2026-09-14 09:43:28
This was the week that AI safety hit the big time. A 27-year-old AI researcher named Jacob Coxon quit his job at Anthropic, declaring that OpenAI and Anthropic are racing to create technology that could destroy the human race:
Other researchers echoed Coxon’s concern, stating their belief that AI has a reasonable chance of killing all of humanity within a very short space of time:
I’m not sure why this resignation and these statements went mega-viral. Plenty of researchers have made similar moves, and similar statements, over the past few years! Geoffrey Hinton, one of the pioneers of modern AI, quit Google back in 2023 over safety fears. Daniel Kokotajlo resigned from OpenAI in 2024, saying that the company wasn’t behaving responsibly in its drive toward superintelligence. William Saunders and Steve Adler did something similar. Mrinank Sharma left Anthropic earlier this year, and wrote a pretty well-read blog post about it.
What’s more, it’s been clear for years now that “AI could kill humanity” is a very common belief among AI researchers. Grace et al. (2024) interviewed thousands of AI researchers in 2024, and found that more than half thought that artificial superintelligence has a significant chance of making the human race go extinct (or causing similarly bad consequences):
The median AI researcher gave “doom” a 5-10% probability (depending on how the question was phrased), while their average probability was between 15% and 20%. Later, smaller surveys found similar numbers. The AI researchers may or may not be right, but the fact that lots of them think AI could kill the human race has never exactly been a secret.
It’s not clear why Coxon went so much more viral than his predecessors. Maybe it was the fact that AI just solved one of the most important open problems in mathematics (which the best human mathematicians had been unable to solve for almost a century). Or maybe it was the Hugging Face attack, where a swarm of AI agents tried to cheat on a test by hacking various companies. Or maybe AI has just obviously gotten so much smarter that people throughout society were starting to get worried.
But whatever the reason, Coxon’s announcement was the one that really penetrated through to the public consciousness. Suddenly, he was getting interviewed about AI doom on national news:
Barack Obama is now urging Democrats to focus on AI risk. Other politicians are calling for federal regulation. Bernie Sanders is drafting a bill to ban AI “superintelligence”, including 20-year prison sentences for anyone working on the technology. Donald Trump is getting asked about an AI slowdown; so far he’s resisting the calls, but there are rumors that his advisors are calling on him to do something.
Perhaps the most notable response came from the top figures in the AI field. Dario Amodei, the head of Anthropic, wrote a blog post called “We Must Pace the Frontier”, calling for a coordinated slowdown in the rate of AI progress, and suggesting some ways to police AI companies to make sure they were all observing the slowdown. He wrote:
[O]ver the last few months, I have become convinced that fully addressing the risks requires even more prudence — not just investing in risk prevention, but pacing the rate of capabilities advancement so that risk prevention has time to keep up. We must slow the pace at which we improve the capabilities of AI models…I’m therefore proposing a three-step plan with the goal of pacing the frontier: building AI at a balanced rate that aims to ensure its safety while still achieving its benefits and grappling with important geopolitical dilemmas.
As reasons for his increased worry, Dario cites A) the Hugging Face attack, and B) the possibility that AI will soon be able to improve itself without human help (a process called “recursive self-improvement”, or “RSI”).
Elon Musk (head of xAI), Sam Altman (head of OpenAI), and Demis Hassabis (former head of DeepMind) quickly agreed with Dario:
At least some of the labs are reportedly holding secret talks on joint action to slow down AI.
This is pretty extraordinary. A coordinated slowdown in AI progress would be bad for these companies’ bottom line, because it would allow upstart competitors to catch up. So the fact that they’re still calling for a slowdown, in defiance of their own financial interests, is a clear sign that their worry about human extinction is sincere.
In fact, anyone following these figures’ public statements over the past few years will have no doubt that they’re all deeply worried about catastrophic AI risks. The leading AI figures — not just the founders and CEOs, but the researchers themselves — feel trapped in a “red queen’s race”. They feel like if they stop working on AI, someone else will build it anyway, so they each feel like they have to beat everyone else in the AI race so they can make sure that the safest possible AI (i.e. their own AI) is the one that becomes the most powerful and dominant.
Anyway, all of this was common knowledge in my social circle years ago, but now all of it has broken through to the mainstream. What do I have to add to this discussion? I’m not an AI researcher or founder, nor do I think I have a superior grasp of the game theory of AI development. But I do think I have two useful thoughts on how to persuade the general public to be more concerned about AI risk.
The first of these is something I’ve written about recently. The second is about how to get China on board for a big AI safety push.
As soon as everyone started talking about the possibility of AI killing humanity, there were two main types of pushback. The first was skepticism. A strange coalition of natural skeptics, libertarians (for whom any restrictions on technological development are a priori bad), and progressives (who have spent the last few years telling themselves that AI doesn’t really work) kept asking the question: How, exactly, is superintelligent AI supposed to kill us all?
This is actually an important and good question to ask. In my experience, AI researchers tend not to think very hard about this question. The reason is that they just assume that if AI gets smart enough, it will be able to kill humanity, and since its motives are alien and inscrutable, it might have its own reasons for wanting to do so.
Maybe superintelligent AI thinks humanity is an evil species who needs to be punished for torturing pigs and chickens. Maybe it’s scared that humanity might interfere with its other goals. Maybe it just wants to turn everything into paperclips. Who knows? AI researchers tend to think of superintelligence as the proverbial 800-pound gorilla who sleeps wherever he wants. As soon as humanity is no longer the most intelligent thing on this planet, our destiny as a species is simply out of our hands.
But to many people, that answer isn’t good enough. They want an actual plausible path by which a piece of software, which exists inside a computer, could slaughter real physical human beings. Fortunately (or unfortunately), there’s a pretty clear and simple answer to this question, which I wrote about two weeks ago. The answer is “bioweapons”:
(This article was paywalled originally, but I un-paywalled it.)
In my post, I wrote a scenario in which a nihilistic angry teenager uses superintelligent AI to release a world-ending bioweapon by ordering it from a gray-market laboratory somewhere in the world. But it’s also possible that a rogue AI agent swarm could decide to do this on its own, just as a way of cheating on some test that human researchers give it. The point is that AI can design viruses, and viruses can potentially kill off all or most of humanity.
A lot of biologists are skeptical of the idea that even the most superintelligent AI could successfully design a doomsday virus. They argue that this is just too hard of a task — that without much better biological data, it’s impossible to understand biological processes well enough to know how to design a virus with all of the necessary doomsday properties.
I urge you not to listen to these biologists. In this case, their expertise might be more of a liability than an asset. They know how hard it is for human beings to model biological processes, given existing data. But this doesn’t necessarily tell us how hard it is — or how hard it will be in five years — for AI to do it! Until LLMs came along, human researchers basically failed to understand natural language, even with all the data on the internet; AI can just do it. Until AI solved the Navier-Stokes problem, forecasters gave it only a small chance of solving it anytime soon.
Domain experts consistently underestimate how quickly AI can master their field and surpass them, because they mistake human difficulties for universal difficulty. When mathematicians underestimate how well AI will be able to do math, the consequences are usually benign — we get some unexpected answers to some cool math puzzles.1 But if the biologists are wrong, and the AI of 2027 or 2032 or 2049 can design doomsday viruses, the consequence could be that our whole species dies.
So yes, we should be worried about vibe-coded doomsday viruses, and we should be doing everything we can to secure biology labs, police the modification of viruses and other pathogens, and so on. “Pacing” AI development would probably help here too.
The primary argument I see against “pacing” AI development is that if American companies slow down, Chinese companies will simply overtake them and build superintelligence themselves. For some, a China-controlled super-AI is a more terrifying possibility than super-AI in general:
But for others, it simply means that slowing AI down is futile because the Chinese can’t be persuaded to slow down:
This is an incredibly reasonable concern. The U.S. is still ahead of China in the AI race, but only just barely. If China is going to create superintelligence no matter what we do, why should we stop developing our own? Unless China can be persuaded to cooperate with the U.S. on AI “pacing” — or at least undertake its own independent “pacing” effort at the same time — anything we do will be futile.
So if we want to slow down AI development, we need to scare the Chinese leadership about superintelligence. There’s no other way.
How do we do that? In a post a week ago, I suggested in passing that simply staying ahead of China in the AI race might persuade them to embrace an AI slowdown, because that would be to their competitive advantage. But upon further reflection, I think I was pretty obviously wrong. If China will only embrace a slowdown if America refuses to slow down, then that’s game over — there’s no way to get both countries to slow down at the same time.
There’s a better approach. China’s leaders must realize that domestic dissidents could use Chinese-made superintelligence to overthrow the Chinese Communist Party.
Currently, China’s worries about AI mostly center around ways that the U.S. government could use U.S. AI models to attack China. That obviously gives the government an incentive to accelerate domestic AI progress, so that China’s own models can stand up to America’s in a fight. But if Chinese leaders realized that superintelligent AI could create a threat from within, this calculus would change.
Thus, China’s leadership must understand that Chinese AI models can pose a threat to CCP rule. The best way to demonstrate this is for American intelligence agencies — or even private hackers — to attack Chinese digital infrastructure using agent swarms created with China’s own frontier models like Z.ai’s GLM-5.3 or Moonshot AI’s Kimi K3.
When I say “attack”, I don’t mean actual warfare. I mean the kind of cyberattacks and data theft that China carries out against America every day. Use Chinese models to steal the CCP’s most heavily guarded secrets and post a few of the more innocuous ones on RedNote. Hack into Xi Jinping’s bank account and steal 100 yuan. I’m talking about demonstration attacks.
And these attacks must be done with Chinese models, not with American ones! If the CIA or some EA nonprofit in Berkeley uses GPT Astra or Claude Mythos to hack the CCP, China’s leaders may well conclude “Wow, we need to win the AI race so that our own models can defend us.” But if China’s own open-weight models are used for the attacks, Xi Jinping and the rest of the leadership will realize that their own push for superintelligence is making them incredibly vulnerable to any Chinese dissident who decides to overthrow them.
As soon as China’s leaders see superintelligence as a threat to their rule, I predict they will act. And their action will probably be to curb the development of superintelligence, especially if they know that America and its AI labs want to do the same.
In fact, China’s current leadership has a history of cracking down on its tech companies when it seemed like those companies might threaten the government’s monopoly on power. In 2021, Xi Jinping cracked down on Chinese software companies; he even (probably) apprehended tech magnate Jack Ma, who had criticized the CCP a little too openly. This action hurt China’s competitiveness in the online services industry, but the government went ahead and did it anyway.
And there’s already a precedent for demonstration attacks against Chinese digital infrastructure. An American cybersecurity company just used AI to develop a computer worm capable of hacking over a billion accounts on the Chinese messaging service WeChat:
Palo Alto-based Calif disclosed the already-patched computer worm to warn the public about the threat of AI-driven hacks…“Exploitation takes only seconds, and gives us full control of the WeChat account. We can read and send messages, make calls, and act on the victim’s behalf,” the company warned, posting a video demo of the WeWorm attack.
But Calif didn’t say what model it used to create WeWorm. Anyone who does this sort of demonstration in the future should make it clear that Chinese open-weight models were used, in order to make China’s leaders realize that the threat comes from their own too-rapid AI development, rather than from American competition.
I believe that this is our best bet for getting China on board for a joint international AI “pacing” effort. If there’s one thing the CCP fears more than an American attack, it’s domestic dissidents overthrowing the Party from within. Superintelligence is creating that vulnerability, but the leadership doesn’t seem to have realized it yet.
Make them realize, and I predict that a whole universe of possibilities for international cooperation will suddenly open up.
There are potential exceptions, such as if P=NP, which would compromise modern cryptography.
2026-09-12 16:44:47
The other day I saw a Harvard Harris poll on the favorability of various political figures in the U.S. Only RFK Jr. (sigh), Marco Rubio, and Mark Carney had net positive approval ratings:
While I understand that these polls all have methodological issues, I was struck by how three figures — Abdul El-Sayed, Zohran Mamdani, and Benjamin Netanyahu — had net approval ratings below almost any American politician. While Mamdani’s low rating might be partially due to his leftist policies and his association with the DSA, it struck me that all three of these unpopular figures had one thing in common — they are associated with the intrusion of Middle Eastern politics into American politics. And I thought: Maybe Americans just want to have nothing to do with the Middle East.
Today1 is September 11, the anniversary of the terror attacks 25 years ago. Though I don’t agree with the leftist line that those attacks were blowback from American involvement in the Middle East, it’s unquestionable that 9/11 inaugurated an era of heavy U.S. involvement in that area of the world — the Iraq War, the follow-up war against ISIS, the War on Terror, greater support for Israel, an increased military presence in the region, and finally the war against Iran.
I don’t believe that all of that involvement was a bad idea — in particular, as I’ll argue, the War on Terror, including the fight against ISIS, was generally successful and necessary. But overall, the era of heavy U.S. involvement in the Middle East has been a disaster for U.S. power and prestige, and it’s time for that era to end.
This is not a recent conversion on my part; I’ve been in favor of general disengagement from the Middle East for a very long time. Five years ago, in the early days of the Noahpinion Substack, I wrote a post called “How to fix U.S. foreign policy”:
In that post, I wrote:
[D]espite modest progress, we still remain too tied up in Middle Eastern conflicts…The U.S. will never be able to ignore the Middle East entirely, but we can remove ourselves much more than we’ve done…[W]e need to draw down engagement in the Middle East, and increase engagement in Asia.
Since then, things have gone from bad to worse, making my message far more urgent than it was at the time. Most obviously, there’s Trump’s disastrous war in Iran, which continues to waste U.S. military resources and make the U.S. look weak while failing to accomplish any significant objective. Recent polls show that a very strong majority of Americans think that the Iran War is not worth fighting.
There’s also Israel’s intensified campaign against the Palestinians. This has become the rallying cry of the American left, which has prompted a backlash and crackdown by the Trump administration. As a result of that conflict, Middle Eastern politics is increasingly becoming the focus of American domestic politics.
The controversy around Michigan Democratic Senate candidate Abdul El-Sayed, for example, has nothing to do with his policy stances, or even American culture wars — it’s entirely about his stance on Israel/Palestine and his ally Hasan Piker’s comments making excuses for 9/11 and Islamic terrorism. El-Sayed recently apologized for tying a synagogue shooting to Israeli warfare in the Middle East.
Many analysts believe that Zohran Mamdani, meanwhile, won the NYC mayorship primarily because of his outspoken stances on Israel/Palestine. And more is on the way. Organizations like CAIR Action that are linked to the Muslim Brotherhood — a sort of international equivalent of the Christian Coalition, but for Islam — are now supporting political candidates throughout the U.S., using the Palestine issue to recruit candidates and win votes. Muslim Brotherhood figures are cheering this effort on from overseas. AIPAC and other Israel-supporting groups, meanwhile, are pouring money into races in order to stop those candidates.
Our media, too, is increasingly filling up with the Middle East’s cultural and religious conflicts. Leftist shouters like Hasan Piker, Mehdi Hasan, and Cenk Uygur constantly urge progressives to base their politics around Palestine. Every day, Americans are bombarded with rhetoric like this:
This is simply bad for America. We have so many pressing issues to worry about — Trump’s corruption and authoritarianism, inflation, AI, etc. We should not be nominating Democratic politicians based on whether they support Israel or Palestine; we should be nominating them based on their stances on issues of direct relevance to Americans, and on their ability to oppose Donald Trump. Furthermore, mobilizing Muslim and Jewish voters to vote based on Israel/Palestine, rather than on issues of importance to Americans in general, provides fuel for rightist attacks on both groups.
What the United States needs, now more than ever, is general disengagement from the Middle East — an end to military adventures, a dialing back of support for Middle Eastern “allies” (including Israel), and a forceful rejection of Middle Eastern issues in American domestic politics.
Fortunately, conditions in the world have shifted. The kind of disengagement I’m calling for is a lot more feasible than it was twenty or even ten years ago. The Iran War has shown that Middle Eastern oil is a lot less important for the global economy than it used to be. And the success of the War on Terror and the general decline of Islamism reduce the necessity for further interventions.
For many decades, the main justification for U.S. intervention in the Middle East has been to keep oil prices low and stable. The Middle East is one of the world’s largest oil producers, and its low extraction costs mean it functions as the world’s “swing producer”. Supply disruptions from the region can cause global price spikes, endangering industrialized economies that depend on petroleum. Oil was a big reason the U.S. intervened to stop Saddam Hussein’s invasion of Kuwait in the early 90s, for example.
Obviously, oil is still a very important commodity. But it’s a lot less important to the U.S. than it used to be. Here’s what I wrote when the Iran War began:
Blanchard and Gali (2007) looked at economic responses to changes in oil prices in the U.S., and concluded that the economy of the 2000s was only about a third to half as sensitive to the price of oil as the economy of the 1970s had been. Their reasoning is that modern economies are more flexible in general, that they have better monetary policy (i.e. we don’t try to print a ton of money in response to a supply shock), and that we depend on oil less.
By their estimates, a 10% increase in the price of oil now (or at least, if “the 2000s” means “now”) leads to only a 0.25 percentage point increase in the CPI and a 0.3 percentage point reduction in GDP over the course of a year or so. Since oil just spiked by 50%, then if that’s sustained, we might expect to see inflation go up by 1.25 percentage points, and GDP go down by 1.5 percentage points over the next year. That would mean inflation would go to around 4% and GDP growth might go down to 1.5% — frustrating and annoying, but not catastrophic…Other estimates seem similarly modest. For example, in a recent roundup, I flagged a paper by Känzig and Raghavan (2025) that looked at the closure of key shipping chokepoints.
In addition to having a more flexible economy, better energy efficiency, and more reasonable monetary policy, the U.S. is now a net oil exporter. That means when oil prices go up, the benefit to the energy sector cancels out at least part of the harm to other sectors of the economy.
But on top of all that, the fact is that the Iran War simply hasn’t raised oil prices that much! Despite Iran’s closure of the Strait of Hormuz, and Trump’s retaliatory blockade of Iranian oil shipments, oil prices haven’t even reattained their highs from the early 2010s:
And in real terms, the spike is even less impressive. If we divide oil prices by average hourly earnings for production and nonsupervisory workers — basically, how many hours an average American worker would have to work in order to afford a barrel of oil — we see that prices really aren’t that high at all:
No wonder the U.S. economy is still doing fine, and inflation has only risen a little bit (and some of that may be due to demand from the data center boom).
2026-09-09 16:39:04
So, Germany’s far-right party, the AfD, just won a huge landslide election victory in the eastern state of Saxony-Anhalt. This doesn’t mean AfD is taking over Germany — the far right is much more popular in the post-communist east than in the more populated western regions. Germany is also a parliamentary democracy, and almost everyone else hates and fears the AfD. But the statewide victory is a warning shot, and everyone in Germany — and in Europe — is taking it seriously.
AfD’s surge means two things. First, it means that the rise of far-right parties was not simply a reaction to the pandemic. Back in 2024-25, a number of pundits I respect argued that voters in the U.S. and Europe were backing rightist leaders out of anger at incumbents over Covid. That thesis now looks dead.
Second, it means that something is making many German voters so angry that they’re finally willing to overlook all of the AfD’s catastrophic flaws — its obvious ties to Vladimir Putin, the fact that the party is filled with crooks, its extreme rhetoric, its lack of governing experience, and so on.
What is that “something”? A number of socialist types have tried to claim that AfD’s new voters are responding to economic despair, and can be won back with more socialism. But more sober voices agree that the “something” is immigration. Adam Tooze, who strongly leans to the left, tries to be gentle as he explains that there’s no getting around the immigration issue:
If you ask AfD voters what they worry about, along with their xenophobic concerns about “too many foreigners”, they will mention the cost of living and their concerns for their standard of living. They also mention climate change and the threat of external war…But if you ask them what they think about the AfD and why they voted for it, economic issues are barely mentioned. What comes first is security, foreigners, woke politics, remoteness etc…
If you are hard up and working-class it would after all be nothing short of bizarre to vote for the AfD in the hope of improved social protection…Voting for the AfD in the current landscape, whatever your economic issues, in short, is not a vote to have your economic issues addressed by social democracy, or welfare or government intervention. It is a vote to crackdown on foreigners[.] [emphasis mine]
Robin Brooks is more blunt:
There’s lots going on in Germany at the moment, but - when it comes to the surge in AfD popularity - you don’t need to overthink it. The AfD is relentlessly campaigning on immigration, which tells you that this is what resonates most with voters…A key driver of the recent surge in AfD popularity is that the CDU - SPD grand coalition is proving itself incapable of confronting immigration with the urgency many voters want.
In fact, anger over immigration is probably the main reason that the right is surging everywhere in Europe. Here are Konstantinou and Roumanias (2024) with some data:
We use regional data spanning over 4500 electoral outcomes…between 2000 and 2017 to assess the impact of immigration on Western European Far-Right voting. To deal with potential reverse causation, we use immigration in neighboring countries as an instrument for domestic immigration. The estimated effects of immigration are positive, significant and larger compared to those obtained by simple OLS and fixed effects regressions. Depending on the measure of immigration used, we find that a 1% increase in immigration stocks leads to a between 1.78% and 2.97% in Far-Right voting…Our estimated effects explain a large part of the observed rise in Far-Right in Western European countries that experienced high levels of immigration during the span of our sample.
2026 is hardly the beginning of the trend. Here’s Brookings in 2024:
In the European Union (EU), one election after another has demonstrated the centrality of irregular migration and border security in public discussions and forced mainstream parties to take more restrictive approaches…The results of the European Parliament election, France’s snap election, three German state elections, and the Austrian election all showed a strong rightward drift and signaled voters’ distrust in their national governments, confirming the notable shift in tone on migration in Europe toward a more securitized, hardline approach, even among mainstream parties.
Trump’s election in 2024 was also partially about immigration. Trump voters rated it as one of their top issues, along with inflation. It was the issue where Trump had the strongest lead over Kamala Harris in polls. American voters clearly soured on immigration in 2023-24.
Progressives in America and socialists in Europe still desperately claim that what angry working-class voters really want is more economic support. They keep offering more and more lavish promises of welfare supports and price controls, while staunchly opposing restrictions on immigration. The approach keeps failing, and the far right keeps rising.
Center-right and center-left politicians, on the other hand, realize the source of their voters’ anger very clearly, and are taking steps to reduce immigration. Germany’s center-right CDU has already stanched the flow with restrictive policies:
And Chancellor Friedrich Merz is responding to AfD’s gains by making it harder to get citizenship. Meanwhile, France and Italy are tightening border controls. France is making it harder to become a citizen. The EU is toughening up its asylum rules. Sweden is offering migrants large sums of money to leave the country. European countries are streamlining their infrastructure for kicking out large numbers of failed asylum-seekers. Japan is tightening its own immigration policies after a period of liberalization.
Even Canada, one of the most immigration-friendly and progressive countries on Earth, has scrambled to reduce immigration, cutting targets for permanent residents, reducing student visas, and slashing the number of temporary workers. Immigration levels are still high, but are falling quickly — all under the center-left government of Mark Carney.
And yet I’m worried that voters around the world will see these measures as superficial — tactical pauses to let populist anger simmer down before resuming the same permissive immigration policies that made voters mad in the first place. This certainly seemed to be the case in Europe, where the government stopped admitting asylum seekers from the Middle East in the late 2010s after a popular outcry, only to resume taking them in en masse in the 2020s:
And it also seems to be true in the U.S.; Biden mostly closed the border to asylum-seekers in 2024 after he saw how mad it was making Americans, but many Democrats are now calling for the abolition of ICE. This is a somewhat popular position right now, thanks to the agency’s abuses under Trump. But if Democrats actually try to abolish federal immigration enforcement instead of just reshuffling and renaming the agencies, I predict it will take just a couple of years for Americans to realize that the difference between “open borders” and “immigration laws with no one to enforce them” is largely semantic.
What’s needed, I believe, is not just a tactical, temporary retreat. We need to stop and think why a maximal pro-immigration policy is something that we need to retreat from in the first place. We need a new concept of what a sustainable liberal immigration policy looks like.
Since I started writing, I’ve been an advocate of more immigration to the United States. This does not mean I ever favored unrestrained immigration or open borders. I’ve consistently argued that favoring skilled immigration will bring more economic benefits to native-born Americans, and be more politically palatable as well. And while I don’t hate illegal immigrants for trying to better their lot in life, I favor strong border controls, because nations have the right to decide, democratically, who gets in and out. It’s understandable when people get mad at seeing their decisions flouted.
On top of that, I’ve always remained agnostic on immigration to other countries; although I find much to admire in Canada’s points-based system, for example, I don’t think that qualifies me to decide whether more immigration is good for Canada overall. If the people of a country decide that immigration is diluting their local culture unacceptably, for instance, I think they have every right to cut it off. That’s just Westphalian sovereignty — not a perfect system, but the best system we’ve ever found for organizing humanity into geographic units. As an American, I don’t view it as my place to tell Japan, or the UK, or any other country that immigration is the right choice for them.
Despite those reservations, I’ve always thought that immigration to the U.S. is a basically good thing, and should be expanded. The economic benefits are pretty undeniable — higher tax revenue to shore up our dangerously depleted government finances, dominance in high-tech industries and innovation, and so on. And while some of the economic costs are real — local housing shortages and strains on local government finances being the two biggest ones — many of the fears are overblown. In particular, the bulk of the evidence concludes that immigrants don’t reduce wages or job opportunities for native-born Americans.
And importantly, lots of Americans share my overall positive view of immigration. If you ask Americans whether they think immigration is good or bad, most will say “good”:
And if you ask Americans whether the annual rate of immigration should be increased, decreased, or kept the same, you get a pretty even split:
So I’ve never really felt like I was going out on a limb or advocating an unpopular position when it came to this issue. Sure, rightists will direct online vitriol toward anyone who supports any immigration at all, but their energy and savagery shouldn’t be mistaken for majority support.
And yet there will always be some amount of immigration — and some types of immigration — that will arouse even the most open and welcoming people to ire and make them think about shutting the doors. We saw this in the U.S. in 2023-24, when anti-immigration sentiment spiked in response to Biden’s permissive asylum policies. Yes, that sentiment crashed again when Trump took power and started committing abuses. But if liberals don’t change how we approach immigration, the sentiment will simply rise again and again, as it has so many times throughout our history. And the Donald Trump and Stephen Miller types will be right back in power — and our country will be worse off for it.
Liberals need an immigration approach that can be sustained for long periods of time — i.e., one that doesn’t enrage the public every time it manages to get in power. What would that look like?
The first thing liberals (and progressives, and Democrats, and European lefties, etc.) need to admit is that migration is not a human right. We live in a world of sovereign nation-states, and unless we find some better way of dividing up and administering the world, we will continue to live in a world of sovereign nation-states. And nations are, necessarily, exclusive clubs; they have the right to restrict immigration for any reason whatsoever.
Liberals must therefore not view borders and citizenship as annoying obstacles to be tactically circumvented or overcome; instead, we must view them as fundamental parts of the social compact that allows nations, including liberal nations, to exist in the first place. Nation-states and their laws and their police and their courts and their armies are the fundamental guarantors of the human rights that define liberalism. And for better or for worse, the ability to decide who gets in and who has to keep out is a necessary precondition for nation-states to exist.
That means we need to recognize that immigration law is legitimate and needs to be upheld. Some progressives have tried to advance the notion that being undocumented is a marginalized identity that needs to be protected and supported by the state. But this is absurd; it’s like if progressives decided that people who drive over the speed limit are a minority group.
Illegal immigrants chose to break U.S. law when they came to this country. Our democratically elected leaders made those laws, and they should be honored. We should treat illegal immigrants humanely, of course, and we should not tear local communities apart just to hunt down a few people. But there has to be some way of enforcing the law, because a law without enforcement is no law at all.
A third principle that liberals should embrace is that the purpose of immigration is to benefit the people who already live in the country that is receiving the immigrants. Immigration to America must be for the benefit of Americans. We must flatly reject any concept of immigration that sees it as a necessary sacrifice on the part of American citizens.
For example, the book This Land is Our Land, by Suketu Mehta, argues that immigration is a form of reparations for colonialism — a sacrifice that Western nations owe to other nations, even at their own expense. This idea has found some purchase in progressive circles, but liberals must reject it as wholly illegitimate.
Instead, liberals need to promote immigration because of the benefits it brings to the American citizenry. This includes economic benefits — the tax revenue, the investment, the eldercare, the innovation, the entrepreneurship, the expanded market size. But it also includes cultural benefits — the constant reinvigoration of this nation of immigrants by new waves of people with the gumption and bravery to pick up and move across the world in search of opportunity and freedom.
America has always been the country of the frontier; in order to maintain that ethos in the modern age, we need people for whom America itself is the frontier. And our founding ideals — which are very liberal ideals, of liberty and opportunity and the rights of the individual — are strengthened by people who make the conscious choice to move to a country that represents those ideals.
These are the kinds of arguments liberals made in the past. We can — we should — make them again.
And if this requires us to be selective about which immigrants we bring in, then so be it. Skilled immigrants bring far more economic benefits per capita than others — so by all means, let us tilt our system toward them, as American voters of both parties want. Immigrants who don’t love and embrace American culture will probably invigorate our nation less — so by all means, let us bar immigrants who have been part of groups that see America as evil, using the law with which we once banned immigration by members of communist parties.
These are the kinds of decisions that nation-states, including liberal nation-states, are inherently entitled to make. And we should expect Europe to make different decisions than America makes. That’s perfectly OK. Because immigration is fundamentally the decision of each sovereign nation-state, it’s inevitable that we’ll make different decisions. JD Vance wants us to think that France’s immigration policy, or Germany’s, is inextricably tied to America’s. But it’s not, and we shouldn’t let him get away with conflating the two.
A liberal immigration program based on these three principles could defuse the anti-immigration sentiment now sweeping the developed world — not just now, but permanently. But it will only do so if liberal leaders explicitly articulate and avow these principles. That’s what’s required in order to convince the electorate that liberals are trustworthy on immigration — that embracing the kind of immigration policies Americans demand represents a principled stand rather than a tactical retreat from a hidden agenda of open borders.
For America, the kind of immigration agenda I’ve sketched out — which all the polls show Americans favor by substantial margins — would not be a “far right” policy, even though some progressives and leftists will inevitably try to label it as such. In fact, it would allow in far more immigration than the policies of Franklin D. Roosevelt or Harry Truman. It won’t satisfy progressives who dream of a borderless world, or leftists who salivate over the chance to make the West pay for colonialism. But I believe it will preserve America as the kind of liberal nation-state that we knew it as in the days before Trump.
As for the rest of the world, countries like Germany and Canada and Japan have to make their own decisions. I can’t tell them what kind of nation to build; I can only try to promise that as an American, I’ll respect their decision. If they want to shut their doors in order to slow the pace of cultural change, it’s not my job to lecture them otherwise. All I can say is that I hope they do what they need to do in order to avoid getting taken over by parties that take their marching orders from the Kremlin.
But speaking only for my own country, I believe that if America gives up immigration, it will lose one of the key things that has made it great. With the GOP in the hands of a xenophobic rightist movement that sees immigration as an invasion, it’s up to the Democrats to craft a system that can be preserved for the long term.
2026-09-07 16:13:49
It’s Labor Day, so here’s a post about how human labor is alive and well in the age of AI.
I live in San Francisco and hang out with a lot of tech people, both in the AI industry and outside of it. And one thing that almost everyone I know here believes is that AI’s main economic effect is to displace humans from their jobs. Most people don’t have concrete arguments for why this should be true; it’s just an article of faith. The conventional wisdom is pretty well summed up by the first line of this tweet:
In fact, AI companies themselves have spent years talking about how their inventions are going to render large swathes of humanity economically obsolete — an odd marketing pitch, perhaps, but one that seemed to reflect their honest expectations.
A lot of times, San Francisco tech people are out of step with the general public. This time, though, the public seems to agree. A recent Ipsos poll found that most Americans expect AI to compete with human workers more than it complements them. And Pew finds that this belief has even strengthened in recent years:
So basically, most people think AI is a job-killer. And yet somehow, this job-killer keeps stubbornly refusing to kill jobs. In the aggregate, the labor market is about as healthy as it’s ever been. The prime-age employment rate — the single best indicator of how many Americans have jobs — continues to hover near all-time highs:
Of course, there are lots of other things going on in the labor market right now besides AI. But most of those things — tariffs, the Iran war, etc. — are bad for employment. It’s not easy to identify some sort of positive shock that is canceling out the job-killing effects of AI.
Or maybe it is, if the shock is AI itself. Theoretically speaking, automation can create jobs just as easily as it can destroy them. Here are Acemoglu and Restrepo (2019), explaining the various ways that technology can affect the demand for labor:
Automation [can be bad] for labor because of a displacement effect—as capital takes over tasks previously performed by labor…
[A]utomation technology also increases productivity, and via this channel, which we call the productivity effect, it contributes to the demand for labor in non-automated tasks…
[T]he displacement effect of automation has [historically] been counterbalanced by technologies that create new tasks in which labor has a comparative advantage. Such new tasks generate not only a positive productivity effect, but also a reinstatement effect—they reinstate labor into a broader range of tasks and thus change the task content of production in favor of labor. The reinstatement effect is the polar opposite of the displacement effect and directly increases the labor share as well as labor demand. [emphasis mine]
In other words, automation can do three basic things. Yes, it can replace people and take their jobs. It can also make them more productive, which can both create jobs and destroy them.1 And, crucially, automation can create new jobs for people to do. Power looms replaced master weavers, but they created jobs for technicians and engineers to make the power looms work. The internet automated much of the work of travel agents, but created jobs for web designers. And so on.
People who think of AI as a job-killer might not have thought of the second and third of these. Or they may have thought of them, but simply assumed they’re not a big deal. Anecdotally, a lot of tech people think that AI will keep substituting for more and more tasks until A) productivity increases just increase the demand for AI, and B) there are no new tasks left for humans to do. AI detractors, meanwhile — like Daron Acemoglu himself — often simply assume that new tasks created by AI will be “bad tasks” like misinformation and cybercrime that hurt the economy instead of helping it.
But these assumptions simply might not be correct. AI might be creating lots of new tasks for humans to do. For example, software engineers are writing less and less code themselves. Instead, they’re spending more and more time telling AI to write code — that represents a productivity improvement. But they’re also trying to figure out what code to tell AI to write, making sure AI is writing the kind of code they want, integrating that code into products, and so on. Those are all new tasks. There are also a lot of software engineers working on improving AI itself, and on discovering new applications for AI. Those are new tasks as well.
This helps explain why in the age of Codex and Claude Code, software developer jobs have been increasing as a percentage of total employment:
Anecdotally, organizations that thought they could replace lots of their software engineers with AI ended up having to hire many of them back — sometimes at a premium.
In fact, this is a story we see throughout the economy. Alex Tabarrok recently reported on a Census Bureau survey about AI that’s been running since 2023. The Census Bureau calls companies up and asks them A) how AI affected their total employment, and B) how AI affects the tasks that workers do.
Most companies reported no change in overall employment, which could just be due to inertia. But of companies that did report a change, more reported an increase than a decrease!
And here’s the breakdown by sector:
The story was similar for tasks. Tabarrok writes:
Among firms using AI, 44% say it supplemented or enhanced work an employee already does. Ten percent say it performed a task an employee used to do. Eleven percent say it introduced a task no one had been doing.
Here’s the chart:
Rigorous research, meanwhile, sometimes finds negative effects of AI on labor demand at the industry level, and sometimes not. But at the company level, the evidence is clearer — Kharazian, Simon, and Stevens (2026) find that when companies adopt more AI, they tend to hire humans rather than replacing them. Here’s a blog writeup of their findings:
And here’s a chart:
Interestingly, they find the same for entry-level jobs — the jobs that people usually identify as being most under threat from AI.
So despite Acemoglu’s skepticism, it looks like for now, the new tasks being created by AI are probably matching or even slightly exceeding the tasks replaced by AI. Of course this measure is “number of companies” rather than “number of jobs”, but the pattern is pretty clear.
The Economist, meanwhile, has a report on how AI is creating jobs, both through the “new tasks” channel and by boosting demand in areas that AI can’t yet touch — physical jobs like construction and HVAC installation. Here’s what they write about the productivity/demand effect:
The Economist estimates that AI has so far created around 1m new jobs in America. That easily exceeds the roughly 200,000 lay-offs attributed to AI since mid-2023, and appears more than enough to offset weaker hiring in many back-office roles. America’s AI infrastructure splurge has created many of them…The Economist tracked five industries at the heart of the data-centre build-out, from electrical contracting to equipment manufacturing. Since 2023 employment in them has risen by roughly 320,000 more than broader…trends would suggest…LinkedIn, a social network for strivers, estimates that nearly half a million data-centre jobs were created between 2023 and 2025 in America, with data-centre technicians and engineers among the most common recent hires…
The scramble for workers is showing up in pay cheques, too. Indeed finds that installation and maintenance jobs at data centres advertise wages about 40% higher than comparable work elsewhere…In the year to June, average hourly earnings rose more than 13% in electrical-equipment manufacturing and nearly 8% among electrical contractors. [emphasis mine]
And here’s what they write about new tasks:
AI is also creating a new class of white-collar jobs. Engineers build the models, data annotators label their inputs and judge their answers, “forward-deployed” engineers adapt them for customers, and newly minted “heads of AI” decide what companies should do with the technology. Some of these roles barely existed until recently. Many are quickly growing in number. Postings for heads of AI, AI engineers and directors of AI have roughly doubled since 2023-24, according to LinkedIn…
Preliminary research by Gad Levanon, chief economist at the Burning Glass Institute…reckons roughly 1% of professional jobs are now “AI jobs”…[P]rofessional occupations closest to the AI boom—engineers, software developers, mathematicians and data scientists…have added roughly 730,000 jobs above trend in recent years[.] [emphasis mine]
What about specific occupations? Technology has certainly destroyed many specific types of jobs over the centuries — there are (basically) no more elevator operators, human telephone operators, or people who do manual typesetting for printing.
And yet in recent decades, we haven’t seen as much of this sort of occupational destruction. For example, a lot of people thought the internet would kill travel agents. And while the industry was hit hard, there are still plenty of travel agents left:
The reason is probably that the job of “travel agent” is much more flexible and “messy” than older types of jobs like elevator operator; travel agents do a whole lot of different tasks, so they’re harder to replace than people who just stand there and press a button. That makes modern jobs harder to replace entirely.
It’s a good bet that AI will eventually make some occupations obsolete. But so far, despite awe-inspiring progress in model capabilities, it’s extremely hard to find occupations that have seen significant replacement by AI. Top AI researchers who famously predicted the end of human radiologists saw their predictions get confounded. Truckers, too, are doing just fine. (Update: Here’s a good clip of Geoffrey Hinton explaining why he was wrong about radiologists.)
The most impressive example might be translators. It seems pretty obvious how AI could replace human translators, and yet it hasn’t done so yet:
Here’s a chart:
If you could go back to 2022, and tell people that in four years, AI would be solving frontier math problems, but we’d still have the same number of people working as translators, how many would have believed you?
It turns out that it’s very natural for people to overestimate the degree to which AI will take their jobs. Hartley et al. (2026) have a really excellent paper called “Job Loss Fears in the First Years of Generative Artificial Intelligence”. Here’s a thread explaining the paper’s findings.
Basically, the authors find that fear of AI job replacement is extremely common:
And they find that the more people’s jobs are exposed to AI, the more they think their jobs are about to be replaced:
In fact, the more of their day people spend using AI at work, the more they’re afraid of being replaced!
And yet when the authors looked for a correlation between AI exposure and actual job loss, they found…absolutely nothing. People’s fears simply haven’t come true yet.
What’s going on? The authors hypothesize that people who use AI more start to understand its ability to replace the tasks they do at work. But as we keep finding, replacing tasks isn’t the same as replacing jobs. People keep finding new things to do in their roles at work — sometimes things AI can’t do yet, but often things that couldn’t even be done until AI made them possible!
It seems like we’re uncovering a consistent human blind spot here: People don’t actually know how they produce value at their jobs. Modern jobs are much more than a simple collection of tasks — they are pieces of a complex machine that produces value in ways that an individual worker often doesn’t even see.2 So when AI comes along and starts replacing people at various tasks, it just ends up making them more valuable as pieces of their corporate machines.
How long that situation will persist, of course, is an open question. AI leaders are starting to realize that it might take a very long time for the full effect of their inventions to be felt:
This is why the AI companies’ recent messaging pivot — many now say that AI will create jobs rather than destroying them — may be honest, rather than a cynical marketing ploy to calm public outrage.
But then there’s the question: Can this situation persist indefinitely? No one knows, of course. But my bet is that while many occupations will eventually be mostly replaced by AI, humans will still have plenty to do. I’ve argued that in order for AI to start replacing human jobs wholesale, it’ll have to get much more agentic — which will make it inherently more unreliable from a human point of view. So I predict that humans will always have jobs keeping AI agents on track.
Even if I’m wrong, though — even if the AI job apocalypse does eventually come — it doesn’t seem like it’s coming soon, and it certainly isn’t here right now. Everyone keeps thinking that AI is a job killer, and AI keeps on refusing to be what everyone expects.
Happy Labor Day!
Update: John Cassidy has another good post on this same topic.
Higher task-level productivity can destroy jobs by letting employers do more with less. It can create jobs by creating economic growth, which boosts labor demand. But I think Acemoglu et al. might overlook another source of productivity-driven job creation, which is variety. When carmakers became more productive, they became capable of pumping out more different makes and models of cars. This probably made consumers want cars more, because people enjoy variety — GM famously overtook Ford by offering more models, more frequent model updates, and more colors.
This is why jobs may feel like “bullshit” to the people doing them, even as they command high wages in the market.
2026-09-05 15:36:17
Most of the debate around AI, at least in the U.S., is not about the international aspect. The local political debate is all about data center construction; the national economic debate is mostly about fear of job loss, with a side discussion about a potential bubble; and the technological discussion, at least in public, is mostly about AI safety and risk. U.S.-China competition gets mentioned in certain circles, but it’s probably safe to say that it’s not Americans’ chief topic of concern.
But it still matters! For one thing, there’s the military aspect to think about. Cyberwarfare so far hasn’t been decisive in military conflicts, but AI’s incredible cybersecurity prowess could change that. If AI ends up strengthening defense more than offense — say, by finding all of the available exploits and patching them before an attacker can get to them — then cyberwarfare will become less important. But if those who possess the best AI models are able to successfully hack anyone using a less capable model to defend, it could lead to a decisive shift in the balance of power.
AI hacking doesn’t have mutually assured destruction, like nuclear warfare does. Imagine if China were to gain a big lead in AI models that gave it the power to easily hack into American banks and brokerage accounts and erase people’s wealth. It would cause absolute chaos in American society, but how could the U.S. retaliate? Launch nukes? Nor could the U.S. hack China in return, since China’s more capable AI would also be used to defend.
If either country opens up a large, sustained lead in AI capabilities, it might upend the balance of power between the two.
Not all AI issues are zero-sum, of course. If the U.S. and China both continue pushing forward with AI research at maximum speed, it may quickly cause safety issues. The recent AI agent swarm attack on Hugging Face shows that AI has reached the level where it can pose a significant hazard to human companies and organizations — and perhaps soon to human society itself. Bioterror risk is certainly the most terrifying, but there are plenty of other ways that highly capable AI could cause chaos.
The U.S. and China have a shared incentive to implement strict safeguards against these catastrophic risks, and perhaps even to regulate the pace of AI development. But given the Chinese Communist Party’s power-seeking nature, it seems much more likely that China would agree to cooperate on AI safety if U.S. capabilities were comfortably ahead. So even if the goal is cooperation, the U.S. should be thinking about how to keep its technological edge.
Fortunately, the U.S. is still beating China in the AI race. Our companies have better models, more compute, and far more revenue. But there are ways that the Trump administration, despite claiming to be the AI industry’s best friend, could squander America’s lead — especially by pushing Chinese AI talent out of the country.
There have been several moments when it seemed as if China’s frontier models were catching up to America’s in capabilities. The most dramatic was the “DeepSeek Moment” in early 2025, which put Chinese AI on the map. More recently, the release of Moonshot’s Kimi K3 this July and Z.ai’s GLM-5.3 a few weeks ago seemed to indicate that Chinese models were nipping at the Americans’ heels.1 Z.ai especially made waves when it beat Anthropic’s famous Mythos model on one measure of cyber-hacking capabilities:
Chinese AI startup Z.ai said on Friday its open-source GLM-5.3 model had neared Anthropic’s restricted Mythos 5 in identifying software vulnerabilities…Z.ai said GLM-5.3 scored 84.5% on CyberGym, a test of whether a model can review code, identify security flaws and confirm that they are real. That was slightly higher than the 83.8% it reported for Mythos 5. The results have not been independently verified.
Note that this is just one measure of cybersecurity prowess, and that Mythos was still comfortably ahead on other measures:
GLM-5.3 lagged behind Mythos 5 in converting discovered flaws into working attacks — a standard part of defensive security research. Z.ai said its model scored 54.4% on the ExploitBench test of this capability, versus 78.0% for Mythos 5…In a separate timed test, Z.ai said GLM-5.3 completed 105 attack-development tasks in two hours and 130 in six hours. Mythos 5 completed 181 and 247 tasks, respectively.
But still, if Chinese AI could get within striking distance of America’s best, it was a big deal.
What this discourse rarely mentioned, though, is that Mythos is not America’s best. It was simply the best that’s been released. Mythos Preview came out in April, four months before GLM-5.3. And the original Mythos actually finished training three months earlier, in January, and was released internally in February.2 Anthropic delayed its release due to cybersecurity concerns. Z.ai, being a fast follower, probably had far fewer such concerns. In fact, Anthropic has stated that it has internal models that are better than Mythos.
2026-09-03 17:55:22
Stripe Press was kind enough to send me several books it had published, and one of these was J. Storrs Hall’s Where Is My Flying Car?. I had been meaning to read this book for a while, especially after Tyler Cowen recommended it and Jason Crawford gave it a glowing review, so I was glad Stripe gave me a copy. I promptly stuck it on my shelf, paid for the audiobook, and listened to it while walking around San Francisco. That’s called ordinary abundance, folks!
In 2011, Peter Thiel famously said: “We wanted flying cars, instead we got 140 characters.” When I first saw that quote, I chuckled, because for my entire life, we’ve had flying buses. And again and again, as I sit on a flying bus and marvel at the thrill of takeoff, and reflect on how amazing it is that man has conquered the air, I look around and see my fellow passengers with their window shades drawn, their noses buried in a book or staring at a phone.
If we had flying cars, we’d enjoy the thrill for a few weeks, and then we’d be back to tweeting on our phones and wondering when the trip would be over.
I’ve noticed a loose collection of beliefs and attitudes that I’ve decided to call “engineerism”, because I see it most often among engineers. I coined the term when I was in college, when I noticed that the engineering majors in my physics classes tended to think differently about the world than the physics majors like myself did. Later, I recognized “engineerism” in various sci-fi novels — Lucifer’s Hammer and Footfall by Larry Niven and Jerry Pournelle, The Peace War by Vernor Vinge, and so on.1
When I say “engineerism”, I am not talking about Friedrich Hayek’s “engineering mentality” — the belief that society can be designed and optimized like a machine.2 Nor am I referring to Evgeny Morozov’s “technological solutionism”, which is the idea that social problems can be fixed with technology. If I had to define what I call “engineerism” in succinct, simple terms, it would be something like: “The idea that if a technology can be built, we ought to build it.” Simply put, engineers like to engineer things, and they become disgruntled when society does not give them the resources to do this.
Of course, engineerism is not quite so simple in the real world. It involves a lot of thinking habits that come in handy in engineering — linear approximation, back-of-the-envelope calculations, and so on. And in America, it also involves a set of beliefs that have sort of accreted over the years — for example, a belief in the importance of nuclear power.
I’ve had the concept of engineerism kicking around in my mind for many years, but in Where Is My Flying Car? I have found its perfect encapsulation — you might even say its Bible. Nowhere are both the value and the limitations of engineerism more perfectly on display than in this book.
Where Is My Flying Car? occupies an interesting middle space between genres. Futurism is about predicting the future. Science fiction is about (among other things) speculating on possible futures. And history of technology explains the past. Where Is My Flying Car? has bits of all three of these, but fundamentally it’s a book of retrofuturism — it’s about the technologies we thought we would get but didn’t, and why we didn’t, and how we could get them now.
The main technology Hall talks about is, unsurprisingly, flying cars. The other three are cold fusion, nanotechnology (Hall’s own area of research), and nuclear (fission) power. Hall argues that a combination of overregulation, scientific groupthink, bad funding mechanisms, and cultural aversion prevented us from achieving all four of these.
Wait…cold fusion? Is that even real?? Well, not as far as we know, no. In 1989, two top chemists reported that they had managed to get much more heat out of a nuclear experiment than chemistry would be able to produce. The chemists thought that they had discovered a way to produce nuclear fusion without injecting huge amounts of energy — smashing ions together at insanely high speed, blasting them with a laser, etc. If it worked, cold fusion would be an incredible energy source.
So naturally, a lot of people tried to follow up on cold fusion. A wave of initial replication efforts mostly failed (though some people claimed to find the effect). But there have been plenty more efforts, including:
A Japanese government project in the 1990s, with funding of around $20 million
A project by Toyota in the 1990s, with around $18 million in funding
A project by the Electric Power Research Institute in the 2000s, with around $10 million in funding
A project by Google in the 2010s, with $10 million of funding
None of these efforts have reliably reproduced the effect that the two chemists claimed in 1989. A few of the researchers found some strange anomalies and possible new physical effects, but nothing even remotely similar to the kind of energy source that cold fusion would represent — and no consistent evidence that fusion is causing the occasional anomalies.3 Some other scientists have found ways to enhance fusion using chemical techniques vaguely reminiscent of the methods in the 1989 experiments, but nothing remotely close to the scale of what “cold fusion” would require. There’s interesting nuclear physics going on in solid-state chemistry, but the original burst of excitement around the 1989 experiment looks like it was misplaced.
That’s not the way Hall tells it, though. He claims that cold fusion is a promising area of research, and that what he terms the “Machiavelli Effect” — basically, vested interests trying to shut down research that would supersede their own research programs — strangled the promising field of cold fusion in its cradle by stigmatizing it and depriving it of funding.
That story just doesn’t pass the smell test. Multiple optimistic, good-faith research efforts, from various countries, from both the public and private sectors, have each thrown tens of millions of dollars at the idea, despite repeated lack of success. That is just not what a marginalized area of science looks like. Yes, lots of people regarded (and regard) the idea of cold fusion as kooky, but plenty of others didn’t and don’t — including the people who headed the many multimillion-dollar research efforts.
Hall knew about all of those efforts, and their outcomes, when he published the 2021 version of his book. But although he mentions some of them, he continues to insist that cold fusion research was mainly stifled by malign social influences. And in his projections of the possibilities of the future, cold fusion figures prominently.
This suggests one weakness of engineerism — the stubborn, contrarian belief that if someone tells you something is impossible, it must be possible. Yes, people sneered unfairly at cold fusion back in the 90s, but that doesn’t mean it must actually work. Not everyone who gets persecuted by the Church is Galileo.
Hall’s stubborn love for the idea of cold fusion also has the unfortunate effect of reducing the credibility of other parts of his book. I am no expert in nanotech, and Hall is an expert. But when he relies on the magical effects of atom-sized nanotech to support key parts of his future visions, I’m skeptical of how much of that is based on careful homework and how much is based on pure optimism. When Hall tells us that nanotech should eventually be able to rebuild the U.S.’ entire existing infrastructure in a few hours, I naturally wonder if the back-of-the-envelope calculations that support that conclusion were the only ones he needed to do.4 If Hall hadn’t gone all-in on cold fusion, I would have probably been less instinctively skeptical of the nanotech sections.
One of Hall’s main points in Where Is My Flying Car? — and the book’s best point, in my opinion — is that physical technology began to stagnate when energy use began to stagnate. In fact, I wrote a post about this a decade ago, before the first edition of Hall’s book even came out! Here’s what I wrote:
Why did mid-20th-century sci fi whiff so badly? Why didn't we get the Star Trek future, or the Jetsons future, or the Asimov future?…[W]e ran out of energy…In the industrial age, we got better at carrying energy around with us. And then, at the dawn of the nuclear age, it looked like we were about to get MUCH better at carrying energy around with us. One kilogram of uranium has almost two million times as much energy in it as a kilogram of gasoline.
I didn’t know it at the time, but I was talking about the Henry Adams Curve. This is a curve of energy use per capita in the U.S., which was rising smoothly but suddenly leveled off in the 1970s:
In fact, the curve is too simplistic, but the basic point is solid. We failed to transition to energy sources better than fossil fuels.
It’s a simple truth that if you want your economy to escape poverty, you need lots of energy consumption:
But that doesn’t mean wealth is always inherently tied to energy. U.S. primary energy use per person stagnated after 1970 and has been falling since the turn of the century:
And yet since the turn of the century, even as energy use has fallen, U.S. per capita GDP has grown by 40%!
This is the magic of dematerialization, and it’s the reason economic growth doesn’t inevitably exhaust the planet’s resources. Not only have humans in rich countries figured out how to produce the same physical stuff with far less energy use, but we’ve found lots of other stuff we like that isn’t physical. Around 1970, Americans started spending more on services than on goods, and the gap has only grown wider since then:
Interestingly, something similar is even happening in China — the country that fetishizes manufacturing the most, and whose autocratic state has moved heaven and earth to provide cheap energy, steamroll the environmental movement, and maintain manufacturing primacy:
It’s possible that this is just a fundamental feature of human nature. Perhaps eventually, once we all have plenty of food, big houses filled with gadgets and nice furniture, and cheap enough transportation to go out to eat twice a week, our desires just naturally turn toward things like health care, entertainment, and spa visits for our dogs.
Nor is it clear that there’s any limit to dematerialization. It might be possible to immerse humans in totally realistic virtual reality environments — allowing us to live in any sort of world we wanted — for only a modest amount of energy. We could conceivably explore virtual galaxies, create virtual ecosystems, live as dinosaurs or sentient spaceships, experience hundreds of lives, all for the low price of an AI to run the whole simulation.
Hall doesn’t really talk about alternative future visions like this. His triumphant futures always revolve around the conquest of the physical — real spaceships, real weather control, real flying cars. And yet he never really explains why we should expend such massive amounts of energy and resources conquering the physical world — it’s simply presented as a triumphant, “Wouldn’t this be awesome?” kind of vision.
But it’s very rare for humans to undertake grandiose endeavors if similar or greater enjoyment can be had closer to home. We’re not going to conquer the stars just because engineers think it’s cool. This is a second limitation of engineerism — the conviction that difficult feats of engineering are desirable in and of themselves.
Of course, there are a few individuals who do think that conquering the physical universe is just really damn awesome, and occasionally they command enough resources to make it happen. But even then, it’s questionable whether they truly derive more value from the physical world or the virtual. Elon Musk has done far more to conquer space than any other human in the last half century, but he personally has never even been to orbit. He has spent a lot of time tweeting, though.
Maybe in the end, 140 characters is just what humanity wants the most?
Of course, I do think the United States needs more abundant energy. We excel in the production of services, but J. Storrs Hall is exactly right when he says that our failure to harness cheaper sources of energy has limited our ability to produce physical goods — and to undertake the kind of engineering feats that we might want to undertake if we had enough energy.
Hall blames America’s energy stagnation on culture — on “ergophobia” (fear of energy), and on an environmental movement that has become more of a religion than a scientifically guided enterprise. I think Hall is generally on the right track here, but I think he gets the specifics a bit wrong. Americans aren’t afraid of energy, they’re afraid of land use; the 70s saw the anti-growth movement impose restrictions not just on power plants, but on housing, factories, infrastructure, and every other kind of physical development.
And it was this more parochial environmentalism — the desire to preserve “open space” near people’s suburban houses — that paralyzed America’s physical economy far more than the climate movement. Endangered species law was often abused to block development, but the underlying motivation was almost always NIMBYism rather than green religion.
Where I think Hall goes even more wrong, though, is in his predictions about what kind of energy technology can break our long stagnation. Hall puts his faith in nuclear fission power, first and foremost. Only the coming of a “second atomic age”, he predicts, will make energy too cheap to meter. And like many, he blames misguided safety regulations for robbing us of this nuclear future.
On one hand, I think Hall is pretty much right about the past. Nuclear power has its risks, of course, but I agree that we significantly overstated the risks and overregulated nuclear power as a result. We obviously could have chosen a different path, because France actually did choose a different path. Most of France’s electricity comes from nuclear power, and has since the 1980s. That could have been us, too, if we hadn’t been so spooked by Three Mile Island.
But the idea that embracing nuclear would have led to cheap, plentiful energy is…well, pretty suspect. France has plenty of nuclear power, but its electricity costs 28 cents per kWh, compared to 18 cents in America. France’s electricity is much cleaner — nuclear power has allowed it to reduce its carbon emissions enormously. But nuclear has not made energy abundant in France.
Perhaps this is also because of regulation? Maybe France allows nuclear, but simply makes it too expensive. Other countries that encourage nuclear construction can bend the cost curve down, and harness scaling effects to make nuclear cheaper and cheaper…right?
Well…maybe. China has probably done the best job of bending the nuclear cost curve downward, and even there, reactor costs aren’t lower than they were in 2010:
But at the same time, there has been another energy revolution that has nothing to do with nuclear. Solar power has become cheaper at absolutely stupendous rates:
You’d think Hall would love the solar revolution, but he doesn’t even recognize that it exists. As far as I can tell, he only mentions solar once, and it’s to dismiss the whole thing with an airy hand-wave:
The currently fashionable “renewables,” such as wind and solar power, have largely escaped the attacks. Battery-powered electric cars are the darlings of the Greens. But this is because they are simply not capable of providing anywhere near the energy or range that civilization depends on at a price it can afford.
This belief — that nuclear power is for real and solar, wind, and electric cars are B.S. — seems to be part of American engineerism. I don’t see why it should be. Getting electricity from sunlight and trapping it in batteries is an inherently very cool engineering task. And yet if you talk to American engineers about energy, nine times out of ten it’s just nuclear, nuclear, nuclear.
Chinese engineers, on the other hand, are embracing the electric revolution with gusto. They’ve created electric cars so cheap and high-quality that they’re conquering the global auto market. And despite the fact that China has kept nuclear costs down, and is perfectly willing to build nuclear, it’s building a lot more solar:
J. Storrs Hall barely even mentions China in his book, and this is one of its biggest failings. We don’t have to think very hard about the hypothetical technological details of nuclear vs. solar; we can just watch what China does. China is ruthlessly focused on growing its economy, its manufacturing industries, and its geopolitical power; it is not swayed by hippie environmentalists. When coal was the cheapest power source, China burned as much as it could.
And yet now, China is building solar far faster than it’s building nuclear. Why? Because solar has, broadly speaking, won the technological race. Intermittency was the last big problem, and batteries have gotten good and cheap enough to make solar reliable. If this were not the case, China would not be transitioning its economy to solar power as rapidly as possible.
Why does American engineerism long for nuclear even after it’s clear it’s been surpassed (for most applications) by something even cheaper and better? My best guess is that this is a historical grudge. In the 70s and 80s, environmentalists told engineers they weren’t allowed to build nuclear power. A lot of engineers still chafe at being told what not to build, and some probably resent solar and batteries for being the things environmentalists told them to go build instead.
But this has resulted in a bunch of American engineers becoming trapped in a retrofuturistic daydream, unable to take advantage of the very real revolution in electric technology.
Which brings me, at last, to flying cars. Hall spends a lot of the book explaining why flying cars are technologically feasible, going through details like the difficulty of flying a plane, prospects for a future air traffic control system to control high volumes of flying cars, and so on.
My guess is that human-piloted flying cars were always going to be a bridge too far, for safety reasons alone — teenagers probably can’t be trusted to fly aircraft over populated areas, to say nothing of potential terrorists. But in the age of AI, we probably don’t need human pilots; we can just automate everything. Here’s a video of EHang’s pilotless VTOL craft giving someone a ride:
The EHang vehicle can’t move along roads, so it isn’t a true, classic flying car. But…close enough, right?
EHang may take off, but for right now it’s a niche type of transportation, authorized at only a few select locations. China has built the world’s most extensive network of high-speed trains, but seems in no hurry to roll out flying cars to the masses. Why?
The obvious answer is that demand for flying cars is limited. Where are you going to go in a flying car? For short distances you already have ground cars, which go slower but are probably a lot cheaper to drive and easier to park. For long distances — international travel, business travel to other cities, etc. — you have airplanes, which are really just flying buses.
There’s an intermediate distance — maybe about 150 to 500 miles — where flying cars might be able to beat both airplanes and ground cars. I had GPT calculate travel times for ground cars, flying cars of the type described in J. Storrs Hall’s book, and airplanes:
Flying cars do OK over short distances, but over intermediate distances they’re the clear winner. (Incidentally, this is also the distance range over which high-speed rail is usually thought to compete effectively with cars and airplanes.)
The real question is what there is within 150 to 500 miles that you’d A) want to visit often enough to justify owning a flying car, and B) be willing to travel 1-3 hours to get to. You certainly don’t need to go that far to shop for groceries or go to the gym. You’re probably not going to go to that many restaurants that require you to travel 1-3 hours each way.
That basically leaves commuting and vacations.
A 1-hour commute is fairly punishing; a 2-hour commute is absolutely brutal; a 3-hour commute is impossible. For shorter commutes, cars (or trains, if they exist near you) work just fine. Even with flying cars, most people aren’t going to want to live 200 miles from their place of work.
As for vacations, these are rare. When people do take trips, they tend to take luggage (which is a lot more expensive to move through the air than along the ground). Planes work perfectly well for most trips, which leaves flying cars to handle short-range vacations. If you’re in San Francisco, that could mean a weekend in Tahoe or Yosemite, or a beach trip to Santa Barbara. Those trips are nice, I’m sure, but probably don’t come close to justifying the expense of flying cars.
In his book, J. Storrs Hall addresses this issue by arguing that if lots of people had flying cars, new destinations would spring up at the requisite distances. First of all, this completely ignores the cold start problem. Without enough flying cars, the new destinations can’t spring up; without enough destinations, owning a flying car is an unattractive proposition.
But even if tourist resorts and awesome restaurants and cool stores sprang up to blanket the American countryside in order to take advantage of swarms of flying cars, their business would have to be diverted from existing destinations closer to where people live. America is a very built-up country with lots of shops, restaurants, and entertainment spots. If you flew your flying car to go eat at a restaurant 100 miles away, you’d be spending almost an hour in transit each way, instead of driving 15 minutes to a restaurant nearby. Sure, you’ll go to the more distant restaurant sometimes, because it’s probably a lot more famous and high-quality than whatever happens to be in your local neighborhood. But will you go often enough to justify owning a flying car?
We should also consider changes in communication technology, which can substitute for some percentage of physical travel; we can now text or video chat with friends, colleagues, or even potential lovers some of the time instead of always driving to see them. Or we can simply amuse ourselves watching TikTok or reading Substacks instead of motoring around the countryside like in 1925 or cruising the strip like in 1960.
In Where Is My Flying Car?, Hall acknowledges this substitutability, but waves it away, saying it would be a shame if communication technology outpaced transportation technology. And yet that may be exactly what’s happening. Young Americans traveled fewer than half as many miles per day in 2022 as they did two decades earlier:
This is just another example of dematerialization of economic output. The internet is substituting for cars. And if the internet is substituting for regular cars, why are people going to rush out and buy flying cars?
In other words, the answer to the question in the title of this post is that you won’t get a flying car — at least, not anytime soon — because you don’t really want one.
This leads me, at last, to the biggest pitfall of engineerism: It focuses too much on supply and not enough on demand. To many engineers, the most important question is “Can we build this?”, not “Why would anyone want this?”. This is a common pitfall for startups, but it applies equally well to futurists (and retrofuturists).
Engineers can grouse all they want, but the blunt fact is that in the long run, technology gets built because human consumers want it. Sometimes, those consumers are governments, who want weapons for war and monuments to prove their greatness. That can sometimes look like building things just for the coolness factor, but in the end, monument-builders tire of making pyramids. And in capitalist, individualist, democratic societies — the kind Americans (roughly speaking) still live in today — the consumers are regular people who mostly just want to get to work on time, watch some funny stuff online, sleep in a comfy bed, and enjoy a nice night out or a vacation once in a while.
Engineers often fail to understand this. Building things is their passion; they want to build, build, build, because it’s awesome. But society will only give them the resources to build the truly big stuff — space elevators and Mars colonies and fleets of flying cars — if they can justify it with a broad-based value proposition. “Hey, let’s embrace our destiny and conquer the stars” makes for a fun rallying cry, but the actual future of technology will be driven by parents shopping for diapers.
Heinlein’s “The Man who Sold the Moon” probably deserves to be on this list, but I actually haven’t read it.
This is also the mindset that Dan Wang ascribes to China’s leaders in his excellent book Breakneck.
In fact, the U.S. government is now trying again, with another $10 million effort.
In fact, just for fun, I spent a couple hours talking to AI about those calculations, and they are not, in fact, the only ones you need to do.
