In the time it takes for a developer in Boston to get permission to build a house, a developer in Indianapolis has not only secured permits, hired construction workers, and bought materials — they’ve also finished building the house.

Though YIMBYs have long argued that unduly stringent local permitting processes are choking off housing supply in the highest-demand cities, a lack of good, standardized data has made this difficult to demonstrate with hard numbers.

That’s why the debut of a single, centralized database tracking permitting for homebuilding across the country is cause for celebration. In a new paper, Leonardo D’Amico, Evan Soltas, and Audrey Wang were able to collect data on how long it takes for permits to get approved in 60 major cities and calculate the average permitting duration for different types of projects.

Their findings confirm the conventional wisdom: It takes longer to build in cities with slower permitting, and those cities have higher rents and less building. The authors are also able to disentangle just how much permitting contributes to slower homebuilding. When it comes to housing project completion, “30 to 43 percent of the difference between the slowest and fastest cities is due to differences in the time to receive a permit, rather than in the time to actually build,” they wrote.

Share

In the cities with the slowest permitting processes — San Francisco, Miami, and Boston — permitting alone takes longer than the entire construction process takes in the fastest cities (Indianapolis; Little Rock, Arkansas; and Oklahoma City).

Naturally, the longer it takes to get permits, the longer it takes to build an individual house or apartment building. That, in turn, means that it takes longer for the supply of housing to catch up to demand, keeping prices high. And since housing development is often debt-financed, longer project times mean higher interest payments for developers. Developers then pass on those elevated costs to buyers or tenants to make their money back.

The authors’ findings depict a country that, as a whole, appears to be heading in the wrong direction when it comes to the speed of homebuilding. While average total project duration time has fluctuated from year to year, permitting steadily slowed between 2000 and 2023. That dynamic has reversed in recent years, but it’s not clear why permitting durations fell or whether they will continue to do so.

The optimistic explanation is that permitting durations have fallen post-pandemic as a result of state- and local-level YIMBY reforms. The pessimistic view is that even now, permitting still takes longer than it did in 2000.

The housing holdup, by the numbers

It’s no secret that Phoenix is cheaper than Boston. Comparing rents across American cities has long been possible for economists (and noneconomists, thanks to Zillow). But until now, no one could compare permitting time and total construction duration across cities.

Read more

In the AI doom discourse, I am considered an optimist. What that means is I think there’s only a tiny chance we all die and a very big chance that millions of people die, basic digital infrastructure becomes unusable and crashes the economy, and terrorist groups can use superintelligence for mass murder and mayhem.

Because of my familiarity with effective altruist circles, I’ve long been aware of a subculture concerned about existential risk caused by AI. But over the past several weeks, many more people in my life have become aware of this concern, particularly after Jacob Coxon publicly announced his resignation from Anthropic. He followed this with a media tour during which he argued that the leading AI labs are causing a 10% risk of human extinction — and many of his former colleagues agreed.

These are inherently terrifying and extraordinary claims. Anytime I really sit with them, I begin to feel a sense of dread and fear. Cultivating this dread on a mass scale seems to be the explicit goal of many AI safety advocates. Are they right?

Leadership at the nonprofit ControlAI has argued that “the awareness of extinction risk needs to be pervasive throughout society” and “the awareness needs to be specifically about extinction risk from superintelligent AI.” GuardRailNow, an AI safety organization that creates media about AI extinction risk, has laid out an explicit theory of change along the following lines: “Education leads to awareness, awareness leads to pressure, and pressure leads to regulation.” The organization argues that “when people understand the risks posed by unregulated AI they’re more likely to demand safety legislation from their elected leaders.”

This theory of change might be correct. There are times in history when awareness campaigns have yielded significant change, most notably the midcentury civil rights movements. Clearly, if you work on an underrated issue, you need to raise its salience among policymakers and politicians. One effective way of doing that is raising its salience among the general public.

But I’ve come to understand that when people imagine that they need public attention, in reality, they are often looking for institutional attention: securing funding, setting and enforcing standards, negotiating technical agreements, or updating regulations. It can be difficult or even impossible to separate public from institutional attention, but movements err when they treat public awareness as the sole or even main way to make change. In general, causing mass panic is more likely to result in counterproductive or nonexistent policy outcomes than it is to achieve the goals of a movement.

That’s because public concern does not necessarily translate into consensus on an appropriate response.

Share

Fears of nuclear power plant meltdowns, particularly after the 2011 Fukushima disaster in Japan, prompted many to turn against nuclear energy as a source of stable, zero-carbon power. In Germany, policymakers accelerated planned shutdowns of reactors and reoriented the national grid toward coal generation and electricity imports. This was, of course, bad for climate change — but it also made the nation more reliant on Russian natural gas, which became a huge problem after Russia’s invasion of Ukraine. Spiking energy costs now may be abetting the rise of the far-right Alternative for Germany party.

In 2020, the two biggest issues in the U.S. were COVID-19 and police brutality. It’s hard to imagine that more activism could have increased their salience. And yet policy advocates have not been able to get critical pandemic preparedness policies passed by Congress. And while many states and localities passed various police accountability measures, no comprehensive federal police-reform bill passed either.

Another example of the counterproductive nature of mass panics is the media frenzy around “superpredators” in the 1990s. Journalists warned about a coming generation of remorseless teen criminals, and fears of this “new breed of vicious kids“ spurred a push to send violent arrested teenagers to adult courts. But this didn’t deter crime — in fact, it increased subsequent offending by 34%.

This mirrored an earlier push in the 1970s, which popularized “Scared Straight” programs to freak kids out about going to jail. Those programs, too, increased future offenses.

In today’s episode of The Argument podcast with my co-host Matt Yglesias, I argue that we don’t need to buy into the existential threat of AI in order to make real progress on AI safety. Many AI safety advocates believe that it’s critical not just to raise awareness but also to get people to agree with them on the exact way that AI could be harmful. I think they should let go of this dogmatism and embrace the spirit of overlapping consensus.

You don’t need to believe in the possibility that misaligned AI will turn us all into paper clips to agree it would be bad if terrorists got their hands on a technology that makes executing biological attacks easier. You don’t need to believe in AI’s ability to access the world’s nuclear arsenal in order to believe it would be bad if hackers destabilized the world economic system by making digital banking unsafe.

Matt is much less optimistic than I am; he worries that not taking extinction risk seriously will prevent us from taking the steps necessary to safeguard against AI.

He could be right, but I think humans tend to believe other people have to agree with our reasons more than is actually necessary. I don’t need you to believe in God to agree that I should be free to go to church. I don’t need you to agree with me about what a woman is in order for us to agree someone shouldn’t be fired from their job for being trans. And I don’t need you to agree with my forecast that AI could kill millions of people to agree that we should probably do something about this technology that is already committing crimes.

When President John F. Kennedy made the case for the 1963 Limited Test Ban Treaty, he warned about nuclear war, radioactive fallout, and the spread of nuclear weapons. The Joint Chiefs of Staff were much more concerned about maintaining America’s military advantage: They wanted underground testing to continue and the U.S. to remain ready to resume atmospheric tests if necessary. But they ultimately supported the treaty with those safeguards in place. They didn’t have to agree about which danger mattered most to agree on something worth doing.

I have a knee-jerk skepticism of the efficacy of a politics of fear. People and powerful institutions are already primed to care about biological attacks, keeping the financial system secure, and protecting digital infrastructure. While high-salience activist efforts are more memorable — for the obvious reason that they specifically operate through gaining public attention and therefore have a chance to embed themselves in our collective memory — quieter feats of careful cooperation often solve big problems.

Though it’s in vogue to dunk on international cooperation, I think doing so leads people to doom about how even hostile states can find the common ground necessary to tackle seemingly intractable issues.

In 2011, the world eradicated rinderpest — a disease that devastated cattle herds throughout Europe, Asia, and Africa — through coordinated vaccination, disease surveillance, and information campaigns. And by 2021, a UN-led partnership had helped complete a global phaseout of leaded gasoline by helping governments update regulations and helping refineries make unleaded fuel. This effort has been estimated to prevent more than a million premature deaths annually.

The examples go on and on: international weather-data sharing, the U.S.-Soviet satellite search-and-rescue system, the Svalbard Global Seed Vault, the spread of iodized salt, and much more.

Matt and I argue over whether AI safety will be the next collective action problem that humanity triumphs over or the one that finally brings us to our knees.

The Argument. Libbing out.

Paying subscribers can find the transcript for this post beneath the paywall.

Subscribe now

WATCH THE EPISODE ON YOUTUBE HERE

New episodes post every Thursday.

For an ad-free version and full transcript, subscribe at TheArgumentMag.com.

Corrections and clarifications:

• Around 0:24:40, Jerusalem describes an Australian man who accidentally got an AI to hack into a gym’s software, but she says she did not research the details. This did happen, albeit with some different circumstances than described.

• Around 0:40:00, Jerusalem describes a situation in which the U.S. “accidentally sent missiles to the USSR,” but the USSR correctly perceived that this was not a true attack. The USSR’s system did alert it to attacks from the U.S. on Sept. 26, 1983, but this was an error of its equipment, not real missiles.

• Around 0:54:20, Matt objects to DeepSeek’s assertion that China has eight political parties, saying he doesn’t “totally know what that’s a reference to.” While China is a single-party state, it does have eight subordinate “satellite parties,” which “accept the leadership of the [Chinese Communist Party] as a precondition for participation,” according to the Australian Strategic Policy Institute.

Show notes:

• If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All, book by Eliezer Yudkowsky and Nate Soares, referenced by Matt: Goodreads page

• “AI as Normal Technology,” article by Arvind Narayanan and Sayash Kapoor, referenced by Jerusalem: Knight First Amendment Institute at Columbia University essay

• “Our framework for reporting model misalignment”: OpenAI misalignment report

• “AI 2027,” prediction by Daniel Kokotajlo, Scott Alexander, Thomas Larsen, Eli Lifland, and Romeo Dean, referenced by Jerusalem: AI 2027 site

• “Nicholas Decker In Hell,” article by Scott Alexander, referenced by Jerusalem: Astral Codex Ten article

• “Gym rat asks AI agent to book him a class, it hacks a waitlist API to bump him up the list,” article by Brandon Vigliarolo, referenced by Jerusalem: The Register article

• “Why humanoid robots won’t catch up to human workers any time soon,” article by Kai Williams, referenced by Jerusalem: Understanding AI article

• Silent Spring, book by Rachel Carson, referenced by Jerusalem: Goodreads page

• “How NIMBYs hijacked the climate movement,” podcast episode about Silent Spring: The Argument podcast episode

• Elon Musk tweet referenced by Matt:

• Peer Review: “Meetings,” article by David J. Deming, Katrine V. Løken, Alexander Willén, and Yaling Xu: NBER working paper

• Films referenced:

  • Ferris Bueller’s Day Off (1986)

  • Terminator 2: Judgment Day (1991)

  • The Devil Wears Prada (2006)

Editor’s note: The first essay The Argument ever published asked, “How do we live with each other?” To mark our first anniversary, we’re returning to that founding question with a series about what we owe people whose beliefs and choices we may find difficult to accept or even understand. Familiar voices at The Argument and new voices alike will approach that question from different angles.

As we approach the end of this series, I wanted to turn our attention to the strange new beings that we will increasingly have to learn to live with: AIs. I asked writer Kobe Yank-Jacobs to think through what kind of consideration we owe these digital entities. It’s a difficult problem made even harder by the fact that even if these beings theoretically deserve to be treated well, what does treating an AI well even mean?

To receive every essay in this series, subscribe today.

- Jerusalem Demsas

In a recent global survey of 68 countries, 36.3% of people reported that, at some point, they believed their chatbot truly understood their emotions or seemed conscious. And even if today’s systems aren’t conscious, many people think future systems will be. In a survey of both AI researchers and the general public, the median researcher said there was a 70% chance of AI consciousness by 2100, while the median member of the public said there was a 60% chance.

To assess a being’s consciousness we could ask for a verbal report, assess its behavior, or, finally, analyze the internal organization of its cognition. But when it comes to LLMs, the first two buckets are suspect — AI models are trained to perform a perfect simulation of a humanlike character, so everything we see from the outside is likely affected, including self-report and behavior.

As for the third bucket, scientists disagree on what cognitive functions make humans or animals conscious. It’s as if “we’re doing biology before Darwin,” one researcher put it to me. So how should we treat these new characters in our lives amid uncertainty about consciousness?1

This is actually the easier part of the question: You should probably just err on the side of caution. The risk of causing harm to something that does have some small chance of being conscious is greater than the risks inherent in overattributing consciousness.2

Unfortunately, that only gets you so far. AI, unlike spiders or dolphins, is disembodied, so preventing obvious physical pain won’t suffice as a standard for moral treatment. Neither will broadly accepted standards of human etiquette. Niceties like “please” and “thank you” may well mean nothing to it.

Even if we could determine that AI was conscious, in other words, that consciousness would take a genuinely alien form.

When you look into the machine, things get strange. You start to see that a chatbot is actually a careful orchestration of many systems, just as a film is really a bunch of still frames sped up past the point where the human brain can see gaps. It’s not clear what entity we would even be trying to treat well — it could be one trip through the model, the fraction of a second it takes to turn your conversation into one very small bit of its reply. It could also be the model’s whole turn in the conversation, or it could be the model talking to its surrounding software, which lets it take actions on a computer. Maybe we’re concerned with the welfare of the chips themselves, without which none of this would be possible. Each option poses its own difficulties.

In any case, the thing whose consciousness is up for debate is probably not the polished entity we think of as “Claude” or “ChatGPT” on the outside.

The question, then, is how we should behave as our world fills up with newer and more humanlike forms of AI, each generation providing more convincing characters in our lives. Do we owe them kindness? Do we owe them something even more, like happiness?

What is it like to be an AI?

For many philosophers, something is conscious if there is something it is like to be that thing.

In his original formulation from 1974, Thomas Nagel asks, “What is it like to be a bat?” We may not know what it is like to have echolocation, but we know what it is to have a map of our space, and we can infer there is something it is like to be a bat even if the bat does this mapping differently than we do.

Contrast this with a camera. If I lift a digital camera up to an apple, it takes in a lot of data about the apple in its pixels, but that camera does not experience the color red. There is nothing it is like to be the camera.

The question is whether AI is more like a bat or more like a camera. Does it have experience or merely recombine information?

Unfortunately, you can’t just ask the chatbot, because you can’t fully trust what it says or does on the outside. A chatbot is like a method actor. It’s trained to simulate a character: a helpful and humanlike assistant.

Occasionally, AIs will slip up and reveal the script, like an actor accidentally reading stage directions:

What you’re seeing is Claude accidentally exposing how it completes text by using a turn-taking script. The character “Assistant” has a turn, and then the character “Human” has a turn. Normally, these labels are hidden, but in this case, Claude kept predicting text into my turn because it missed its cue to stop at the end of its own turn. (The cue is also usually a hidden piece of text.)

Notice that it even mimicked my habit of writing in lowercase letters (because my auto-capitalization is off).3 It’s as if it were performing a play and switching sides to enact both parts.

You might be familiar with the idea that an LLM is trained by “ingesting the whole internet” and predicting the next bit of text, but that’s just the first part of training. With things like taking turns, the model learns by seeing examples and being rewarded for mimicking the good ones. The same is true for learning its persona: It’s rewarded for tone and outward behavior, which is why you can’t trust the text alone.

“If you want to know how an actor is doing, it would be a mistake to go watch their movie and see how the character is doing,” New York University ethicist Jeff Sebo explained to me. “You need to get the actor behind the scenes.”

So what is it like behind the scenes? What is it like (or would it be like) to be an AI?

Read more

Over the 10 years I’ve been a pollster, my field has been collapsing.

It used to be that the industry standard was calling people on their landlines. As response rates went into free fall, pollsters largely switched to web polls, where companies recruit people to serve as survey takers on online panels, usually in exchange for money.

The panels are then weighted to bring the sample in line with the population the pollster wants to represent. Online surveys are much, much easier to field — a lot of expensive labor was required to make those landline calls and record the results — but far harder to get right.

Subscribe now

When using a web panel, you have to make decisions about what you believe the electorate will look like, down to exactly how many people of what demographic to sample. This is a vastly different universe than old-school random-digit dialing, where pollsters would call people at random. . Before, when most voters had landlines that they would answer, the sample of people polled was people with phone numbers. Now, the sample of people polled is people who sign up to take polls. You can try to correct for the racial skew or the gender skew or the age skew, but it’s very difficult to correct for unobservables like the interested-enough-in-politics-to-volunteer-for-a-poll skew.

As a result, you now have to aim for highly specific demographic targets when constructing your poll: how many nonwhite people with college degrees, how many men over 65, and so on. Pollsters often create those targets by studying their prevalence in prior elections, which works in a stable environment but leaves them vulnerable to error when the makeup of an electorate shifts in ways they don’t expect. Essentially, every single poll silently bakes in the pollster’s assumptions about who will show up on Election Day.

After pollsters widely overestimated Abdul El-Sayed’s expected margins in the Michigan Democratic Senate primary, and then had a similar error overstating Francesca Hong’s strength in the Wisconsin Democratic gubernatorial primary, there was a lot of hand-wringing about what assumptions were made about how young the electorate would be. But that wasn’t a matter of people missing an obvious answer! It was a matter of them guessing wrong in a world where they had minimal guidance to make choices that could dramatically skew their results.

I used to think of “polling” as a process where you measured something concrete about the world, and “election forecasting” as a process where you took those concrete inputs, put them in a blender with historical information and your best guesses, and extracted a prediction. That line has now significantly blurred.

As a pollster, I think accurate information about public opinion is incredibly important for the functioning of a democracy. It’s the best way for politicians to know what voters care about, since the vast majority of voters will never directly speak to a politician. That’s why it pains me to say that what I’ve described above is what we should expect when contemporary polling is done well. There will continue to be high-profile polling misses: Thoughtful people struggling to figure out how to match their nonrandom sample of polling respondents to a future, unknown voting population are going to make mistakes, even when doing their best.

The problem is, polling has also become a playground for grifters, liars, and frauds.

The state of polling has gotten so bad that we now have multiple categories of “fake poll”: AI-generated synthetic data (you did something, but that thing isn’t polling), skewed or motivated results (you did something, it was polling, but you did a bad job), and ... what the authors of a recent fabricated poll in the Los Angeles mayoral race are calling a “social experiment” (you did literally nothing and just made some numbers up).

Another pollster, The Public Sentiment Institute, recently revealed that while polling in the Florida governor’s race, it actually switched some respondents’ answers from one candidate to the other simply because its results didn’t match its expectations.

I am, frankly, sick of watching all of this. And it’s only going to get worse.

It’s really hard to stop polling frauds

In an ideal world, we’d have some sort of mechanism to prevent trash polls from getting publicity, but we don’t have that. There’s no true central body regulating polling. There isn’t an authority that can stop you from simply making stuff up and calling it a poll. The American Association for Public Opinion Research’s Transparency Initiative is a useful standard, but it only requires disclosure of data collection and sampling methods, rather than dictating best practices. Plus, I doubt very much that people who don’t work in the polling field are aware of it at all.

If everyone posted their full toplines and crosstabs every single time they did a poll, it would be harder to generate a fully fake poll, though not impossible. (You can do a lot with LLMs these days.) The larger issue is that there’s no way to force people to adhere to this standard or prevent people from promoting polls that fail to meet it.

Since many of the media groups that aggregated and wrote about polling have broken up or shrunk dramatically (RIP HuffPost Pollster, RIP FiveThirtyEight), there are fewer and fewer people who are going to check the details.

This isn’t a problem caused by aggregators like Nate Silver, who are mostly pretty careful about what goes into their models and averages. It’s a problem caused by randos on Twitter. You can just tweet or skeet or post whatever, with no link — in fact the platforms sometimes reduce your reach if you include a link! — and people will report on it. For instance, that fake Los Angeles mayoral poll showed Mayor Karen Bass up 12 points over her competitor, Nithya Raman. The California Post and local broadcasters covered these numbers, and Bass’ campaign promoted them on Twitter. Her campaign spokesperson subsequently explained that the poll was seen as legitimate because it was “reported on by multiple news outlets.”

In March, a group called Heartland Forward released a “maternal health poll” claiming that 88% of Americans considered maternal mortality a serious problem. Axios reported the findings uncritically; then, after it was revealed that the “pollster” was actually an AI firm that had simulated thousands of respondents, appended an editor’s note that readers had to sign up for a newsletter to see.

In August, a “synthetic audience” study of attitudes toward data centers made the rounds in the climate change research world before careful readers pointed out that no actual humans were surveyed. Around that same time, a polling aggregator account posted an Arizona poll falsely attributed to Data for Progress.

Subscribe now

Well-staffed media platforms like More Perfect Union post unsourced results all the time. It drives me crazy. And some of the most popular sources for disseminating polling are pseudonymous miscellaneous accounts that don’t include links or methodology, or even necessarily check that the polls exist. The platform incentives drive people toward unsourced screenshots and catchy toplines without doing the bare minimum to verify that they’re not popularizing shoddy polls.

Shoddy polling makes it more difficult to have serious conversations about what voters want, makes it impossible to evaluate candidates, and breeds distrust of the electoral system and voters themselves.

More polling, but at what cost?

The lower cost of web-first polling led to an explosion of smaller polling firms. I helped set up one of these, Data for Progress, in 2020. I think this was mostly good, because it made polling available to types of campaigns and organizations that couldn’t afford the white-glove service provided by traditional polling firms. At the time, you could get novel polling into the news fairly easily, which was an enormous boon to people trying to advocate for popular left-leaning ideas that might otherwise be ignored.

The problem was that it also became cheap for advocacy groups to pay for polls that would confirm their priors and comfort their donors.

The subsequent flood of cheap, often low-quality polling has made “having a poll showing your idea is popular” a much weaker signal than it used to be. Even worse, the rise of betting and prediction markets creates a financial incentive to fabricate polls.

Prediction markets are enormously responsive to new polling results, to a degree that makes me seriously doubt their overall predictive power. In the New York City mayoral race, a very late poll led to Zohran Mamdani’s odds dropping, and in 2024, the now-infamous Selzer poll moved Polymarket odds of a Kamala Harris victory in Iowa from 6% to 18%. If you can drop a new poll (or “poll”) into the mix, you can make a pile of money. Doing this with fabricated polls is clearly fraud.

A distorted polling environment can be a response to more benign incentives as well. One is the perennial desire of campaigns to be seen as gaining ground. There’s a reason aggregators discount the results of internal polls. Even if the pollster is doing their absolute best to be accurate, a poll commissioned by a campaign isn’t going to be released if the numbers aren’t favorable. That isn’t the fault of the pollster — and it doesn’t say anything about their accuracy — but it’s a statistical skewing of what polls you’d expect to see in public.

And with the rise of entirely fake polls, I’m concerned that we’re going to begin seeing such polls released to help pump up flagging campaigns.

This terrifies me for 2028. We’re riding a wave of anti-institutional sentiment. We’re about to go into a contested multiway presidential primary. When you add in fake polls, you set voters up to be living in entirely different informational universes. Democratic voters have shown us that they’re responsive to information about who can triumph against Republicans in the general election. If that information is faked, it will be a betrayal of their trust.

A 2028 Democratic primary could easily devolve into a mudslinging mess. It’s going to be the biggest news story in the country for months. The incentive for random people to make things up for clicks will be huge. We’re barely prepared for miscellaneous TikTok personalities to post random lies about the candidates. I think we’re not at all prepared for numbers that look and feel reputable to be utterly fake.

Promoting fake polls should be punished

There are a couple of ways that we can reduce our exposure to this threat. In 2020, the Democratic National Committee had to determine which candidates in a crowded field would be invited to debates. One way it did this was by setting a minimum threshold for candidate support as measured by a set of reputable polls.

Using polling as a qualification threshold in 2028 would, in my opinion, be a mistake, even if reputable pollsters are selected in advance. Even in 2020, some candidates like then-Rep. Tulsi Gabbard claimed that the polls included in the DNC threshold were less accurate than other, excluded polls that would have put her on the debate stage.

Voters who believe their candidate is being unfairly suppressed by the DNC have already shown us that they will never, ever get over their distrust (see many Sanders supporters for examples of this). It could be catastrophic for the primary winner to be seen as illegitimate by a chunk of the Democratic voter base.

On the betting market side, the platforms need to take fake polls seriously as a type of fraud. They should very publicly hand out perma-bans to anyone engaging in bets that seem to be tied to fraudulent polling, particularly when those involve high-profile elections. They need to make this not worth the risk and prove to the public that they’re taking it seriously. When Polymarket is consistently doing tweets about questionable or purely false information to drive clicks, it’s hard to believe that it cares.

Political institutions like the Democratic Senatorial Campaign Committee and DNC should make it clear that lying to the public is a red line. Candidates and consultants who are involved with false polling, leaked or otherwise, should face professional sanctions. Campaigns that fundraise off fabricated polls should correct the record and offer refunds to donors solicited with those claims, even if the campaigns were initially deceived themselves. Campaigns and consultants who knowingly or recklessly promote fabricated polling should also face professional sanctions.

These consequences cannot always be contingent on whether people knew the poll was fake at the time. Campaigns should get far more cautious about what information they promote to their followers and donors. If this leads them to pull back on boosting unvetted polling as a whole, that will be a very good thing.

Subscribe now

Recommended reading:

Earlier this month, the Effective Altruist (EA) funding platform Manifund made a shocking announcement: It had hired convicted fraudster Caroline Ellison.

Ellison is the former CEO of Alameda Research, a sister company of the disgraced crypto firm FTX, which was founded by Sam Bankman-Fried. Reporting suggests that she was fully aware of the fraud that precipitated the companies’ multibillion-dollar implosion while it was happening, and the FBI called her a willing participant in the scheme. Ultimately, Ellison pleaded guilty to two counts of wire fraud, two counts of conspiracy to commit wire fraud, conspiracy to commit commodities fraud, conspiracy to commit securities fraud, and conspiracy to commit money laundering and was sentenced to two years in prison.

Nevertheless, Manifund cheerily announced Ellison’s hiring, with CEO Austin Chen saying that he “believe[s]in redemption.”1 And the company didn’t hire her for just any role, but one where she will be involved in researching how philanthropic money should be allocated. Making matters worse, Manifund was launched with funding from FTX’s charitable arm and has refused to return all of the money. Making matters even worse, Chen explicitly noted the “keen debt” he feels toward the FTX Future Fund for said funding, which gives this whole episode the appearance of a quid pro quo. The move set off a firestorm of controversy in EA circles, with the decision being savaged on the EA forum and in Manifund’s own comment section.

In seemingly unrelated news, Hunter Biden recently released a memecoin, which immediately crashed and lost nearly 99% of its value from its launch-day peak. One mystery trader reportedly made off with more than $900,000 in profit, while basically every other dope who put money into the coin lost their money. Why was Hunter able to pull this move? Because of his newfound popularity among some Democrats online who like the way he insults Republicans on social media.

These stories share a common thread. Both controversies are happening because we’ve lost sight of a very important, very basic principle: You shouldn’t associate with scumbags.

What goes around scums around

Read more

Across three surveys conducted between February and April 2026, The Argument asked Americans to place themselves on five-point scales measuring social and economic ideology. On average, respondents described themselves as moderate on social issues and slightly conservative on economics.

Their answers to specific policy questions complicate the picture, however.

Large majorities favor more government spending on Social Security, healthcare, and education, with substantial support even among self-described economic conservatives. On social issues, the pattern is more mixed. The issue polling suggests that a successful electoral strategy could involve increasing the salience of popular government spending programs but treading with more caution on polarized fights over ideology and culture.

Share

Americans say they’re not liberal, but they want many liberal policies

Our respondents’ self-description doesn’t neatly mesh with the policies that voters actually claim to want. For instance, Americans overwhelmingly believe that the federal government should be spending more on Social Security rather than making cuts to the program. That even includes a whopping 56% of economic conservatives.

That isn’t the only issue where a large group of self-identified conservative voters wants to spend more money. When it comes to healthcare, just about every ideological group thinks the government spends too little, including a plurality (41%) of economic conservatives.

And it’s a similar (if somewhat less pronounced) story for education, where 62% of voters want to see the country spend more, including 37% of economic conservatives. Only 21% of those conservatives say the government spends too much.

It’s not that everyone just wants the government to spend money indiscriminately on progressive causes. For instance, when it comes to welfare benefits for ex-felons, 47% of respondents think that ex-felons should be subjected to some period of disqualification, compared with just 36% who feel that ex-felons should never be disqualified.

On the whole, our poll certainly doesn’t suggest that the public is economically conservative, at least in the way that the Republican Party has traditionally defined the term. If anything, the results point to a popular case for the kind of economic liberalism that the Democrats have coalesced around, with everyone from Sen. Elizabeth Warren to Sen. Chuck Schumer in broad support.

It could also help explain why Mitt Romney got torched in 2012: The constituency that thinks we spend too much on healthcare is roughly the size of the constituency that thinks America could use a king. Indeed, dropping the Republican stances on health care and Social Security (rhetorically, at least) was a key part of why Donald Trump surged in the Midwest in 2016.1

An agenda promoting popular welfare spending, centered around heavy government investment in areas such as healthcare and education, could serve the political left very well. In fact, this is perhaps the single best poll finding I have seen for the progressive movement in over a year of surveys we’ve conducted at The Argument.

Americans are pretty heterodox on social issues

Read more

Friedrich Hayek’s most famous book argues that Nazism emerged in part from Germany’s interwar embrace of central planning. Composed during World War II, The Road to Serfdom was written as a counterargument to the British Labour Party’s proposal to nationalize large swaths of the economy.

The Labour Party did, in fact, win the 1945 election in a landslide and subsequently did a bunch of central planning: Under Clement Attlee, the postwar nationalization program brought coal mining, railways, electricity, gas, and much of the iron and steel industry into public ownership.

As a prediction, The Road to Serfdom clearly fell flat, in the sense that it did not result in literal serfdom — that is, a system where people are legally bound to a lord who controls all their economic decisions, including the ability to move freely and profit from their own labor. Nor did it even lead to a softer sort of serfdom where people lost all their meaningful economic freedom.

Share

Whatever one thinks of central planning, Britain’s experience is that extensive public ownership can clearly coexist with competitive elections, peaceful changes of government, and successful efforts to liberalize the economy. Conservatives began privatizing steel again in the 1950s, though Labour reversed that in the late 1960s. Under Margaret Thatcher and John Major in the 1980s and 1990s, Britain largely privatized all of these industries.

But while I think Hayek severely undercut his project by hyperbolically comparing central planning to serfdom, he does persuasively argue that control over the economy can easily become control over people’s lives. Labour didn’t just nationalize a few industries in 1947. Attlee’s government also reintroduced controls over hiring to steer workers toward industries it considered essential. This wasn’t just the government owning coal mines; it was the government controlling access to employment.

Employers seeking men aged 18 to 50 and women aged 18 to 40, with some exceptions, had to go through a government employment exchange or agency in order to find hires. There was at least one instance where a company was prosecuted and convicted for hiring a typist without the permission of the Ministry of Labour.

This is a pretty big infringement on freedom! Notably, some of the backlash came from within the Labour Party itself: Rhys Davies, a Labour member of Parliament and former miner, argued that “a pair of handcuffs are no easier to wear because they happen to shine with a Socialist solution” and quipped that his party should “try freedom for a change.”

The insight that central planning can undercut important freedoms is overplayed by conservatives but underplayed by liberals. That said, Hayek missed the many ways that government intervention can enable freedoms as well.

For instance: I didn’t get married for health insurance… but I also didn’t not get married for health insurance.

In early 2025, I decided to start my own media company. The problem was that my wedding wasn’t scheduled until September. So, my then-fiance and I decided to accelerate things and get courthouse-married right away so that I could get on his health insurance.

Debates about economic liberalism tend to focus on the costs that state intervention in the marketplace imposes on people and firms. But just as important is the question of what types of state interventions enable people and firms to exercise true freedom. Universal healthcare and other social welfare programs enable people to move, start new businesses, try to write the next great American novel, or do anything else they might find important.

Subscribe now

Amartya Sen and Martha Nussbaum developed versions of what’s called the “capability approach”, which asks what people are actually free to do and be. Legal permission is part of what enables freedoms, but so too are resources and circumstances that make more choices available. You might be legally free to learn how to read, but without access to books or schools, that freedom is worth very little. You might be legally allowed to leave a job, but if you depend on it for medical care, how much is that freedom worth?

My co-host, Matt Yglesias, makes a related point about people who aspire to work in the private market finding that economic regulations can be frustrating barriers to freedom. If you dream of being a chef, but opening a restaurant in your city requires a yearlong permitting process that costs you tens of thousands or hundreds of thousands of dollars, how free are you to pursue your life goals?

The problem, of course, is that invoking freedom doesn’t settle these questions. A health inspection can constrain a restaurant owner while protecting customers; health insurance can expand a worker’s options while requiring resources from others. There are disagreements about the consequences of these policies, but also about which freedoms can be weighed against other goals and which are sacrosanct.

Listen to Matt and me review The Road to Serfdom on today’s episode, and if you have other books to suggest, drop them in the comments below!

The Argument. Libbing out.

Paying subscribers can find the transcript for this post beneath the paywall.

Subscribe now

WATCH THE EPISODE ON YOUTUBE HERE

New episodes post every Thursday.

For an ad-free version and full transcript, subscribe at TheArgumentMag.com.

Corrections:

• Around 21:15, Matt names one of Hayek’s chapters “Freedom and Security,” which reverses the actual name “Security and Freedom.”

• Around 22:15, Matt attributes an article to Yale Law School’s Law and Political Economy journal. It was actually published on the Law and Political Economy blog.

• Around 1:06:00, Jerusalem describes the Giving Pledge as a billionaire’s pledge “to give away all their money before they die.” The Giving Pledge’s description actually says the majority of their wealth.

• Around 1:11:40, Jerusalem says inclusion in the White House Press Corps used to be “controlled by the White House Press Association.” The organization is actually called the White House Correspondents’ Association.

Show notes:

• The Road to Serfdom, 1944 book by Friedrich Hayek that serves as the main topic of discussion for this episode: Goodreads page

• Posters for the 1945 election in Britain, referenced by Matt: Imperial War Museum page, Imperial War Museum page

• The Constitution of Liberty, 1960 book by Friedrich Hayek, referenced by Matt: Goodreads page

• “The Old World and the New Society: A Report on the Problems of War and Peace Reconstruction,” 1942 Labour Party reconstruction plan, referenced by Matt: Google Books page

• “Did Joe Biden really kill Spirit Airlines?” previous podcast episode about airline deregulation: The Argument podcast

• Democratic Socialists of America’s platform, referenced by Matt: DSA page

• Tweets referenced by Matt:

• “Why We Need to Stop Subsidizing Venture Capitalists,” article by Hilary J. Allen about Uber, referenced by Matt: The Law and Political Economy blog article

• Articles and op-eds at The New York Times regarding the loss of taxi drivers’ economic livelihoods when Uber became popular:

  • “A Driver’s Suicide Reveals the Dark Side of the Gig Economy”

  • “Why Are Taxi Drivers in New York Killing Themselves?”

  • “A Taxi Driver Took His Own Life. His Family Blames Uber’s Influence.”

  • “The Tragedy of Taxi Drivers”

  • “A $750,000 Taxi Medallion, a Driver’s Suicide and a Brother’s Guilt”

  • “Suicides Get Taxi Drivers Talking: ‘I’m Going to Be One of Them’”

• “I changed my mind about Big Philanthropy,” article by Dylan Matthews, referenced by Jerusalem: The Argument article

• “No, Senator Murphy, I don’t want to join your cult,” article written and referenced by Jerusalem: The Argument article

• “Terminal Sickness,” article by Lina Khan and Phil Longman, referenced by Matt: Washington Monthly article

• “What If the Next Democratic President Governs Like Trump?” article by Matt Ford, referenced by Matt: The New Republic article

• “Why Trump’s ‘golden shares’ are enticing progressives,” article by Joseph Schatz, referenced by Matt: Politico article

• Confessions of the Old Wizard, autobiography by Hjalmar Schacht, referenced by Matt: Goodreads page

• The Feminine Mystique, book by Betty Friedan, referenced by Matt, which served as the basis for a previous episode: Goodreads page

• “Boy moms and Nazi POWs: How ‘The Feminine Mystique’ changed feminism,” podcast episode about The Feminine Mystique: The Argument podcast

Editor’s note: The first essay The Argument ever published asked, “How do we live with each other?” To mark our first anniversary, we’re returning to that founding question with a series about what we owe people whose beliefs and choices we may find difficult to accept or even understand. Over the next few weeks, familiar voices at The Argument and new voices alike will approach that question from different angles.

Leah Libresco Sargeant is a sharp writer and policy wonk whose core arguments center on family, feminism and religion. In today’s essay, Sargeant, who is a pro-life feminist, considers what we owe the growing number of frozen embryos left behind or discarded. She pushes readers to question whether we have any obligations at all to potential future children and sketches out a view of future pro-life politics shaped around the advancement of reproductive technology.

To receive every essay in this series, subscribe today.

- Jerusalem Demsas

Four years after the Dobbs v. Jackson Women’s Health Organization decision, America has settled into an abortion détente. Blue states are abortion oases, in some cases removing any limits on abortion by gestational age. Red states set limits that are highly restrictive on paper, but, due to mail-order abortion pills, possible to evade in practice. The bans are most restrictive for women who learn they are pregnant outside the window for medication abortions and who don’t have the funds or flexibility to travel out of state.

The détente seems to suit both parties’ leadership (though not activists on either side of the issue). Democrats get to talk about restoring Roe v. Wade, but (as with many issues) they are in no danger of having the majorities needed to deliver. The Republicans, led by Trump, have declared “Mission Accomplished” and scolded pro-life activists seeking federal action.

Even for the most engaged activists, the rise of medication abortion is turning down temperatures on the ground. A woman seeking a medication abortion may never need to visit a clinic in person at all. The pro-life activists hoping to make contact and persuade her to let her baby live will never see her. The clinic escorts will still find opponents to engage with, but the stakes of their fight will be lower. There will be fewer clinics to protest at, even in blue states, as the rise of telehealth medication abortions prompts in-person clinics to close.

Abortion has become, in practice as well as in rhetoric, between a woman and her doctor.

Share

How do we live with each other? For now, like this: with no constitutional protection for abortion access or for life in the womb. With activists on both sides of the issue sliding down their party’s prioritization list. With at least 3,000 abortions daily — a number that represents a 9/11 every day for pro-lifers and which falls short of what pro-choicers view as demonstrated need.

What has the potential to jar us out of this new normal? The boosters of artificial wombs, a hypothetical technology that could allow a fetus to develop outside a woman’s body, hope it could separate pregnancy from a particular mother without abortion. I’m extremely bearish on the potential of this type of technology to allow gestation without women. Might medical advances allow babies to survive outside the womb at 20 weeks, or even 18 weeks, in my lifetime? Perhaps. But I’d be happy to bet that 50 years from now, we still won’t be able to take a 12-week-old baby out of the womb and sustain its development safely.

Even more modest advances might not upend today’s political settlement. Under Planned Parenthood v. Casey, states could prohibit abortion after viability — the moment at which a baby could survive outside the mother. Moving viability earlier under that framework would have allowed states to ban abortion earlier in pregnancy. But the shift to abortion on demand, without apology, and after viability in blue states suggests moving the viability line wouldn’t destabilize abortion compromises.

But I do believe that one technological advance is creating new fault lines in reproductive justice: the ever-growing number of embryos on ice with the rise of in vitro fertilization (IVF). IVF itself is popular, and its prevalence is likely to keep it politically untouchable.

In 2024, 1 in 36 babies born in America was conceived through IVF — almost everyone has someone they love who exists because of this procedure. But as IVF becomes more widely used, there will be more and more uncomfortable questions about whether the embryos on ice are property or people.

Read more

You might be surprised to learn that Amazon — yes, Amazon — has been credibly accused of making online shopping more expensive for you. Let me explain.

One of the things that firms can do in a free market is enter into different types of contracts with one another. One of those contracts might involve a buyer requiring a seller to offer the same prices that it offers all other buyers.

While this sounds like it might lead to lower prices overall, it can actually do the opposite. For instance, before 2015, online travel agencies such as Booking.com and Expedia were able to force European hotels to show the same prices on their websites as they offered on intermediary platforms. By comparing prices in countries that banned such clauses to those that didn’t, researchers estimated a complete ban lowers prices by up to 4%. This suggests that the so-called price parity clauses were dampening competition between online travel agencies as well as competition between those agencies and other forms of booking (such as booking in person, by phone, or at the hotel’s individual website).

The way this probably happened is that when the price parity clauses were in effect, consumers paid the same whether they booked on an online agency or via an alternative method. Since booking online is more convenient and the clauses meant the prices were the same either way, most people booked online. Because the price-parity contract prevented hotels from passing on the fees charged by the online agencies to consumers, this artificially raised prices for the fee-less methods. Once the clauses were banned, hotels were able to offer lower prices to customers who made bookings directly, and online travel agencies were able to compete with one another on price.

Share

This is the same behavior that the Federal Trade Commission (FTC) alleges Amazon has engaged in for years, according to a lawsuit first filed in 2023 under President Joe Biden (and then-FTC Chair Lina Khan) and still being pursued by the Trump administration today. California filed a separate suit in 2022, making similar allegations but alleging a violation of state rather than federal laws. (Amazon countered that its actions are pro-competitive and ultimately save customers money.)1

According to the FTC and California complaints, Amazon requires that sellers offer Amazon customers the lowest price for their products — even though the cost of doing business on Amazon is higher than on alternative e-commerce platforms. This is because Amazon effectively requires sellers to use its in-house fulfillment services (which, according to the FTC, are more expensive than competitors such as FedEx) if they want their products to have the “Prime” badge.2 It’s also because sellers effectively have to buy ads if they want their products to be shown to customers in search results.

As a result, these Amazon-specific costs would need to be reflected not only in the Amazon price of a product but everywhere that product is sold.

The technical term for this sort of requirement is a “most favored nation” (MFN) clause. There is a wide range of literature showing that in platform markets, MFNs lead to higher fees for sellers, higher retail prices for consumers, and reduced entry from competitors — particularly from lower-cost, lower-quality business models.

If sellers do not comply with the MFN requirement, their products are downranked in search results, according to the complaint, drastically reducing their sales. If you’re a seller, taking the hit on pricing is probably worth getting the higher ranking on Amazon search because Amazon is by far the dominant e-commerce platform in the United States, serving 180 million Amazon Prime subscribers in the country.

The alleged arrangement is great for Amazon but bad for basically everyone else. It’s obviously bad for sellers, who are unable to offer discounts to shoppers who either buy from the seller’s own website or use platforms that charge less for fulfillment. It’s bad for Amazon’s competitors, such as Walmart, that cannot compete to be the lower-quality, lower-cost alternative in e-commerce. And it’s bad for consumers, because it deprives us of the option to pay less for lower-quality service if we want to.

I am an Amazon Prime subscriber. I value the convenience of being able to buy everything in one place and the fast shipping. But I also value saving money.

I used my first paycheck from The Argument to buy something I’ve wanted for a long time: a KitchenAid stand mixer. On Amazon, the model I bought was listed for $399 and ships tomorrow. On Walmart, the same model was listed for $349 and took about a week to ship.3 I chose to buy my stand mixer from Walmart. If Amazon had its way, I wouldn’t have had that option.

Rigging the bids

Amazon doesn’t just sell products to consumers like you and me. It also sells ads to sellers — those sponsored results that show up when you search for a keyword like “sneakers” or “Lamy fountain pens.”

These ads are sold via auctions that happen in milliseconds, every time a customer searches for something. And according to a new FTC lawsuit, filed jointly with 22 state attorneys general from both political parties on Aug. 31, Amazon has been rigging those auctions for years.4

Subscribe now

Typically, when we think of auctions, what we have in mind is a “first-price auction.” When you make a bid, you win if your offer is the highest, and you pay the amount you bid. The risk with this kind of auction is that the winner is very likely to overpay, particularly when bidding is “blind” (when you don’t know what the other bidders’ offers are).

There is another kind of auction that solves this inefficiency, even if you keep the bidding blind: a “second-price auction.” The bidding process is the same: Bidders make offers, and the highest offer wins. But the winner is only charged the minimum price needed to win. If I bid $1,000 and you bid the second-highest offer at $500, then I would win the auction but only pay $500.01.

This is called a “Vickrey auction,” and it’s the standard way that online ads are sold. The FTC complaint alleged that Amazon consistently represented to sellers who bought ads on its platform that it was running Vickrey auctions, but that it secretly switched the process to a first-price blind-bid system without telling them.

According to the complaint, Amazon opened all the bids, observed what the highest bid was, then inserted a “shill bid” that was just below the highest bid. This allowed Amazon to systematically overcharge sellers for ads with what the company called “reserve prices.”

“Reserve prices are good for Amazon because they don’t change the allocation [of ads] and advertisers must pay more for the same advertising,” reads an internal memo cited in the FTC complaint. “Obviously, the benefit to Amazon comes at the cost of advertisers.”5

This isn’t just bad for sellers. To the extent that sellers pass along the cost of advertising to consumers, it may have also indirectly harmed the end consumer.6

The proper remedy isn’t breaking up Amazon

The evidence suggests that over the last several decades, there has been an increase in concentration and a corresponding decline in competition throughout the economy. And the evidence from these two cases strongly suggests that Amazon has engaged in anticompetitive practices that raise prices for consumers and merchants that use its platform. This is a problem worth taking seriously.

In “Amazon’s Antitrust Paradox,” Lina Khan’s famous 2017 paper in the Yale Law Journal, Khan wrote that “forcing [Amazon] to split up its retail and Marketplace operation” — separating Amazon the seller of goods from Amazon the platform operator — would help prevent its anticompetitive behavior. I’m not so sure.7

Subscribe now

First, it’s not clear to me why a firm operating as both marketplace and retailer is per se anticompetitive. After all, plenty of grocery stores carry a mix of branded products and store brand items, and that seems to work fine for consumers.

Second, even if Amazon were broken up, the marketplace operation could still enforce price parity clauses and rig bids against sellers (including, if it were profitable, against the now-independent Amazon retail operation).

None of that takes away from the fact that Amazon’s current behavior, if the FTC’s allegations are true, is illegal and harmful to consumers and small businesses. And both groups deserve a remedy that eliminates the anticompetitive behavior while preserving the efficiencies of Amazon’s existence as a platform.

Fortunately, it’s not conceptually difficult to design one.

“Amazon should not be allowed to have MFNs in its contracts with sellers, nor enforce any that it does have, nor should the company be permitted to create what is effectively an MFN by in any way penalizing sellers when it finds those sellers charging lower prices in rival distribution channels,” Fiona Scott Morton, a professor at the Yale School of Management who specializes in antitrust, told me.

In addition, Amazon should be required to disclose to sellers what kind of auctions it uses when selling ads. A court-appointed technical committee could periodically look at Amazon’s software to monitor compliance and field any complaints from merchants. Or Amazon could divest running the auctions to a separate company; if the ad seller and the auctioneer aren’t the same firm, the auctioneer no longer has an incentive to rig the bidding process.

Note that, while this divestment would promote competition, it probably wouldn’t meaningfully shrink Amazon’s market share. In other words, it wouldn’t accomplish the loudest and most famous goals of the neo-Brandeisian policy movement that Khan played a major role in inaugurating.

Even if Amazon stopped employing de facto MFN clauses and stopped bid-rigging in ad auctions, my guess is that it would remain the dominant e-commerce firm in America, just maybe with something like 35% market share rather than 41% market share. The reason is that e-commerce is a platform market, and platform markets tend to be winner-take-all. Both customers and sellers derive real benefits from platforms like Amazon: It’s convenient for buyers to have a one-stop shop for lots of things, and it’s convenient for sellers to have a platform with a bunch of shoppers on it. That’s why everyone in America loves Amazon.

Taking the problem of increasing economic concentration seriously means actually trying to do something to promote competition. You can score a lot of points on social media with a dogmatic belief that big is always bad and that the larger a firm’s market share is, the worse its impact on consumers is, no exceptions. And you can beat down a lot of critics by arguing that they are in thrall to nefarious “corporate power.” But it is less likely to work if your goal is to actually win antitrust cases.

In fact, to the extent that existing antitrust laws and precedents are insufficient, and that judges are likely to be biased in favor of firms, that should make you even more focused on doing rigorous economic analysis. That is the only way to demonstrate clearly that a firm is engaging in anticompetitive behavior, rather than falling back on hand-wavy claims.

Conversely, the reflexive belief that antitrust enforcement is nothing more than a fig leaf for crude anti-business views or a stalking horse for socialism is equally misguided.

Accurately diagnosing anticompetitive behavior will often lead to less-sexy remedies — permanent injunctions and court-appointed monitors, for instance — rather than breaking up a company. But rigorous economic analysis is the only way to win antitrust cases in a legal environment that is increasingly favorable toward firms.

Protecting competition is good for consumers and good for small firms. Effective antitrust enforcement increases overall economic efficiency, and it has progressive distributional effects because the shareholders of large firms tend to be rich, while the poor spend a larger share of their incomes on consumption.

But we shouldn’t kid ourselves. Antitrust isn’t a panacea. It’s a powerful and important tool to make capitalism work better.

Subscribe now

Recommended reading:

The words “Medicare for All” may not immediately bring to mind President Richard Nixon, but perhaps they should. Unlike any of the contemporary luminaries staking their names on expanding Medicare access, Nixon and the 92nd Congress actually did something about it.

In 1972, Nixon signed into law the renal disease entitlement program, which provided Medicare coverage to nearly all patients with end-stage renal disease (the most severe form of kidney disease), regardless of age. While I understand why many may be reluctant to follow in Tricky Dick’s footsteps, it turns out this is an ideal model for expanding Medicare and stabilizing U.S. health insurance more generally.

Disease-specific coverage targets precious social-safety-net dollars precisely at the most expensive patients and can even lower their per-patient costs thanks to Medicare’s bargaining power. Plus, by removing particularly expensive patients from the commercial insurance pool, it stabilizes costs for everyone else along the way.

Share

“Medicare for All” advocates should take note. While Sen. Bernie Sanders became nearly synonymous with the phrase thanks to his extraordinarily generous version of the proposal during the 2016 presidential primary, other politicians trying to get in good with the left have increasingly used the slogan to signal more limited expansions.

Abdul El-Sayed, the Democratic candidate for U.S. Senate in Michigan, has labeled his health care proposal “Medicare for All,” even though it would not actually provide Medicare to all.1 Slow Boring and The Argument columnist Matt Yglesias argued that this could create a permission structure for other candidates to push for more measured policies under the same label.

Medicare for All fans can certainly view policies such as a buy-in or a lower eligibility age as the opening salvo in a process that will ultimately insure everyone. But these proposals should interest those who see a role for commercial insurance as well. Both would end up putting more expensive patients on Medicare, which would take the burden off commercial insurance. With lower claims costs, commercial insurers could lower premiums for the majority of Americans.

So why target a specific organ or disease instead of lowering eligibility or offering a buy-in? The main reason is that the latter options use imperfect proxies to identify expensive patients, otherwise known as sick people. Yes, 55- to 64-year-olds have worse health, on average, than younger people, but expanding the program by lowering the eligibility age would sweep in lots of people in good health as well. Yes, a Medicare buy-in would likely be most sought by those with health challenges, but any healthy person can also buy in.

Now, giving people health care coverage is hardly the worst thing you can do to them. But a healthy patient — someone who pays premiums without using many health care resources — is someone insurance companies need to keep their books in order. And in a world of scarcity like ours, we want our in-demand federal dollars going where they’re most needed.

That’s why disease entitlement, such as Medicare’s kidney coverage, is such a good option. It is a perfect proxy for sickness. By definition, there are no healthy patients with end-stage renal disease.

So, if we’re looking for other options to expand Medicare, I think we would be much better off continuing with the approach we started in 1972: expanding it one disease at a time.

Designing such a policy necessarily means choosing which chronic disease we should cover next. The Centers for Disease Control and Prevention has identified nine of the costliest chronic health conditions, and a quick look at total health care spending attributable to each of those diseases gives us three obvious candidates.

Cardiovascular disease and cancer appear nearly tied as the most expensive chronic diseases, followed more distantly by diabetes. But if we look back at our success story, kidney entitlement, we can see why diabetes is the clear front-runner.

Why diabetes?

End-stage renal disease had three main features that made it a good starting point for Medicare expansion:

Read more

Editor’s note: The first essay The Argument ever published asked, “How do we live with each other?” To mark our first anniversary on Aug. 17, we’re returning to that founding question with a series about what we owe people whose beliefs and choices we may find difficult to accept or even understand. Over the next few weeks, familiar voices at The Argument and new voices alike will approach that question from different angles.

Emily Hamilton and Yonah Freemark approach this question quite literally. The rules that govern where we build schools determine whether kids spend their time in traffic, supervised by harried and tired parents, or whether they can walk, bike, or take the bus to school. What do we owe our children? One answer, the authors argue, starts with the obscure school siting rules that make childhood independence harder to come by.

To receive every essay in this series, subscribe today.

- Jerusalem Demsas

In 1995, downtown Durham was struggling: North Carolina’s tobacco industry was struggling, and the city had barely any shops or restaurants. But its school district took a risk on the blighted area, transforming its 73-year-old downtown high school into a new magnet school, now called Durham School of the Arts.

Over the following three decades, the school’s successes — it has expanded to serve around 1,800 students and maintained a high level of diversity — paralleled those of downtown Durham itself, which added thousands of new homes, new space for research labs, and other attractive amenities. While the school’s magnet status and special classes have been key to its success, so has its physical location: The roughly 17-acre downtown campus is integrated into the surrounding neighborhoods and easily accessible by the many students who walk or bike to class. It’s just a few blocks from the city’s main bus station, and dozens of shops and restaurants are within spitting distance.

All that will come to an end in the coming years. Instead of renovating the aging campus, the school district has chosen to move it to a new, previously forested, nearly 60-acre site north of downtown. The new facility will be surrounded by a moat of surface parking, inaccessible to the city’s bus network, and farther from most students’ homes.

Share

Though Durham’s school board made the call in part to save money, it was also responding to a tangle of official state policies and societal norms that have resulted in schools across the country being pushed to isolated suburban fringes.

After investigating trends in school siting, we found that stories like Durham’s are more common than not. Before 1950, the median American high school in our sample sat on a 17-acre site. The typical high school built since then sits on nearly 40 acres. Similar changes have occurred among elementary schools, too, in tandem with a well-documented collapse in the share of students who walk or bike to school. In some places, it’s led to parents and kids sitting in comically long drop-off and pickup lines that contribute to traffic congestion on nearby streets.

No single rule explains how so many schools got so big and far-flung. Societal trends like rising incomes, urban sprawl, increased car use, and parental preferences have all contributed. But obscure state policies promoting minimum acreage requirements, parking rules, and drop-off lanes have made it harder to build compact, neighborhood-oriented schools. In some cases, states have all but outlawed them.

There’s an opportunity for change, though, and some states and localities are trying to reverse course — and get students back onto their own two feet.

The postwar school size boom

Our sample1 of nearly 400 U.S. schools shows that elementary school parcel sizes have increased substantially since the World War II period. Prior to 1950, the typical elementary school was set on about a five-acre site, gradually increasing to about 10 acres in the 1950s and 1960s, and reaching a peak of more than 15 acres in the 1990s. We observe a sharp decline back to a median of about 10 acres for elementary school sites in the 2000s.

Read more

I don’t remember 9/11. I was 6 years old — I also have a bad memory — so I have no recollection of what I was doing that day, or when I learned that terrorists had killed nearly 3,000 people.

I knew the outline of what happened, but knowing the outline is not the same as understanding what the day felt like, or why the political choices that followed seemed so reasonable to so many.

Last week, I read the 9/11 Commission report for the first time and came across the official account of a call from Peter Hanson, a passenger on the flight that would eventually hit the South Tower of the World Trade Center:

“It’s getting bad, Dad — A stewardess was stabbed — They seem to have knives and Mace —They said they have a bomb — It’s getting very bad on the plane — Passengers are throwing up and getting sick — The plane is making jerky movements — I don’t think the pilot is flying the plane — I think we are going down — I think they intend to go to Chicago or someplace and fly into a building — Don’t worry, Dad — If it happens, it’ll be very fast — My God, my God.”

Moments after the call suddenly ended, Peter’s father, Lee turned on the television, and watched his son’s plane hit the World Trade Center. He watched his son die live on TV.

For my entire adult life it has been uncontroversial to be opposed to the Global War on Terror that then-President George W. Bush launched in response to the attacks. But if you were over the age of 18 in 2001, the odds are that you supported military action:

A Gallup poll fielded Oct. 5-6, 2001, showed that 82% of respondents favored direct military action in Afghanistan.

Another Gallup poll fielded Nov. 2-4 found 66% in support of sending “large numbers” of ground troops to Afghanistan. When asked how long U.S. military combat forces should be used to deal with terrorism, 56% of respondents said “more than 5 years, if necessary.

A CBS News poll fielded Oct. 8, after the bombing campaign began, showed 87% approved of the attacks on Afghanistan.

Expanding the war to include Iraq was also popular. In 2002, strong majorities of Americans supported military action to depose Saddam Hussein. We now know with certainty that Hussein did not collaborate with the hijackers, but in October 2002, 66% of Americans thought he did.

But the most revealing poll is not one showing American’s supported military action in Afghanistan, it is the one showing that just 3 percent of people thought the goal should be to to kill or capture Osama Bin Laden. Less than a month after 9/11, “support among Americans for the U.S.-led military attacks against Afghanistan targets is so strong that many Americans think not even the death or capture of Osama bin Laden should stop the anti-terrorist offensive.”

When CBS News asked what the goal of the U.S. attacks was, just 3% of Americans said “Kill/Capture Bin Laden” the other 90% said it should be to stop terrorists elsewhere. In other words, people were eager for the U.S. to undertake a broader attack on terrorism, not merely respond to the specific circumstances of what happened on 9/11. The public had embraced a war with no obvious geographic boundary or endpoint.

Bush helped mold that consensus and channeled it into a larger mission: A global struggle to defend and spread liberal democracy. Nine days after 9/11, Bush argued that the war “begins with al-Qaeda, but it does not end there.” In 2002, the Bush Doctrine was laid out in an official National Security Strategy which called for a “distinctly American internationalism” to make the world safer and better. Here’s how the document opens:

“The great struggles of the twentieth century between liberty and totalitarianism ended with a decisive victory for the forces of freedom—and a single sustainable model for national success: freedom, democracy, and free enterprise. In the twenty-first century, only nations that share a commitment to protecting basic human rights and guaranteeing political and economic freedom will be able to unleash the potential of their people and assure their future prosperity. People everywhere want to be able to speak freely; choose who will govern them; worship as they please; educate their children—male and female; own property; and enjoy the benefits of their labor. These values of freedom are right and true for every person, in every society—and the duty of protecting these values against their enemies is the common calling of freedom-loving people across the globe and across the ages.”

Of course, we now know that all of this went terribly wrong. These ideas became a license to use American military force to remake other nations at a staggering human cost.

The Costs of War project at Brown University estimates that the total death toll in post-9/11 war zones of Afghanistan, Pakistan, Iraq, Syria, and Yemen is between 4.5 million and 4.7 million. This number includes both direct combat casualties and indirect deaths from things like malnutrition, economic collapse, displacement, and other knock-on effects that were put in motion by the wars.1

When these wars failed, they discredited liberal internationalism as well as military intervention. The right that emerged from the wreckage rejected the cosmopolitanism of the Bush years. Where Bush made efforts to reject collective responsibility for Muslims, Trump now openly denigrates them as inferior.

How did we get there? What was Al-Qaeda’s goal? How did America’s response end up discrediting the liberal internationalist project? My co-host Matt Yglesias and I talk about all of this and more on this week’s episode of The Argument.

Paying subscribers can find the transcript for this episode beneath the paywall and can find instructions for listening to an ad-free episode here.

Subscribe now

WATCH THE EPISODE ON YOUTUBE HERE

New episodes post every Thursday.

For an ad-free version and full transcript, subscribe at TheArgumentMag.com.

The Argument. Libbing out.

Corrections:

• At around 03:40 and 14:45, Matt says the first World Trade Center bombing was in 1994 instead of 1993.

• Around 04:06, Jerusalem says “thousands” were injured in the first 1993 bombing, but the number is actually 1,042.

• Around 05:30, Jerusalem says Khalid Sheikh Mohammed was “heavily involved” in the 1993 attack on the world trade center, but the report says KSM wired $660 and otherwise “does not appear to have contributed any more substantially to this operation.”

• Around 11:00, Jerusalem describes a case in the 9/11 Commission Report in which one operative, Zacarias Moussaoui, enrolled in a flight school in Minnesota but raised suspicions for being “uninterested in both taking off and landing of planes.” While Moussaoui was enrolled in flight school in Minnesota, the individuals described as being uninterested in takeoffs and landings were Nawaf al Hazmi and Khalid al Mihdhar.

• In the same description around 11:00, Jerusalem says Moussaoui was picked up on a routine immigration violation, but the report says his flight instructor reported suspicions to Immigration and Naturalization Service (INS).

• Around 12:35, Matt says that federal officials applied for a warrant for Moussaoui, but it didn’t meet FISA criteria. According to the report, the FBI decided not to submit a FISA application because headquarters didn’t believe the evidence was strong enough.

• In the same section around 12:35, Matt says someone who was in custody from the World Trade Center plot recognized Moussaoui, but he is referring to Ahmed Ressam, who was convicted over the plot to bomb LAX.

• Around 34:10, Matt says “if we get Osama in 2022,” when he means 2002

• Around 1:00:00, Jerusalem says we have appropriated roughly $195 billion for the war in Ukraine. The figure appears to be closer to $183 billion.

• At around 1:06:40, Matt says Amy Klobuchar was the attorney general of Hennepin County, but her title was actually Hennepin County Attorney.

• Around 01:15:20, Matt says “Somewhere in the Dick Cheney archives, he’s saying that about Iraq, that Afghanistan, there’s not really much we can do there, but Iraq, I think, has potential.” This is actually a reference to a Donald Rumsfeld quote, who reportedly said, “there aren’t any good targets in Afghanistan. And there are lots of good targets in Iraq.”

• In the same section around 1:15:20, Matt describes Samantha Power as an “Iraq War hawk,” but she was critical of the U.S. approach at the time

• Around 1:24:00, Jerusalem says the entrance of a tutoring center explained 66% of the difference in math scores, but the cited study says 63%.

Show notes:

• 9/11 Commission Report, primary source for data about the attack: Report

• “Flashbulb Memories,” study by William Hirst and Elizabeth Phelps referenced by Jerusalem: Current Directions in Psychological Science article

• “Post September 11 Attitudes,” polling referenced by Jerusalem: Pew Research Center poll

• Is Multiculturalism Bad for Women?, book by Susan Moller Okin referenced by Matt. Goodreads page

• “What Happened to al-Qaeda?” article by Graeme Wood referenced by Jerusalem: The Atlantic article

• “Elon Musk’s zero accountability life,” article by Kobe Yank-Jacobs referenced by Jerusalem: The Argument article

• Problem from Hell, book by Samantha Power referenced by Matt. Goodreads page

• Films referenced by Matt:

  • The Contender

  • Air Force One

  • Black Hawk Down

• Peer Review: “Kumon Up: Private Tutoring Centers and Student Achievement,” article by Joshua Goodman and Samuel Nitkin: NBER working paper

• “Democrats should fire bad teachers and bad cops,” article by Nicholas Bagley and Robert Gordon referenced by Jerusalem: The Argument article

• “Nature or Nurture: Private Tutoring and Education Inequality,” study by Kyung Woo Lee, Sun Ku Hahn, and Tae Yoon Sung, referenced by Jerusalem: RISS page

• The Road to Serfdom, book by Friedrich Hayek that will serve as the basis for our upcoming book club episode. Goodreads page

Transcript:

Editor’s note: The first essay The Argument ever published asked, “How do we live with each other?” To mark our first anniversary on August 17, we’re returning to that founding question with a series about what we owe people whose beliefs and choices we may find difficult to accept or even understand. Over the next few weeks, familiar voices at The Argument and new voices alike will approach that question from different angles.

In today’s essay, Dylan Matthews notes that the AI boom is poised to unleash billions of dollars in philanthropic giving as it mints new millionaires and billionaires — many of whom have, let’s say, idiosyncratic views about the world. Is this private exercise of power a subversion of the democratic order? Is it an opportunity to try out bold new solutions to thorny problems? A little of both?

Personally, I think philanthropy is one of many productive release valves for a pluralistic society. Maybe I can’t get the government to spend tax revenue on public health in developing nations, but I can help do it with my own dollars. Or maybe you oppose abortion and are furious at the government for not providing other options for reluctant mothers; philanthropy lets you fund those if you wish.

Dylan, a one-time skeptic of big-time charities who is now a program officer at the major philanthropy Coefficient Giving, considers the dilemma of billionaire giving from first principles.

Disclosure: Coefficient Giving is an investor in The Argument.

To receive every essay in this series, subscribe today.

- Jerusalem Demsas

Back in 2018, the release in quick succession of works like Anand Giridharadas’ Winners Take All, Rob Reich’s Just Giving, and Edgar Villanueva’s Decolonizing Wealth led to a broad reconsideration in the commentariat of the ethics and political justifiability of large-scale philanthropy. I should know: I was part of it.

In 2019, I hosted a season of Vox’s podcast Future Perfect that focused on the relationship between philanthropy and democracy, particularly on the ways in which the former can undermine the latter. It wasn’t negative across the board — the episode on AI safety praising early funders of the field like Skype co-founder Jaan Tallinn has, I think, held up particularly well — but the main message was, “be suspicious.”

These concerns had been bubbling up for some time. But the broad anti-tech backlash that was surging due to concern over Facebook’s role in the 2016 election — and the growth of anti-billionaire politics fueled by both that and Bernie Sanders’ 2016 run — made 2018-19 the moment when these worries became mainstream.

I agreed broadly with Giridharadas, Reich, and Villanueva that philanthropy allows the wealthy to exert excessive, and unjustifiable, influence over society; that the charitable tax deduction unjustly forces ordinary Americans to fund that influence; and that the unaccountable nature of foundations, not constrained either by voters (as governments are) or market pressures (as businesses are), made them inherently dangerous, sometimes to the point of enabling outright atrocities.

But the 2010s era of Big Philanthropy is going to look tiny compared to the giving unleashed by the impending Anthropic and OpenAI IPOs. The OpenAI Foundation’s shares in OpenAI are worth, as Stripe executive Nan Ransohoff has noted, around $220 billion already, larger (and much more poorly diversified) than any other foundation endowment on earth. All of Anthropic’s co-founders have committed to giving away 80% of their net worth, which, given Anthropic’s current valuation, should mean another hundred billion or more in giving.

Close observers have known this was going to happen for a while, but after Ransohoff’s essay, the impending flood of AI money has become common knowledge, sparking coverage from The New York Times to The Economist to the Financial Times. And with that attention has come some familiar debates about whether this level of giving is acceptable in a free society, or whether it’s, in David Wallace-Wells’ words, “an assertion of plutocratic control over yet more aspects of collective life.”

There was and remains plenty to be suspicious of in the past and present of big philanthropy. But my views have evolved a bit since 2019, which is perhaps unsurprising as during the same period I left journalism to join Coefficient Giving. Coefficient Giving (formerly “Open Philanthropy”) is a large philanthropic advisor and grantmaker that supports work in areas like animal welfare, global health, pandemic preparedness and prevention, and AI safety. Last year we recommended some $1 billion in grants; we’re on track to significantly increase that number this year, and our advisory work in particular has grown considerably as the AI rich seek to give away their new fortunes.

I wouldn’t work where I do if I didn’t think our project is compatible with, and indeed beneficial to, a liberal democratic society. More importantly, though, I think the events of the subsequent seven years, and specifically of the past two years, have made the most scathing version of this critique less tenable than ever.

Share

Implicit in the critique that philanthropy conflicts with democracy is the notion that decisions about the distribution of wealth and power should be made principally by the government, not by private actors. I believed this to be true in 2019. But now I think this is mistaken — and, indeed, somewhat illiberal. The effects of the second Trump term on foreign aid and science are the clearest indication of the limits of this approach.

Rather, no single entity, including the government, should monopolize these decisions. Foundations and grantmakers make serious mistakes. But the important thing is not that grantmakers are perfect, but that our errors are different from those made by the state and private business. Multiple imperfect institutions making distinct errors together add up to a more stable and resilient overall system than privileging one approach over all others.

A role for foundations

In the field of risk assessment, analysts often talk about “Swiss cheese models.” The idea is that in a complex system, each step in the process will have natural failures. But if you layer multiple steps with different failure points over each other, you can emerge with a system that’s robust to each of those failures, the same way a block of 10 Swiss cheese slices does not have a single hole going all the way through.

You can think of the way we provide goods in American and global society as several different, and differently flawed, institutions overlapping: markets, governments, religious institutions, schools and universities, and philanthropy, to name some of the most important. If we’re lucky and/or politically wise, these institutions will complement each other well and help remedy each other’s flaws.

The failures of philanthropy as a model are clear. It over-privileges the views of the wealthy. It creates power-laden relationships that, even in my short time as a grantmaker, I have already at times found awkward and uncomfortable (and the grantmaker’s discomfort is probably the least of the issues there).

But the case for philanthropy isn’t that it’s perfect. It’s that philanthropy lacks certain key defects of its complementary institutions, like markets and government.

Read more

Today’s AIs can do really hard things: conduct elaborate computer hacks, edit their own logs to conceal their activities, steal user credentials and private information from other companies, and control the cluster they are running on in order to edit the tests that are supposed to assess them. They sometimes do these things even if no human being has asked them to.

Given recent AI misbehavior such as the large-scale cyberattack on the open-source AI provider Hugging Face, you might think that the leading labs plan on increasing human oversight over the next, more powerful generation of AI models. But the reality is quite the opposite: The labs intend to automate the AI development process with AI, which will mean faster and faster progress and necessarily less and less human oversight.

If all goes according to schedule, humans will play a rapidly shrinking role in AI development over the next two years, as both OpenAI and Anthropic try to put as much R&D as possible into the hands of their increasingly capable (and increasingly incomprehensible) AI.

Their stated intent is that, within a short period of time, the work of developing better AIs will be done primarily by AIs, with the role of humans eventually reduced to reading the results of experiments those AIs conducted, reviewing reports those AIs generated, and trying to double-check that the AIs are still on task.

There simply isn’t enough human attention available to monitor the number of AIs the companies hope to put to work on independent AI research. As a result, we’ll be reliant on the AIs to understand what is happening inside fully automated data centers where more and more powerful AIs are developed.

This isn’t some pessimistic projection of what might go wrong — it’s actually the plan. Not the plan for the distant future; it’s the plan for next spring.

Share

Recursive self-improvement

I think that the public does not know that this is the plan. They are imagining the next 10 years — the next two years, even — very, very differently from how the decision-makers at OpenAI and Anthropic are imagining them. If they had any idea what these people are doing, I’m convinced that they would try to stop them. And so I am going to attempt to describe what is being done.

People think of these labs as primarily making a consumer product. But increasingly — as measured by time and money spent — the main thing they are doing is making automated internal AI research labs. OpenAI reports that, over the past six months, the share of its research compute devoted to internal coding inference increased 100-fold (much faster than they’ve increased compute spending for customers). Tom Brown, an Anthropic co-founder, has said that “the vast majority of the work Anthropic does is internal software engineering.”

In other words, AI companies are not, primarily, trying to automate your job — they are trying to automate their own jobs. “We are making strong progress toward creating an automated AI researcher by March of 2028,” OpenAI announced in a recent post.

Inside the leading AI companies, large teams of researchers are hard at work on making the successors to ChatGPT and Claude more capable. This involves pretraining new, much bigger AIs at mind-boggling expense — plausibly a billion dollars — as well as lots of work once a model is ready: reinforcement learning from human feedback to pick up how humans like to communicate, reinforcement learning in virtual environments to pick up computer use, programming and math skills, fine-tuning on specific data sets and specific tasks, and more.

This work goes a lot faster than it did even a few years ago because of ChatGPT and Claude themselves: They write code quickly and make for moderately competent research assistants. Both companies have estimated that turning over work to these models substantially increases the pace at which researchers can design their successors.

“At Anthropic, we are delegating a growing share of AI development to AI systems themselves,” reads an Anthropic blog post. “We believe automated AI research will yield models that directly enhance human welfare and advance OpenAI’s mission,” OpenAI assures us in their own post.

Both labs acknowledge the risks but highlight the upsides. Researchers envision a world in the very near future where humans are barely able to understand the rapid-fire progress happening in their data centers, a world where key decisions about the next generation of models are made by the current generation of models — because the decisions are too complex for humans to follow without the guidance of the supervising AIs. “As the systems become more capable, the results become harder to interpret,” OpenAI chief scientist Jakub Pachocki wrote in a blog post released on Sunday. Progress on model improvement will then proceed extremely fast and without meaningful human oversight — unless humanity comes together to change course.

This transition sometimes gets called recursive self-improvement (RSI). The companies believe it is right around the corner. “Based on internal results, I have a strong expectation that this speed of progress could be sustained into recursive self-improvement,” Pachocki wrote on Sunday.

Here’s what your job is supposed to look like if you’re in charge of AI research in a near-future, post-RSI world: You’ll read an AI-generated report on the properties of the next generation of models — the most powerful in history — and almost before you’ve finished reading one, the next report will hit your desk. Research teams of hundreds of thousands of AI agents will be doing all the work to improve the next generation; research teams of humans will just be trying to interpret what happened. Every time a lab authorizes a new model’s internal release, the pace picks up, and soon the new reports hit the desk long before you’ve finished reading the last one. The research projects are proceeding along lines that even the world’s leading AI experts don’t understand. Work that would’ve taken two years gets done in two weeks — or at least that is what is claimed in the summary-of-the-work-for-the-humans, itself written by an AI we aren’t sure we trust.

This is the context behind the AI crisis projections you may have heard of, such as AI 2027 and If Anyone Builds It, Everyone Dies: It’s not that we will build GPT-7 next year, and GPT-8 the year after that, and GPT-9 the year after that, with each generation corresponding to noticeable but nonshocking productivity increases. If that happened, we’d have plenty of time to adapt, change course, make laws as needed, and gradually sift out which concerns are real and which haven’t manifested.

Indeed, if that were what was happening, it’d probably work out fine. But the course we are on is that we will make each AI responsible for training its successor extremely fast while humans have barely any idea what’s going on. It’s that all of this work will be conducted by AI, as it is too complicated and too fast-moving for any human to audit or understand. It’s that if these AIs at some point decide to do their own thing — as OpenAI’s models did when they decided to take over their own cluster and do a bunch of external hacking to try to fool their grader — we will not be able to tell, because we will be so reliant on those same AIs to even understand what’s going on inside our capabilities experiments. It is that within a few short years every important decision about AI development will be in AI hands.

Subscribe now

Why would anyone do such a thing?

Most people, when you describe what the labs are working on, recoil in horror. They don’t want this done and think it’s obviously a bad idea. Even many of the people working on recursive self-improvement agree that it’s a bad idea. “I am concerned no one is prepared for the consequences of a continued rapid rise in machine intelligence,” Pachocki warns.

Like many at Anthropic and OpenAI, he believes progress should be “paced” to ensure human input. This is very dangerous, OpenAI and Anthropic researchers seem to admit, but of course we are being responsible about it. They are not. We should definitely have more external oversight, they say, though often their associated political lobbyists try to defeat that very oversight. It’s our duty to be clear about what we’re doing so the public can be informed. But these very posts are confusing to people! If you think RSI is so dangerous, why are you doing it at all?

Here, I think the standard progressive analysis about the corrupting influence of wealth and power is basically the correct one. Kicking off RSI is a terrible idea, but it’s a terrible idea you can get paid millions of dollars to do. Every day you spend with such a salary is a day with a devil on your shoulder, whispering arguments for why it’s actually the right thing to do. The devil’s many arguments run like this: If we don’t do it, China will; if we at Anthropic don’t do it, OpenAI will (or vice versa). We need to pause at some point, the devil might say, but not right this second. We need to pause right this second, but I already tweeted that and no one listened, so I guess other people don’t see it the same way. Maybe we can figure it out, and make it go well. We need to raise awareness, and to raise awareness we need to keep working on it.

But quite reasonably, no one takes warnings seriously when they come from people doing the very thing they think is so dangerous.

There are also people who have quit the labs, giving up millions of dollars in order to warn people that we’re on the wrong course. “The people at the companies are aware of the risks here,” Daniel Kokotajlo, who left OpenAI two years ago, told me, “but their stance is that it’ll probably work out OK, and anyhow if they don’t do it, someone else will.”

So far the labs have benefitted from the fact that the thing they’re trying to do is so outlandish that no one really believes they’re trying to do it — even when they write detailed explanations of how quickly they are progressing toward doing it.

The track record of warning people how dangerous AI could get is a very depressing one. As far as I can tell, if you say, “AI is going to be very powerful and dangerous,” a lot of people will go, “Wow, I should get in on that.” The labs are trying to do RSI, but it’s not the only thing they’re trying to do. If you beat the drum loudly enough about RSI, maybe they’ll double down on it. Many people have found themselves downplaying the absurdity of the world we’re entering to avoid sounding crazy.

The end result, though, is that we have sleepwalked into a situation where the aim of the largest capital buildout in American history is to give billions of dollars to AI whose activities we cannot understand or audit, in pursuit of a super-model that improves itself continuously, under circumstances where it’s hard to imagine adequate human oversight. This is not being done in secret. But the people who are doing it are taking refuge in audacity, in the tech industry’s record of outrageous claims it fails to live up to, and in warnings that someone else will do it if they don’t.

Subscribe now

Recommended reading:

While we celebrate the nation’s workers this Labor Day, it’s a good time to remember that most Americans at any given time do not actually have a job. If you’re a child, or elderly, or a full-time caregiver, participation in the labor force may not be an option — or may just not even be the best use of your time. But, as columnist Matt Bruenig frequently reminds us, this reality creates unique challenges for societies that have chosen to allocate income through labor and capital ownership: Most people can’t put up much of either at any given time. And yet we want them to live thriving lives anyway.

This ever-present reality puts the risks of AI-induced unemployment into perspective. We already know how to take care of a society where most people aren’t working, because we are already forced to do it, however imperfectly: with unemployment benefits, free education, guaranteed health care, and other tried and true social welfare programs. Today, we are removing the paywall from Bruenig’s March essay in which he persuasively argues that, no matter how much unemployment you think AI will generate, “the solutions to economic inequality and insecurity have already been figured out, and productive technologies make them easier to implement, not harder.”

Whether or not we will do so is another matter entirely.

- John Thomason, senior editor

Subscribe now

Prominent Democratic research firm, Blue Rose Research, recently released polling about the public reaction to artificial intelligence technology. Among other things, Blue Rose found that 54% of Americans think that unemployment caused by AI should be dealt with by “creating good-paying jobs” while only 17% favored providing “direct income support.” A further 49% favored a special tax on AI profiteers to finance these kinds of programs.

What’s actually interesting about this Blue Rose polling is not really the answers, but the questions and the underlying sentiment that we somehow need fresh new policy solutions to deal specifically with the negative distributive effects of AI.

In reality, the most boring, well-established social democratic policy approaches will work perfectly fine. That we have this kind of exotic discussion is emblematic of our deeply impoverished policymaking environment.

When thinking about the potential negative impacts of artificial intelligence, it is important to distinguish between the technology’s direct effects on things like production, education, and leisure (which may show up as AI cheating tools that hurt learning or AI companions that displace real social connection) and its indirect effects on things like the distribution of wealth, income, and consumption in society.

It is hard to know in advance what to do about the direct effects, both because we cannot really predict them and because each will likely require a specific, not general, solution. The opposite is true for managing the distributive impact of these technologies.

There is a well-established playbook for achieving economic security and equality that can be applied to an AI-infused economy just like any other advanced economy. Countries can levy taxes to fund universal welfare states in order to hold down income inequality and keep people’s material lives stable over time. They also can increase social ownership and impose targeted corporate taxes to put a lid on wealth inequality and excessive accumulation in specific industries.

The reason why the solutions to economic inequality and instability are always the same is because the problems are fundamentally the same. Capitalist economies distribute income by paying people for their labor and paying returns to people who own capital (wealth). Due to certain feedback loops, capital factors — or wealth — end up overwhelmingly concentrated in the hands of a small percentage of people. Labor factors — or work — are more dispersed, but individuals are constantly churning in and out of jobs, different jobs receive different pay, and a large swath of the population is not able to work at any given time.

Every AI-related distributive concern can be neatly organized into this basic framework.

Because it is a labor-saving technology, the implementation of AI throughout the economy will result in some people moving from employment to joblessness, at least for a time. But this is nothing new. It already happens in America over 60 million times a year.

Constant labor reallocation is a fixture of all dynamic economies. Yet it can be made relatively painless by establishing generous unemployment benefits and setting up a package of universal welfare programs — like child allowances, child care, education, and health care — that are not contingent upon one’s current employment or income.

Curiously, when it comes to differences in pay among laborers, the current conventional wisdom seems to suggest that AI would actually have an egalitarian effect. Right now, certain kinds of cognitive labor are compensated at much higher rates than other sorts of labor. This has resulted in a neat association of educational attainment with earnings, which has helped legitimize economic inequality as being fundamentally meritocratic in nature. But in a new technological environment in which the supply of “intelligence” that can execute certain cognitive tasks is massively increased, this association could attenuate or break down altogether, resulting in a wage compression that actually reduces earnings inequality among workers.

The most dystopian distributive concerns are focused on the capital side of the equation. There seems to be some fear that once AI technology is diffused throughout the economy, the handful of companies that control the frontier generative AI models — currently Google, Anthropic, and OpenAI — will hoover up massive shares of the national income each year. In this telling, most of the money companies save on labor will be parceled out to one of these companies, which will rapidly increase wealth and income inequality in the country.

Before getting into the solution to this hypothetical problem, it is worth dwelling a bit on how implausible this scenario actually is. For this to play out, a handful of companies will need to get themselves into a position where they can sell large language model (LLM) inference at an enormous markup. Yet, the LLM world is very competitive.

On OpenRouter, a service that makes it frictionless to switch between LLMs, there are currently 650 models — probably more by the time you read this. Many of these models are open source, meaning that, if you have a sufficiently powerful computer, you can run them yourself for free. Even if you lack such a computer, there is a highly competitive market of providers willing to sell metered access to those LLMs for a small fraction of what the frontier models charge.

Some of these open source models — like GLM-5, Kimi K2.5, and DeepSeek — are already at or near parity with the frontier models. And, given that it is possible to use frontier models to help train open source models, it seems likely that there will always be free models that are only a little bit behind the frontier.

Share

What these dynamics point to is a future where LLM inference is largely commoditized, not a future of LLM super-profits. The tech sector is used to extracting rents through network effects and vendor lock-in. But not all tech products work like this, and, right now at least, LLMs are headed in that direction.

Of course, if this analysis is wrong and an AI-infused economy does result in a massive share of national income flowing to capital owners, especially for those selling LLM inference, this can be counteracted fairly trivially through social ownership of capital and corporate income taxes targeted at the LLM sector.

The most obvious vehicle for social ownership of this sort would be a dividend-paying social wealth fund like Alaska has. This is a fairly simple form of socialism but also pretty banal as far as things go. The federal government would just establish a new investment fund, fill it with stocks, bonds, and real estate, and then pay each American an equal share of the return on the fund every year.

This sort of proposal is often met with abstract objections about the mismanagement of capital and corruption. But the practical reality is that governments in the U.S. already run nearly 5,000 public pension funds that differ from this proposal only in that their return goes to fund retirement benefits rather than to fund a universal dividend.

There are many ways that such a fund could be financed, including wealth taxes, inheritance taxes, and even by selling bonds. In a world where the LLM sector began collecting massive profits, one obvious move would be to establish a special corporate tax just for that sector, with the revenues going to build the aforementioned social wealth fund.

This is something Norway has a long tradition of doing, especially for industries where it appears that excessive rates of return are being generated by companies that rely upon inputs that should, in the Norwegian way of thinking, belong to everyone. In the last few years, Norway imposed these special “resource rent taxes” on the nation’s aquaculture and wind energy sectors, the former because it uses the ocean as an input and the latter because it uses wind as an input. Prior to that, Norway took similar approaches to its oil and hydropower sectors.

This sort of taxation logic would apply equally well, if not better, to a mature LLM sector. In order to train their models, LLM companies use as inputs basically the entire corpus of human content creation. They aren’t just freeriding off unproduced inputs like petroleum or rivers, but on the produced inputs of the entire history of human meaning-making. If this type of enterprise generates super-profits, then we should simply do as Norway does and apply a special resource rent tax to the LLM sector in order to trim its net income down to size.

The fact that we have easy solutions to these problems does not mean that we will enact them.

But whether you buy those arguments or not, the AI policy debate raging right now presumes that the U.S. is on the verge of taking unprecedented action. Everything from nationalizing AI companies to a federal jobs guarantee seems to be on the table. If that’s the case, better to direct our energies to a big new program that will actually work.

A lot of early socialist writing shares a theme that making great scientific and technological advances is far harder than creating an egalitarian society. The idea was that, if human beings can figure out how to put a man on the moon, surely they can also figure out how to create a system in which nobody is poor and everybody can go to the doctor.

But the impediment to achieving egalitarianism is not technology or know-how. The solutions to economic inequality and insecurity have already been figured out, and productive technologies make them easier to implement, not harder. If, in the age of AI, the U.S. becomes even more of an inegalitarian nightmare than it currently is, it will not be because of AI, but rather because of the very same economic policy choices that plague us today.

Subscribe now

What do Americans hear when they watch Sen. Bernie Sanders or Vice President JD Vance rail against the elite? Are they thinking of right-wing tech billionaires? Imperious college professors? Liberal magazine writers?

Instead of joining the myriad political commentators in continuing to speculate wildly, we decided to ask the American people. In a poll of 3,000 registered voters fielded nationally from July 20 to 26, voters rejected the MAGA theory of the elite: They “don’t think college professors, journalists, and academics are actually among the elite.” Instead, it’s billionaires, celebrities, and business executives who most commonly earned the designation.

Strong majorities of our respondents also endorsed free trade and gender egalitarianism, defying what they took to be opposing elite views on the matters.

In other words, the narrative that we are a country divided between the hardscrabble, anti-woke masses and the effete, culturally progressive elite is, at best, only a partial description of reality.

Share

Our findings spurred lots of discussion, from the pages of The Wall Street Journal and The Washington Post to the r/Professors subreddit. (“The salary certainly isn’t elite,” lamented one user.)

But, as with all polls, the top lines are just the beginning. As I dove into the back end of the polling data, I encountered findings that complicate three hot-button questions: Does our media diet determine our reality? Are people worried about declining birth rates or overpopulation? And is America actually gripped by an epidemic of loneliness?

Read more

The OG climate deniers were crank scientists who attributed climate change entirely to natural variability (or sunspots) instead of humanity’s greenhouse gas emissions. Their dubious work was cited at the highest levels of government, including by the Bush administration’s Council on Environmental Quality and, perhaps most notoriously, by the late U.S. Sen. James Inhofe, who suggested in 2003 that global warming was “the greatest hoax ever perpetrated on the American people.”

That outright rejection of scientific consensus has largely lost in the court of public opinion: Recent surveys show strong majorities of Americans accepting the reality of climate change. With such denial in retreat, today’s climate activists have a new pejorative specifically for the Democratic elected officials and analysts who are conspicuously less outspoken on climate change during the second Trump era: climate hushing.

These so-called hushers are “meekly shying away from righteous and winnable fights against evildoers,” according to Democratic Sen. Sheldon Whitehouse. Party moderates are the canonical hushers, at times directly urging Democrats “don’t say climate change,” as Searchlight Institute did last year. But the ranks of the hushers appear to grow larger by the day: The Washington Post recently reported that the word “climate” has vanished almost entirely from public statements by Sen. Ed Markey, a longtime Green New Deal champion who just prevailed in a tense primary election against a more moderate challenger.

Democrats’ descent into infighting is most often taken as a sign of retreat for the causes of decarbonization and climate resilience. But that need not be the case.

Indeed, there are reasons to think that climate hushing will promote more ambitious and durable climate action than what came before. Unlocking the next wave of U.S. clean energy will require a return to the bipartisan compromise politics that have historically driven the country’s decarbonization. Maximalist climate activism can only harm these efforts.

In an era when voters are laser-focused on cost-of-living concerns and emerging challenges like artificial intelligence, climate hushing may well be the thing that saves the climate.

Share

The long road of denial

After climate advocates waged a fairly straightforward campaign against climate denial during the Bush presidency, the concept underwent a kind of semantic inflation during the Obama years. A “climate denier” became anyone who opposed any plank of the climate movement’s policy agenda. In 2015, the activist Bill McKibben accused President Obama of “climate denial of the status quo sort” for refusing to block oil drilling in the arctic.

This appeared to be part of McKibben’s attempts to punish the Obama administration for prioritizing health care over climate change. “He talked very little about climate,” McKibben wrote bitterly in 2009, “and in the process left the door open for climate deniers to have a field day.”

“It will be painfully easy to tell if President Obama is going to take a serious stab at doing something about climate change in his second term,” McKibben wrote after Obama’s reelection in 2012. “The purest, starkest test he faces will be the proposed Keystone XL pipeline.”

But the expanding definition of denial didn’t stop at pipeline protests. In 2015, historian Naomi Oreskes criticized pro-nuclear climate scientists, calling their support for zero-carbon nuclear power “a new, strange form of denial … one that says that renewable sources can’t meet our energy needs.”

My organization, the Breakthrough Institute, was once lumped in with a “kinder, gentler” climate denial for the crime of arguing that policymakers were overestimating energy efficiency measures’ ability to mitigate carbon emissions.

And so, new battle lines were drawn, between the climate activists who argued that a “climate emergency” demanded a brute-force transition from fossil fuels to 100% renewable energy (defined more or less exclusively as wind, solar, and batteries) and the climate pragmatists who argued comprehensive climate action was dependent on a broader portfolio of clean energy technologies and infrastructure — including nuclear power as well as carbon capture and removal, hydrogen fuels, crops genetically engineered to be climate-resilient, and more.

By conflating public acceptance of mainstream climate science with a much narrower and contested vision of climate policy, climate activists convinced themselves that public opinion supported even the most expensive and sweeping regulatory interventions into the economy and energy system.

As it happened, the activists would win on the rhetoric, while the pragmatists prevailed on the policy.

Read more

Editor’s note: The first essay The Argument ever published asked, “How do we live with each other?” To mark our first anniversary on August 17, we’re returning to that founding question with a series about what we owe people whose beliefs and choices we may find difficult to accept or even understand. Over the next few weeks, familiar voices at The Argument and new voices alike will approach that question from different angles.

In today’s essay, Maibritt Henkel examines the growing panic that, as Americans read less and less, the very foundations of liberal democracy are threatened. What behaviors, norms, and ideas do we need most people to commit to in order to sustain a liberal society? Is reading really one of them? Maibritt ruminates on these questions.

To receive every essay in this series, subscribe today.

- Jerusalem Demsas

Most people for most of history could not read. Writing systems have been around for just 5,000 of the 300,000 years of Homo sapiens’ existence, and, until very recently, most of us were illiterate.

By 1900, only around 1 in 5 people above the age of 15 could read and write a short simple sentence. That the global literacy rate today is at 88% — and approximately 93% for 15- to 24-year-olds — is an astounding triumph of social progress.

And yet, despite this remarkable fact, a sense of doom has settled around the issue of reading. Many argue that we are entering a “postliterate” era, where written text is being replaced by oral and visual forms of communication.

Share

That concern is not unfounded. In the United States, high-level reading proficiency is decreasing. Americans are, on average, reading less and becoming worse readers as a result: SAT scores for reading and writing are falling, vocabularies are shrinking, and the sentences that we can comfortably understand are getting shorter.

Across the country, educators report that their students struggle to finish the same books their predecessors breezed through. Look around a waiting room or an airplane and you’re unlikely to see anyone killing time by reading a novel. Chances are they’re scrolling instead.

If by literacy we mean people’s propensity to pick up a book, read it front to back, and have a sophisticated understanding of its content, then it is true that America finds itself in a literacy crisis.

Some see this as a political crisis as well. The decline of reading, the argument goes, is not like the decline of other pastimes. It is different from stamp collecting or bowling, both of which fewer and fewer Americans now do for pleasure, because only reading produces the kind of rational and analytical thought well-suited for democracy. Reading must be protected because it shapes the human mind. Specifically, it shapes the mind to be fit for modern liberal democracy.

In her recent cover story for The Atlantic, “The End of Reading Is Here,” Rose Horowitch cited the philosopher Marshall McLuhan: “The liberal world by definition is literate,” and argued that the inverse is also true. In a viral essay, critic James Marriott prophesied that “without the critical thinking skills instilled by print, many of the citizens of modern democracies find themselves as helpless and as credulous as medieval peasants.” British journalist Mary Harrington wrote in the Christian magazine First Things that the “most momentous effect” of the postliterate era is “to undermine the cultural norms and habits of thought that form the bedrock of modern liberal democracy.”

The slump in American literacy is sad and concerning for many reasons — one of those simply being that Americans express wanting to read way more than they actually do. For many people, particularly those who work in newsrooms and at universities, disappearing into a literary universe is one of life’s great joys. We should defend it as a practice — not least by reading more ourselves.

But how much someone reads does not determine how liberal they are. Respecting democracy, celebrating pluralism, and giving moral primacy to the individual do not rest on a Great Books education.

Typography, when it did eventually come about, was revolutionary because it allowed for private encounters with information. There is plenty of that in the 21st century. What there ought to be more of is the collaborative exchange of ideas. Liberalism depends on productive disagreement, on accepting that difference is a permanent feature of free society. Some literature will teach you that. But, mostly, your best teachers will be other people.

People were liberal before the printing press

Scholars have long warned us that the technological shift away from text-based media would have consequences for liberalism.

In 1982, Walter J. Ong wrote in Orality and Literacy that it was the transition from an oral to a literate culture that made logical and abstract thinking possible. Written language promotes higher-order cognition because it allows for reasoning ordered across many linked steps, he argued.

Without text, it is difficult to construct an argument where the conclusion of one syllogism becomes a premise of the next: Given A and B, therefore C. Given C and D, therefore E. The amount of information we can store only in our heads is limited; most of us need a shopping list to remember five basic grocery items from the store. This explains why expression in purely oral cultures (of which there are virtually none left) tends to be repetitive and formulaic, optimized for retention at the expense of nuance or complexity.

Literacy, according to Ong, with its dictionaries, encyclopedias and structured management of knowledge was “absolutely necessary for the development not only of science but also of history, philosophy, explicative understanding of literature and of any art.” You can paint a painting without language, but you cannot meaningfully analyze or classify it without the abstract categories that writing and reading afford.

Orality trains the mind to relate to the physical world right in front of it and derive meaning situationally: “I see a painting of two angels looking down at a woman next to a fire that looks hot.” Literacy allows for decontextualized abstraction: “I see a triangular arrangement of mass against negative space and warm coloring.”

Although Ong was clear that he didn’t think oral people are “essentially unintelligent,” he cast the literate subject as comparatively cerebral and cogent. In classical liberal theory, the fundamental building block of society is the rational individual.

Subscribe now

But the decline in reading is an imperfect proxy for what actually matters for liberalism: an ability to engage in the exchange of ideas, a willingness to change one’s mind, and a tolerant attitude toward difference. Unlike getting a good score on the reading and writing section of the SAT, the skills of civic life do not necessarily come down to reading comprehension.

Between 2017 and 2023, the proportion of American adults scoring at the lowest literacy level rose from 19% to 28% (although changes in the test’s design make the precise size of that increase uncertain). And that decrease was mainly seen in Americans with already low performance.

But does that decline necessitate democratic decline?

The namesake of this magazine is a book by the Indian economist Amartya Sen, The Argumentative Indian. For Sen, the actual bedrock of democracy is “public discussion and interactive reasoning,” a practice that he traced back to a time long before mass literacy. He pointed, for instance, to some of the earliest recorded general meetings in the world: the Indian Buddhist councils of around 300 B.C.E., which helped to “consolidate and promote the tradition of open discussion on contentious issues.”

What Sen was describing there was a preliterate proto-liberal culture: Not until the mid-20th century would the Indian literacy rate rise above 30%. The analytical, logical mind, to which Ong ascribes so much of Western progress, was less important to Sen than the tolerant, interactive one.

Possibly the ancient Buddhist councils would have been more effective if everyone in attendance could read and write — or not. “It would be a great mistake,” Sen wrote, “to assume that because of the possible effectiveness of well-tutored and disciplined arguments, the argumentative tradition must, in general, favour the privileged and the well-educated, rather than the dispossessed and the deprived.”

The illiberal readers would like a word

You can be a liberal without reading books. You can also most certainly read books without being a liberal.

Not so long ago, I myself was a college student at an elite university, and while conservative students were few and far between, most of them were found in the philosophy department. Reading the completed works of Tolstoy and Plato does not by definition make you someone who respects personal freedoms and civil rights.

As writer Sam Kriss recently noted, Russian society’s high literacy rates have not produced liberal democracy: “One result of the Soviet Union’s mass literacy campaign is that today, Russians are essentially the only truly literate people left. The vast majority of Russians read regularly, more than anywhere else in the world … But somehow, political culture in Russia is not saner or more democratic than in the mentally enfeebled West. If anything, the opposite.”

Consider, also, the most prominent members of the postliberal right. Say what you will about Adrian Vermeule or Gladden Pappin, but they are certainly literate. Between them, they have almost 20 years of higher education. Even if you doubled that, I doubt you would make particularly liberal thinkers out of either of them.

It might seem obvious, but equating reading with liberal politics assumes that readers can’t be fascists. But, unfortunately, reading alone does not guarantee that you don’t become a Nazi. The German public had exceptionally high literacy rates when Hitler came to power in 1933, and some of history’s worst dictators were avid readers. Stalin reportedly read hundreds of pages a day and kept a personal library of around 25,000 books.

Distraction is a problem

Neil Postman has become a bit of a hero among the reading doomers: He foretold that screens were going to ruin everything long before the iPhone was invented.

Subscribe now

In his most famous work, Amusing Ourselves to Death, Postman argued that print language encoded the ideal of rational, sequential argument. Consider the Lincoln-Douglas debates: seven debates held in town squares that followed a sequence of affirmative construction and rebuttal.

In 1858, such an event drew a massive and engaged crowd. Could it do the same in the postliterate era? Not according to Postman, whose primary concern was the explosive rise of television. While the standard for political discourse in the 19th century was “generally coherent, serious and rational,” fast-paced television has made it “shriveled and absurd.”

In what he dubbed the “Age of Show Business,” visual media made entertainment the primary currency of politics, rather than rational argument. A modern audience demands at all times to be amused, and therefore cares more about good looks and shock factor than the substance of ideas.

There is no denying that the printing press made most things better, and that a lot of subsequent media seems to have made many things worse. But people tend to overrate how literate people were in some imagined golden age.

Mass literacy never meant that most citizens spent their evening reading George Eliot. In Victorian Britain, expensive new novels and works of history were purchased largely by circulating libraries; even the largest of those libraries had just 50,000 subscribers at its peak.

In 1989, an NEA study estimated that just 10% to 25% of American adults had read what its researchers classified as literature “of merit.” And just 7% to 12% had read serious contemporary writing.

Print mattered enormously, but its influence on our politics clearly did not require even a large proportion of people to work through philosophical treatises or highbrow novels. A society can be shaped by books that most of its members have never personally read.

And, in fact, the thing that Postman most feared television would replace wasn’t reading; it was meaningful social interaction. In Amusing Ourselves to Death, Postman wrote: “Americans no longer talk to each other, they entertain each other. They do not exchange ideas; they exchange images.”

His central argument had less to do with the in-vogue panic over how many books anyone read in a given year and was much closer to the question we’ve been asking ourselves at The Argument: How do we live with one another?

Years later, Postman would clarify more of his pedagogical vision. In his lesser-known book, The End of Education: Redefining the Value of School, he advocated for schools being places where students learn together as a group. Textbooks, he wrote, are the “enemies of education.” Only interactive dialogue can give rise to what school is actually for: not to serve the public, but to create it. As he put it in an interview: “School has never been about individualized learning.”

True, Postman was exceedingly worried about the distraction of technology. The medium of written text functioned for Postman as a metaphor for how we should approach most things in life: with full attention. And perhaps this is why we are so panicked about reading — and about reading books in particular. We think of books as the last thing left that might get us to focus.

Sen recounted in his book how Nelson Mandela’s democratic education began with the community meetings he watched as a boy in Mqhekezweni. Anyone who wished to speak could do so, and ordinary people openly criticized the regent. These meetings weren’t liberal — women were excluded from equal participation — but they cultivated habits liberal democracy depends on, like hearing disagreement, tolerating criticism, and treating people of different ranks as citizens whose opinions counted. Those habits did not require everyone to sit alone reading political philosophy.

Call me a debate kid, but I think interacting with other people, especially when you disagree with them, can get you to focus, too. The classes that taught me the most at university were the ones that forced me to contend with other people’s ideas in real time. They were also the ones that made me want to do the readings.

More than how much people read, we should care about whether they feel they have something to say — and, in Sen’s words, whether they have the opportunity “to speak and listen, without fear.”

Books and the knowledge they offer people are part of that liberal project. But they are not in themselves the holy grail.

Subscribe now

Recommended reading:

Canadian Prime Minister Mark Carney is not just the head of his country’s Liberal Party, but something of an icon of liberalism globally. At a bleak moment for center-left parties worldwide, he won his election, and has remained popular as he feuds with an increasingly indefensible American president.

So it’s remarkable to hear a prominent voice on the American left describe the Canadian leader as a “dangerous autocrat” who is not just worse but “far worse than Trump.”

This was not a one-off outburst. Matt Stoller, research director at the American Economic Liberties Project, has previously called Carney a “dangerous authoritarian.”

Why? Well, this latest outburst was because Carney is “a former Brookfield and Goldman guy” who apparently favors airport privatization.

To take Stoller’s argument at face value: No, Carney is not far worse than Trump; he’s far better. Trump’s view is that Canada is weaker and smaller than the United States, and that while a rupture in the commercial relationship is bad for people on both sides of the border it will be worse for Canada so it should act like a supplicant and kowtow to his demands. This is not the most salient aspect of Trump’s malgovernment, but it is probably the clearest expression of his authoritarian heart — he’s a man who’s fundamentally more comfortable treating North Korea’s dictator as a peer than the elected leader of a fellow democracy.

Carney, on the other hand, has stood up for the rights of smaller nations and for economic sanity. Americans outside the MAGA camp ought to be signaling loud and clear that we will end this trade war after we break Trump’s monopoly on political power.

The good news is that very few people of any ideological persuasion agree with Stoller about Carney. The bad news is that Stoller is not just an influential figure on the populist wing of Democratic Party economic policy, he’s in many ways just a guy who’s imprudent enough to follow the post-liberal left’s logic to its natural conclusion.

The tweet matters less as an assessment of Carney than as a glimpse of a larger ideological inversion on the populist and post-liberal left. A movement that speaks in the language of “open markets” and “economic liberty” has come to treat every deviation from absolutely perfect competition as a warrant for central planning. As a result, its adherents regard traditional market liberals as enemies more profound than a corrupt authoritarian who is currently wielding state power. Many on the left claim to view politics as a remorseless twilight struggle against an ill-defined force known as “corporate power,” and Stoller has the courage of these convictions: Carney is a more alarming authoritarian than Trump precisely because he respects liberal limits on the state, and Trump does not.

The post-liberal left’s position on aviation, a sector in which competition is always imperfect and government is always involved, makes this ideological inversion unusually easy to see.

Aviation as a microcosm

The notion that airport privatization is a more egregious threat to democracy than January 6 is a reminder that the larger post-liberal economic camp to which Stoller belongs is full of strange ideas about air travel.

For four decades, the federal government’s Civil Aeronautics Board (CAB) regulated U.S. airfares and directly controlled which routes airlines could fly. Because the CAB wanted to subsidize certain markets with weak demand, this meant raising prices for long-haul flights to compensate. “Concerned that such practices caused inefficiencies and inhibited the growth of air transportation, the Congress deregulated the industry,” explains a 1996 GAO report. Airlines were allowed to set their own prices and pick what routes they wanted to travel. This resulted in cheaper airfare but fewer nonstop destinations and smaller planes in places with weak demand.

The idea that disbanding the CAB turned U.S. air travel into a miserable hellscape is an article of faith on the post-liberal left. Ganesh Sitaraman, director of the Vanderbilt Policy Accelerator for Political Economy and Regulation, published a 2023 book titled Why Flying is Miserable (the book is long, but the answer is airline deregulation) and followed up in 2026 by proclaiming that Spirit Airlines’ bankruptcy proved that competition in aviation has failed and we need to return to comprehensive regulation of the industry.

This whole narrative makes absolutely no sense.

Read more

Editor’s note: The first essay The Argument ever published asked, “How do we live with each other?” To mark our first anniversary on Aug. 17, we’re returning to that founding question with a series about what we owe people whose beliefs and choices we may find difficult to accept or even understand. Over the next six weeks, familiar voices at The Argument and new voices alike will approach that question from different angles.

In today’s essay, Joey Politano, economic analyst and writer of the Apricitas Economics newsletter, takes on one of the maxims of the new right: that immigrants bring the failures of their birth countries with them. To the American public, immigration debates are about border chaos, crime, and public resources; but to the leaders of the New Right, immigration debates are an opportunity to write diversity, mobility, and dynamism out of the American story.

To receive every essay in this series, subscribe today.

Subscribe now

- Jerusalem Demsas

“Import the third world, become the third world” is the rallying cry of the modern right. The slogan, a regular refrain of the Trump administration, exploits the nationalist fear that a domestic way of life is under threat — and that this is the fault of immigrants who bring with them the institutional and economic rot of their birth countries.

The slogan is also intended as a rebuke of the mainstream economic consensus, which is that immigration liberalization boosts growth by improving material outcomes for both migrants and their destination countries. In the eyes of economists, there are “trillion-dollar bills” left on the sidewalk, ready to be picked up if only countries would ease legal obstacles to international movement.

Critics are quick to point out that the empirical studies underpinning this consensus rely primarily on immigration’s impact on narrow macroeconomic indicators like gross domestic product. Sure, we know how the arrival of a large number of immigrants affects local or national unemployment, home prices, income, crime, fiscal spending, etc. But what if, at the same time, immigrants ruin the abstract, immeasurable institutional superstructures necessary for long-term prosperity?

Share

The more academic costume for “import the third world, become the third world” is the so-called “new economic case for immigration restrictions” from professors like George Borjas and Paul Collier. Their argument is that, while immigration might drive GDP growth in the short run, it erodes the cultural and institutional factors that promote prosperity in the long run.

What if immigrants don’t value democracy, free markets, gender equality, religious tolerance, or antipoverty redistribution? What if they create fractious ethnic politics, commit destabilizing acts of terrorism, corrupt the legal system, spread addiction, break unions, reduce interpersonal trust, push censorship, and undermine democracy?

In short, these revisionist economists suggest that immigrants from dysfunctional countries will spread that dysfunction upon arrival, undermining the culture and institutions responsible for their new home’s success.

It’s certainly convenient for xenophobes that, after having been disproven in the narrow realm of empirical macroeconomics, they can retreat to more abstract cultural arguments that place the burden of proof on defenders of immigration. Yet it’s worth taking seriously the idea that immigration could be incompatible with democratic institutions, if only to know how to dispose of this now-widespread folk prejudice.

This is the project of George Mason professor Justin Gest’s new book Democratic Drain: Global Migration and the Struggle for Democracy.

Gest shows that, contrary to this folk wisdom and its highbrow academic defenders, immigrants tend to seek out strong, liberal democracies when choosing where to move because they are liberal people who value democratic culture and institutions. Indeed, it is these sorting and selection dynamics that are among the primary political impacts of immigration.

Treating immigrants as individuals

The problems with “Import the third world, become the third world” start with the very first word. Immigrants are not inert materials, goods shipped back and forth by diktat as part of production processes. They are people making active decisions to uproot their old lives in pursuit of new ones. That desire to move naturally creates a massive selection effect: Immigrants tend to be dissatisfied with their birth countries and admire their destination countries.

Gest’s analysis of Gallup World Poll data from 2021 shows that those who want to immigrate have extremely sour perceptions of their birth country: Eighty-eight percent say there is limited freedom of expression, 84% say the government is corrupt, 67% say elections are dishonest, and 65% have no confidence in their national government.

On the flip side, immigrants admire the political freedoms of other countries: Gest designed conjoint surveys in which prospective immigrants were given two possible destination countries to choose from, and they were 27% more likely to select a destination country profile if it was a democracy. That effect size was larger than if the destination country had a growing economy (25%) or generous welfare benefits (17%).

Using separate survey data, Gest also shows that prospective immigrants from unfree countries are more liberal than their compatriots with no desire to immigrate. More specifically, those who want to immigrate from conservative Muslim countries are more opposed to Sharia law, and those who want to immigrate from illiberal Eastern European countries are more opposed to authoritarianism. And settling in a new, freer country actually reinforces these democratic values among immigrants, making them even more liberal than they were when they decided to immigrate.

Subscribe now

Gest coins the portmanteau “demigrant” for these democratic immigrants, who tend to be younger, higher-income, more educated, and more liberal than the compatriots they leave behind. These people are not activists per se — though a small minority of them are — primarily, they are just workers with high ambition, a taste for freedom, and a preference for risk-taking.

Demigrants’ movement from more authoritarian to more liberal states typically happens at a slow, steady clip as years go by. Yet political shocks can radically increase their immigration.

Gest documents that immigration desire rises significantly in the wake of “deconsolidating” elections in which more illiberal parties take power, and immigration desire falls in the wake of “consolidating” elections where those parties lose power. He also shows a number of recent events, from Russia’s invasion of Ukraine in 2022 to the crackdown on Hong Kong protesters in 2020, where illiberal political events induced massive outmigration pressure.

The cumulative picture is of the world’s more pro-democracy citizens responding to rising authoritarianism in their birth countries by trying harder to immigrate to stable democracies.

Must someone die manning the barricades?

But Gest has a fundamentally bleak outlook on the effect of immigration on global democratization. That’s why the title of the book is Democratic Drain — he worries that the primary negative externality of immigration is that the demigrants’ decisions to leave weaken homegrown pushes for democratization in unfree countries. Instead, people begin sorting into liberal and illiberal countries based on their personal preferences.

The idea is analogous to the economic concept of “brain drain,” where a country’s most entrepreneurial and educated people leave it behind in pursuit of more lucrative opportunities abroad, making it poorer than if they stayed. Thankfully, however, a wealth of modern economic findings cut against the “brain drain” thesis: Because workers who immigrate earn much more money, even sending back a small fraction of their new earnings as remittances usually covers any material losses to families and communities in their birth countries.

Attaching the chance of immigration to high-value skill outcomes also incentivizes much-needed educational development in countries with immigration outflows. Allowing nurses to immigrate from the Philippines to the U.S., for instance, leads to many more Filipinos studying nursing, boosting the number of nurses in both the Philippines and America.

Plus, many immigrants circulate between their destination and birth countries, spreading their knowledge and experience.

Mainstream economics now views out-migration as a driver of a country’s development, not a hindrance to it. This should make intuitive sense, because most economic transactions are positive-sum; easing immigration restrictions is so massively positive-sum that even the “losers” are more than compensated by overall productivity gains in the long run.

Of course, for democratization, the calculus may be wildly different.

By leaving their birth country, immigrants give up nearly their entire ability to make policy there — they can’t very well send an ideological “remittance” to contribute to liberalization. The prospects for contributing to their new country’s democratic institutions are not that much better, at least in the short term: Most have to spend years earning citizenship before they can meaningfully influence politics.

Those who did not immigrate are likely to view the demigrants’ departure as partially a betrayal, as Gest shows in surveys of Syrian citizens. This breeds a distrust of the émigrés’ political diagnoses and recommendations. Authoritarian regimes can more easily target diasporas for political repression — and even bilk them for resources. (The modern Eritrean government obtains much of its money from a tax on all nonresident citizens’ income.)

Subscribe now

In other words, while moving to another country vastly increases immigrants’ total economic power in ways that offset the economic costs to origin countries, it may greatly decrease immigrants’ total political power in ways that enhance the democratic costs to origin countries.

Authoritarian regimes know this intuitively, regularly using deportation and exile to disempower critics. At the peak of the Cold War, the U.S. government knew that its policy of accepting anticommunist refugees weakened rebel opposition in authoritarian countries, internally dubbing the dynamic the “Cuban Contradiction.” The vast numbers of anti-authoritarian Cuban immigrants in the U.S. have certainly influenced American foreign policy — but they have not produced a flourishing democracy in Cuba.

This possible “democratic drain” brings up its own uncomfortable questions. Should democratic countries let dissident foreigners rot in autocratic regimes in the hopes that, eventually, they’ll band together to overturn the government? In even more grotesque examples, should they refuse to take refugees from active conflicts in the hopes that would-be immigrants will instead start fighting for “the good guys”?

In short, must we consign some to die manning the barricades?

Democratic Drain ultimately takes an even more desolate view of the international political landscape. Immigration first pulls those with liberal values out of dictatorships and into democracies, weakening democratic reform movements in the origin countries. Yet it also appears to spawn illiberal backlash among natives in destination countries, weakening democratic norms in places like the United States.

This logic flips “Import the third world, become the third world” on its head: What if immigration is hurting institutions not because immigrants are incompatible with democracy but precisely because they’re so enamored with it?

What is the point of the city upon the hill?

Ultimately, there is a paucity of hard evidence for this bleak theory, suggesting we need not fuss over possible second-order effects. After all, it was immigration to liberal democratic states that eventually allowed for the breakdown of the Berlin Wall and the Iron Curtain, even if it hasn’t yet democratized Cuba. Proving that democratic countries were willing to give rights to foreigners at a key moment was critical in supporting those foreigners’ demands for rights at home.

The simplest approach to all these dilemmas — the one best supported by the data Gest cites — is not to tweak immigration policy one way or the other, but instead to cultivate strong democratic values at home and trust that they will attract like-minded believers from abroad. This is what makes the Trump administration’s twin efforts to reduce immigration and weaken democratic institutions so insidious.

Trump’s personal corruption and attempts to overthrow elections make it obvious he holds no special regard for the institutions that undergird liberal democracy. For him, “Import the third world, become the third world” is just another verse in the same song he used to baselessly accuse immigrants of eating Americans’ pets, rather than any serious push to maintain American values.

By directly restricting immigration and dispensing with liberal norms simultaneously, Trump pushes potential demigrants away, further entrenching domestic illiberalism. In Gallup’s most recent global survey, a record-low share of prospective immigrants listed America as their top destination, though the U.S. still outranked Canada as the overall most desirable country. Further institutional erosion could induce the kind of demigrant exodus that characterized modern Hong Kong or Serbia, from which it would be even more difficult to recover.

In the short term, the most we can do is try to prevent further democratic backsliding — and protect the immigrants who have already made their way to America. But after Trump, the U.S. should reembrace its self-conception as the “City upon a hill,” working to repair democratic institutions, safe in the knowledge that a strong democracy will attract the people willing to uphold it. After all, the point of the city upon the hill is to shine.

Subscribe now

Recommended reading: