to organize and sustain unions a bedrock part of our overall approach to AI regulation. If we really think it’s important, we can even pursue mandatory measures like reserving a significant chunk of board seats for worker representatives at these companies, as Germany does. It’s ridiculous for the federal government to be involved in boardroom agitation—but it is incredibly healthy for workers to do so.
AI… so new! So powerful! So unpredictable! However shall we regulate it, make it safe, channel it in the best interests of humanity? My friends, we can do it. In the most boring ways possible. In ways that already have centuries-long track records of being effective. We tax the companies. We pass laws to regulate their conduct. And we empower the workers at the companies to unionize and act as a check on the power of the cutthroat bosses. This stuff works. My plea—to Bernie, to progressives, to everyone with common sense who is nervous about how the AI industry is going to fuck us all up—is for us to focus on these powerful tools that we already have, rather than wasting more time brainstorming needlessly elaborate new tactics.
When Donald Trump and Xi Jinping walked side by side through the Temple of Heaven in May, the headlines went to Taiwan, to tariffs, to Nvidia’s chips. The thing that may prove to matter most barely registered. Only afterward, almost in passing, did mention it to reporters on Air Force One: he and Xi had talked about “possibly working together” on guardrails for artificial intelligence – and, he acknowledged when pressed, on the kinds of risks neither side may be able to contain once the technology is built.
That conversation, however elliptical, marks a genuine inflection point. Not because it produced an agreement, but because it revealed something that the “AI arms race” narrative has obscured: both Washington and Beijing are more uncertain about what they’ve built than about what the other side has built.
Beijing’s 2-trillion-yuan blueprint to build a nationwide AI infrastructure network, mandating 80 percent reliance on domestic suppliers like Huawei, looks at first like a declaration of technological total war – a calculated squeeze on Nvidia and AMD. The framing practically writes itself. Rival superpowers. Digital hegemony. A new Cold War fought in silicon rather than steel.
But the architecture of the plan tells a different story. The emphasis on domestic supply chains is not an offensive posture. It is a bunker. China is not building toward dominance so much as insulating itself against dependency – hedging against the possibility that the technology it is racing to develop might be turned against it, or might simply get away from it. That is a different kind of fear than we are used to hearing about.
The same anxiety is audible in Washington, if you know where to listen. Treasury Secretary Scott Bessent – whose portfolio is the financial system – has warned that frontier models could be turned to malicious ends by nonstate actors, and has pressed for a US-China protocol to guard against it. The Pentagon’s guidance on military AI was notable less for what it proposed than for what it insisted on preserving: human beings in the decision loop, especially where nuclear command and control is concerned. Chinese and American officials, it turns out, are unnerved by the same scenario – a crisis in which neither side is confident it can tell whether an autonomous system has made a decision, or simply made an error.
This convergence does not mean the two countries trust each other. They don’t. Chip export controls remain in place. Chinese labs are advancing rapidly on models designed to route around American restrictions. The competition is real, and in many domains it is intensifying.
But competition and restraint are not opposites, and the emerging reality is more complicated than either hawks or optimists tend to acknowledge. What is taking shape between Washington and Beijing is not d̩tente Рno treaty was signed in Beijing, and the first bilateral AI dialogue in Geneva in 2024 collapsed almost immediately under the weight of incompatible expectations. What is taking shape is something more provisional and more fragile: a shared reluctance to be the party that tips an already unstable system into genuine chaos.
Call it a Cold Peace. It is not a doctrine. It is not even an agreement. It is a posture – maintained not by trust but by mutual anxiety about what comes next if restraint breaks down.
The Cold Peace has already begun reshaping markets and industries, often invisibly. Venture capital firms in Silicon Valley are quietly recalibrating portfolios to hedge against regulatory slowdown, betting that governments will impose friction on frontier model deployment before the technology fully matures. In Beijing and Shenzhen, compliance reviews have lengthened development cycles for autonomous systems – not because regulators are opposed to the technology, but because no one is confident yet about who bears liability when an algorithm fails at scale. These are not dramatic reversals. They are adjustments, the kind that accumulate before anyone has named what is happening.
The rare earth ban on ten American companies announced in late June – targeting MP Materials and USA Rare Earth alongside US defense contractors – illustrates precisely this dynamic. Analysts called it symbolic retaliation for the Pentagon’s own blacklisting of Chinese tech giants like Alibaba and Baidu. But “symbolic” is doing a lot of work. The move came just five weeks after the Temple of Heaven summit, and it exposed the fragility of whatever goodwill was generated there. China controls over 90 percent of rare earth refining – the same materials that go into the data center hardware, autonomous systems, and defense electronics at the center of the AI competition. The Cold Peace does not prevent these moves. It only ensures they are calibrated carefully enough not to tip into something worse. That is a thin margin.
The deeper irony is that the AI race may be the first great-power competition in modern history where the rivals are more uncertain about the systems they’ve built than about the intentions of the other side. The nuclear age produced a similar reckoning, eventually – Eisenhower’s warning about the danger of a garrison state, Kennedy’s confrontation with the logic of mutual assured destruction. But that reckoning took decades and several near-catastrophes to arrive at. The AI reckoning is arriving faster, partly because the technology moves faster, and partly because its failure modes are less predictable than a missile trajectory.
The question now is whether fear is a durable enough foundation for stability. History suggests it is not – or not for long. The absence of escalation today is not a guarantee of equilibrium tomorrow. A single cyberattack convincingly attributed to an AI system, a market crash triggered by algorithmic mispricing, or a military incident involving autonomous weapons could unravel the current equilibrium with a speed that traditional diplomatic channels are not built to handle.
What would make this moment more durable is not a grand bargain – neither side is ready for that – but the slow accumulation of precedents: shared definitions of what constitutes a destabilizing AI capability, back-channel communication protocols for autonomous military incidents, agreed norms around AI in nuclear command systems. These are not romantic ambitions. They are the minimum infrastructure for managing a technology neither side fully understands.
Trump and Xi did not produce any of that in Beijing. But they did, apparently, produce something: Trump’s acknowledgment, however offhand, that the two might “work together” on AI guardrails – a concession that the machines they are building are outpacing their ability to govern them, and that some informal floor on recklessness is in both their interests. In the history of great-power competition, that is not nothing.
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