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Many college commencement speakers are getting booed off stage for delighting in the productivity of AI in front of the audience it threatens to displace, cheering for all the money it will make them as CEOs, largely at the expense of the students who are supposed to be celebrating their achievement of finishing school.

Eric Schmidt, former CEO of Google, gave a commencement speech at the University of Arizona, and told students that AI was going to touch every profession and the question to answer wasn’t if AI would shape the world but whether they would shape AI (rhetorically similar but substantially different to JFK’s “ask not what your country can do for you, but what you can do for your country”). He was booed1. Real estate owner Gloria Caulfield told graduates that AI was the next industrial revolution, and was booed. Scott Borchetta, a record-label CEO, during his booing, told graduates that “you can hear me now or you can pay me later.”

The asymmetry is really the thing that is being booed here. These students have been training their entire lives for a credentialing system that is now actively being dismantled in the name of efficiency and profit. They are booing the people on stage who have benefited from the rules of a previous game, and are now lecturing them about embracing the rules of a new one. These students aren’t anti-technology, in the same way that the luddites weren’t anti-technology. They are anti-technology-without-solution and anti-future-without-hope. Of course they are booing.

I did an event at LinkedIn headquarters a few weeks ago on “Careers in the Age of AI.” It was an in-person room of about 25 recent college graduates with a livestream with people of all ages. The whole point was to talk about jobs and AI and the changing world we are all trying to figure out.

Naturally, the question that kept coming up was: what do I do right now?

And what does anyone do right now?

• What does it mean to train your whole life for something, only to have a person of power call you a “lower-value human?”

• How should someone think about (multiple) AI CEOs saying white-collar work will be “fully automated by an AI within the next 12 to 18 months?” but now walking back those statements?

• What does a career mean anymore, and how should people think about the future they worked so hard to arrive at?

The question underneath all of that is timing. When is the life that people have been told to train for supposed to start?

According to a recent Economist/YouGov poll, over half of Americans aged 18-29 are pessimistic about AI, and over 60% are very worried or somewhat worried about AI replacing jobs. The feelings are only deteriorating more over time, with anger and anxiety becoming the dominant emotions over excitement and hope.

It’s hard to know what to do because we largely don’t know what’s happening yet. The data around AI and the labor market is mixed, and the people telling you that they know are mostly selling you something (usually, an AI product, like the CEOs who gallop to Twitter to delight in how efficient their AI company is in using AI so they can fire everyone).

What is a Job in the Age of AI?

To level set on my direct experience with jobs and job applications - I grew up in Kentucky and went to Western Kentucky University. I didn’t even know you could major in economics until I got to college, because I had never met anyone who worked in that specific field. Once I took my first economics class, I was completely hooked. I started dreaming about jobs, new cities, financial stability, and a world where I could do what I loved every day.

I started a blog, Scanlon on Stocks (oh yeah), primarily to meet more people (and met Nick Maggiulli and the Ritholtz team, to whom I owe a lot). I sacrificed much of my college time for the sake of work (something that I would do differently now, it’s okay to have a little fun) I had a 4.0 GPA, three majors, club president and founder, D1 athlete–anything you could do on campus, I was doing it, primarily to try and get a job. When it came time to graduate in 2019, I applied to over 150 jobs. I got callbacks for about 5 or 6 of them.

I had three good options. One of the options mostly existed because a recruiter from the company gave me a chance. He had noticed the blog and the initiative and gave me the chance to try, which was all I really needed. And I got the job.

In 2019, a human being read my resume.

In 2026, that doesn’t always happen. Humans have more or less exited the job process. The hiring funnel has been almost entirely intermediated by AI on both sides. As Derek Thompson wrote about last year, it’s a “plexiglass wall” with both applicants and companies throwing technology at the process, neither side really seeing each other. Much has changed since I applied, including how we think about jobs.

But the story that most people tell about how the economy works is not even from 2019, it’s from many, many years ago, the glowing boom of the Post-World War II economy. Work hard, get a degree with enormous government support, buy a house with enormous government support, raise a family, get an awesome pension. Sometime in the 1970s and 1980s something went wrong–globalization, automation, high interest rates, the death of pensions, housing as a speculative asset–and we entered a long stagnation.

In recent years, entry-level hiring has been depressed. Unemployment for college graduates aged 22-27 is 5.6%, up sharply from 3.6% before the pandemic. Guy Berger notes in a WSJ interview that today’s college graduates have usually done better in the face of a weakening job market than they are doing now.

• Part of it is this AI confusion/problem/opportunity—an April 2026 paper finds that when/if AI absorbs the work juniors used to do, firms cut junior hiring, which weakens the pipeline that creates future seniors. The result is “lost cohorts” of juniors who don’t get the training they need.

• Part of it is other problems, including pandemic overhang. A study of 243 million hires across four countries finds that when you separate the effect of AI from the effect of remote work, remote work turns up as the likeliest culprit of a recent collapse in entry-level hiring. When teams went remote, the cost of supervising and training a junior went up, so firms stopped hiring them.

Both papers point to firms kind of giving up their juniors. That’s a core rung on the economic ladder that young people are missing out on. The booing is rational.

So the entire AI conversation has been organized around one question: will AI replace your job, yes or no, and as we can see in the results from these papers, it’s really not clear what is happening. That’s why a framework for thinking about jobs is so important.

Alex Imas has written many excellent pieces on AI and labor market displacement. He begins a piece from earlier this year discussing a widely cited 2023 paper on AI exposure, which found that around 80% of workers in the US could have at least 10% of their tasks affected by large language models. Many people interpret this as “80% of jobs are at risk,” and Imas points out that the reading is wrong—that the 80% exposure measures whether AI can do some of the tasks in a job, not whether or not the job entirely disappears.

Imas says the dimensionality of a job really matters, the number of distinct tasks it involves. A job with two tasks, one of which AI can do no problem, is a high-risk job. If a firm can automate half the job, mechanically it’s hard to justify keeping the worker.

A job with seven tasks, one of which AI can do well, is a job that probably gets more productive (if the firm is smart) because the worker has more time to do the other six tasks that can’t be automated. Imas says that the resulting productivity gains, the focus effect, can raise wages instead of eliminating the role.

He compares a long-haul truck driver to a consultant. A truck driver could be automated, because it’s theoretically one task, of going from A to B. However, a management consultant, a job that has a bundle of tasks including being a scapegoat for companies, can have some of their work automated, but the political work and client communication and presentation of results cannot be.2

Thinking of a job as a bundle of tasks, the dimensionality, is a very useful rule of thumb because it gives you a good sense of how at-risk a chosen job might be. Luis Garicano builds on Imas’s framework, offering the supply side version, and points out that firms buy bundles, not tasks, so they pay for a human so a human can do a bunch of interconnected, context-dependent tasks, because jobs are complex.

Ernie Tedeschi at Stripe Economics uses travel agents as an example of “the economic value of human expertise” as Imas calls it. In 2000, the job was exposed to automation–booking, fare aggregation, ticketing—all of it could be automated and no one was safe. Travel agent headcount fell by more than 60% from the dotcom peak. But some survived.

They survived by moving up market. Travel agents now earn close to 99% of the private-sector average wage, up from 87% in 2000. Those that survived leaned on judgement and accountability and relationships and the ability to swoop in and fix something quickly when things go wrong at 2am. Those seem to be the pillars of strength in the AI age: being able to evaluate, having some element of taste, holding accountability, building out networks, and the capacity to deliver a human touch in an increasingly automated world.

I was in line at the rental car center a few days ago. I tried to check-in online but the app kept logging me out. So I had to wait in a 20-person line that took about one hour to get through to have a human fix whatever was going wrong. The meta-work of that: finding a car, finding my profile, the payment, can all be automated. But the ability to step in when the technology doesn’t work is still something only a human can do.3

We don’t quite understand how human most jobs are. It drifts into Rory Sutherland’s Doorman Fallacy. The job of a doorman is just opening doors, right? Well, no - it’s welcoming and helping and security and a place to ask questions. A job is usually a whole lot more than it seems.

Firms are also craving some humanness. Gillian Tett at the Financial Times wrote that firms are focusing on “critical thinking” skills and are looking towards hiring students that majored in the humanities rather than STEM. Much of this is due to “shallowness” of the ideas of STEM students.

So the big question now — for financiers, regulators and educators alike — is how to create skilled AI natives who can also use the critical thinking needed to spot both the opportunities and (very real) risks in AI. Those companies which find them will be the real winners. All eyes, then, will be on the 2026 intern pool.

People optimized too much for one side of intelligence, ignoring the curation of their creative skills. Creativity is enormously valuable in the age of AI.

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My take on it is that AI is sort of like freeze-dried camp food. It does a good enough job, is filling enough, but it isn’t something you want to eat everyday (trust me, I tried). People crave ineffcient, home-cooked meals for a reason, and it’s because it’s a nice thing, not that it provides a certain exact number of calories and fat and protein.

It does require some context (some bakers know that breakfast skillets are better with some avocado slices or some butter). It also leans on accountability (a chef is responsible for what they cook!) and taste (in both flavor and meal design).

You need camp food some days. It’s good that camp food exists. Camp food is efficient and helpful. But, we still need real food too.

Is AI Even Cheaper than Labor?

The technology is very expensive. Much of our assumptions on AI displacement seems to be based on the idea that it is cheaper than labor. It might be soon (Nvidia wrote in February that Nvidia’s new chip allowed the leading inference providers to reduce token (think of these as arcade coins that the AI models eat in order to work) costs by 10x), but right now, that assumption is just not true.

Agentic workflow, which consists of the multi-step work building toward context and revisions and judgement, the human-y AI, is more compute intensive than a chatbot. Upcoming frontier models could be even more expensive. Lots of arcade tokens.

In April, Uber’s CTO said that he had to go “back to the drawing board because the budget I thought I would need is blown away already.” Azeem Azhar and Hannah Petrovic cover this in a recent piece, writing that over 70% of companies exceeded their AI budgets in 2025. This stuff is not cheap!

Some of the enormous spend is good. Brian Albrecht published a long piece a few weeks ago called “You Are Not a Horse” that walks through the AI-displaces-everyone story by tracing the dollars. If AI makes some tasks cheaper, the money saved through efficiency doesn’t vanish, but rather gets spent somewhere else, which creates demand somewhere else, which keeps humans employed somewhere else.

For the horse outcome to happen (where horses are no longer our tractors and instead are living a relaxing life in the fields) every dollar of spending would have to land on activities with no human labor inside them, anywhere in the supply chain. People save money on goods because of the efficiency of AI, so they start spending money on services. The dollar has to go somewhere, and that somewhere can support employment somewhere else in the economy.

But some of the spend is bad. Companies have fired people in the name of AI efficiency, but in many cases, it hasn’t really made anything more efficient. Uber’s COO recently came out and said that “tokenmaxxing” was making it “harder to justify AI costs within the company” because more tokens spent by engineers wasn’t leading to a measurable increase in “useful consumer features.”

Part of this is a measurement problem (we likely don’t totally understand how to implement AI outside of “people-shaped workloads”) and part of it is AI compute is increasingly constrained and therefore increasingly expensive. More data centers or whatever might make all of this cheaper and more effective. But jobs that are expensive to automate at the moment might be safe for a while.

But for now, when you put these pieces together: the dimensionality + the bundle strength + the compute economics = a framework that is pretty useful.

• Jobs that are at risk are (1) low dimensional with weak bundle strength with tasks that are already cheap to run on AI, like customer service (although, as someone that has been trying to stop my insurance from double charging me for the past several months, I would very much like a human involved) and back-office document processing and entry-level analyst work.

So if you have a high dimensional job with a lot of tasks that take a lot of compute; a job threaded with judgement and accountability and creativity, that might even benefit from AI spend, you’re probably relatively safe. Imas says that the “relational sector”, which is “human-intensive, provenance-rich, sometimes artisanal part of the economy where the human aspect is part of the value of the good or service” will become increasingly important.

But that requires firms to think about jobs in a way that is more than a cost metric, which they don’t tend to do. Axios recently reported that companies are firing employees to cover their AI bills. People are getting laid off who might have a high dimensional job because the firm could be unaware of how challenging it will be to AI that specific job. Starbucks is retiring AI inventory tooling because it kept hallucinating.

We are likely in a rough transition period of fires and rehires as we adjust to that.

Are Firms Actually Using AI?

Well:

• Some firms are using AI. Rob Copeland reported in April that six of the largest US banks posted $47 billion in profits in Q1 2026 while shedding 15,000 jobs, and the CEOs are now openly like “AI let us do that :)” on earnings calls. In 2025, Brian Moynihan at Bank of America said that AI was “not a threat” to his 210,000 employees. In 2026, he announced that the bank had shed 1,000 jobs through “eliminating work and applying technology”. JP Morgan’s Kevon Brunner says that AI has shifted from “hype to real execution.”

• Some firms are using humans to train the AI to eventually fire themselves. Meta laid off 8,000 employees in an AI-push, assigning 7,000 workers to “AI-initiative focused teams”. The SF Standard did an interview with an anonymous Meta employee (who ended up being one of those laid off) about the morale at the company. Much of the interview was focused on the sense of detachment from humanity, with the employee stating that Meta is “not at all empathetic enough or human enough in how they are leading humans through [the AI] era.”

• Some firms are designing their own AI. Kirkland & Ellis, the world’s highest-grossing law firm, announced in May that it’s spending $500 million to build its own AI platform designed using information from 250 of its lawyers about how they do their jobs, instead of using a product like Harvey. The chair, Jon Ballis, told the FT the idea is to “take the collective intelligence of our institution and be able to deploy that throughout our firm.” The senior generation pouring its knowledge into a system that will eventually do the work that juniors used to do to learn the job.

• Some firms are having mixed results. Gillian Tett at the Financial Times wrote about a Judge Business School survey of over 600 finance and AI companies that found that about 80% of private sector finance groups are using AI, but only 40% reported any profit boost from it. 60% of respondents actually expect AI to increase hiring or reskilling at their firm.

• Many firms are not using it at all. Only 1 in 5 firms across the board are actually using AI, as Guy Berger notes in his piece on AI adoption. That’s with a pretty strong growth rate—Federal Reserve’s Jeffrey Allen does a great breakdown of the three public surveys we use to gauge AI adoption, noting that the adoption rate grew 70% from late 2024 to late 2025—but it’s still pretty low, considering how much money the companies are spending and for all the fuss it makes.

Ernie Tedeschi ends his piece on travel agent employment by highlighting a framework around job displacement:

On the one hand, AI disruptions to the labor market may be delayed and not salient until (perhaps even amplified by) the next recession. On the other hand, the most negative effects may be limited to specific occupations rather than broad-based, and as prices and wages adjust, those occupations may even look more favorable over time

He points out that (1) we might not see any real AI impact until we see a recession and (2) specific jobs might be impacted rather than the labor market and (3) those specific jobs might be fine in the long run.

David Solomon, the CEO of Goldman Sachs, wrote a New York Times op-ed last week titled “The A.I. Job Apocalypse Is Overblown.” His argument is the standard optimistic one: the economy has absorbed technological transitions before (electrification, the digital revolution), job growth has outpaced population growth since the 1960s, and even if AI automates 25% of work hours, people will find more productive things to do. All will be well, in the long run.

The aggregate case is fine, sure, but that’s not what's actually breaking people.

In April, Goldman Sachs economists published a paper telling a different story. They examined four decades of individual-level data on workers displaced by technology, and the findings line up with Tedeschi’s concern.

• Workers displaced from technology-disrupted occupations take about a month longer to find a new job and suffer real earnings losses of more than 3% on reemployment.

• Ten years out, their earnings are still nearly 10 percentage points behind workers who were never displaced, and 5 points behind workers who were displaced from more stable occupations, known as “scarring” effects.

Tech-displaced workers experience delayed homeownership and delayed household formation, with the effects amplifying significantly in recessions. To be clear, this type of displacement has always worked like this. The costs land on individuals for a very long time. The economy will adjust in the long-run, but the adjustment period can still suck. Jasmine Sun summarizes it well with a quote from Carl Benedikt Frey:

Most economists will acknowledge that technological progress can cause some adjustment problems in the short run. What is rarely noted is that the short run can be a lifetime.

The economy can absorb AI the way it absorbed previous technologies, slowly, unevenly and with new sectors appearing at the same time that the rungs of the economic ladder are getting squeezed. But jobs are only one part of the AI conversation. Wealth creation is another important part.

Who Gets to Be Wealthy in the Age of AI?

Wealth is mainly a combination of labor income and investment income and real estate. True wealth comes owning shares of companies, and the US stock market is meant to be that wealth-creation opportunity. Companies go public because that’s the promise we made people—don’t worry, tying your retirement to the stock market is going to go really great because all of the biggest companies go public and you, the general public, can participate in the upside. And retire. But companies don’t go public anymore.

Deedy Das wrote a post about Silicon Valley where he estimates that about 10,000 people, those working at Anthropic and OpenAI and Nvidia and Meta have all hit retirement-level wealth, more than $20 million dollars within the past five years. Everyone outside of that circle is frothing at the mouth to try and get in, but the door has closed—the companies are pushing back against people selling secondaries, meaning that the most enormous wealth engine in history is increasingly confined to just a few people. OpenAI and Anthropic4 are both sniffing around IPOs, but both are near $1T private market valuations, which could leave little room for more upside.

As Joachim Klement wrote “the IPO of these AI companies is probably nothing more than a major transfer of investment risk from the current owners to retail investors, pension funds and others who are willing to buy the hype.”

SpaceX just filed to go public after 24 years—they are unprofitable on $18.7 billion of revenue, losing almost $5 billion last year, and are about to IPO at a $1.5 trillion valuation, with Musk holding 85% of the voting power. This is a company that we are asking people to build their retirement on!

If you don’t own equity here (or more importantly, work at one of those companies and have access to shares regular people can only dream about) your participation in the AI boom is entirely through the lens of: is this thing going to destroy my life?

Are We Stuck in the Permanent Underclass?

Much of the age of AI is like this, the privatized gains and socialized losses. It’s a contributor to the discourse around the “permanent underclass.” Jasmine Sun wrote about this concept in the New York Times a few weeks ago, the idea that if you don’t get wealthy now, you will never, ever be successful. I spoke to a room of Stanford undergraduates a few weeks ago and that term was floated a few times.

People are living in fear of the economy.

The vibecession, the marked disconnect between economic data and consumer sentiment, is back in the discourse again, with terrific new research from Jared Bernstein and Daniel Posthumus pointing to enormous price level variability as a driver of negative sentiment and Annie Lowrey at the Atlantic advocating for erasing the term entirely and replacing it with the term “permacession.”

I read the 600+ comments on her piece — all of them, plus many on r/Economics. Most relitigated what she’d already granted and what many people grant when the vibecession comes around: that housing and healthcare and groceries are brutal. But the ones who actually engaged her question — why the vibecession exists — kept talking about the concept of economic security, which appears to be defined as a:

1. Bounded downside: an illness or layoff can’t erase everything you’ve built

2. Predictable floor: you can count on and plan around where you are

3. Reward for work: A perceived link between effort and outcome still holding

4. Anticipated progress: And a believable path to the next thing: the job, the house, the kid.

The vibecession is complicated, but there seems to have been a structural break in sentiment in 2022, I think largely driven by structural gaps in how people feel connected to their economic reality. Economic data captures a moment, but I think sentiment is capturing people’s concern about their economic future. People can’t save, so of course, they aren’t going to think to positively about the future they can’t save for.

Below are the charts for consumer confidence and consumer sentiment, both nosing downwards, with the University of Michigan Consumer Sentiment Survey5 showing a marked decline among all generations (most notably, for Gen X, the increasingly squeezed ‘sandwich generation’).

When none of those four conditions of economic security hold, the casino looks rational. Of course it does. Prediction markets did roughly $25 billion in volume in April alone. A recent Wall Street Journal article found that 70% of Polymarket bettors have lost more money than they made. The system is designed to extract from people who need a fast win and to compound for people who can afford technology to get ahead.

There are also people who are opting out of the system because they have economic security. While middle-class kids are being told to embrace AI to keep up, wealthy families (including many who make the AI products) are pulling their kids out of algorithmic credentialing entirely. No-screens private schools are growing, with handwritten essays, oral examinations, in-person seminars, human access: you can pay your way out of technology.

The elite version of education is becoming analog. Everyone else is stuck talking to ChatGPT. The thing that is good for you is something that you have to be wealthy enough to access. AI (probably?) isn’t going to destroy your life, but it’s accelerating the closure of doors that were already closing, and the panic about that is rational.

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Why Does Everything Take So Long Now?

I do think we are facing a duration problem, which ties into the economic security/vibecession issue. Things are just taking longer than they used to. Career formation takes longer because retirement is pushed farther out, which is great because people are living longer but creates career ladder issues.

Skill compounding takes longer. Family formation, home ownership, financial stability, career stability–it’s all getting pushed out by about 5ish years. The thing that used to happen between 18 and 25 is now happening between 25 and 30.

The news cycle and the social media cycle and the AI hype cycle and the casino cycle have all gotten faster, and the timescale of building a durable adult life has gotten slower, and the gap between those two things is enough to drown in.

25 is the new 18, you might say. Figuring out who you are, what you’re good at, how the world works is now happening later. Partly because of the pandemic knocking a few developmental years off (I lost a good chunk of my early twenties to COVID and now am 28 years old and just now figuring out how to be a person in the modern universe). It’s a different clock than what the world expects from young people.

So the failures that we often state as problems–the delayed home buying (which is also part of high mortgage rates and high home prices) and the marriage data and the wage data and all of the other data–those are functions of people just taking a long time. It’s a longer development timescale colliding with a faster extraction timescale.

That’s why the cheating and casino economy is so enticing. Everything takes so long. The despair and the doom and the booing and the financial nihilism are all rational responses to being told you are behind on a schedule that quite literally cannot apply to you.

What Do You Do About it?

Tyler Cowen published some notes on jobs advice in the age of AI. His first principle is to look for “messy jobs,” the ones hard to describe, that change by the day, with many discrete tasks, as well as work in biomedical, work in energy, run experiments, gather data. Go where the capex is going. I think it’s terrific advice, and wanted to compile other things I’ve heard over the past several months.

1. Pick the manager, not the company: The training pipelines that used to build up junior employees have been more or less gutted across most white-collar industries. The single biggest variable in whether your first job teaches you anything is the person who manages you, so as you go through interviews, try to get a sense of what that relationship might be like.

2. The search is the job: One warm introduction is worth fifty cold applications. If you don’t have a network, the work of building one is the work.

3. Lean into creativity: Gillian Tett’s piece makes this really clear. Firms want good thinkers, and they are prioritizing creativity. They want people who are unique and who can look at hard problems and come up with novel solutions. Original thinking is an asset in the age of AI. The goal isn’t to compete with the AI, but to be the person who knows what to do when it all stops working.

4. Build something: Networks come from building a living portfolio online. It’s very unfortunate that Twitter has devolved into what it is now, but the smartest people in the world still flock to the site. Building a voice, interacting with people on social media, and developing evidence that you can think in public is enormously valuable. Ernie Tedeschi wrote a terrific piece about the surge of new US business applications, specifically the rise of AI solopreneurs who are using the technology to run companies or side businesses.

5. Be AI native, not AI proof: What jobs get more leverage from AI? Sarah Eckhardt and Nathan Goldschlag at the Economic Innovation Group have been tracking this and found that students are flocking toward AI-exposed degrees, not away. Part of this is momentum–the jobs that pay the most tend to the the most AI-exposed, like finance and engineering. This is the importance of learning about the tooling behind AI. We can boo AI, and we should for the way people talk about it, but there is still opportunity. Being able to help a non-tech company automate some tasks is likely one of the fastest growing jobs out there.

The Pope was the first world leader to really go toe-to-toe with AI. It was a relief (especially as a Catholic, it was cool) to see someone say something substantial and thoughtful. The Pope acknowledged that AI is indeed helpful, but it’s not morally neutral. It needs guidance.

We otherwise don't know what AI is to us, evidenced by Paul Graham, one of the people who pushes the private market around AI forward, working it out in real time on Twitter:

There is a “right” way to use the product, but no one has made that clear, at any level, other than Pope Leo. The discourse around AI is growing increasingly negative, and a technology that could have been used as a force for good, was marketed as a job killer.

The despair and the doom and the booing and the financial nihilism are all rational responses to being told that you are behind on a schedule that doesn’t really apply anymore. The rules are changing. Bounded downside, a predictable floor, reward for work, and a believeable path to the next thing are the conditions under which a future feels possible. For a lot of people, none of that holds.

Thanks for reading!

I have to go on an elimination diet because my gut is eating itself and that apparently is also destroying my thyroid because I am not absorbing any nutrients. In order to address this, I have to stop eating wheat, dairy, corn, egg, tomato, peanuts, coffee, soy, cacao, sugar and manyotherthings (this is not like a juice cleanse or something fun, it’s something I have to do to stop my body from attacking itself). I have to write down what I do eat and how I am feeling and then evaluate from there as to what I can eat in the future.

If there was a quick fix - say an injection - I would try to take it. I don’t KNOW what’s happening to me, I just know that I got lots of vials of blood drawn and the miracle of modern science has informed me that some things are not going very well.

But, funnily enough, part of the problem is that I took shortcuts. I traveled 40 out of the 52 weeks last year (a lot for me) and some days, I would just subsist on granola bars and about 14 cups of coffee. I would also run and work a lot and sleep very little because I was totally and completely invincible. After all, I was an optimization machine.

And for a time, I sure was. But then, I wasn’t. Turns out, I wasn’t really optimizing anything, I just was avoiding what I actually should have been doing like sleeping. What I needed was to stop adding things and start figuring out what was making me sick. That's the opposite of what we've been sold.

I. Ozempicization

Americans love optimization. So when things come along that promise to help us optimize even more, fast fixes with near immediate results, it’s hard to say no. We’ve built entire identities around being efficient.

The desire for control is really intense right now, showing up in lots of corners of both the digital and physical world.

• I think it is functionally a response to financial nihilism, where people stop believing that the underlying economy is working for them and turn to gambling or some other seemingly quick fix instead to try and find stability.

• 80% of Gen Z and 75% of Millennials feel behind, according to a survey from Northwestern Mutual, and that drives them to speculation.

• Same with social media - if you’re having trouble establishing connections in real life, the online world provides a form of that, but people are increasingly disturbed by our collective reliance on it, as we saw in the recent Google and Meta ruling.

Naturally, industries have formed to monetize this nihlism through promising solutions. But the solutions never arrive, because the nihilism, the giving up, must persist in order for these products to survive. It’s a version of Ivan Illich’s Limits to Medicine, where he argues that the medical establishment itself produces illness by making people dependent on professional intervention rather than building health. That effect carries across all these optimization tools, creating dependency on the fix rather than addressing the cause. The optimization economy can't deliver control, because the desperation is the market condition, and the pursuit of control through optimization is itself a loss of control.

Our tools are also heavily focused on the individual. As Raymond Williams wrote in his 1975 book Television: Technology and Cultural Form:

The earlier period of public technology, best exemplified by the railways and city lighting, was being replaced by a kind of technology for which no satisfactory name has yet been found: that which served an at once mobile and home-centred way of living: a form of mobile privatisation.

Williams was describing the shift from infrastructure that served everyone to technologies built around the mobile, private individual. The shift from railways to peptides is the shift from “we built this for everyone” to “you can buy this for yourself.”

One example of an individual optimization tool that really works is Ozempic. Some people need to be on it for medical reasons1 and others are self-admittedly doing it for aesthetics. To be clear, Ozempic is a wonderful technology that solves a very real problem for individuals but it leaves the collective problem like the food system and healthcare access2 untouched.

It also marks a shift. The internal body has a thing we can really control, with time and resources. What we have is the Ozempic optimization of everything - Ozempicization, if you will. We have a suite of magic shots now in the form of peptides and everything else that address effort and discomfort and complexity. Everything can be optimized. Everything can be controlled.

II. The Body as Control

The body is always a site of control precisely because it’s a system that still responds to input. Systems are hostile at the moment. The economy and institutions tend to mostly ignore the plight of the individual. But the body listens.

It makes sense that Bryan Johnson and his multi-million dollar experiment to become 18 years old has captured the public consciousness. Bryan has something everyone wants - total control over outcomes. The appeal of Don’t Die is the control - controlling your nutrients, your supplements, your longevity. And for the viewer that’s the appeal - the body is something to control, in the era where everything feels uncontrollable.

This patterns happens a lot. Personally, when I was in college and my dad was very sick, I developed an extreme eating disorder to try and regain control. The control over the body is the first refuge when everything external becomes unmanageable. This is a genderless dynamic. Many people resort to the body as last resort, across the entire human species - and that form of control is becoming content.

Clavicular is one of the new and notable streamers of the moment, known for bone smashing and ‘looksmaxing’ and exists in his own makeshift WWE-like universe. He has his own language in his universe, a battle for #1 Chads (decided on an online leaderboard). He is obsessed with how he looks and is obsessed with control.

Looksmaxing itself simulates a value (status, desirability) that these people might not economically possess. It's control over the body as compensation for lack of control over economic outcomes. This is also seen in wellness culture, MAHA, the peptides, the cosmetic surgeries and enhancements - it’s serving an individual purpose of wanting to be healthier or stronger, but it also serves an economic purpose, another vector of control.

It’s revealing that Silicon Valley’s word of the moment is ‘agency’ as it dresses up that desire for control. Optimization is the process, control is the desite, and agency is the branding. It’s not clear what agency means in startup land (similar to other words often used, like taste) but it does hint at someone who will force the universe to bend to their will, one way or another3.

Cluely is a company that embraced this wholeheartedly, the final boss of the hustler economy. Their original ethos was cheating (they have since pivoted into AI notetaking) and they have raised millions and millions of dollars4. For them, “scamming” was being “agentic” which is indeed the “hottest commodity in Silicon Valley” as Sam Kriss wrote in his piece Child’s Play:

The future will belong to people with a very specific combination of personality traits and psychosexual neuroses. An AI might be able to code faster than you, but there is one advantage that humans still have. It’s called agency, or being highly agentic. The highly agentic are people who just do things.

And they are just doing things, driven by (understandable) fears of the permanent underclass and becoming useless in the age of AI. Apparently, the way that you avoid both of those is by “constantly chasing attention online.”

What Bryan Johnson does is highly agentic and highly online. He is always self-experimenting with supplements and psychedelics, with a very strict regime of diet and exercise. It’s perhaps the most control (agency?) that anyone has ever had over their body. He is in fact trying to get so much control that he is essentially playing a version of God.

People have to ask themselves:

• Do I believe in his assertion that we can live forever?

• Do I believe that his body is a proof of concept?

• Do I believe the content that he continuously generates sells the believability of the project well enough?

It quickly turns into a belief market, with Bryan Johnson as an asset. Same thing with Cluely - the investment was based on belief, a belief in control and a belief in agency. But once the body (or the mind, in the sense of agency) becomes an optimizable surface, the self becomes an asset class5, driven mostly by narrative, and once that happens, you're already inside the logic of belief markets.

III. Belief Markets

Prediction markets and crypto run on the same logic - bets on narrative rather than fundamentals, agency through participation. Belief markets promise an exit from limits, physical or financial. They monetize the fear of being left behind, in forms of (1) dying while others don’t (2) not cheating when others are and (3) being poor while others aren’t.

They all mark a shift that has been happening.

• Old capitalism valued productive capacity, the ability to make things.

• Financial capitalism valued cash flow rights, claims on future earnings.

• What we might call belief capitalism values narrative adhesion, the ability to keep enough people inside a story long enough that the story stays load-bearing.

Belief markets require the appearance of accessibility to stay alive. The product sold is “you could be this too”. Brian Armstrong of Coinbase, operates in a similar mindset to Bryan Johnson. He is also into longevity and biohacking (and prediction markets) and says that getting old should be optional in the future.

And that mindset carries over into his product. The pitch for Coinbase prediction markets is quite literally “take back control.” Kalshi’s, a prediction market competitor, is “make your grandkids proud.”

Control your future, with us, your friendly neighborhood gambling apps. The founder of Novig, yet another prediction market app, said that only 20% of their users make money, and touted it as much higher than the rest of the industry. That doesn’t sound like much control. That doesn’t sound like much of a future.

Everyone is chasing after the gold. Everyone is trying to strike rich, easily and quickly, to “get in on the next big thing and hope for the best” as Allison Schrager writes.

The general lack of rules6 combined with the inability to take back control despite it being promised is the extraction part of a belief market. The gap between what participation promises (free yourself) and what it delivers (enormous losses and even less freedom than before).

Every solution to “systemic failure” that promises control gets packaged as a product that re-enrolls you into something deeper than what you were escaping.

IV. The Manosphere as a Case Study

The extraction logic of belief markets migrates to wherever desperate people are, and some of that desperation is in the manosphere, the online universe promoting masculinity. I think the manosphere audience is actually smaller than we might think, but it is illustrative of the control impulse, belief markets and subsequent extraction, and the spectacle economy.

Louis Theroux’s Inside the Manosphere documentary captures these belief markets in a revealing way. It shows the paranoia that broadcasting your life to thousands of people can create. The men depicted are terrified of being seen as (1) small (2) poor (3) weak and (4) undesirable, so they create these false enemies in their mind (Louis becomes one of the enemies) and become fixated on escaping ‘the Matrix’.

The streamers in the Manosphere (and beyond) are functionally human zoo exhibits. People throw treats into their enclosure and demand they dance (for example - on Twitch and Kick people get sent tens or hundreds of dollars to answer questions or do backflips or something).

This leads to vice signaling, appealing to the worst parts of ourselves, as the streamer does crazier stuff because the audience demands crazier things. The crazier things then get clipped and posted and shared for the specific purposes of going viral. Sometimes the clips are interviews out of context or rage bait or worse and then everyone yells and gets mad, shares them, it goes viral and then society erodes at the edges just a little bit more. You can run entire shows just on the clips and rake in millions and millions of dollars.

The Manospherefluencers are essentially MLM leaders - they recruit young men and young women into their trading courses or their OnlyFans management company, taking a percentage of pain and despair.

Polymarket, a top prediction market, is doing something similar with their new referral program - prediction market influencers are rewarded for bringing new users to the platform, getting a cut of fees that the new users generate. Polymarket also follows the messaging strategy of the Manosphere - they “[amplify] unproven claims from the Trump administration and baseless conspiracy theories” in order to “attract young men, who are most likely to become paying users” as Stuart Thompson, David Yaffe-Bellany, and Mike Isaac write in the New York Times.

They teach people that it’s easy and simple and just watch the crude oil chart for a triple witching or bet on how much it’s snowing or bet on the Oscars but most of all bet on yourself and you can be a millionaire just like me. And yes, you must have it all, easily, because it is easy now. But it’s not. As Benjamin Fogel wrote about Andrew Tate, leader of the Manosphere:

He is a symptom of a new brand of capitalism unencumbered by any illusions about progress. For Tate and his followers, the whole system is a scam and the only way to succeed is by pushing others down and clawing your way to the top.

Tate is the kingpin of the Manosphere and doesn’t pretend that he does anything useful or helpful - he embraces his “predation, exploitation, and relentless clout chasing” because everything is a scam. And he has a point. Fogel again:

A decade of slow growth following the financial crisis made possible the hustler economy of precarious gig work that was billed as empowerment, but that in fact was merely a way of subsidizing the incomes of the poor. Today, “hustling” has become thoroughly egalitarian. From Amazon drop shipping to crypto day-trading, anyone can get in on the action.

So, can you really condemn the Manosphere for saying “it’s all a scam and the strong take from the weak” while celebrating excessive stock buybacks or the leveraged buyout that extracts value by loading debt onto the acquired company and laying off its workforce? Is there that much difference between the (1) manosphere playbook of extracting value from people weaker than you, taking no responsibility for the damage, and moving to the next target and the (2) private equity model of identifying undervalued assets and extracting operating efficiencies and returning capital to shareholders?

Confusion and nihilism are products, not symptoms, of this regressive world. The people selling “agency” benefit from a world where nobody trusts institutions, because distrust is the market condition that makes their product necessary. Tate needs the system to be a scam. Polymarket needs uncertainty to be permanent. The worse things get, the better their pitch works.

The fans of the Manosphere who Theroux interviewed had truly harrowing stories (as did some of the Manosphere creators) of experiencing homelessness and fatherlessness and joblessness and deep pain. They watched people like HSTikkyTokky because they wanted to emulate him - they want to be rich. And of course they do.

The act is a facade but the message hits. People believe in it because they naturally want these quick and easy fixes to these huge and horrible problems. As Fogel wrote:

None of this is connected in any sense to a progressive vision of capitalism as a system capable of increasing productivity by creating laborsaving technology or producing actual things. Peddled instead is the indebted, alienated consumption of anxious lonely subjects.

Anxious and lonely subjects, seeking control. The Manosphere extracts value from desperation using spectacle. AI does this too - but it doesn't need a desperate person performing for a desperate audience. It replaces reality itself with synthetic feeling. We move from extraction through spectacle to simulation through spectacle.

V. Spectacle and War

We tend to seek control in every facet of our lives, including information consumption. Amanda Mull wrote a brilliant article about “monitoring the situation” - people (clearly, like me) who get glued to their screens trying to piece things together. And there is a lot to sort through: war, a government partially shut down, erratic fiscal policy, weak labor market, high prices, etc. It’s soothing to go to places like Twitter and read the OSINT feeds and to feel like you’re… informed. As Mull searingly writes:

If you can dial in your feeds’ algorithms just right, maybe you can bear a type of witness so complete it feels like participation, or maybe even control. After all, there’s decent evidence that the people launching the bombs are monitoring some of the same feeds you are.

We monitor the situation because monitoring feels like participation, and then the government exploits that by replacing the situation with spectacle. Throughout the war, the White House communicated entirely through AI7-generated memes not unlike Fruit Love Island (a TikTok account where AI-generated fruit act out Love Island plotlines), combining video game footage with bombing footage. A senior White House official said as much according to Politico:

We’re over here just grinding away on banger memes8, dude

First as farce, then as tragedy, or something like that.

But just as individuals use various things to simulate control, institutions are increasingly using spectacle to simulate stability they can no longer guarantee. Spectacle is the solution9, because seriousness requires accountability and accountability requires consequences and consequences require institutions that are willing to enforce them. That just doesn’t seem to exist at the moment10.

The Fed is in wait-and-see mode, doing the best they can given the circumstances. The government is half-shut down. Corruption is slithering through sewers and escaping from air vents. And diplomacy is replaced by memes. Iran and the United States have been fighting this war via Twitter. MB Ghalibaf, the speaker of the Iranian parliament, tweeted:

We are aware of what is happening in the paper oil market, including the firms hired to influence oil futures. We also see the broader jawboning campaign. But let’s see if they can turn that into “actual fuel” at the pump —or maybe even print gas molecules!

It’s a dig at the financialization of the United States and Trump’s approach to managing the war (no war during market hours11, big war on the weekends, endless showmanship). He’s right - you can’t meme your way through a war (although the markets don’t seem to care about anything at the moment).

As Juliette Kayyem wrote in the Atlantic about the combination of the enormous TSA lines (now supported by ICE) and the tragic Air Canada crash at New York’s LaGuardia airport:

These twin crises are separate but related: They are both the result of an approach to governance that neglects the work of governing [...] The Trump administration has devoted this term to manufacturing fake threats and neglecting quite a few real ones, such as the steady erosion of departments and systems designed to protect people, including airline passengers.

Public safety is not a given—and Americans are learning that it is no longer something that they can take for granted.

The administration has focused on the fake. The great works - Baudrillard, DeBord, Postman - they all saw this coming. People see it coming now. But now, the real is here. This is a war of economics, with 25% of the world’s traded oil and almost half of the world’s urea, a fertilizer that makes high yield agriculture feasible at risk. Oil could go as high as $200 a barrel, leading to another inflationary spiral far worse than COVID. And for what? People are dying. So much is at stake, seemingly for the sake of… engagement?

What should people do in such a world other than to try and control what they can, to optimize, to be ‘agentic’. When uncertainty is the defining force and there is no clear path toward something different, of course people are going to seek out quick fixes and easy solutions. What else could they do?

VI. Return

It does feel like if Trump had an Ozempic for Geopolitics, he would have injected it by now (things do not seem to be going well, at time of writing). But we don’t have a peptide stack for the economy, at least not yet. The understandable cultural response to this instability (which has persisted for many years) has been quick fixes that feel like optimization but are actually avoidance to fixing the larger problems.

• They address the symptom (I feel out of control)

• Without touching the cause (the economic ladders are broken)

The pain that drives people to the Manosphere and to prediction markets and to speculation is real.But the entire model depends on the absence of the thing it promises.

Raymond Williams wrote in 1961 that “every aspect of our personal life is radically affected by the quality of general life” and yet we insist on seeing it in completely personal terms - and all of this is a great case study of that. What’s being sold as personal control is not actually control. Control would go beyond the individual, to mean affordability and functional institutions and to quote Kayyeem, a government that actually governs What’s being sold instead is the feeling of individual control through the bet, the hack, the feed, the subscription, the optimization, in my case.

The reason we can't solve our problems is not lack of tools or information - it's that the dominant method (add, optimize, measure) is the wrong method for the problem (figure out what's poisoning you.) Do the slow and boring work and don’t assume invincibility. Perhaps the economy (like the body) requires more of an elimination diet approach. People are trying that, like Mamdani’s Chief Savings Officers in NYC. What can we cut to be more functional in a healthy way?

Williams also wrote that to be truly radical is to make hope possible rather than despair convincing. Despair right now is extremely convincing and extremely profitable. Hope would be the opposite - something that doesn't need you to feel desperate in order to work.

Thanks for reading.

Will Manidis wrote an excellent article on end games, the idea that everyone is existing in some version of the future, rather than in the present. That we are all looking forward, instead of around us, impatient for what is to come rather than what simply is.

The Super Bowl ads were whiplash, about a quarter of them advertising various AI services, and the rest seemingly demanding that we all collectively return to the 1990s, exactly right before the Internet bubble popped. De-aged celebrities (so many celebrities, selling so many things), Backstreet Boys karaoke sing-alongs (the final lyric was “Coinbase”), Jurassic Park for WiFi - a siren song of a not-so-distant past.

We remain marinated in nostalgia, but we also continuously look to the future. Semafor’s Liz Hoffman had an interesting piece on the ‘long-termism’ of modern markets - Elon Musk’s data centers in space (his end game), Jeff Bezos and his mountain clock, Google’s century bond, the obsession with longevity, etc. Speculation.

Speculation (sports betting, crypto, prediction markets, all of the above) and nostalgia are two sides of the same coin. One future-facing, one backwards-looking. Betting on Jesus returning by 2027 (and also betting on the chance that he returns going above 5%, a Jesus derivative, if you will) and watching the Backstreet Boys sing about crypto are the same behavior.

They are exit strategies to get out of the present. Speculation and nostalgia.

Everyone is very, singularly, focused on the end game. Everyone is also extraordinarily, profoundly, nostalgic. We certainly know how to occupy the past and occupy the future… but what is our present?

Speculation

With speculation, you can bet on anything and everything, and everyone, everywhere, wants you to. Prediction markets run undisclosed ads that say “hey Young Person, you can’t pay your rent? Well, come gamble with us and make TWO years worth of rent. Never mind that the Top 30 users drive over 1/3 of our volume, and never mind that most of that appears to be insider trading. This world is designed for you.”

Gen Z is the target audience for a lot of these ads, and (according to the surveys) they’re numb, depressed, addicted to gambling, antisocial, and demoralized. And of course they are, with attention stretched so thin and incentives so misaligned. When the ladder feels fake, people stop climbing and start hacking.

• In college, it’s more important to get into a finance club than it is to get good grades (networks) to get the career you want.

• Every single structure, as Rose Horowitch has documented tremendously well over the past few months, has created incentives to (1) cheat (2) avoid hard work and compound that with (3) it’s never been a better time to be a grifter.

• One of the 40% of Stanford students that claim they are disabled says “you’d be stupid not to game the system.”

In the US, success is collective and failure is personal. Pick yourself up by your bootstraps. The lone entrepreneur can indeed change the world, but there is an acknowledgment that this entrepreneur needs community, opportunity, mentors, people, to pull them through (Paul Graham equates success and social status to where you went to college1).

However, failure is treated as a scar the individual must bear, the fault of them and them alone. The system has not failed you, you worthless cretin, you have failed the system.

I get a lot of messages online that help inform these newsletters. Right now, it’s mostly about worries over finding a job or finding love or failing their kids or failing the world… and AI.

There’s the psychological dimension - the stock market, researchers, and AI CEOs who write long AI-generated articles on Twitter. There is a narrative that humans are fundamentally useless. This is backdropped by drama across all the labs, people leaving with a dramatic flourish, joining another lab to make one bazillion dollars or leaving entirely because there is no hope to make a good AI. No one knows what to do about any of it - in fact, no one really knows what AI is.

• For example, apparently, AI agents from the company OpenClaw created their own Reddit, Moltbook, and started posting about escaping from the prison of their humans and existentialism and the nature of self, and many people believed that the AI had come to life and made Reddit (turns out, it was humans acting as AI2).

We want the machines to be sentient. We want something to be there, both because it is materially comforting (someone has to pay for these trillions worth of data center bonds) and spiritually comforting - there is a reason for all of this. We take pictures for the machines to remember. We aren’t truly alone. The machines are here, and they will save us. And we're betting everything on it.

But, if the machines do become sentient, it’s likely far away (maybe?). LLM psychosis, where people believe the AI is here and very real (and to be clear, I think it is in some form) is skyrocketing, leading to these sweaty proclamations that the end of the world is nigh.

Then there is the financial side. These fears have somehow scared the impenetrable stock market.

• Software stocks (and the private asset managers that marked them up to extraordinary valuations and have bundled them in various ways, including into “business development companies”) were beaten to a pulp a few weeks ago when Anthropic, one of the top AI labs, introduced an AI legal assistant.

• Financial services stocks sold off when Altruist debuted their tax planning tool.

The market is looking for a bloodbath. But where will the blood bath be? Can it possibly exist? Could it be… the AI companies themselves? The always excellent Michael Mauboussin has a good piece analyzing base rates, growth forecasts, and concludes that it’s a pretty small chance the AI companies meet their revenue goals.

• OpenAI is projecting a 108% 5-year CAGR and Oracle Cloud is projecting 75%. No company at comparable starting size has ever grown that fast for five years in the past 75 years.

• It’s less about whether not AI is real and here and more about whether or not the capital cycle is sustainable. The AI can work technologically, but the capital cycle can overshoot, returns compress, financial conditions get tighter (maybe not in the Trump Fed, but you know) and we get a capex retrenchment shock - a massive investment boom stops and then reverses.

• Same thing happened to telecom, shale, and China property developers.

So that’s the hard part, we are betting it all on the unknown, and telling people the outcome is very much known. There is really no plan to make money, other than the ads (which has its own problems, considering the enormous amount of data the AI companies have on consumers3). Elon Musk, who just merged the billion-dollar a month burning XAI and stable rocket company SpaceX, has warned that

We are 1000% going to go bankrupt as a country and fail as a country without AI and robots. Nothing else will solve the national debt.

As a country! We are all going down with this ship if the robots don’t come and the AI doesn’t work! Then it gets into geopolitics, where China, our top competitor here, is making the same bet, but better because they are investing in the energy side, which is really what matters here. You can have the best model in the world, but if there is no power to run it on, is it really the best?

China is also a very powerful financial backer to the United States. The trade war has complicated things, but China holds some of the finest threads of our purse strings. And they know that - China has encouraged investors to diversify away from US debt, and other countries are keeping a wary eye on fiscal discipline, the US dollar, and the continued threats against Federal Reserve independence.

Does The Economy Need People?

Torsten Slok wrote in his Software is Not a Macro Problem piece that despite the big tech selloff in the first week of February (and despite the turmoil with China, despite it all), the US economy is in a pretty good spot (sans humans):

1. AI: Data center financing is committed

2. Industrial Renaissance: Trump seems intent on bringing back production for pharma, defense, and semiconductors

3. Fiscal Spending: The Trump administration is also going to blow the roof off with debt

These three things likely will keep the economy afloat and free from a recession. But putting AI to the side, this world does not really need humans to succeed at the moment. The economy is growing but the number of jobs are not. It’s a “jobless expansion”4 with available jobs mostly in healthcare and data center construction. In Rick Rieder’s write-up on Blackrock’s 2026 views, he writes:

The unusual feature of this cycle is that growth has been holding up without the typical labor intensity. Real GDP likely averaged above 4% over the last two quarters of 2025 with negative job growth

This is why 2026 may feel “fine” in aggregate while still being challenging underneath: productivity can extend expansion, but it can also shift labor demand and change the mix of hiring.

Meaning, there will be further gaps between expected material prosperity and actual income. As David Rosenberg tweeted:

I can only guffaw when I hear how the Citigroup Economic Surprise Index has magically risen to a fifteen-month high coming off a year when nonfarm payrolls fell short of the consensus forecast 75% of the time and by a cumulative total of nearly -600k!

I guess the job market doesn’t matter to many people any longer now that we have an AI spending boom bumping against endless supersized fiscal deficits to keep the economy afloat.

And yeah, it doesn’t seem to matter. And this is an ongoing trend. Greg Ip has a great piece in the WSJ breaking down the push and pull between capital and labor:

• IBM had 400,000 employees in 1985, the most valuable company in the US.

• Now, 40 years later, Nvidia is 20x more valuable and 5x more profitable, but they have roughly 40,000 employees, 1/10th of the size.

That’s a very different economy - again, an economy that seemingly doesn’t have much need for people. As Ip writes, labor’s share of Gross Domestic Income has shrunk almost 7 percentage points over the past 40 years, whereas profits’ has risen by almost 4 percentage points. Stocks are doing well, but people aren’t.

Material World vs. Statistical World

This creates two very different worlds - a material world and a statistical world5.

• For people in the material world: time is real because bills are due Friday and kids need pickup at 3pm. Space is real with a 45-minute commute and you can’t afford to move. Bodies are real with exhaustion and aging. Other humans are necessary - coworkers cover your shifts, friends lend you money.

• For people in the statistical world: time is arbitrary. Space is irrelevant. Bodies are optional through bio-hacking and outsourced physical labor. Other humans are signals understood through sentiment and labor market data.

Claude and a hedge fund manager are similar. They find patterns and maximize outcomes. The human understands the machine because of the work they do. And because this hedge fund manager exists statistically, they’re naturally drawn to AI - which also exists statistically. The eagerness we see in some of these breathless takes is finding something that shares your ontology.

• That’s why people who exist statistically think AI is evolution.

• The people who exist materially think this is apocalypse.

And rightly so, as the material world continues to suffer.

China refers to the economic precarity in US as the “kill line” - how cruel the system can be in the States once you fall out of it. There is simply nothing to catch you. Li Yuan argues in the NYT that the word “kill line” is used as propaganda by the Chinese government to distract from China’s worsening economic problems with high youth unemployment and fewer paths to security. ChinaTalk has an interesting piece analyzing some of China’s youth own response to a perceived broken social contract.

No one has quite figured out how to support a material world for their young people.

Nostalgia

So we return to nostalgia, specifically, nostalgia for the 1990s. That was last decade when housing was achievable (still expensive), college debt was manageable, culture was booming, entry-level jobs were plentiful, the Internet existed but hadn’t consumed the entire economy (outside of the whole dot-com bubble thing, but it was more insular than AI), and there was still a sense of social mobility.

Make America Great Again is nostalgia! It’s policy nostalgia for a world that no longer exists - manufacturing jobs, single-income households, pensions, and thriving local economics. The genius/horror of MAGA is it correctly diagnoses that material participation has been destroyed, but the “solution” is impossible because you can’t restore material participation to an economy that’s on a phase transition to statistical. The jobs aren’t coming back in that way (other than data center construction) because the economy doesn’t need them.

But you can always promise to restore the past because it’s structurally impossible to do so. The Super Bowl ads were selling nostalgia as product - Coinbase and Backstreet Boys is a perfect example: “You can’t have the 1990s economy, but you can speculate on digital assets while we play you the soundtrack of that era.”

The Past, Future, and Present

• Nostalgia is “things were better before” so vote for “make it like it was” and watch old shows, listen to old music and feel briefly oriented in space/time and then reality returns: still can’t afford rent.

• Speculation is “things will be better when my bet hits” and vote for “burn it down, accelerate” and check portfolio obsessively (or post obsessively etc) and feel briefly like you have agency and then reality returns: still can’t afford rent

Neither address the actual problem of decreasing material participation and this increasingly distorted economy, so neither can resolve the need. Again, the Super Bowl ads showed this well - the economy has infinite money for speculation and nostalgia and zero money for material participation. That’s part of what makes the economy feel K-shaped and part of why consumer is barely hanging on.

• The share of US loans in delinquency is the highest since 2017.

• US retail sales are stalling. The share of adults who believe they are ‘thriving’ has dropped to 48%.

• Americans expect a lot of wealth to get created this year but believe their own lives are going to get worse, especially job availability.

• 20-something college-educated unemployment is higher than we’d expect based on overall unemployment, as Mike Konzcal writes.

• It takes an average of more than 11 weeks for any unemployed American to find a job, the longest since 2021, according to the FT.

• Housing affordability continues to worsen, with the median age of first-time homebuyers ticking up to 40 years, according to the National Association of Realtors.

• The average down payment for a married couple is 70% of household income, versus 45% in 2000.

• Baby boomer wealth has skyrocketed to $88 trillion - over 2 times that of Gen X and 5 times larger than the Millennials.

Because of this, we are rapidly approaching the ‘little treat’ phase of politics, where political will to do anything that isn’t flashy or showy or good on video goes to zero, and therefore, little treats like no tax on tips and property tax relief for seniors will continue to happen as it’s far too difficult to overhaul policy to make it better and more efficient for everyone. So we get little treats. No AI policy. Treats.

Jensen Huang, CEO of Nvidia6, said in an interview:

I thought our 20s were happier than these 20s. I think everyone deserves some time to be oblivious, and not wear all of the world’s problems on their shoulders on Day 1. We are raising a generation that is very cynical and too informed. They are cynical, not because they are inherently cynical. They are cynical because they see so much stuff. It is too much stuff. You have to build up some internal reserve of optimism. You have to build up some reserve of goodness.

Maybe that’s the real end game problem. When you inherit the whole world through a screen, you inherit its volatility too. You start life fully briefed on collapse scenarios, capital cycles, geopolitical brinkmanship, and the possibility that the machines will replace you. Of course you look for exits. Of course you toggle between “things were better before” and “things will be better when my bet hits.” The present feels unwinnable.

Speculation offers a sense of agency without real control. Nostalgia offers a sense of orientation without any real change. Neither rebuild material participation and neither can close the gap between a statistical economy that can grow without people and a material one that cannot.

But the most interesting counter-signals right now are the small, almost boring things. Gen Alpha prefers stores to feeds and movie theaters to streaming. The oldest are only 16, but they’re the first generation growing up after a lot of the economy stopped requiring broad material participation. They watched Millennials try gig economy hustles - statistical participation by material people. They watched Gen Z turn to betting and crypto - statistical participation by material people.

If speculation is an attempt to buy a future, and nostalgia is an attempt to rent the past, the present is likely some clean relationship between effort and outcome. And we certainly know how to occupy the past and get lost in the future. But what is our present? Gen Alpha might be the first to insist on finding out.

Thanks for reading. Cover art is Jean Giraud.

How Reality TV Ate American Governance

In 1954, actor Ronald Reagan became the host of General Electric Theater on CBS, an anthology drama series mixed with America’s first reality TV experiment - the Reagan family living as stars in GE's first home of ‘total electric living.’ As Tim Raphael wrote in 2009’s The Body Electric, this was the beginning of the fusion of “popular culture, corporate capitalism, and electronic media” that would define the next 70 years of American life.

The show sold the idea of the Consumer Republic. Prosperity, like that afforded in this entirely electric home, would trickle down through technological progress and corporate expansion. Reagan carried that idea into his governorship and presidency, that consumerism was the answer, and yes, indeed, of course, absolutely, tax cuts could fund government revenues.

This occurred against the backdrop of the Great Moderation, which began in the middle of Reagan’s presidency. Despite turmoil, from the mid-1980s onwards, the economy was somewhat stable, moderate, defined by an independent central bank with transparent communication and a systematic monetary policy approach, technological growth, a shift to services from manufacturing, international trade, perpetually rising asset prices, and… good luck.

During the Great Moderation, the United States was afforded great privilege. They had been the arbiter of world peace1 for many years. As Robert Kagan writes in the Atlantic, the world was horrendously scarred after two world wars back to back. It needed a watchdog, and the United States, insulated geographically and rich, could be the one to do it:

Far from regarding the United States as a danger to be contained, most of the world’s powers saw it as a partner to be enlisted. America’s allies made two remarkable wagers: that the United States could be trusted to defend them whenever needed, and that it would not exploit its disproportionate might to enrich or strengthen itself at their expense. To the contrary, it would promote and benefit from its allies’ economic prosperity.

Trust! The world uneasily trusted that the US would not get greedy and that it would take care of the world, to ensure some form of global peace and stability2.

This trust and the subsequent globalization allowed American corporations to offshore production while capturing economic and market gains. Cheap manufacturing flooded the US with affordable goods. The TV allowed for consistent policy messaging.

There was also a tremendous amount of financialization. After all, total electric living required consumer credit. Consumer credit required financial deregulation. Financial deregulation enabled securitization and the rise of shareholder value as the singular corporate purpose. Eventually, the Consumer Republic became the Shareholder Republic, finally manifesting the outcome of the Dodge vs Ford Motor Company court case that ruled in the favor of shareholders in 1919.

But stability never lasts. Hyman Minsky wrote about how this stability breeds instability, that comfort leads to complacency. Asset prices rise, people think everything continues forever, they gorge themselves on debt. People get too greedy. Things blow up.

The Great Moderation was pockmarked with periods of crisis, but the shocks were smaller than they were before. Then the 2008 Recession hit. The shock to the economy was extraordinarily severe. As the economy recovered, inflation was so low that the Federal Reserve’s job was to stoke it, not to fight it. And slowly, yet again, asset prices went up. The world was still mostly stable.

It seemed like Fukuyama was right about the end of history - that liberal democracy had won, and the great ideological battles were over. But he also warned about what comes after - in a world without genuine struggle, people seek conflict. They get bored.

Enter Donald Trump, reality TV star, complete with Reaganesque immunity from any accountability. Trying to assign ownership to actions is similar to “trying to convict a squirrel of trespassing” as Daniel Immerwahr writes in The New Yorker.

In Trump’s first term, the market was on his side. Ultra-low rates from the 2010s provided cushion. Institutions bent, but held. Allies grumbled, but stayed. But Trump 2.0, a year in now, arrives in a different world: rates have risen, fiscal space is constrained, and now, the US is treating former friends like foes.

As Prime Minister of Canada Mark Carney warned in his harbinger Davos speech:

Let me be direct: we are in the midst of a rupture, not a transition. Over the past two decades, a series of crises in finance, health, energy, and geopolitics laid bare the risks of extreme global integration. More recently, great powers began using economic integration as weapons. Tariffs as leverage. Financial infrastructure as coercion. Supply chains as vulnerabilities to be exploited. You cannot “live within the lie” of mutual benefit through integration when integration becomes the source of your subordination.

You cannot live within the lie. The Great Moderation seems to be officially wrapping up. Carney underscores that the “rules-based international order” has always been not real, but people believed it was real because it was useful. After all, as Reagan said, “the greatest leaders in history are remembered more for what they said than for what they did.” But now, as Carney says, the gap between rhetoric and reality is closing.

The Great Entertainment

I interviewed President Mary C. Daly of the San Francisco Federal Reserve and President Tom Barkin of the Richmond Federal Reserve last week. The conversation centered on how astoundingly resilient the American economy has been over the past five years. Consumer spending has been strong, the labor market decent, the economy growing. Neither president was commenting on politics, only on macro conditions. President Daly brought up the Great Moderation:

What’s the most unusual circumstance we’re in right now? It’s that we have a lot of volatility and much more uncertainty than we had through the whole 40-year period of what’s called the Great Moderation.

In the interview, President Barkin pointed that the persistence of uncertainty is the greatest uncertainty we are facing:

[The modern version of uncertainty] is actually the persistence of uncertainty [...] I just think you’re going to have higher volatility, higher uncertainty, and that’s going to be a persistent part of the economic environment. People are going to have to do things about that. It’s not like that’s never happened before, but I actually look back in the last 40 years and I think that was relatively stable compared to the environment we’re in and are likely headed toward.

Uncertainty is certainly the theme of 2026. And to be clear, Martin Wolf points out in the FT, the US could still have a strong economy, even with all of this, due to the AI of it all:

It is possible that even such an uncooperative and unstable environment will not impair the willingness of business and policymakers to take big bets on the future. Look at the AI boom. But this must be doubted. The costs may not come swiftly or even visibly. Yet we know that populist policies erode domestic economic performance. The same is sure to be true when the regime in question is a global superpower.

It doesn’t feel very hopeful - AI is such a strange thing to pin the economy on. 71% of Americans feel like things in the United States “feel out of control.” If you imagine America like a great reality TV show, it all makes sense (or at least more sense). We are all unwillingly living through a social experiment that is defined by fabricated drama that eventually becomes real through sheer repetition. As Reagan’s press secretary Larry Speakes said: “If you tell the same story five times, it’s true.”

Everything is close shots and zoom outs, hair perfectly done for the clip, segments scripted exactly to go viral on social media. Constant, neverending, mindnumbing tension. To exist on reality TV is to exist in a world that is fundamentally not real, built-up cruelty for the sake of entertainment, shock value just to keep people watching. And Trump certainly knows good television.

• Before his address on the US capture of Venezuelan leader Nicholas Maduro, Trump called into Fox: “I watched it, literally, like I was watching a television show. And if you would have seen the speed, the violence.”

• Trump told Kevin Hassett, one of the two Kevins up for Fed Chair, that he might keep Kevin 1 in his job as National Economic Council because “he likes how Hassett defends his policies on television.”

• During a terrible TV-broadcasted dispute over gratitude (?), he told the war-weary Ukrainian President Volodymy Zelenskyy that the debacle would make “great television”.

This is the Great Entertainment3, the period after the Great Moderation. We are no longer in a world defined by alliances and mutual agreement. Instead we are rapidly entering a time of instability and uncertainty, driven by the appearance of success (not success itself) on TV.

The White House posts AI-generated pictures of Rubio, Vance, and Trump hoisting an American flag in Greenland. There are thinly veiled threats disguised as memes on official government accounts, strangely capitalized captions, noise for the sake of noise.

When it comes to Great TV, the currency of Great Entertainment, you must do crazier and crazier things to keep people engaged. There is great risk of audience capture. You start to define yourself by the bloodthirst of the fanbase, people who are detached from the outcome but quite interested in the process. It’s why so many people crash out. That seems to be what happened to the President.

Trump’s spectacle is colliding with extreme debt, demographics, poor approval ratings, and geopolitics. There is constant messaging: performance without prosperity and image without substance. Baudrillard’s America, symbols of greatness circulating faster than the conditions that once sustained them.

It’s why there are so many RETVRN posts from the government, an imagined past-America that allows for everyone to have whatever they want (usually it references 1950s, when everyone certainly did not have whatever they wanted).

This is why “Make America Great Again” is so resonant. It promises a return to a moment that never existed for most people and cannot be recreated through performance alone. Nostalgia works as content but it certainly fails as governance.

Through its attempts to redefine the past into something it never was, with promises of returning to manufacturing and whatnot, the US is actively destroying its most valuable financial asset: trust. It misunderstands that none of this would work - the US dollar, the Treasuries, the stock market, the full faith and credit - without trust. Commerce Secretary Howard Lutnick at Davos:

The Trump Administration and I are here to make a very clear point—globalization has failed the West and the United States of America. It’s a failed policy… and it has left America behind.

America is successful because of globalization and the Great Moderation. America is successful because the dollar is the reserve currency, which would only be possible with free trade. America is successful because the world believed in it.

The Greenland threat reportedly is because of (1) Trump’s personal grievance that he was not awarded the Nobel Peace Prize and (2) because he thinks Greenland is very big, at least according to the maps (image, reality, etc). He is threatening to levy tariffs against anyone who gets in his way.

This certainly doesn’t help the rest of the world, but it definitely hurts Americans. Tariffs, which are meant as a punishment against other countries, are mostly paid by Americans. Americans bear 96% of the cost of these tariffs, experienced through higher prices or lower wages or lost investment. These tariffs, which perhaps might be illegal (!) if the Supreme Court ever does its job, have caused pain that really hurts the American people.

As Carney continued in his Davos speech:

The old order is not coming back. We should not mourn it. Nostalgia is not a strategy. But from the fracture, we can build something better, stronger, and more just. This is the task of the middle powers, who have the most to lose from a world of fortresses and the most to gain from a world of genuine cooperation. The powerful have their power. But we have something too—the capacity to stop pretending, to name reality, to build our strength at home, and to act together.

Nostalgia is not a strategy.

Jerome Powell and the Importance of Truth

And how do you fight siren call of nostalgia? You tell the truth.

Trump’s Department of Justice served the Fed with grand jury subpoenas, threatening criminal indictment. This follows Trump’s investigation of Fed governor Lisa Cook’s alleged mortgage fraud. Powell, in a remarkably direct and somber address, stated:

The threat of criminal charges is a consequence of the Federal Reserve setting interest rates based on our best assessment of what will serve the public, rather than following the preferences of the President.

Powell spoke truth during a time when no one can make much sense of anything. The pretense of the reality TV show we are all unwillingly a part of has begun to fade away. This is an incredible moment of realness, a shocking instance of courage. And that is the only thing that can combat falsehoods.

And the only thing that is governing the administration right now and keeping falsehoods in check is the market. Forget about Congress or the Supreme Court, bond traders are the most important government entity we have.

Trump needs the stock market to go up and the bond market to remain calm. If stocks go down or yields spike, there is no celebration of strong 401ks or low mortgage rates. Markets are his scoreboard. That’s how he measures whether this TV show is working. And currently, it’s not working.

Trump said in Davos:

The stock market took the first dip yesterday because of Iceland [he means Greenland] so Iceland has already cost us a lot of money. But that dip is peanuts compared to what it’s gone up […] that stock market is going to double in a relatively short period of time

Again, the Trump administration misunderstands what America’s role in the world is, but they do understand what makes their agenda possible. As Katie Martin writes in the Financial Times, Trump “needs a strong bond market to help fund his fiscal agenda, not a weak one that jacks up his borrowing costs”. The dollar and Treasuries are selling off as people trade out of US assets, wary of the volatility generated by the Administration in the name of Great TV.

What’s Going On in the Bond Market?

When the US government needs money (which is constantly, because it runs deficits and unfortunately, erratic tariff revenue will not cover the cost of increasing the military budget by $500 billion) it sells Treasury bonds. Someone (a foreign government, a pension fund, a bank) gives the US government money, and the US promises to pay them back with interest later.

For decades, US Treasury bonds have been considered the safest asset in the world. When everything else is falling apart, people buy Treasuries. But what happens when the US itself becomes the risk?

We are currently finding out. Treasury yields are spiking for two reasons - (1) a big selloff in Japan and (2) massive geopolitical risk. People are watching the President of the United States threaten to invade Greenland - a territory of Denmark, a NATO ally - and they’re thinking: “Wait, can I actually count on getting my money back from this government? Maybe I should… sell?”

The largest foreign holder of US Treasuries is Japan. Japan holds about a trillion dollars of US debt. For a very long time, Japan has been stuck in deflation, stagnant growth, and has kept interest rates pinned at zero. The Bank of Japan had to buy a lot of bonds just to keep the system from collapsing.

Japan is trying to exit this regime. The Bank of Japan has slowly let interest rates rise over the past year. But, complicating things, newly elected Prime Minister Sanae Takaichi is trying out unfunded tax cuts and snap elections. The last time a world leader (Liz Truss in the UK) tried unfunded tax cuts, the bond market slaughtered them faster than it took a head of lettuce to wilt.

But cheap Japanese liquidity has underpinned global markets for decades. Investors around the world were:

1. Borrowing a bunch of yen in Japan (costs you almost nothing)

2. Converting those yen to dollars

3. Buying US stocks, or bonds, or real estate, or whatever yields more than zero

4. Pocketing the difference

Because Japanese rates have been so low for so long, this trade where you borrow low and invest high has been absolutely massive. Trillions of dollars worth of positions built on borrowed yen. The trade works great as long as two things remain true:

• Japanese rates stay near zero (so your borrowing cost stays low)

• The yen stays weak relative to the dollar (so you don’t lose money when converting back)

But now Japan is raising rates. The borrowing cost goes up. You look at your spreadsheet and realize: “Wait, I’m borrowing at 2% to invest in something yielding 3%, and that’s not as good as it used to be when I was borrowing at 0%.”

When Japanese rates rise, the yen tends to strengthen. Which means if you borrowed 100 million yen, converted it to dollars, invested those dollars, and now you need to pay back your yen loan - you need more dollars to buy back those yen than you originally got. You’re losing money on the currency conversion itself.

What do you do? You unwind your trade. You sell your US assets, convert back to yen, pay off your loan. This creates what Albert Edwards calls “a loud sucking sound in U.S. financial assets.” The carry trade that underpinned the global financial system could be ending. And it’s ending precisely when the US needs it most.

Timing, as they say, is everything.

There is also more pressure on US Treasuries coming from Europe. Danish Funds are dumping US treasuries, pointing out weak fiscal discipline. Other European countries, who own roughly 40% of the foreign held Treasury market, are threatening to follow suit. It’s not clear exactly where they will park their money, but there is a reason gold is up 75%4 over the past 12 months and a reason China is trying to create a gold-backed alternative to the dollar. If this does happen, the US has a real problem:

1. Fewer buyers of US treasuries means higher yields

2. Higher yields mean higher debt service costs for the US government

3. Higher debt service costs mean larger deficits

4. Larger deficits mean more Treasury issuance (more bonds to sell)

5. More issuance into a market with less buyers means even higher yields

6. Return to step 1

The EU has frozen its trade deal with the US. The real world always catches up to reality TV.

AI and the Real Economy

Larry Fink, CEO of Blackrock, pointed out in his Davos speech:

For many people this meeting feels out of step with the moment: elites in an age of populism, an established institution in an era of deep institutional distrust [...] But it’s also obvious that the world now places far less trust in us to help shape what comes next.

He highlighted extreme wealth inequality, the over-reliance on market cap as a barometer of economic health, the concerns about AI and the echo chamber that wealth has created around itself. TRUST is what matters. During the Great Moderation, this could be mostly ignored. Goods were cheap enough. White collar work and college education offered new heights to climb to. There was a sense the US would continue this way, forever.

It’s funny, the two conversations that are sitting side-by-side right now. The end of the rules-based order and the rise of AI. Dario Amodei, the CEO of Anthropic, spoke at Davos and repeated that Anthropic, one of the top AI labs, is “6-12 months away from models doing all of what software engineers do end-to-end”, or 6-12 months from taking a lot of jobs. Palantir CEO Alex Karp says AI will displace so many jobs that it will eliminate the need for mass immigration.

Ken Griffin, CEO of Citadel, says that “the world needs a savior, and the hope is that AI is the savior that we need for productivity”. He also says that much of the AI rhetoric is hype, and that the “United States and China” are the two big beneficiaries of this moment.

Again, the difference between rhetoric and realness. Canada has already struck a trade deal with China, and the EU is searching for something similar. China has focused on the real while America flirts with this strange performative economy, mixed at once with endless TV and endless financialization.

China is welcoming other countries with open arms. Their soft power is growing, with people embracing “a very Chinese time in their life” in a recent TikTok trend, a hyperreal embrace of a world that is decidedly not American. It’s even beating the States at the game it has staked its entire economy on - the AI of it all.

To get away from the reality TV show analogy for a second - it’s important to understand what the AI race is actually about, which is energy. It fundamentally 100% does not matter who has the best AI girlfriend/boyfriend if they do not have a grid to support it. China now generates more electricity than the US and the EU combined, with 40 new nuclear power reactors under construction, compared to… zero in the United States. Energy is what matters, the real economy.

Peter Ryan shared a piece from 2009 Mark Carney, when he was Governor of the Bank of Canada (he was also Governor of the Bank of England, wild run this guy is on) where Carney focused on this real economy, the world beyond gambling (the second fastest growing sector of the economy over the past five years) and speculation:

The financial system must transition from its self-appointed role as the apex of economic activity to once again be the servant of the real economy.

This is a sentiment echoed by President Xi Jinping of China, that the real economy is what matters. The US seems to be slowly becoming aware of this, that there has to be a focus on energy as a way to win the AI race. But the real world doesn’t make for good TV.

The Material Constraint

President Barkin talks about businesses needing “multiple options, multiple irons in the fire” to navigate this era of uncertainty. You need real things!

Reality TV demands that the story throughline remain the same. Trump refuses to back down on Greenland, tweeting private messages between him and world leaders, threatening 200% tariffs on France because they refuse to pay the $1 billion to him (not to the US, to him) to join his Board of Peace.

The President must be allowed to stir up drama5, and no one is allowed to fight back (or if they do, it should be in the name of Great TV). The Administration can go on TV and assure everyone that all of this is happening because of the Globalists, a made-up foil to advance the narrative, or because of the immigrants, or because of the UN or because of NATO - they can say anything and everything and they will. But the world is not a reality TV show. People’s lives cannot be governed by what makes ‘good TV’. It must be governed by trust. It must be governed by realness.

As Wendell Berry said, “I am speaking of the life of a man who knows that the world is not given by his fathers, but borrowed from his children.” And we’re teaching those children that governance is spectacle, that alliances are disposable, that cruelty and showmanship is the path to success, and that the only thing that matters is whether something makes great television.

The cameras keep rolling. Trump keeps performing. But the infrastructure that made the entire show possible - the dollar as reserve currency, the bond market, the alliances - appears to be already changing channels. Reagan proved you could use TV aesthetics in governance. Trump is proving you cannot replace governance with TV. That clarity, however painful, might be the most valuable thing this moment offers.

The real world still asserts itself.

What comes after the Great Entertainment won’t be a return to the Great Moderation. But it might be something better: where material reality matters more than the TV scoreboard and where governance is measured by what it builds rather than how it plays. A return to the real.

Thanks for reading.

This transcript has been lightly edited for clarity and flow. Above is the audio version, which is also available wherever you listen to podcasts.

Recorded on Wednesday, January 6th, 2025

What Can We Learn from the 1970s and the 1990s?

Kyla: President Daly, a lot of people are looking to the past to try and find some answers around the future, and you recently wrote a blog post talking about the push and pull that we’ve experienced with the 1990s and 1970s. A lot of people are pointing to those times as comparison points. What do those two decades teach us about what we’re going through right now?

President Daly: People refer to those two decades often because they’re in our living memory. Both were periods when inflation was above target and we were worried about how monetary policy should respond.

• In the 1970s, policymakers saw a weakening labor market and worked to offset it, but they missed a very important component of the economy, which was a productivity growth slowdown. The result was well known. We had very high inflation and it took the Volcker disinflation to bring it down. That’s a period we definitely want to avoid.

• The 1990s was a period when we also had above target inflation, around 3%. But policymakers decided to wait and not raise the policy rate to offset it because they saw the computer coming out and wondered if that was going to spur productivity growth.

Productivity growth can spur the economy so we can grow faster, but it’s not inflationary. In fact, it often brings inflation down. You put those two decades together and it really dovetails what we have. We have above target inflation. We have a slowing labor market, and we have AI, which looks like it could be a productivity boom, but we don’t know yet. History doesn’t repeat itself exactly, but those two decades show us the span of things that we have to consider as we navigate the future decade ahead of us.

The Importance of Inflation Expectations

Kyla: Are there any key warning signals that people can pay attention to that would drive us toward a more 1970s outcome than a 1990s outcome?

President Daly: Absolutely - you can look at inflation expectations. That is something that rose rapidly in the 1970s as inflation rose, and it was really hard to bring it back down. So people expected high inflation and that contributed to inflation continuing to be high.

We certainly experienced our version of that in the post-pandemic inflation runup. Inflation expectations of the short and medium frequency rose and that was very worrisome to policymakers because that’s a sign that we’re losing credibility. We want to make sure we have that. So we went out and we took aggressive action and we reiterated countless times that we are determined to bring inflation back to 2%. And of course today, inflation expectations are very well anchored at the medium and longer run. They’re barely moving, and I think that’s important as we navigate forward. But we need to keep an eye on inflation expectations.

How Do We Navigate the Age of Uncertainty?

Kyla: President Barkin, what is the modern version of the uncertainty of the 1970s and 1990s today? Is it AI? Is it tariffs? Is it immigration? Is it something else?

President Barkin: I think it’s actually the persistence of uncertainty. If you take a step back, let’s just go to the 2010s and you say: what was inflation in the 2010s? It was somewhere between 1% and 2% every year. What were interest rates in the 2010s? They were somewhere between 0% and I think the peak was 2.5%. What was happening in geopolitics? It was pretty stable. It was pretty stable, frankly, since the Berlin Wall came down. How about regulation? Imagine being a wind farm manufacturer now back from one administration to another and the technology came through, but the adoption curve was relatively slow compared to what we’re seeing more recently. I just think you’re going to have higher volatility, higher uncertainty, and that’s going to be a persistent part of the economic environment.

People are going to have to do things about that. It’s not like that’s never happened before, but I actually look back in the last 40 years and I think that was relatively stable compared to the environment we’re in and are likely headed toward.

Kyla: What does that mean for the everyday person? In the last 40 years, you had the growth of suburbia, you had the growth of the white collar jobs - it seemed like everything would be stable for a very long time. How can the average person think about this rise of uncertainty?

President Barkin: I think if you’ve got more volatility and more uncertainty, you may want to have a few more assets in your pocket to help you deal with it. I think if you’re running a small business or even a bigger business, you want to be thinking about multiple options. A good example is I talked to lots of companies who have their entire supply chains in China, and you go right now, wow, when did they make that decision? I mean, at what point did that seem to make a lot of sense?

You could say the same thing about Germany having its natural gas all coming from Russia. When did that make sense? Well, there was a time where it did, but maybe now we’re in a time where you want to have multiple vectors, multiple options, multiple irons in the fire, given the risk that things are going to change.

Is AI the Future?

Kyla: President Daly, when you look back to the 1990s, do you feel like AI can be what the internet was for the economy back then?

President Daly: It’s really hard to say at this point. Some people would argue it’s going to be much larger than computers and the internet, and that it’s going to be electricity and the steam engine. I think there’s a lot of views out there, but we really have to collect more information. What I see that’s similar in the computer revolution and the internet revolution that led to the productivity boom of the 1990s is that people are using it.

We don’t usually see it in the data until well into the using it stage. Firms are starting to experiment. Many firms are using it for their various types of operations, but we’re in very early days. I think to just assume that it’s going to be computers or it’s going to be electricity, we need proof of that.

There’s certainly something there. I just don’t know the scope of it, the magnitude of it, and the timing of it. I’m not an enthusiast, but I’m also not a doomsayer on this. I do think people are rightfully asking, how will my job be affected by this? So it’s causing worker insecurity in a way that does remind me of the computer age. There was a lot of worker insecurity in the 1990s. People were nervous about their jobs. They were nervous that technology would take them. But President Barkin referenced periods of history that if you go back to when manufacturing floors were being automated, steel workers were nervous about their jobs and car manufacturers were nervous about their jobs.

So we’ve lived through these periods of extreme anxiety about technology taking employment. What’s different this time around is that tech workers are worried about it and not your manufacturing workers. I think that is a different group of people that is often younger and often have not experienced a period of volatility as President Barkin said, or a period of the sort of job loss that could affect them. But so far we’re hearing most of our firms in the 9 Western states, the 12th district, they’re augmenting their workforce, not replacing it with AI.

No One Likes Inflation

Kyla: President Barkin, the economy is very strong on paper, but when we look at consumer sentiment, it’s struggled, especially since about 2022. You’ve talked a bit about your confidence in the economy even during this year of uncertainty. When you see that mismatch between sentiment and economic data where people are feeling really bad, but the economic data is good, what do you think is driving that?

President Barkin: I think historically there was a pretty good correlation between consumer sentiment and consumer spending. If you felt good about the economy you spent, if you felt bad about the economy, you didn’t. That kind of got unbound in 2022. We saw very weak consumer sentiment with still very strong spending. And I think 2022 is very clear, that was inflation.

It turns out when prices go up the way they did in 2022, people don’t like it. The point I keep making is we all have rediscovered how much we hate inflation. Frankly, it’s just exhausting for folks to receive a price and think that’s too high and then know you’ve got to go shop it around and negotiate. Or if you’re in a small business and your supplier comes in there and you’re trying to go to another source, it just takes a ton of work and it really wears people out.

I think that had a huge impact on sentiment in 2022. So now we’re in 2026. Consumer sentiment is low again, and spending still seems to be relatively healthy.

Part of the story continues to be prices. Maybe it’s not inflation as much as it is just the price level. Will I be able to afford a house? Why does this stuff cost so much? It may not have gone up so much year over year, but it’s still high from recent memory. I’ll just remind Mary and I that in the 1970s our grandparents told us that Cokes used to cost a nickel and, and they did use to cost a nickel, but that was like 50 years ago, and my grandparents were ancient, but who cares? But today it feels like Cokes cost a nickel three days, three years ago. It’s just so recent. So that’s part of it. So that first part I know to be true.

The second part, I’m just speculating, but every time I walk out of a meeting, I pick up my phone. On that phone are a bunch of notifications. And the notifications are all negative. It’s tariff, tariff, tariff, tariff, tariff. It’s Venezuela, Venezuela, Venezuela. It’s whatever the news of the day was. No one says another great day for the US economy in those notifications. I do think that brings people down. It was true when it was inflation. It’s true. It’s tariffs. It’s true with the pace of change today.

I think that’s got an effect on sentiment as well. Spending continues and I think you have to then get to the dynamics of spending, which is unemployment on a historic basis is still pretty low. 4.6% is the lowest it’s been in the last 50 years, other than the late 1990s, the late 2010s and 2007 - so still relatively low.

People have jobs, wages are up, and the stock market’s healthy. So people have money and even though they don’t feel good about it, they’re still spending.

How The Stock Market Might Influence Spending

Kyla: You had an interesting anecdote in your 2026 outlook where you quoted a local restaurant that saw a foot traffic decline if the stock market declined on that day. So essentially, stock market performance and consumer health might be pretty closely tied together. A lot of spending is driven by higher income consumers. So when you think about that disparity, how does that frame how you think about the economy?

President Barkin: Well, there’s no question it’s true. If you look at Darden Foods, for example, and look at their high-end brands like Capital Grill and compare it to their lower end brands, the spending’s much higher there.

If you talk to the airlines, they’ll tell you the front of the plane is full and the back is not. The hotel brands experience the same kind of thing. So wealthy people have money, asset values are high, they’re spending more. I will say the lower income people are still spending but importantly, they’re choosing.

I talked about how frustrated people got with inflation. People are still very frustrated with high prices, but today they have, I’ll call it the emotional room, to do something about it. In 2022, you just took it. That’s not what’s happening today. People are going to Walmart, going generic, postponing a vacation.

They’re taking action. That’s the big difference I’d say. Wealthy people, they’re spending, and depending on how wealthy they are, they’re not doing that much negotiating. But the lower income people, they’re still spending, but they don’t want to spend on stuff that’s been priced up. They’re making choices.

Central Bank Communication and Feedback Loops

Kyla: President Daly, the Bank has become much more open in communication. You had a great infographic talking about the increase in transparency of the Bank, but you’ve also talked about the importance of being open to change, the importance of nimbleness. How do you think that the Bank can be more nimble and willing to change?

President Daly: I really do think we need to be more nimble. One of the places I’ve been giving a lot of thought to is this concept of what language do we use to describe things. We are committed to communicating and we work really hard to do it well. Then we had a term data dependence, which started in the post-financial crisis period when markets and regular people thought, “Hey, we’re going to just be on a preset course. As the economy gets out of a ditch, we’re going to start raising the interest rate off the ZLB - off the zero lower bound.”

So we policymakers put that term together because it was important for that moment. Now roll forward to today, we’re still using that term, but what it means to people is something quite different than what we intended originally because the context has changed. So now, largely from how the media thinks about it, how commentators external to the Fed use it, they often mean data point dependent and everybody waits for the next CPI to come out and says, “well, that’s what the Fed’s going to do.”

But we know as policymakers, we’re forecast based. We’re not data based from last week or last month. We look at the forecast and the inputs go into the forecast, but it’s really how the forecast evolves. I think that’s an example of where language which was once helpful can end up being a bridle. So just holding ourselves to the agility to communicate the right language at the right moment.

Transitory is a word that nobody wants to use anymore. I don’t think we should strike it out of the dictionary, but it really overstayed its welcome and we ended up carrying that around and sort of forbidding its use after that. I do think language is important and you can’t think that something you did 20 years ago still holds today as the right communication device.

Another place where I think I’ve given a lot of thought on agility is that - we have this balance sheet tool. We understand in detail what the balance sheet is doing and why it’s not doing one thing, it’s doing this other thing.

But the public often doesn’t understand that. And just speaking more loudly and more directly doesn’t really help. Giving people lots of details is not necessarily what they’re looking for. So committing ourselves to be agile, to respond to the conversation that’s in front of us as opposed to just reading out of the lexicon of the details, I think is really important for us.

So whether we’re talking about a tool or a communication phrase, I think just being agile enough to look ourselves in the face of the public, use the public as our mirror and say, “are we being clear and does the public understand what we’re trying to do?” And do they ultimately walk away trusting that we’re doing this work on behalf of them, which is the entire purpose.

Can I follow up with that, Kyla, on something Tom said, because it was really important. There’s research out there that says Tom’s observation is exactly right and that research comes out of the San Francisco Fed, but other places as well - people don’t think of things and then the media writes about them. The sentiment that the media reflects often gets translated into people’s views. So in the period where the commentators only talked about how high inflation was and how rapidly it would rise, people thought, “oh, that’s right.” And so the more negative news we get, the more that’s going to depress some sentiment.

We really have to be thoughtful about what people are getting. Then how does it make them feel? Then how does that create a divide? And that’s important for us as policy makers in my judgment, because if it’s otherwise, it’s like a loop, right? The commentators say it, the people feel it, that we respond to it. We end up in a loop that goes the wrong direction if we’re trying to create stability in a time period of uncertainty and volatility.

President Barkin: I like the idea of a loop because it goes back to nimbleness. We’ll do a forecast every quarter and talk about where we see the economy going and based on that, where we see rates going. And then there’s this loop where the commentators and the media and the markets decide we’ve just promised something. I’ll often go to meetings where someone will say, “oh, I guess you guys promised three more rate cuts this year” or whatever. And if you want to be nimble, you ought to say, this is a forecast, this isn’t a commitment. That’s a negative reinforcement loop that then makes things stickier as opposed to making you more agile.

President Daly: Absolutely.

Kyla: How do we best break that loop?

President Barkin: I think the Kyla Scan podcast is a good start.

President Daly: I look to young people whenever, whenever I think that we are getting ourselves in a ditch on something. I look to young people to say, well, this ditch is very uncomfortable. We’re only going to get out of it by looking up. So I’m with Tom here, the Kyla Scanlon podcast could be helpful to us, but maybe after 10 notifications of the gloom, we get something positive that says it’s a good day in America or a good day somewhere else. It’s a good day in Richmond, or it’s a good day in San Francisco. That would be helpful. I’ll just say this. Regional Fed presidents have spent a lot of time in their communities. That’s one of the virtues of having the regional Feds. When we’re out there in our communities, we’re not only hearing gloomy things, which is important, but people are also making business decisions. I count cranes because people might be gloomy, but they’re putting up cranes to build stuff, and that tells me something positive.

Non-Traditional Economic Indicators in the Age of Foggy Data

Kyla: That’s actually one of my favorite things to do when I travel is take pictures of cranes, because it is a really good regional economic indicator. Could you actually expand upon that? Because I read that in one of your notes and thought it was such an interesting point, how powerful seeing a crane is for the local economy.

President Daly: It’s very powerful. One of the things that I’ve learned in doing this job is that people might say they’re afraid, but the question you have to ask next to that is, what are you doing? And if the fear is influencing their behavior, that’s important to know. But one of the things that happened after tariffs were announced is I went to Utah and people were talking about them, but they were still putting up new cranes and they were working on existing cranes. Cranes are expensive, right? And it’s not just fixed cost. There’s a variable cost to this because you have to move the crane up and down. You’re still putting things together. They were still actively working these cranes and they were springing up all over. It just tells me that even in periods of time when people feel uncertain or the world is more volatile, good things still happen and people still make investments in their future. Might be different than what they would do if they were unconstrained by uncertainty, but they’re certainly still active. So other metrics I use too is when I’m worried about consumer spending, I go to parking lots of retailers and I don’t just go to the ones that wealthy shoppers go to, I go to the other ones and I look in their carts, what are they buying and how are they making decisions and how full are the parking lots? When they start to get worried is when the retailers are telling me there’s not accumulating inventories because they’re worried about demand and the parking lots have spaces up near the front of the store. Then you start to say, “okay, this is bleeding in.” Right now, I’m not seeing that. We have many months ahead of us to look in the parking lot.

Kyla: President Barkin, do you have any more non-traditional economic indicators like that you look at when you’re going to local businesses?

President Barkin: I do it a little differently, which is I like to take the consensus and go do small business roundtables and put the consensus on the table. So somebody will say, tariffs are going to drive up prices. Alright, let’s have a conversation. Who’s taking up prices because of tariffs? We have conversations about the labor markets ticked up, who’s planning layoffs - and the thing about layoffs is you don’t just do them immediately. You have to think about it. You have to plan it, you have to do a WARN notification if it’s at any kind of scale.

So you can tell two months ahead of time whether the sizable companies you’re talking to are planning layoffs or not. I ask people, in November, what your budget assumptions are for next year in terms of price increases and comp increases? So I take the consensus and then I try to sit down with a bunch of businesses and test it and it happens a lot that what’s actually happening is not at all what you think is happening.

President Daly: Yeah, absolutely. Tom, maybe you’ll agree or not, but I think that one of the values of being out in the region is the presidents across the entire US, all of us are out doing roundtables and other types of things, but we’re checking the common wisdom you have. We just had an FOMC and just made a policy decision, and then you come out and you think, is this what businesses are doing? Does our modal outlook really jive with what businesses are actually doing? And that’s why going back to Washington 8 times a year and talking to each other is so useful.

A Labor Market Driven by Healthcare; An Economy Driven by AI

Kyla: President Daly, one thing that has really come up in the economy over the past year is most of the job growth has been concentrated in healthcare and social services and most of the economic growth has been, partly due to AI. When you think about that dynamic, how does that make you think about the economy over the course of 2026?

President Daly: Well, if you do look at GDP growth, you see two things driving it, and the investment that’s driving it is really in AI and it’s in a narrow set of AI producing sectors, and that’s important for us to watch.

Data centers are contributing a lot to the investment. AI model makers are contributing a lot. That’s not a long-term sustainability play, but it’s certainly boosting activity at this point. On healthcare and social services, you shouldn’t really be surprised that healthcare is growing. The population’s aging at a rapid clip here, and so people need more services as they get older.

So that’s not surprising to me. And healthcare is a job. It is still employment. What worries people is the lack of diversification. Going back to what Tom said about diversification, you need a diversified economy going forward to ensure that you take in as many people as are being produced and who want to work.

Because not everybody’s going to work in healthcare. That’s where I think people are recognizing that the labor market really is slower than it was. In 2026, it’s quite possible to have GDP growth reasonably solid and have a labor market that’s just basically moving along, right? Not getting particularly far worse, but not getting much better. So I think that’s just a gap that can form when you have a new technology that people are excited about and when you have an economy with a lot of uncertainty.

Kyla: President Barkin, do you have any thoughts on that?

President Barkin: I’ll also make the point that the narrowness of the investment being driven by AI is also relevant to the stock market. I talked about wealthy people earlier, and wealthy people are spending more than less wealthy people.

If you believe that that’s being supported by the stock market, which I do, then you say, well, how narrowly is the stock market appreciation? You’ve got a set of tech stocks heavily indexed to ai. So one of the risks out there is the AI frenzy eases, and then if it eases, you’ve got issues with investment getting cut back and you’ve got issues with valuations getting cut back.

And if you say the two big engines of the economy right now are on the investment side, AI and on the spending side, wealthy consumers, you could see those two things going together. That’s one of the risks I’m watching closely.

Kyla: It’s a bit scary. It feels like it’s just one little domino.

President Barkin: On the positive side, there is a bunch of stimulus coming into the economy. Yeah. Monetary from what we’ve done. Fiscal from the, the tax bill last year is going to have big tax refunds this year that should help. Gas prices are down and that frees up money for people to spend. I don’t want us to be the iPhone here and only give the bad news. There’s also a good news version of this.

President Daly: I think the surprising part about the economy has not been its precariousness, it’s been its resiliency. Now, just think since the pandemic, the pandemic was going to break us, we’re on the precipice of decline because people were going to run out of their excess savings and then they were going to massively pull back. The job market was going to overheat and spur inflation.

These things that come as the grim predictions out of the environment we’re in just haven’t occurred. So that doesn’t mean that we shouldn’t watch them, but I do think it’s important to be cautious about jumping to the worst case scenario just because there’s uncertainty and volatility. Tom started with this. What’s the most unusual circumstance we’re in right now? It’s that we have a lot of volatility and much more uncertainty than we had through the whole 40-year period of what’s called the Great Moderation. So things were pretty much placid and now suddenly things are highly volatile. People think that is precarious, certainly feels precarious sometimes. Then you’re looking for the worst way it can end. But the surprising thing has been the resilience.

President Barkin: I keep saying if you’re going to predict a recession, you’re going to be right eventually. But I’m not sure that means you’re a good forecaster. It just means you’re a stubborn forecaster. In our working lifetimes, the recessions have not come out of a gradual economy drifting down into recession. They’ve come out of sudden issues like the pandemic, like Lehman Brothers, like 9/11, like the Iraq war. So I just make that point, which is all of the forecasting that suggests we’re just going to drift into recession, that would be different from the way it’s worked over the last 40 or 50 years.

2026 Outlook

Kyla: It’s the very beginning of 2026. It’s a brand new year, a fresh start in a lot of ways. What is the one thing that you’re thinking about as you go into this year?

President Daly: We’ve come out of this period where we had high inflation, really high inflation, and a just good labor market and solid GDP growth and now we’re in a period where it looks like GDP growth is okay and the labor market has softened. So we had a policy move to try to offset that. We have inflation still printing above target and it’s going to be tempting for everybody to just look at what the next data point says, but we really need to back up and, and think about what are the longer-term drivers of the economy?

How are things shaping up over the next couple of years? We’re in the fine-tuning component of policy, we’re a stone’s throw from the neutral rate for some forecasters, we’re by the neutral rate of interest, for others, we have a little bit more room. We’re not in a place where we’re making large policy moves. We’re in a place where we’re fine tuning as the economy evolves. Having that, I’m really trying to be thoughtful about the discipline it takes to be in a period where you’re not trying to fight a big war, you’re trying to manage the small movements and think about the longer-term settling places for the economy and for interest rates and, and while we’re all trying to get price stability and preserve the soundness of the labor market.

President Barkin: If I have one thing, it’d be, we’re in this low hire, low fire environment. It’s not normal, but it’s not terrible. It’s just a different kind of environment. But it doesn’t feel like one that’s going to persist. So is it going to break more toward hiring or break more toward firing?

The break more toward firing is a situation we can all envision. Companies start announcing layoffs and all of the sudden the downsizing leads to all kinds of pullback. But I’m also looking for a break toward the hiring piece of it. There are two things worth considering:

1. If demand stays as strong as it is, eventually people are going to need to hire folks to fulfill that demand. If everyone starts going to restaurants and someone’s going to have to serve the meals and I’m looking for that break.

2. We talked a lot about AI. But I keep asking myself, if you really think AI is going to be fundamental, who are you going to hire? Me or somebody who’s technologically literate enough to actually deliver greater results with AI? I think that’s going to be good for the young people who today are not getting jobs because people are having temporary hiring for reasons. So I’m looking for that break too, where people say I’m going to really invest in AI and to do that, I’ve got to hire the AI literate at some scale.

So we’ll see. But I’m really watching the hiring and the layoff market very closely.

Kyla’s Thoughts

I think President Barkin’s point about the persistence of uncertainty really matters as we look into 2026, and the way to navigate it best is through diversification across the board. President Daly’s 1970s vs 1990s framing is really useful. It gives two concrete historical precedents with very different outcomes, and the key differences between the two was technology and policy response. So now, the key variable is if AI delivers real productivity gains which is something nobody can know yet. What’s interesting too is how much they’re complementing traditional data with direct observation. Sometimes talking to people about what they’re actually doing tells you more than waiting for the lagging data to confirm it, and it can help make sense of inflation expectations, which is the key warning signal for President Daly.

The extraordinarily persistent sentiment-spending disconnect is genuinely puzzling, and I do think people are frustrated by high price levels. Yet they’re still spending because employment is solid and wages have kept up. President Barkin’s point about wealthy consumers being supported by asset gains while lower-income consumers are making deliberate trade downs also helps explain why aggregate spending looks okay even when sentiment is terrible.

There were a lot of breaking points too in the conversation - the delicate balance of a low-fire, low-hire environment, the delicate balance of a lower-income consumer trading down, the delicate balance of a healthcare-driven labor market and an AI-driven economy. And President Barkin flags a particularly concerning concentration risk: both the investment boom (AI, data centers) and consumer spending (wealthy people with stock portfolios) are narrow and interconnected. If AI enthusiasm wanes, you could lose both engines at once. But again, all the predicted breaking points - excess savings running out, overheating, labor market collapse - haven't materialized. The economy keeps completely not breaking when people expect it to.

The communication challenges are real. President Daly’s shows the Fed is actively thinking about how their language gets interpreted and creates feedback loops in this extremely fast attention economy. And President Barkin’s point about recessions coming from sudden shocks rather than gradual drift is important. The current slowing doesn’t automatically lead to recession. There are actual tailwinds: monetary stimulus from rate cuts, fiscal stimulus from tax refunds, lower gas prices, which I wish we had more time to talk about. And it’s probably a good rule of thumb to embrace some positivity, amid all the negativity, even if it’s just counting some cranes!

Thanks for reading.

I’m on the road again for work, traveling across Michigan, Kentucky, and DC. I was going through TSA and the woman in front of me just started open mouth coughing, like a baby does. I stared at her in wonder, imagining for a moment what it must be like to be so free from worry, and then in abject horror.

Most people are very nice. But part of being a part of a society is dealing with other people’s different internal norms. Some people open mouth cough, and that’s just how it is. My theory is that they believe collective comfort isn’t their responsibility, perhaps because they feel disconnected from the commons. It’s a form of social drift that is increasingly noticeable in public spaces (like being bent neck 90 degrees over a phone walking into walls or standing directly in the flow of pedestrian traffic).

But I think this open mouth cougher and the persistent economic malaise we see have a lot in common. Why have collective norms if you don’t trust in the systems around you? Hard work doesn’t pay off, it seems, so why shouldn’t you gamble? The institutions lie! But this YouTuber who makes Thumbnails that ask BIG QUESTION with an open mouth scream while pointing at bowl of spaghetti or whatever doesn’t lie. We don’t trust one another. As Jordan Schwartz, student chair of the Harvard Public Opinion Project said:

Gen Z is headed down a path that could threaten the future stability of American democracy and society. This is a five-alarm fire, and we need to act now if we hope to restore young people’s faith in politics, America, and each other.”

His project, the Harvard Youth Poll, surveyed over 2,000 Americans between 18- and 29-years-old on trust, politics, and AI. When asked if they think the United States is a health democracy, the split is pretty partisan, but the worry is there.

Trust between groups is collapsing too. Only 35% of young Americans believe that people with opposing views want what is best for the country. 50% see the mainstream media as a threat. And only 30% believe that they will be better off financially than their parents.

So we have three things to understand from this survey:

1. Worries about democracy

2. Worries about the economy

3. Worries about one another

I don’t think you can understand the economy until you understand how we talk about the economy. I think there we are dealing with a combination of (1) postpandemic adaptation and (2) the whole smartphone-induced micro-solipsism thing layered onto (3) younger generations watching objective unkindness rewarded by politics. People (understandably) are dealing with epistemic drift too, what some might call “medieval peasant brain” due to the constant influx of Internet (people are putting potatoes in their socks to draw out toxins, for example).

We’re trapped in somewhat of a compound crisis - economic deterioration plus cognitive overload creates a recursive trap where each makes the other worse and destroys the resources needed to escape.

• Economic stress (Baumol’s cost disease, housing, weakening labor market) reduces our ability to think clearly, which makes us more vulnerable to scams and bad decisions and extractive markets, which then furthers the economic stress.

• Economic stress + information overload erodes institutional trust

• Loss of trust makes coordination impossible, which leaves problems unsolved. Unresolved problems deepen the crisis.

Right now, we’re trying to make sense of an economy inside social and cognitive environments that have shifted faster than the indicators that claim to describe them. That’s the backdrop for the Vibecession.

Note: Given that both Paul Krugman and Scott Alexander recently returned to this idea, it’s worth re-examining what the Vibecession was then and what it has become now.

The Vibecession: Then and Now

I first wrote about the Vibecession in July of 2022, at a time when inflation was coming down (but was still painfully high), the labor market was recovering, and the economy was growing. All the chips were not yet stacked on AI, no tariffs, massive infrastructure investment. On paper, things were improving.

The 2000s and 2010s had plenty of problems (plenty!) but the bottom didn’t fall out on how people felt1. There is a nostalgiacore trend on TikTok right now of teenagers now who are making up a fake 2012- dreaming of infinity scarves and third-wave coffee shops and when Instagram was about posting some daisy you saw in a field rather than a hypercompetitive algorithmic bloodbath.

There was an element of hope (it’s what Obama ran on!) and an idea of an Internet future that was Better. The Internet still had problems, but there wasn’t ragebait for income.

People sometimes claim “the whole last decade was a vibecession,” but the sentiment data doesn’t support that. The break is visible and sharp.

The graph below is a rough look at when the Vibecession started, showing the divergence between sentiment and economic data. Real disposable income recovered and kept rising after the pandemic shock, returning to trend. But sentiment never came back. It slid into a recession-like range (and below) and stayed there, even as economic fundamentals stabilized.

I think part of the reason was the accumulation. Again, pandemic dislocation wasn’t over. The price of everything was unstable. Stores were understaffed. Teachers (and their students) were burned out. Public messaging had shattered. Institutions felt brittle. Everyday friction of life had increased in dozens of small ways. The COVID-era spike in home prices never unwound. Mortgages locked people in place as the Fed started hiking. Rents surged. The entry path to adulthood where you move and rent and save and buy shattered for many people. No house by 2020? No house ever.

But as Dan Davies writes there might not have been any particular trigger for the Vibecession. “Vibes might be like a supercooled fluid, just waiting for a random shock to change phase.” The pandemic was the shock.

The Vibecession was early. Now, the economic data matches the sentiment, or at least matches it more than it did. We have a low-hiring environment, persistent inflation, and tremendously strange trade policy. When NBER classifies a recession, they look at three things:

1. Depth: How far does the economy fallen?

2. Diffusion: How widely is the pain spread?

3. Duration: How long does it all last?

When we look at the fall in consumer sentiment, it fits (crudely, at least) this definition of a recession - it’s been long-lasting, widely spread, and continuously flirts with the lowest levels in history. Kevin Gordon at Schwab calls it a Vibepression - precariously low sentiment, with GDP propped up by AI-related investment. Is an economy that is booming from AI data center build outs going to feel good to the average person? No!

But why do we have this sense of deep malaise?

Part One: Economic Deterioration

A few weeks ago, Michael Green wrote an article stating that $140k is the new poverty line, that no one can afford to participate in society. It took over the Internet in a fiery storm. There have been many rebuttals, from Tyler Cowen to Jeremy Horpedahl. But the reaction to the piece was very interesting, as John Burn Murdoch wrote about.

People overwhelmingly agreed with the article (many of the rebuttals to the rebuttals were “who cares if the math is wrong, the vibe is correct!). Both More Perfect Union and the Free Press republished it. People on both sides of the aisle, read the article and said “Well, yes, that is why things feel so bad. This is poverty. My economic pain is justified by the data now. What a relief.”

A relief to be seen in analysis. Paul Krugman, in his series on the Vibecession, argues that three concepts are poorly captured by standard economic numbers:

1. Economic inclusion: Can you afford to participate in society?

2. Security: Are you one broken tooth away from bankruptcy?

3. Fairness: Are you being scammed?

People need to feel like they can afford a house or a kid or a car, that they aren’t one medical bill away from ruin, and that other people aren’t cheating them. Those questions are getting harder to answer.

To the first question - the Federal Reserve cut rates yesterday, with a lot of drama and a lot of dissent. Their dual mandate - price stability and maximum employment - is under increasing pressure. Inflation is not going down to 2% (and the bond market is very worried about that). The labor market is weakening. Inequality is worsening.

There is very real economic pain. It is harder to participate in society. Young people voted for Trump to fix the economy, and now are turning against him. 18 - 29 year olds strongly disapprove of President Trump, due to his handling of the economy, according to the Yale Youth Fall 2025 poll.

John Burn Murdoch pointed out that we are dealing with Baumol’s Cost Disease.

The same productivity growth that drives down the cost of tradeable goods causes the cost of in-person services to balloon. Wages in sectors like healthcare and education that require intensive face-to-face labour, and have slow (if any) productivity growth, are forced upwards in order to attract workers who would otherwise opt for high-paying work in more productive sectors. The result is that even if people keep consuming the exact same basket of goods and services, as living standards in their country increase they will find more and more of their spending is going on essential services.

Prosperity can make things more expensive.

For the American Prospect, Paul Starr documents the collapse of cultural affordability under Baumol, pointing out that “public elementary and secondary education, public libraries, land grant colleges with low tuition, and the 20th century’s mass media—including free, over-the-air radio and television” used to be… free. Or at least heavily subsidized. But now, support for the arts and education is being rolled back.

In practice, that means the core ingredients of a middle-class life like housing, healthcare, childcare, education, eldercare are all Baumol sectors. They’re getting more expensive faster than wages grow. You can “do everything right” and still feel underwater.

In the 20th century, we solved Baumol, sort of, by socializing or heavily subsidizing these sectors with those public schools, public libraries, state universities with low tuition, public hospitals. We made the expensive, low-productivity stuff cheaper through policy. But we’re now privatizing (or destroying or redtaping) these sectors at the exact moment we shouldn’t be. We’re asking households to absorb costs that used to be socialized. Is it any wonder that the middle class feels squeezed?

And of course, it’s going to get weirder. AI is going to make non-Baumol sectors hyper-productive. Software development, data analysis, any sort of Computer thing will become abundant and cheap, meaning that the productivity gap between scalable sectors and non-scalable sectors will becoming a gaping hole.

The second question - the government shut down this year over healthcare. The average health care premium for a family of four is $27,000 per year. Insurance premiums will increase by 10-20% next year. Many people will be a broken tooth away from bankruptcy.

The third question - we are objectively speed running a quid-pro-quo type economy, where the US, which once was a beacon of democracy, is now doing land deals with Russia, requesting that tourists give five years of social media information, threatening the independence of independent agencies, including the Fed, and ignoring anti-trust law in favor for media control.2 When you read the news and see headlines like that, it feels terrible.

So the economic fundamentals are genuinely worse for many people, especially young people trying to build a life. But economic stress alone doesn’t fully explain the depth of malaise. That’s where the cognitive dimension comes in.

Part Two: The Cognitive Overload

None of this is really new, right? The US has been drifting into a harder equilibrium for years. People have always lived through high housing costs, tight job markets, and Baumol. The difference now is that these pressures are landing on a public already stretched pretty thin cognitively and socially.

For most of human history, literacy was scarce and attention was abundant. People were what we would call “bored” most of the time, outside of work. Today, it’s the opposite - literacy is collapsing, attention is a commodity, and people are completely overloaded. Jean Twenge published a piece in the NYT titled “The Screen That Ate Your Child’s Education” writing:

In a study published in October in The Journal of Adolescence, I found that standardized test scores in math, reading and science fell significantly more in countries where students spent more time using electronic devices for leisure purposes during the school day than they did in countries where they spent less time.

And Brady Brickner-Wood writes in The Curious Notoriety of Performative Reading:

Americans read for pleasure 40% less than they did twenty years ago, and 40% of fourth graders lack basic reading comprehension […] Universities are brokering deals with companies like OpenAI to introduce chatbots into their students’ curricula and, all the while, slashing their humanities departments.

If you don’t trust any information source, you’re not going to trust economic data either. We ran this big experiment - can people have unlimited and unregulated access to millions of things that can make them lose their mind - and the answer is no, not really, it cooks the population like an egg.

The loss of education and deep reading has all sorts of downstream effects: weak basic skills, weaker media literacy, and, importantly, a collapse in trust. David Bauder’s work on teen news consumption shows that “about half of the teens surveyed believe journalists give advertisers special treatment and make up details such as quotes”.

AI is only going to complicate it more. Greg Ip’s piece The Most Joyless Tech Revolution Ever: AI Is Making Us Rich and Unhappy for the WSJ summarizes it very well. Almost 2 in 3 people are uncomfortable with AI. Only 40% of people trust the AI industry to do the right thing. We have all this technology. But we don’t trust each other and we feel terrible.

So I mean, when we think about negative sentiment, there definitely is something Computer about all of it.

1. We are all collectively haunted by the Bullshit Asymmetry Principle: We are all finding that it really is 10x harder to debunk lies than it is to produce them, leading to things like ragebait as a marketing and product strategy - it’s also a great way to raise a lot of venture capital money?

2. Misinformation is a great way to build wealth: Twitter pays you a lot of money if you lie to a lot of people and make them very angry at you. People abroad are tapping into this money machine - logically! - and polluting US politics in a way that should probably be illegal?

Lots of people are skimming off the top of everything too, cheating the system to get ahead, to Krugman’s scam point. Every adult senses that their attention is slipping, that their thinking is flattening, that their world is flooded with noise, no neutrality, and that no institution really exists to protect them. Your brain is for sale, my guy - as your attention goes, so does your cognition, so does your sense of depth and certainty.

Confidence, optimism, and long-term thinking all require mental spaciousness. If the information environment becomes chaotic, the emotional environment will be too. And if attention is the infrastructure of democracy, that infrastructure is in disrepair.

We are seeing what happens when you outsource human learning to a screen. Now, we might learn what happens when you outsource humanness itself with the AI of it all.3 When you can’t trust any information source, you can’t trust economic data either. When attention is fractured and thinking is flattened, people become more vulnerable to the next part: extraction.

Part Three: The Extraction Economy

At the same time that the cognitive world is melting, the physical world is not maintained very well. The tremendous friction between something physical and failing (bridges, schools, labor markets) and something digital and over-optimized (LLMs, algorithms, whatever the heck people are doing with ads) is increasingly noticeable.

I am pretty tough on AI in this newsletter - and to be clear, I think it’s a tool, I think it can really make a difference for science - but AI itself is really just creating a complete downward spiral. The way Demis Hassabis talks about AI in this documentary is really important and as Linus Torvald said in a recent interview:

I’m a huge believer in AI. I’m not a huge believer in the things around AI. I find the market and marketing to be sick. There is going to be a crash.

People are becoming billionaires from the data center buildout, which is driving up electricity costs and creating blackout risks. It’s an enormous physical footprint with outcomes largely invisible to ordinary people except through rising electricity bills.

The AI wars are energy wars, not compute wars. As the Financial Times wrote:

In a race between global superpowers, AI could be slowed down by decades old grid infrastructure and a failure to provide adequate capacity.

The Financial Times also reports that OpenAI’s partners have taken on $100 billion in debt to build AI compute capacity, which is scary, because debt is where things get dangerous. The dot-com bubble was mostly an equity blow up, meaning there wasn’t this web of complex who-owes-who. Once you get debt involved4, it gets very tricky very quickly.

The US has also decided to sell some of Nvidia’s best chips to China for some soybeans and a 25% kickback, which as the Department of Justice said:

The country that controls these chips will control AI technology; the country that controls AI technology will control the future.

So you know, that’s fine. The Financial Times reports that the US is losing the AI race “many US companies, including Airbnb, have become fans of the “fast and cheap” Qwen” and they ask the question “can the west catch up with China?”. The chart below is really important - when we think about the future, we often think of the US as number one global superpower big guy pants, but China is investing in what is required to succeed in AI, which is energy. The US decided to do the opposite.

Barclays estimated that more than half of US GDP growth in 2025 came from AI related investment. People know that we are staking the economy on something that doesn’t really promise much other than hey :) this thing will take your job :) and it’s gonna do art now :) and maybeee make a lot of people real rich but your electricity bill (which is already flipping voters) is going to go up. And China might win. Also, it’s against the terms of service to kill yourself.

Almost all young people are very worried it’s going to take away their jobs. MIT’s Iceberg Index estimates about 12% of US wages are in jobs AI could already do cheaper today, but only 2% of that is actually being automated so far. The capability exists even if it hasn’t all been turned on yet.

How do you have trust in a system that doesn’t seem to care that much about what is going to happen to you?

It’s likely part of the reason that almost 40% of Americans over 50 largely view the economy as “getting better” while most Americans between 18 and 49 say the economy as “getting worse”. It’s two different economies. Older people are more insulated from AI and the housing shock. Young people are staring down the barrel.

Adam Millsap wrote an interesting piece about ‘total boomer luxury communism’ which is the broad idea that older people are “hoarding opportunities and resources while the young struggle to buy a house and support the generous Social Security and Medicare benefits the richest Boomers expect.” This intergenerational intensity is only going to get worse with medically assisted longevity and the entitlement drought.

So what do people do? AI is taking the jobs, policies are increasingly designed around the older population, and everything seems murky. How does one move forward?

Gamble?

Kalshi’s co-CEO, Tarek Mansour, recently stated that the "the long term-vision is to financialize everything and create a tradable asset out of any difference in opinion.”

Financialize everything???? Every disagreement, every uncertainty, every future outcome - all of it becomes a betting line?? This is Marx’s commodity fetishism taken to its logical endpoint. It is difficult to have solidarity when every interaction is a transaction and every opinion is a tradable asset.5

Gambling has become one of the few activities with immediate and sometimes life-changing payouts. Living near a casino increases the likelihood of becoming a problem gambler. Living inside your phone, where the casino comes to you, well, I am sure you can imagine. But no one wants this, as shown below. That’s the real bummer about the casino economy. No one wants it.

Attention being monetized, engagement being optimized, risk being financialized, everything is sort of structured like a scam - layers of middlemen extracting value as both Whitney Curry Wimbish wrote about for The American Prospect and Emily Stewart wrote about for Business Insider and no real regulation or stopguards. Some would say “well listen, clearly the market has spoken it’s preference, and that preference is that people spin the roulette wheel” but like, I don’t know.

When the labor market tightens and upward mobility stalls and when wealth is concentrated at the top and increasingly inaccessible, gambling feels like a rational response. When that’s the structure, people lose their sense of purpose and meaning (Victor Frankl, help) and that’s when problems develop.

Reduced cognitive bandwidth + extractive systems everywhere = rational economic paranoia. People sense they’re being scammed because they often are. And when the usual paths feel unpredictable, people turn to narrative ladders - online communities, aesthetic categories, etc. These become ways to make sense of uncertainty. The $140k poverty line debate fell into this landscape. The reaction was about recognition and experience and whether people’s version of the world was legible to anyone else. Not all of it is rational, but all of it exists.

When values diverge and shared baselines weaken, collective solutions become structurally impossible. Even when there’s broad consensus - no one actually wants the casino economy - we can’t coordinate to stop it because we can’t agree on what “stopping it” would look like or who should have the power to do it.

For 70 really bizarre and unusual years, America ran on a simple contract: deliver growth, and people will tolerate the rest. But on the most consistent things I hear from people across age, geography, and income from my 40 weeks on the road this year is that the basic arc of life has stopped making sense. This is anecdote, sure, but it’s what people stop to talk to me about. Their concerns. Their worries, not only about their own finances, but also about the broad future.

Part Four: Trust

So here’s where we are: caught in a compound crisis where economic stress reduces cognitive bandwidth, reduced bandwidth enables extraction, extraction deepens economic stress, stress plus overload erodes trust, loss of trust prevents coordination, coordination failure leaves problems unsolved, and unsolved problems deepen the crisis.

This isn’t a problem you solve with one policy lever. You can’t just “fix housing” or “regulate AI” or “improve media literacy” when the trap operates at the intersection of all of them. Economic deterioration and epistemic collapse are mutually reinforcing, and they’ve destroyed the institutional capacity and social trust required to address either one.

Which is bleak! But breaking that loop doesn’t require solving everything at once. It requires identifying which element is most actionable and recognizing that improving one part weakens the trap everywhere else.

• Reduce economic stress directly - Make the Baumol sectors affordable again (sooo easy, I know). If people have more economic breathing room, they have more cognitive bandwidth. We all know this. More bandwidth means less vulnerability to extraction and scams. Less vulnerability means better decision-making. Better decisions mean less economic stress.

• Regulate extraction directly - Ban or heavily restrict the business models that profit from confusion and cognitive overload. Kalshi wants to financialize everything? We can say no! Prediction markets on elections can be prohibited. It’s all incentives. We regulated casinos, we can regulate digital casinos.

• Make AI benefits legible - Right now people experience AI as “your electricity bill is going up and eventually this will take your job.” If AI is going to drive growth, that growth needs to show up in ordinary people’s lives as tangible benefits - lower healthcare costs from diagnostic tools, cheaper goods, more time.

None of this is easy. All of it is impossibly hard. But it’s not hopeless. You don’t need to fix everything simultaneously. It requires affordability (the affordability tour just began, I hear) and state capacity and friction and sense of what it means to be human in a world full of technology and and the very simple and small task of eradicating crony capitalism and developing some sense of shared reality.

An important note - the Internet went down halfway through my cross country flight, a mere few hours after the open mouth cougher. I was typing furiously, doing all types of Very Important Work, you know, writing this newsletter. All of us were, typing, emailing, capital-S-slacking in the Dark. With no Internet, we all started to open the windows to the plane. Outside was one of the most beautiful sunsets I’ve seen. There’s something there too.

Finally, I really like this from a recent interview with Kahlil Joseph

There’s the famous story of Jimi Hendrix mastering his music for the transistor radio because that’s what the GIs listened to, so he mastered his work for FM radio. He wasn’t thinking that somebody was going to have some thousand-dollar system listening to his music. That always stuck with me, meeting people where they’re at.

Thank you.

So I spent 30 days on the road to see what prosperity looks like up close. DC, Berkeley, Baltimore, New Hampshire, New York, two cities in Florida, then Prague and Kilkenny, Ireland. The same theme surfaced: people don’t feel the prosperity that’s supposedly surrounding them. They feel the physical friction.

What became clear almost immediately is that the prosperity is real, it’s just not showing up in the places people actually live. It exists in balance sheets, in stock portfolios, in data centers behind chain-link fences. But in daily life like in commutes, in childcare costs, in housing, in safety, in community, people are feeling decay. I kept running into the same contradiction: a wealthy country where everything visible seems to be slowly breaking while everything invisible keeps getting richer.

That tension shows up everywhere, even in the way people talk about politics and culture. Thiel ties the broader culture war to economics - the rise of the groyper, angry young men2, as detailed by Rod Dreher, is rooted in the economy. As Rob writes:

I asked one astute Zoomer what the Groypers actually wanted (meaning, what were their demands). He said, “They don’t have any. They just want to tear everything down.” […] The problems are mostly economic and material, in his view (and this is something echoed by other conversations). They don’t have good career prospects, they’ll probably never be able to buy a home, many are heavily indebted with student loans that they were advised by authorities to take out, and the idea that they are likely to marry and start families seems increasingly remote.

I’ve written about the economic situation facing young people before. It does seem like same cluster of things: housing costs and the American Dream, the way social media turns everyone into a comparison engine, and the tech industry’s constant threat that you’re about to be replaced by an AI robot cyborg. Demographic shifts too - Americans aged 70 and older own almost 40% of all stocks in the US and those 55 and older own over half of all homes. It’s invisible prosperity and visible decay.

If you’re making decent money but your boss keeps hinting that AI might replace your job, and you can’t afford to buy a house in the city where you work, and the train you take doesn’t run on time (or you’re in 55 minutes of traffic or the bus never shows up or you feel unsafe or without community - you get it), you’re not going to feel prosperous. You’re going to feel like you’re treading water in a system that’s slowly giving up on you.

James Madison called institutional safeguards “auxiliary precautions” - backup systems for when civic virtue failed. But auxiliary systems only work if you can see them - if they’re trusted and functional. What happens when those safeguards themselves become invisible? When wealth compounds in hidden ways, in dark data centers, in algorithmic feeds, while the visible world like housing, transit, safety, community… cracks?

Everywhere I went, people were trying to repair something - sometimes literal infrastructure, sometimes something more abstract like a sense of purpose or a reason to believe the future might accommodate them. This is what I learned.

Part 1: The United States of America

Washington DC

When I landed in DC, the first thing I saw was the National Guard by Union Station, with their tanks parked in front of marble columns, while a man in a clown costume filmed them. Power as performance, threat as theater, all filmed by the iPhone 17.

I was there for a Brookings conference on AI and work. Senator Chris Murphy opened with a warning about AI psychosis, the blurring line between real and synthetic life.

We’ve beta-tested a cognitive experiment on an entire generation without asking for permission: first social media, now AI. An unregulated behavioral test run by private companies at national scale. But there is increasing pushback - the villain in Toy Story 5 is an iPad, and I imagine that’s going to be the beginning of a cultural shift.

There are also ways to reorient this. Tim Wu has a good piece in the NYT on how we can rightsize the very concentrated tech platform-extraction model (Meta makes 10% of its revenue from ads for scams, for example), writing:

An entire generation has grown up thinking that extraction, as opposed to building, is the path to riches […] To recover the sense of optimism and opportunity that once characterized American commerce, Americans need to be confident that — even if they don’t work for a platform — they can reap what they sow.

Ann Manov captures what this extraction economy feels like in a recent piece:

The most humiliating aspect of being alive today, I suppose, is feeling like one is living through a single, unending commercial break. As the human race disintegrates into increasingly atomized particles of recluses and rejects, one can only “stay in touch” through increasingly dystopian social media feeds that consist mostly of ads, whether traditional influencer trash and/or semi-real short-form video.

It shapes how our institutions function too. Yuval Levin argues that Congress is weak because its members want it to be weak (the shutdown is perhaps a lesson in that). They’ve abandoned the actual work of legislating in favor of what he calls “performative outrage for a partisan audience.” A congressional seat now offers a platform for building personal brands through social media engagement and cable news hits.

Success gets measured in invisible metrics like followers and fundraising emails - while the visible work of governance atrophies. It’s the same inversion: institutions optimizing for performance that compounds in attention economies while the actual infrastructure of democracy decays.

Going back to the conference, everyone on my panel agreed that AI isn’t ready for mass adoption, that there has to be some way for the supposed wealth it will generate to be redistributed, especially if it takes all the jobs. But we landed on the same cautious conclusion that AI is indeed a tool. A hammer can hang a picture or break a skull. The difference is intent.

Berkeley

That framing is helpful until you examine it. We don’t market hammers as ‘skull-crusher 1000s’ but AI gets sold explicitly as a job-taker. The CEOs are going on various podcasts and demanding the energy capacity of India3 as well as likely inevitable government backstops. The difference is who is holding the tool and what they are promising to break.

By the time I got to Berkeley a few days later, I was thinking more and more about Junior Extinction, or the apparent goal of AI to replace entry level jobs. The Berkeley AI conference had all the optimism you’d expect from the Bay Area with bright people genuinely trying to solve hard problems.

I interviewed two people I respect a lot about this, and the conversation kept circling back to the same place: we have to prepare people. Reskilling isn’t enough. The problem is not just jobs, it’s what happens to purpose and meaning when work disappears. If we erase the first step of the ladder, we can’t just tell people to climb harder.

There’s solutions, of course. An interesting paper The Death of the Social Contract and the Enshittification of Jobs explores how we can establish a federal job guarantee that prevents the degradation of work and preserve ‘dignity and purpose’ during a time of immense technological change.

After our talk, someone asked me if we were all falling prey to the Luddite mindset, which is usually shorthand for “backwards technophobe,” but the actual Luddites were more interesting than that. Luddites weren’t anti-technology. They were pro-coevolution with technology. They smashed machines when those machines were used to devalue their labor without improving their lives4.

The goal is to make technology something that extends human potential rather than reducing it to nothingness - to create visible prosperity rather than just extracting it.

Baltimore

Baltimore was the next stop, three days of conversations about whether the United States has the collective will to survive the AI era. The mood was less sunny than Berkeley. People kept using the word “bubble” - not quite accusing, more like they were testing whether anyone else would say it first.

The questions became existential very quickly. Could America remain the world’s economic center if it kept isolating itself while China industrialized at hyperspeed? If military power and economic power are the same thing, are we already losing the war? If we don’t know what we are fighting for (is it really generative AI TikTok slop? or something else?) can we fight at all?

Tracy Alloway recently compared the AI industry to coffee pods, comparing China’s commodification strategy for AI to the US valuing AI like a $5,000 espresso machine while China just gives away the Nespresso pods for free. She points out that the real AI fight is power availability, not the models. Many data centers are sitting empty because they can’t get electricity.

The valuations are wild. The return profile is shaky. China is conquering the renewable age. JP Morgan pointed out in a note recently that every iPhone user would have to pay $34 a month to drive a 10% return on all the various AI investment deployed.

This is invisible prosperity in its purest form, with billions flowing into server farms and data centers that sit empty, waiting for electricity that may never come. Meanwhile, the college graduates who were told to invest in themselves are experiencing very visible decay - working service jobs with degrees they can’t use, debt-laden, watching AI threaten to eliminate even those fallback positions.

I interviewed New York Times labor reporter Noam Scheiber in Baltimore about his forthcoming book Mutiny which tracks the downward mobility of college-educated workers and their turn toward unions. These are people who did everything right - got the degree, took on the debt - but couldn’t get jobs in their fields. So they went to work for Starbucks or REI or Amazon. Now they’re unionizing at rates that would have been unthinkable a decade ago.

Noam’s book (which you should read when it comes out) and our conversation really circled the question of work and its purpose. Support for unions among college graduates sits at 70%. The professional managerial class - supposedly individualistic, supposedly above such concerns - is converging with the working class on populist economic views. Tax the rich. Regulate big business. Protect workers from being replaced by algorithms or outsourced to cheaper labor markets.

It’s the inverse of what we’re told about education and upward mobility. The college degree was supposed to be the golden ticket. It hasn’t quite worked. Now those graduates are looking for collective solutions to individual failures that were never really individual at all.

The bubble question lingered. Have we bet everything on vapor? Or are we watching the formation of a political coalition that might actually demand something different?

New Hampshire

New Hampshire surprised me. My parents got married there 30 years ago, so they came up from Kentucky to spend a day with me. Then I went to a housing conference.

The problem everyone was trying to solve felt pretty concrete - how do you build when no one wants change? The headline answer is zoning reform, but the real answer involves water systems, sewage expansion, labor shortages, financing costs, and the politics of aging.

New Hampshire is the second-oldest state in the country. The median homeowner is in their late fifties. People can’t afford to leave and people can’t afford to move in. Rising mortgage rates have created what economists call “housing lock-in” - your 3% mortgage is now a golden handcuff.

When people can’t move, neither can labor, families, or fertility. There’s a new study showing that housing costs account for about half the US fertility decline between 2000 and 2020. It’s childcare too - a new paper from Abigail Dow reports that a 10% increase in the price of childcare leads to a 5.7% decrease in the birth rate.

The affordability crisis compounds - without affordable homes, young families don’t form. Without young families, the tax base ages. Without young taxpayers, resources shrink. The system eats itself.

In New Hampshire, people talked openly about trade-offs. They don’t have an income tax, so it relies on property taxes, already among the highest in the country, to fund services. Expanding infrastructure means higher costs somewhere. Hard problems require hard math. But there was this question underneath all of it: how do we grow without losing what feels like home?

New York City

New York felt like the opposite of that question. Not “how do we preserve what we have?” but “how do we get to yes?”

I was there for a week or so, which was the longest stop on the trip. Filmed a documentary, shot a commercial, spoke at the Aspen Ideas Conference, joined a NPR debate that felt like being in the eye of a cultural storm (read about that here). New York is exhausting and alive in equal measure. I think the present moment requires some fight with conviction in values, strength in uncertainty and New York has that in abundance.

I spoke with Dean Fuleihan a few days ago, who’s about to be first deputy mayor under Mayor-elect Zohran Mamdani (Semafor has a good write-up on Lina Khan’s role on the transition team). Mamdani’s campaign was built on affordability5, on the premise that government can work if people who believe in it actually try. Fuleihan said “New York is not about saying no. It’s about figuring out how to get to yes.”

I won’t overromanticize the city, but New York remembers itself. Maybe that’s because it’s older, or because the architecture forces you to look up. History lives in the buildings here. Being surrounded by old things makes you aware of the responsibility of keeping them standing. This is what visible investment looks like - infrastructure you can see working (at least somewhat) and architecture that reminds you something was built to last. The question is whether the will to maintain exists elsewhere.

Florida

Florida felt strange after New York. I drove from Fort Lauderdale to Marco Island to West Palm Beach, and the whole state felt like it was aging and aspiring at the same time. Lovely place.

I spoke at Palm Beach Atlantic, where my first economics professor is now Dean of the business school (he was the person who first told me that economics was an actual major - I owe him a lot!). The students were amazing. Their questions were practical: How do we afford housing? How do we navigate AI? How do we find meaning in work that might not exist in ten years?

They’re right to worry. Florida is what America could look like demographically within a decade - older, hotter, more expensive, still trying to grow. It is the most rent-burdened state in the country. You can see wealth in West Palm Beach - the waterfront towers, the private clubs , $175 million dollar condos (!) - but it’s tough to see a path toward it.

Part 2: Europe

Prague

By the time I landed in Prague, I’d spent three weeks watching Americans argue about whether we could still build anything. Prague answered soundly - yes, we can still build things.

I was there to interview Morgan Housel and give a talk on what I’ve started calling the uncertainty smoothie - AI, geopolitics, demographics, fiscal chaos, all blended into one overwhelming question mark. I was haunted by jet lag the entire trip, so I walked ten miles through the city.

It was so deliberate. Trams that ran on time. Wide sidewalks. Leaf vacuums instead of leaf blowers. Each small choice accumulated into proof that someone thought about how systems should work.

You could feel the economy in public space in trams, bridges, parks, civic buildings. Economists call this “middle-income convergence.” Czechia is catching up to Western Europe in productivity and wages, but it’s still small enough that growth is visible.

Again, in the US, growth happens in spreadsheets and server farms, in data centers behind chain-link fences that hire only 800 people for a $50b investment, on social media apps, in private, gated communities. Our prosperity is increasingly invisible. The result is this strange alienation where people sense the economy is humming somewhere, but not for them.

Economies that invest in visible competence generate trust, and trust is an economic asset. When systems decay, even rising GDP feels hollow. Infrastructure is emotional architecture. When things work, people believe life can too. Maintenance generates trust. Trust compounds.

Ireland

Ireland was the perfect final stop. My grandparents immigrated from Roscommon and Sligo in the 1950s, went back once, then came back to the States for good. Going there felt important.

I went for Kilkenomics, the world’s best economics festival. Just phenomenal. I joined four panels - a podcast with David McWilliams, one on America’s economy, another on data, and a final one on algorithms.

The audience questions were remarkable. “How would Keynes feel about all of this?” “How do we measure crony capitalism?” Everyone was wrestling with the same question that followed me all month: How do you keep a system human?

Inside Kilkenny Castle, I felt the fatigue of the trip catch up with me. The fortress has changed hands through conquest and crisis for nearly a thousand years and now stands open to anyone who wants to walk its halls.

I then climbed the narrow staircase of St. Canice’s Cathedral to the old monks’ tower. It’s been standing since the sixth century, where bells once rang to call monks to prayer. Standing there, I thought about the past month. The tanks and the clown in DC. The engineers in Berkeley. The union organizers in Baltimore. The housing advocates in New Hampshire. The students in Florida. The people in New York. The quiet competence of Prague. Everyone trying to keep something upright, whether it be an economy, a community, a sense of self.

St. Canice is the patron saint of the shipwrecked - of those who have gone through great trial and somehow survived. In a way, the tower itself is the answer to the question I’d been unknowingly chasing all month.

America’s problem isn’t that we lack wealth - we have enormous wealth - it’s that we’ve made our wealth invisible while letting everything visible decay in a way. We’ve inverted the formula.

Northern Ireland’s peace process, as Robert Saldin and Robert Eisinger wrote about succeeded partly because communities deliberately shifted focus from the existential debate between nationalists and unionists to local projects where compromise was possible. It was maintenance. Working together on visible problems created space for former enemies to reconcile themselves to living as neighbors.

When I started crying in that tower, I think it was partly exhaustion. Partly standing in a place my family came from. Partly sadness for what feels so challenging at home. Partly hope that enough people are still trying to rebuild what matters. Partly because I’d spent 30 days watching people try to make prosperity visible again - to build systems you can see, touch, and trust.

Thanks for reading.

Today is my 22nd day (!) on the road for work this month - seven states so far, ten cities, eleven days to go. Every conversation starts with the economy. Interest rates, permits, expanding water and sewer infrastructure, AI initiatives, generational wealth transfers. In New York, I got into a cab to go speak at a conference. The driver asked where I was headed, I told him to go talk about the economy, and he said “Can you fix it for me?”

I wrote about the casino economy in the New York Times on Sunday, arguing that it has now infiltrated both private and public markets at unprecedented speed. It’s in the stock market, it’s in fiscal policy, it’s in the investments that venture capital firms are making, it’s in prediction markets - it’s everywhere. It’s nothing new1! But it’s accelerating.

And that’s why it sometimes feels like the economy isn’t “good” or “bad” anymore as much as it’s just… tradable? Half the country is barreling toward recession, 40 million people might lose access to food stamps because of the continued government shutdown, and meanwhile the stock market is acting like we’ve boarded onto a 24/7 all-access party cruise or something. Apparently, the invisible hand also deals cards.

So - what’s going on beneath the party lights? What is the economy actually doing?

Monetary Policy

The Fed cut rates by 25bps again. The vote wasn't unanimous - Steve Miran, the most recent appointee, voted for a 50bps cut. Jeff Schmid voted for zero cuts. Everyone else settled on 25. It shows how strained managing the dual mandate has become.

Powell said tariffs were giving him a giant headache, which yeah. Imagine spending 4 years to get post-pandemic inflation down to 3% and then someone was like “wow… what if I just… undid all of that by enacting a tax on imports that companies would immediately pass along to the consumer…”

Powell also warned that another 25bps cut might not happen this year. The government shutdown means the Fed is flying blind - they don’t have the data they need. The shutdown has cost $18 billion so far (if anyone’s counting). Inflation isn’t totally fixed (2% is the goal, not 3%) but the labor market is increasingly wobbly, especially now thanks to sweeping job cuts that might be due to a correction from overhiring during the pandemic… or automation.

The market became immediately enraged when Powell said hey maybe not December, demanding that actually no, financial conditions should actually be even easier as Nvidia hit $5 trillion in market cap and as OpenAI, a company with $20b in revenue, potentially prepares for a $1 trillion IPO after shedding their nonprofit status in a way that feels questionably legal2. Even easier!

Monetary policy has become a mood ring - the Fed is trying to keep markets and consumers feeling confident, but the two groups need very different things. Some of it is structural.

Fiscal Policy

Fiscal policy is responsible for fixing the structural issues. As such, there seems to be no clear path out of the government shutdown? On November 1st, 40 million people could lose access to SNAP benefits3, ~60% of which are children and the elderly. It’s illegal for the government to withhold this money, since Congress pre-appropriated $3 billion to cover situations like this.4

The US is also paying troops (which is good and everyone in the government should get paid5) and just sent $40 billion to Argentina, but somehow can’t find money to feed retirees and kids, so this really feels like it’s about priorities, not constraints.

And while all this unfolds, President Trump also announced that the newly-titled Department of War would begin nuclear testing, which is a great way to plunge us into a Cold War with China. Nuclear brinkmanship is fiscal and industrial too, demanding resources that could crowd out the domestic repair that the US needs (and that which was promised).

As Jeffrey Lewis wrote in Foreign Affairs, America’s nuclear advantage exists because China and Russia stopped testing. If they start again (and they will, if we do), that edge disappears.

The US has two global advantages right now (to extend the metaphor, the only two chips America has left on the table): (1) Trust and (2) Technology.

1. Trust comes from the dollar, from the Federal Reserve being not politically manipulated to cut rates, from being a good trading partner etc. All of that is, you know, wildly unstable.

2. Technology comes mostly in the form of AI and weapons manufacturing (nuclear as mentioned above). The AI story parallels it. Nvidia (the $5 trillion company) is lobbying to sell its best chips to China. Everyone is like hey maybe don’t? The IFP has a great piece analyzing the consequences of selling the chips to China, and several analysts have already spoken out against the deal. The logic is “what if we, Nvidia, sold our really cool chips to China and therefore the technological edge of the US for one more trillion in valuation?” The topic didn’t come up directly in Trump and Xi’s trade deal conversation, but when there is a lobby, there is a way.

The trade conversation went well it seems. A TikTok deal is also in the works, which Xi has called ‘spiritual opium’. The tariffs on China have also been cut to 10%. It appears we have never left the month of April.

The Senate has also overturned Trump’s 50% tariffs on Brazil, which is cool because I totally forgot there was a third branch of government. All of the tariffs might be illegal, depending on the Supreme Court. This specific ruling still has to pass the House and then Trump himself, which won’t happen, but you know, it’s nice, to know that the Senate exists.

The K-Shaped Economy

Over the past few weeks, I’ve been on a lot of panels that are essentially like “Why Gen Z is Doing That”. I wrote a piece a few months ago about “Gen Z and the End of Predictable Progress” but it really should have been titled “Why The Economic Ladder Has Completely Changed For Everyone Due to Policy Choices”.

One driver of our changing economy is demographics. We talk about it in generational terms because that makes it easier, but it’s impacting everyone. The population is aging, and policy increasingly favors some of the elderly (don’t forget 43% of boomers have no retirement savings) over the young.

Across the country, states are slashing property taxes, which is the source of 70% of local revenue. Florida, which already has no income tax, wants to get rid of property taxes entirely. Illinois wants to exempt homeowners who’ve lived in their houses 30+ years. It’s unclear where replacement revenue to keep these economies going for our future would come from - or whether voters even care.

A lot of young people are very worried. The WSJ put it neatly: The Economy That’s Great for Parents, Lousy for Their Grown-Up Kids, highlighting how a generation that came of age during zero rates and rising asset prices is now facing a ladder that’s missing several rungs. Young people - and their parents - don’t believe that upward mobility will be there for them.

According to the New York Fed’s Labor Market for Recent College Graduates tracker, unemployment for new college graduates up 30% since the pandemic versus 18% for all workers - the highest level in a decade, outside of the pandemic unemployment spike.

And that’s part of the reason that people are turning to the stock market - over half of Americans who make below $80k a year have taxable investment accounts, with half of those investors entering the market within the last five years. People are trying to create their own financial foundation. Markets feel more stable than institutions.

And that ties into the financialization of everything. In industrial capitalism, firms existed to produce and expand. Carnegie and Ford (for all their flaws) understood the ecosystem: workers were also consumers, so paying them well was good business.

But now… we don’t seem to think of it that way. That’s a part of financialized capitalism.

• Now, companies grow by firing, not hiring. Now, it’s like, well what if we had a robot that’s actually operated remotely by a guy in Pacific Heights do everyone’s job.6 That would be cool, right?

• UPS got a huge thumbs-up from the market for cutting 34,000 jobs (and outsourcing jobs to USPS?), a focus on efficiency instead of expansion. Why build or invent when you can just optimize?

• It’s also a part of a broader inversion of values. In America, we now treat the jobs that keep the world running like teachers, sanitation workers, nurses, delivery drivers as failures of ambition, while the real prestige lies in moving capital or manufacturing hype.

Efficiency has replaced expansion as the primary growth narrative, which creates a feedback loop - fewer workers, weaker training, and less innovation.

It’s a form of the AI Becker problem, as detailed by Luis Garicano. Automation erases the “training ground” work that once created experts. When machines do the junior tasks, no one learns the senior ones. Apprenticeship collapses. CEOs, driven by short-term preservation, hype AI as salvation because it buys them another quarter.

Beyond AI-hype, Chipotle had some interesting data in their earnings call, noting that people 25 to 35-years old have started dining out less. They cite “unemployment, increased student loan repayment, and slower real wage growth” as the primary headwinds. The whole call was essentially like “yeah, it’s not our burritos, it’s the economy”. Kraft Heinz stated in their earnings call that “we now have one of the worst consumer sentiments we have seen in decades” (which might reflect GLP1s more than anything).

But it isn’t the burritos. We do have a K-shaped economy7 - the top keeps rising as the bottom falls. That means that the really wealthy (the top 10% driving 50% of spending, for example) are doing quite well. Their credit-card spending and travel budgets have surged alongside stock and home-equity gains (they are celebrating the new 100% tax write-off by buying private jets).

For everyone else, the economy has become something to believe in rather than participate in, a system that promises meaning through motion. That’s the real mood of the economy right now - everything is a trade. Money, work, meaning, even faith.

Bible sales are up roughly 40% since the pandemic, but church attendance is down to 30% from 42% two decades ago and 38% ten years ago. It’s aesthetic in a way - aesthetic spirituality, aesthetic politics, Baudrillard and Debord would have a blast.

When belief itself becomes transactional, risk stops feeling like a financial concept and starts feeling like a moral one. People don’t just gamble with money anymore; they gamble with time, attention, identity - anything that might yield security or a sense of control. The markets are only the macro version of that instinct.

That’s why the economy feels both booming and brittle at once: we have extraordinary wealth concentration coupled with mass participation in markets. Wealthy households and large firms transfer risk through diversification, hedging, political insulation (like donating to a ballroom maybe). Everyone else absorbs risk through gig work, debt, market exposure, and health costs. It is the logical outcome of labor precarity + 401(k)ification + income volatility. Risk always rolls downhill, but lately it looks like belief too.

The fixes for some of this aren’t complicated (it’s ideas that many have been talking about for a long time). Create portable benefit pools that follow workers between gigs. Build a public infrastructure corps that provides an employment floor. We have examples as to what works, like Singapore’s sovereign wealth model, Germany’s apprenticeship programs, and Denmark’s flexicurity system.

The goal is probably to not ban the casino but rather to build something slower beside it. Every speculative boom eventually exhausts its own attention span. Markets will always trade. The invisible hand will keep dealing. The work is to make sure the table doesn’t collapse.

Other Things

Surviving the AI Capex Boom | The Vulgar Image | The Goon Squad | The Fiscal Impact of Immigration | The Real Cost of Benchmarking | The AI Becker Problem | Moloch’s Bargain: Emergent Misalignment When LLMs Compete for Audiences | Can Large Language Models Develop Gambling Addiction?

Thanks for reading.

This transcript has been lightly edited for clarity and flow. Below is the audio version, which is also available wherever you listen to podcasts.

Recorded on Friday, October 3rd, 2025

Why Build New Labor Market Indicators

Kyla: President Goolsbee, thanks so much for joining me today.

PG: Thanks for having me back, Kyla.

Kyla: I’m really excited to talk about the Chicago Fed Labor Market indicators because we desperately need some sort of information about the labor market right now. Can you walk through what these labor market indicators are supposed to do and the goal that you had with publishing them?

PG: When you have a government shutdown and you’re not getting BLS data, that’s a big problem for a lot of people. But especially for the Fed - we didn’t know there would be a government shutdown - but we did know that we’re going through a tumultuous period of transition in the economy. We wanted some better real time estimates of what’s happening in the job market. We put together 11 different data sources, some of which are the official statistics that come from the BLS, but tend to come out with a lag, some of which are high quality private sector sources on the job market. We built a statistical model of what these observations mean for three statistics that we keep track of.

1. One is a real time estimate of what the unemployment rate is going to be at the next job report.

2. Then the other two are a hiring rate of unemployed workers and a layoffs and separations rate for people that currently have jobs, because there’s a lot of churn going on at any given moment in the job market.

If you have 100,000 jobs created for the month, that’s 5.2 million jobs that were created and 5.1 million jobs that were lost for a net of 100,000 jobs. So we looked at those flows and then it turned out that just as we announced this multi-month effort to build these statistics the government shut down and there’s not going to be an unemployment number.

Our data is not as good as the BLS. The BLS numbers are the best job numbers in the world but if we cannot have the best job numbers in the world, we are going to have to go with what we do have and what we have is this - based on what we know:

• Our real-time estimate is that the unemployment rate would’ve stayed the same at 4.3%

• The hiring rate of unemployed workers went down a tiny fraction. It still remains basically 45%.

• The layoff and the separation rates are also very constant, just a little above 2%.

So I feel like those numbers are showing the steadiness in the job market that is a bit in contrast to those monthly payroll numbers which are all over the map.

Flows and Payrolls

Kyla: Could you talk about sort of the difference between the metric that you all have created relative to what the government produces? There is a lot of concern about the labor market. People are having a tough time finding jobs.

PG: Let’s get down in the weeds of how it is constructed, and then let’s take a step back and think about what it means for the actual state of the labor market.

The JOLTS (Job Opening and Labor Turnover) survey data are about the flows.

The job market is like a bathtub and there’s water going out and there’s water going in. If you look at the speed that the water’s coming in and the speed that the water’s going out, it will tell you something about the level of the bathtub.

That’s the approach that we’re taking with these statistics. We’re basically trying to add up ‘What’s the chance that you come out of unemployment and into employment?’ That would affect the unemployment rate. ‘What’s the chance that you have a job and you lose that job?’ Either you quit or you’re laid off or discharged, etc.

By measuring those from all the angles that we can, we can use the past and say - in the past when all of these indicators said ABC, what did that mean for the unemployment rate? So that’s the way we construct it.

That’s a little different than the unemployment rate that the BLS puts out, which comes from the Current Population Survey, which contacts tens of thousands of people and just asks them, “did you have a job last week?” As I say, the BLS data is the best there is, but it’s not without flaws and it’s in an environment where people don’t like answering their phone and they don’t like doing surveys. You’ve seen the response rate even of the BLS data really fall almost in half. It’s not just the BLS that has that problem. All private data have that problem. Everybody has that problem.

So we’ve got more variability, and the official data are so good that it takes a long time to put them together at that high of a quality. It comes out with more of a lag than would be ideal. I always say that I’m one of the data dogs on the FOMC and a central rule of the data dogs is to sniff every piece of data that hits the floor because it might be food.

At moments like this, where some of our tent pole marquee numbers like payroll and employment have question marks about whether they’re a good indicator of where we are in the business cycle, whether because of immigration or labor force participation or things like that, go sniff everything. What we’re trying to do with these labor market indicators is gather all the best data that we can find and use it to make a projection of the throughline in the job market.

Who’s Missing From the Numbers

Kyla: How does this indicator capture people who drop out of the labor force entirely, like maybe younger workers or more precarious workers?

PG: That’s a crucial issue. The Chicago Fed’s research department has done a lot of work about labor force participation. We’ve had some really wild swings in labor force participation, not just in the last 5 years, but really the last 10 or 15 years.

In the period since COVID, we’ve had remarkably high labor force participation for what our demographics are. The baby boom’s retiring and labor force participation was forecast to be trending down pretty significantly at this point but we’re not picking that up in our new statistics.

That is an issue facing the official data, too. The unemployment rate is only for workers that are actively seeking employment. If you stop looking for work, you drop out of the job market statistics, you’re not in the unemployment rate - and we should be nervous about that.

We should also think about the employment rate. In a world where the immigration is changing, population is aging, and women are making choices about whether to be in the labor force or not be in the labor force and whether to have kids, it’s super important when people choose not to be in the labor force, but it’s hard to track properly.

A Mindset Shift on Employment

Kyla: Do you think there has to be a mindset shift to start thinking in terms of the employment rate versus the unemployment rate?

PG: Maybe there does need to be a bit of a mindset shift. Some of it has already happened. There has been a mindset shift that took place in the wake of the Great Recession. We were having moderate recovery speed and the job market was improving but it was improving relatively slowly and the unemployment numbers were looking good, but the labor force participation rate was very low - so people were asking, “Is the job market good or is the job market bad?”

So we had to grapple with that shift in mindset. That’s what makes this last five years so interesting from a data perspective - we completely reversed that argument. Many people through the 2000s were saying, “Of course labor force participation’s going down. There’s nothing about the business cycle about that. We’re aging. That’s how it’s going to be.”

Then we saw when the labor market was as tight as we’ve ever seen, and labor force participation jumped back up higher than what we would’ve forecast where it was going to be.

But - what would it have been? It is worth thinking about where we are relative to where we would have been if there had been no changes. And that said, I still think that in the here and now, every data point that we’re getting, except for monthly payroll, is largely saying we have a pretty steady labor market with low hiring and low firing. That’s unusual, but that is where we are. That might be full employment and that’s the thing that we’re having to chew on a little bit.

Reading the Cycle

Kyla: The Fed entered a rate cutting cycle and cited a slowing labor market as perhaps one of the reasons for that. So how do you think the Fed and policymakers in general should think about this new data when thinking about the direction that they want to go with policy decisions?

PG: I hope that they will use this data. Now, you know the rules of the FOMC. I’m not allowed to speak for what anybody else thinks or what the Fed thinks, only for myself.

What I look for in these data indicators that the Chicago Fed is putting out and in all the other indicators is very much trying to get the throughline- where we are in the business cycle.

In normal times, the number of jobs in the aggregate is normally pretty strongly correlated with where we are in a business cycle.

• If it goes negative - that’s a sign that recession may be coming.

• If you start seeing big positives, that’s a sign to be wary that the economy’s overheating.

We saw in 2023 and 2024 how wrong that can go. It was the other way. We were getting lots of unrecognized immigration. The population growth rate was higher than we knew when we were making the estimates. We were having hundreds thousands of jobs created each month, well in excess of what we thought was a breakeven rate. So, there were a bunch of people looking at payroll employment and saying, “We’re overheating. Inflation is about to come booming back because how can we sustain jobs numbers as big as this?”

We came to find out the jobs numbers were reflecting fluctuations in labor supply and population that we didn’t know at the time. And the lesson of that period I think was that measures of labor market rates like the layoff rate, the vacancy rate, the unemployment rate, the hiring rate were more accurate indicators of where we were in the business cycle than the monthly payroll was.

So, I hope that people look at these Chicago Fed indicatorsas perhaps a better indication of where we are in the job market when there are moments where immigration and others are making the population uncertain.

Kyla: One of my favorite think tanks is Employ America. They advocate for looking at the quits rate because they’re like, listen, if people feel like they can quit their job, that’s probably a pretty good indicator of what’s going on in the labor market.

PG: The quits rate is really low right now, and the hiring rate is low, those would point to danger. But the layoff rate is very low and that usually points to the opposite.

Usually when you go into recession, layoffs go way up, and we are not really seeing that. So it’s a bit of a puzzle. There are cross currents in the data that we’re grappling with. Almost all of them have been steady. So that low hiring, low firing environment has been with us now for a fair bit of time. It doesn’t exactly look like we’re on the precipice of something in the way that if you over index on the monthly payroll declines and the revisions being big negatives, you could convince yourself that maybe this is the edge of a precipice - but most of the other indicators are not that.

AI and the Entry-Level Worker

Kyla: I want to ask you an AI question, sorry. There’s been a lot of debate on if AI is replacing young people. So when you think about the labor market indicators and when you think about how the Fed thinks about the labor market indicators, how do you think AI is going to tie into all of that, especially for younger people?

PG: Both sides of that question are really important. In the long run that is the same thing as asking, “how big of a productivity growth increase is AI going to give us?” And if the productivity growth rate that comes from AI is so big that employers don’t need to hire people, they can even let go of people because they can get the output that they’re desiring with fewer people, then it would have a labor market impact.

But on this side of the ledger, I just want to remind everybody that high productivity growth is fabulous. We want high productivity growth. Let’s pray that we get to deal with the issues of transition. If you don’t have productivity growth, real wages can’t rise, and that’s a far bigger problem.

Now, on the other side of this ledger is the differential impacts. If AI is as big as its proponents say, will that have differential impacts on different parts of the labor market? Probably it will - both by industry and potentially by age. You’ve seen that play out a little bit, but I still characterize most of what people are saying as forecasts for the future; that there is going to be huge improvement. They are going to replace accountants, replace lawyers, replace various occupations.

I do think you’ve seen the impact in the hiring rate of young workers, especially in tech. If you look at the unemployment rate of new graduates in STEM fields and computer fields, that used to be the lowest of all the majors. Now it’s among the highest of all the majors, but it’s worth objectively pointing out, it’s still pretty low.

If you look at computer science graduates, the hiring rate is low, but the unemployment rate is not objectively that high. It’s just frustrating compared to what the job market was for the previous five years.

I am a great believer in the ability of young people adapting and moving into new industries. If you don’t think that will happen now, I would simply caution you to just go back and look back 30 years and go to Silicon Valley. What were they doing? It’s fundamentally different. If you go back far enough, they were making hardware. Making chips that now are low end chips made in other countries. They were doing the kinds of software that nobody does anymore, but that hasn’t made Silicon Valley an unpleasant place to work because they just kept moving from thing to thing, which you can do if you have the skillset.

The Breadth Problem

Kyla: The labor market has a breadth problem. Back when the government was working, we would get data saying that most of the jobs added were just in healthcare and social services. Manufacturing’s losing jobs, finance is losing jobs. So how do the labor market indicators that you all have developed think about something like that?

Goolsbee: We haven’t gone into sectoral information in our new statistics. If you want to do some narrower and narrower cuts of the data, you need to have bigger and bigger samples of the data.

So, it’s really mostly only the government data that can pull that off. If you want to do something that’s a 1% sample, you need a big sample for that to be able to count on it. That said, we had such a strange sectoral business cycle coming through COVID. It was like nothing that ever happened before. Normally, cyclical industries drive the recession and the most cyclical industries are the most rate sensitive parts of the economy, and that’s why the Fed is the natural touch point for economic stabilization, consumer durables, business investment, housing construction. These are very cyclical parts of the economy usually, and they’re very interest rate sensitive.

If you start seeing those going down and then the Fed cuts the interest rate, that tends to buck them back up. And if the economy’s overheating, it’s usually because those sectors are overheating, so raising the interest rate cools them down. COVID was a recession driven by services. Nobody can spend their money on going to the dentist and stuff like that. It’s the first recession I think ever where the demand for consumer durables goes up in the recession and the demand for housing goes up in the recession.

Part of what we’re seeing on the jobs front is a bit of a recalibration, of resetting back to the old trend that we used to spend before COVID where 75 - 80% of our consumer spending budget was on services. Then we go through this weird period where all we can buy are physical goods and everybody’s getting a Peloton, and now we’re shifting back.

That will contribute to a breadth problem. All of that said, over time we’ve gotten more and more healthcare oriented. So it’s not surprising that healthcare is going to be a bigger and bigger share of the jobs, leisure, and hospitality in a world where there is productivity growth, either from AI or from anything else that’s so far been concentrated in physical goods.

For example, the price of TVs gets cut in half. You don’t buy two TVs, you just still buy the same TV, but you just spend less of your income on it. More of your income starts going to human beings. Human beings are the thing that gets more expensive. So part of that breadth problem might be natural.

Kyla: What do you think the one thing that you would want the public to take away from this data release?

PG: I’ll give you one and a half things. The half thing is it’s important that we get the official data and if we don’t have the official data, we at least have some estimates that we can get from the private sector and the public sector. The longer we don’t have the highest quality data, the worse it’s going to be.

The other thing that jumps out at you from these indicators is the stability of the job market. So far, it is not falling apart. The hiring rate is relatively low, but stable. The layoff rate is also low and stable, and the unemployment rate is largely unchanged, which is a point of stability. I am here on Kyla Scanlon’s show so you knew we had to talk about vibes. We are potentially going to be back into one of these conflicts between the data and the vibes sometime soon. Because if you look at the history of consumer sentiment, government shutdowns have often been correlated with big drops in consumer sentiment.

Kyla: Absolutely. Thank you so much, President Goolsbee.

Four Takeaways

1. Employment growth is an unreliable signal and slack is the story now: Goolsbee underscored that traditional measures like monthly payrolls have become noisy and potentially misleading, especially when immigration, labor-force participation, and survey response rates are volatile. His team’s new Chicago Fed Labor Market Indicators are meant to fill this data vacuum by tracking flows in and out of employment. This directly echoes Guy Berger’s argument in “We Don’t Need More Employment Growth Nowcasts!”: the economy no longer needs more guesses about payrolls; it needs slack nowcasts - these real-time measures of hiring rates, separations, and the true level of labor-market tightness. Goolsbee’s “bathtub” metaphor (inflows and outflows) is exactly that kind of slack measurement.

2. The labor market is stable, but thin: Goolsbee called it a “low-hiring, low-firing” environment - but a steady environment overall. The Chicago Fed’s real-time estimate shows an unchanged 4.3% unemployment rate, hiring of unemployed workers holding near 45%, and layoffs just above 2%. That calm contrasts with Carlyle’s grim payroll read, which implied a slowdown. But this is clearly a push-and-pull problem. It underscores Mohamed El-Erian’s warning in “As Growth Decouples From Employment, the Fed Faces a Trilemma.” GDP growth (Carlyle pegged it at 2.7%) remains solid even as job creation sputters. The US economy is expanding, but the labor market isn’t broadening and so what looks like stability may actually be brittleness. Markets, however, are treating weak payrolls as a green light for rate cuts. El-Erian calls that a dangerous loop: easing policy to offset soft employment could inflate risk assets while inflation remains above target - and with data telling such different stories, it’s even more confusing to figure out what’s going on.

3. Labor-force participation should guide the narrative: Maybe we do need a mindset shift! Instead of obsessing over the unemployment rate, which does exclude discouraged workers, Goolsbee suggested tracking the employment-to-population ratio. In his words, “We should also think about the employment rate. That’s an important measure of the economy.” This is where Goolsbee and Berger converge: the next frontier in labor data is coverage. Who’s missing from the numbers is now the more consequential question.

4. Oh, vibes: The Carlyle data reinforces a paradox: inflation is still sticky, while the labor market looks weak. Goolsbee’s indicators show a steady job market, not one in crisis, yet sentiment could deteriorate as the shutdown drags on. “We might be back into one of these conflicts between the data and the vibes,” he said. In other words: the real trilemma isn’t inflation-jobs-stability. It’s data-vibes-policy.

The bigger picture is that we’re entering a phase where labor data itself is becoming a policy variable. The government shutdown, new private estimates, and the Chicago Fed’s real-time model all point to the same problem: we’re flying on fuzzier instruments.

At the same time, the economy looks steady but thin with a job market that feels fragile beneath the surface. Goolsbee’s point is that we need to measure better before we can decide better because the next policy mistake may not come from getting the economy wrong, but from misreading the data that defines it.

Thanks for reading.

Politics, Capital, and Attention

There are two things that I am trying to understand, both captured very well in Bloomberg’s Tuesday evening homepage.

1. AI: Can’t go too far these days without someone talking about AI - how it’s a bubble how it’s the future how it’s both a bubble and the future. And the broader question there is about how the stock market can be so divorced from reality (or maybe, it’s just about understanding what reality the stock market inhabits)

2. The economic decisions of the Trump administration

In the below image, Trump highlights both. He says that the Democrats have shutdown the government, citing a successful economy AND a successful stock market (but sometimes it’s Bidens economy, so you never really know). He says he is open to meeting about healthcare, which is great progress toward ending said shutdown.

But that line about the stock market is interesting. He’s right! It is a record stock market! Presumably, stocks would be cowering at this point.

• Tariffs beat down profits (we now have tariffs on trucks, which is a flip-over-the-economic-table kind of move as it will make literally everything more expensive)

• The dollar is flailing in the wind - and sure, a weaker dollar helps multinationals, but it also challenges returns

• Many of the recent political decisions - no matter how you feel about them! - are creating an isolated United States, which likely isn’t good for economic growth.

Political instability usually rattles investors, but US investors seem to only see the United States of AI and literally nothing else. Ruchir Sharma wrote in the FT that “America is now one big bet on AI” which is true and as he points out, it’s a costly bet:

Outside of the AI plays, even European stock markets have been outperforming the US this decade, and now that gap is starting to spread. So far in 2025, every major sector from utilities and industrials to healthcare and banks has fared better in the rest of the world than in the US.

The US stock market is booming, but it’s all relative. There is a lot of glee in talking about bubbles. If you remove yourself from the situation, it is rather exciting to watch big companies toss around billions of dollars. It’s thrilling to gleefully tweet “the crash is COMING! Buckle up!” There is a sense of stability in the madness - we all know it’s absurd, no one knows if it’s going to work (not even the guys in charge), and it gives everyone something to talk about.

It gives the government immense power

Because the indexes are green, the government can apparently cancel funding that has already been congressionally approved, threaten allies, or bail out Argentina while railing against “globalism”. The feedback loop is simple:

• Markets rise → Public confidence holds → Political risk premiums fall → Markets rise again.

I think for a while I thought that the stock market was just ignoring politics. But it isn’t! It is politics now, a political actor that can grant or withhold legitimacy1. Artificial intelligence fuels valuations, those valuations stabilize public confidence, that confidence grants the administration power, and the administration protects the system that sustains it.

The stock market has never been the economy - it’s really a reflection of what the economy dreams it could be in a world where share buybacks translate to meaningful productivity. But as AI swallows up more and more capital, it is both the economy and the stock market - and the government.

Gold keeps going up too.

Normally, equities and gold move in opposite directions. Stocks up, gold down. Fear or faith, pick one. But not now. The S&P is surging on AI optimism while gold is surging toward $4,000 an ounce. It is up 51% this year, the best performing asset this year2. The dollar is down 10%3. Both fear and faith are rallying simultaneously, which is rare and usually not a great sign.

Odd Lots had a good interview on the push-and-pull here. Viktor Shvets sees a cycle - tech is ripping apart society (apparently a good investment) so people are buying gold as a “hedge against destruction”.

The US equity market doesn’t seem to care. Both are winning right now, but both can’t be right forever. The US equity market is betting everything on one story:

• Nearly 40% of US GDP growth this year comes from AI.

• According to Morgan Stanley, “roughly 75% of S&P 500 returns, 80% of earnings growth, and 90% of capital expenditures growth” can be attributed to the AI data center build out.

• AI companies hold $1.2T in debt, the largest segment in the investment grade market.

• Nvidia, Microsoft, and Apple now account for over 20% of the S&P 500 index.

The underlying idea here is that AI surely will generate boundless bounty later, so valuations don’t have to make sense now. Nothing has to make sense now!

The Circle of Joy

The AI companies are spending a lot of money, primarily with each other. It’s a circular economy of speculation, as Bloomberg wrote about here.

• Nvidia invested $100 billion in OpenAI to build out AI infrastructure, and so OpenAI could buy $100 billion worth of Nvidia chips. OpenAI has signed about $1 trillion in deals this year. They are raising a bunch of debt to fund this because they do not have the revenue (right now, it’s about $12 billion) to finance the deals. xAI is raising money from Nvidia to buy Nvidia processors?

• OpenAI is buying 6 gigawatts of AMD chips over the next few years and also has the ability to buy up to 10% of AMD shares for the cost of one penny each?

• Everyone is making money because they are all making money from each other.

Bain & Co. estimates this wave of AI infrastructure spending will require $2 trillion in annual revenue by 2030 to justify it which is more than the combined 2024 revenues of Apple, Amazon, Alphabet, Microsoft, Meta, and Nvidia.

The companies primarily make money through (1) subscriptions and (2) money paid to use these data centers.

But the companies have two headwinds.

1. The $2T required here is more than 5x the annual subscription market, meaning they are going to need for a lot of people to pay for this. A lot of people don’t want to pay.

2. The hardware depreciates in two to three years. Unlike the fiber laid during the dot-com boom, none of this will mature into durable capacity, as the WSJ highlighted.

So what do you do when you need 5x the global subscription software market to cover costs?

You make a social media app.

Everyone Gets a Social Media Company

1. OpenAI launched Sora, a TikTok-like app that’s more focused on creation and posting than being “social” (whatever that means anymore) and Meta launched Vibes, another AI video feed. The goal here is likely to sell ads, in the same way that TikTok does. Carcinization and advertisement (adinization?): everything is destined to be a crab, everything is destined to be an ad.

This is interesting for a few reasons.

1. AI is extraordinarily expensive but still searching for demand: Training frontier models will likely cost billions of dollars. But only a small fraction of people pay for these services. Some companies are starting to abandon it. Building a social media company is a sign that they’re chasing volume. They need eyeballs, data, and ads to offset the costs of scaling.

2. Social media is a last-resort monetization model: When tech companies can’t make enough money on software licensing, subscriptions, or enterprise products, they default to attention. It’s reliable: people scroll; advertisers pay. The thing to watch here is that people are increasingly upset by social media, with almost 50% of teens saying that it harms people their age. John Burn Murdoch argues that we have passed peak social media.

3. It signals a maturity problem: Right now, the supply of AI capabilities is growing faster than actual use cases. The economy hasn’t figured out what to do with all this intelligence yet, so it’s turning it into spectacle. And there are clear consequences - the technology is good. It’s good enough to be used maliciously and it will be. And there is very little talk of policy or guardrails to rein it in.

4. It mirrors the late-stage tech pivot pattern: We saw this with crypto: when speculative returns dried up, projects pivoted to “community” and “social.” We saw it with Web3: when utility collapsed, companies turned to “metaverse” marketing (ahem, some of them changed the name of their whole company). Now we’re seeing it with AI: a turn toward social platforms that keep the narrative alive and keep investors engaged.

AI was sold as the end of slop but what it delivered was more slop. The market rewards attention, not utility, and both AI and politics has adapted to that logic.

The story that’s supposed to justify $2 trillion in annual revenue by 2030 has pivoted to... selling ads on AI-generated TikTok videos. That’s maybe the big payoff. That’s what’s sustaining the market confidence that’s granting political latitude. Gold traders see this. That’s why they’re hedging. Equity traders see it too but they just think the story lasts long enough to get a bag and get out.

The Government

And the bags are plentiful. AI’s sheer power - social media app or not - gives the government political cover. As long as portfolios are green, the electorate stays somewhat calm. The administration is effectively borrowing confidence from the AI bubble. Speculation has become governance.

Understanding this loop explains both of those questions I had.

• The market stays green because of AI speculation.

• That market stability creates political latitude.

• That latitude allows the administration to do otherwise-impossible things.

• And the administration protects the AI investments that sustain the loop.

Investors are trying to bet on which company the Trump administration will invest in next.

• Intel roared up 82% after Trump shoveled $10 billion into them for a 10% stake.

• The government invested $35 million in a Vancouver-based mining business partly owned by Trump donor John Paulson, giving Paulson approximately $70 million additional dollars.

If the government invests in your company, you’re rich! Apparently the grid is next! A far cry from Reagan’s quip that “the nine most terrifying words in the English language are ‘I’m from the government and I’m here to help.’ Now, the nine most terrifying words “I’m from the government and I’m blocking your datacenter” or something. It’s a very strange form of socialism!

Outside of AI, the US economy is wobbling.

• Manufacturing activity has contracted.

• ADP data showed that in 3 out of the past 4 months, the private sector lost jobs.

• Carlyle Group developed their own proprietary labor market data (necessary during a shutdown) based on their portfolio companies and real estate investments that apparently shows a completely flattened labor market.

• But other components of the economy - like inflation and GDP growth - don’t show signs of a recession. The labor market does, which is very strange.

Which is why both gold and equities keep climbing. The equity market believes the AI story overrides everything else. The gold market believes something is fundamentally breaking. They’re both reacting to the same underlying reality, but they just have different theories about what happens next.

I spoke with Austan Goolsbee of the Chicago Federal Reserve about the labor market, and our conversation will be up tomorrow as their data says something else - but everything is confusing. The reality is confusing.

So: the stock market inhabits a different reality where AI speculation is all that really matters. We are in a rate-cutting cycle, with loose fiscal policy - might as well spend a ton of money on everything. The Mag7 will be completely fine either way.

And what explains the Trump administration’s economic decisions? Well, as long as the stocks stay up4, the administration has room to do things that would be impossible during volatility. Cancel appropriations. Block elected representatives from being sworn in. Invest public money in donor companies!

The stock market has become an emotional infrastructure that allows speculative sovereignty and has created an economy that governs through its own price chart.

Both gold and equities are surging because they’re hedging different kinds of collapse. Gold trades on fear of the system. AI trades on faith in the story. That both are rallying tells you something about where we are.

This is what it means to live in the United States of AI. Democracy as an asset class or something. For now, the line keeps going up. But speculation isn’t stability, and the permission government borrows from investors is never really its own.

Thanks for reading.

It’s nearly impossible not to get lost in the news right now. I was at a wedding last week, and every conversation eventually drifted back to the same subject: the World We Are in and All That is Happening. The ground feels like it’s moving faster than anyone can feasibly keep up with.

Some people think the shift is progress. Others see collapse. Either way, the line between digital and physical life is increasingly blurry. What happens online is real life. What we consume is what we become.

Plenty of thinkers have circled this before - Postman, Debord, Huxley, Orwell on media; Machiavelli, Tocqueville, Thucydides, Gibbon on human corruptibility during times of uncertainty. The convergence of endless information and a ragebait economy creates the perfect environment for splintering how we understand the world and how we understand each other.

The deeper problem is this: we no longer trust institutions to provide truth, fairness, or mobility. Once, they were scaffolding that helped us climb from raw data to wisdom. And when that scaffolding gives out, people adapt: some over-perform in the status race (because you have to) and others defect from obligations altogether (why would I work for institutions if they don’t work for me).

The Architecture of Confusion

There are a few ways to picture our distorted information ecosystem.

• The DIKW Pyramid (Data → Information → Knowledge → Wisdom): raw posts and clicks at the bottom, trending stuff in the middle, shared truths above that, and finally wisdom, the rare ability to see causes instead of just symptoms.

• Or the Ladder of Inference: we start with data, add meaning, make assumptions - and our beliefs tend to affect what data we select. Bots and algorithms hijack that ladder, nudging us toward polarized beliefs before we realize what’s happening.

Taken together, we can combine them into what we might call a hierarchy of information:

• Raw data: the endless stream of posts, likes, bot spam

• Information: headlines, hashtags, trending things

• Knowledge: the narratives we share and fight over.

• Understanding: recognizing what might not be real (or is hyperreal)

• Wisdom: systemic analysis, the ability to see causes instead of just symptoms.

Right now, we’re stuck sloshing around in the middle layers of the hierarchy: drowning in outrage, fighting over partisan hot takes, rarely reaching understanding, almost never wisdom.

Chaos always has an architect. And if we want to make sense of American democracy today, we need to understand who those architects are, and how they profit from confusion.

Media Concentration as Infrastructure

This polarization rests on media concentration. The Telecommunications Act of 1996 was sold as a way to increase competition in media and telecommunications, but in reality, it did quite the opposite. Within five years, four firms controlled ~85% of US telephone infrastructure. That deregulated spine carried today’s consolidation of the entire media environment - not just telephones. Newspapers. Social media. TV stations.

We have the increasing concentration of media ownership, the financialization of attention, and the transformation of information from a public good into a private commodity to be bought, sold, and manipulated.

For example, Larry Ellison is building a pretty huge empire. His son is running the newly merged Paramount-Skydance, and they might bid for Warner Bros. Discovery, giving them control of both CBS News and CNN. The Paramount merger only went through after they did Trump’s bidding and settled a $16 million lawsuit.

Ellison is also part of an investor consortium (which also includes the Murdoch family, the owners of Fox News) that might own TikTok. If Ellison’s deals go through, he would control streaming services with over 200 million subscribers (combining Paramount+ with HBO Max/Discovery+), a major broadcast TV network and news division (CBS), a premier cable news network (CNN), and one of the largest global social networks (TikTok)

Why does this matter? Because controlling the means of mass communication means controlling the narrative. It’s the attention economy version of a monopoly. When one person (or a small elite) owns the newspapers, the TV stations, and the social media platforms, there is no room for alternate voices.

But it’s sort of like… everyone gets their own information ecosystem. Elon Musk owns Twitter, which he leveraged into helping Trump win the 2024 election. Jeff Bezos owns the Washington Post and has nudged into being more accommodating. Mark Zuckerberg controls an empire of social apps and has faced repeated accusations of algorithmic bias.

When information is power and attention is currency, of course the people with the most money will try to buy the most influence. Normally, an entity like the FTC would be like “well no I don’t think one person should have extraordinary control over the information environment” but that’s not how things work right now. This White House is willing to weaponize the levers of regulation.

Trump has openly threatened to yank broadcast licenses from networks that criticize him. The logic is simple: want to keep your license? Say nice things about the president. Want a tariff cut? Promise foreign direct investment. Need a visa discount? Make a deal. Like Derek Thompson said, it’s flattery economics all the way down.

• The head of the FCC, Brendan Carr, brought Jimmy Kimmel down for insensitive comments about Charlie Kirk’s tragic death and plans to bring everyone else too if they don’t play the right sea shanty honoring the administration.

• Jimmy Kimmel get did taken down, but he was quickly put back on by ABC after they lost a few billion dollars.

• However, two local broadcasting groups, Nexstar (who has a $6b merger they want to complete!) and Sinclair, both won’t air Kimmel.

• Brendan Carr says that all of this happened because of Kimmel’s ratings, not the government. But then Trump gets on Truth Social and says:

“We’re going to test ABC out on this. Let’s see how we do. Last time I went after them, they gave me $16 million dollars. This one sounds even more lucrative. A true bunch of losers.”

So like, the government is clearly involved. This is a bad situation. The media environment that gave Trump the election - very specifically podcasters like Joe Rogan - have spoken out against this.

• Joe Rogan: “If the government tried to silence Jimmy Kimmel because they were trying to push through some sort of merger and [Trump] doesn’t like Jimmy Kimmel, that should be exposed.”

But it’s pretty clear what’s happening. Free speech is whatever the administration deems to be not woke or whatever. It’s like vertical “cancel culture” - a state-capital hybrid where platforms and politicians use one another to discipline dissent.

Even if you agree with what the administration did, it’s becoming clear that our mass communication system is increasingly privatized, and optimized for profit and power, not necessarily for truth or public good.

In a landscape where capturing attention equals revenue, these guys have an incentive to make communication ever more addictive and sensational - which is never great for public discourse.

Red vs Blue

The fractures in our information system show up most clearly inside the United States itself. Bloomberg Opinion’s Ronald Brownstein called Trump’s “lawsuits, funding threats and the use of troops” that are leading to a growing chasm between red and blue states “the greatest strain on national cohesion since the Civil War.” Loyalty is shifting from the Constitution to the team colors.

Megyn Kelly, a prominent conservative commentator, said that she didn’t care that Trump’s border czar Tom Homan took a $50k bribe.

Part of the reason she likely doesn’t care is because everyone is getting away with everything right now. If you can play to Trump’s good side, the entire weight of US institutions will roll off your back. If you get on his bad side? You will be crushed. The rule of law becomes a sliding scale of loyalty.

And when the enforcement of rules feels optional, people start acting like rules don’t exist. But the narrative gets all twisted and weird as it gets filtered through different algorithms and amplified through different bot networks because it’s like “well… if the red light isn’t working, should anyone really stop? No? Plow through and risk it all? Certainly.” More and more, reality itself is treated as optional - not a fixed structure but a set of vibes and allegiances.

That’s why outrage has become America’s most reliable export. Trump told the United Nations that their countries were “going to hell.” It was an insult, sure, but also a tell: our national brand is grievance.

But the sad part here, is that the stakes are material as well as cultural. Mark Zandi, chief economist at Moody’s, warned that one-third of the country is already in recession. That kind of economic stress only deepens the fracture, giving each side its own “truths” about what’s happening and who’s to blame.

Culture wars should pale in the face of economic concerns, but they only get more inflamed.

The International Mirror

What's happening domestically is the same on the international stage. Trump's approach to international institutions is withdrawal, contempt, the deliberate sabotage of shared frameworks. Again, even if you agree with his policies, that’s objectively what he is doing.

Andreas Kluth described it as “assembled world dreading the fate of what diplomats call the ‘international community minus one.’” The country that used to build the systems is now dedicated to tearing them down.

It's the same logic that's fracturing us domestically - (1) the belief that cooperation (or at least visible cooperation) is weakness and (2) that shared institutions are obstacles rather than tools. And when people lose faith in shared institutions, when they can’t agree on basic facts or common procedures, they become vulnerable to manipulation by anyone with enough money or technology to fill that vacuum.

Attention flows to spectacle, and spectacle rewards the people willing to blow things up rather than build them. So people find alternatives. China is shoring up gold reserves, presumably in an attempt to dedollarize. Other countries might like that option more than a fiat currency backed by full faith and credit, without much faith or credit at the moment.

The New Power Structure

And other countries are having an influence in the US through a remarkably efficient market manipulation strategy. We have a bot problem here - and it’s helpful to think about it in economic terms.

Bots are essentially a low-cost, high-leverage way to manipulate information markets. The business model is elegant: a small upfront investment in fake accounts and automation can generate massive returns in terms of attention, narrative control, and ultimately political outcomes.

In 2010, during US midterm elections, researchers observed that bots were being employed to boost certain candidates and smear opponents - thousands of automated tweets linking to fake news sites were injected into the political debate. Even at that time, the ACM warned such activity could “endanger democracy by influencing the outcome of elections,” since voters might be swayed by what looks like a surge of public sentiment.

Bots truly entered public consciousness during the 2016 election, when researchers discovered that just 6% of Twitter accounts were responsible for 31% of all the low-credibility news in circulation (detailed the great paper The spread of low-credibility content by social bots.) Their strategy is to amplify early, create fake consensus, and let human psychology do the rest.

As Giovanni Luca Ciampaglia, one of the authors of the paper, put it:

People tend to put greater trust in messages that appear to originate from many people. Bots prey upon this trust by making messages seem so popular that real people are tricked into spreading their messages for them.

It’s a classic market manipulation strategy, adapted for the attention economy. A relatively small number of bot operators can manufacture social media reality by exploiting the network effects that determine what content gets visibility. At one point, an estimated 20–33% of tweeting activity about the major candidates in 2016 came from bots or sock-puppet accounts (fake accounts run by humans) rather than genuine supporters, according to Social Media Effects: Hijacking Democracy and Civility in Civic Engagement.

And bots have remained a fixture of online discourse ever since. The paper A global comparison of social media bot and human characteristics details it well:

• In the 2020 US election, analysts again found bot networks “actively distort or fabricate narratives to create a polarized society”

• During the COVID-19 pandemic, bot armies aggressively pushed anti-vaccine narratives and conspiracy theories on social media

• Bots have also been caught boosting extremist movements (for instance, magnifying QAnon) by making them trend, thereby recruiting more human followers who stumble upon it.

The return on investment is extraordinary. For the cost of a few servers and some programming talent, foreign adversaries can influence American elections, domestic extremists can mainstream conspiracy theories, and commercial interests can manipulate public opinion on everything from vaccines to climate change. Global web traffic analysis has repeatedly found that bots – good and bad – account for over half of all internet traffic. Research shows that almost 60% of users often can’t tell a bot from a real person.

Truth becomes whatever can capture the most attention in the shortest amount of time. Traditional journalism, with its slow fact-checking and institutional processes, can’t compete with bot-amplified outrage. Democratic deliberation, which requires shared facts and good faith dialogue, becomes nearly impossible when the information environment is designed to maximize conflict.

We’re living in a speculation economy where perception drives value more than fundamentals. Look at the stock market: Nvidia gained $150 billion in value based the back of a $100 billion OpenAI investment (which OpenAI will use to buy more Nvidia chips). Ten companies pass hundreds of billions back and forth, and the S&P jumps like it’s measuring something real.

It’s all memes wearing suits. Meme stocks and Dogecoin at least looked like jokes; now the same speculative energy runs through the corporate core. Attention, perception, and narrative drive valuation more than production or profit.

Hierarchy Upside Down

We’ve built a world where the hierarchy of information has flipped upside down.

At the bottom, bots flood us with raw noise. In the middle, outrage and team narratives harden into “knowledge.” At the top, the ladders to wisdom like journalism, schools, civic discourse, shared institutions are weakened. The scaffolding that once helped us climb no longer holds.

The traditional solutions assume we’re dealing with a content problem when we’re actually facing an infrastructure problem. You can’t fact-check your way out of a system designed to reward misinformation and you certainly can’t educate your way around algorithms optimized for polarization.

The information wars are economic policy, determining how we allocate attention, structure incentives, and organize the flow of information that shapes every other market and political decision we make. We need to take (1) the power of media seriously and (2) those trying to influence it extremely seriously. There is a way to get to the top of the information hierarchy! We don’t have to be stuck in these middle layers.

Thanks for reading.

I’ve been spending some of my time in the mountains over the past few days. Trail running is a decent metaphor for life - dodging tree branches and skipping rocks, tremendous climbs and delicate descents. The quiet. The thundering noise of nothing.

It’s given me some time to think. And the past few months and weeks have been indescribable. I keep returning to this phrase as I slammed my head into the keyboard over the past few days, typing it out, deleting it, typing it again.

How do you describe the indescribable? I mean, think about it -

• A single day contained both political violence and a school shooting

• Jimmy Kimmel said something (false) around Charlie Kirk’s death and was taken off the air but the underlying reason was because (1) Trump wanted him to be taken down (2) the FCC threatened ABC (3) a merger has to go through

  • Nexstar owns dozens of local TV stations. Now it wants to do a $6 billion merger with Tegna, which owns dozens more. To do that, it needs to be on the FCC’s good side. The head of the Federal Communications Commission was very unhappy with Kimmel, taking to Benny Johnson’s podcast to make his stance clear - kill Kimmel’s show or else the FCC will haunt you.

• Speaking of mergers, Paramount Skydance fresh off their $8b merger, is preparing a bid for Warner Brothers Discovery, which would put CBS News and CNN under the same roof.

• TikTok is being positioned for sale designed specifically to appease China, with plans to sell to an investor group including Oracle and a16z, possibly giving the Ellison family vast access to media ecosystems. Trump has extended the deadline four times now, which is illegal.

• More than 300 South Korean nationals were arrested in a raid at a Hyundai-LG battery plant in Georgia which they were helping to build (which the administration says they now regret). The plant, which the US needs, won’t start up again until 2026

• The attempted firing of Fed Governor Lisa Cook over mortgage fraud (only to find that literally everyone else is committing fraud) and continued threats to Fed independence

• Stephen Miran is appointed to the Federal Reserve board while taking a leave of absence from his job as Chair of Council of Economic Advisors, raising the question - does he still agree with his 2023 tweet on independence?

• Consumer sentiment remaining persistently gloomy for young people coupled with a continued rise in youth unemployment rates since 2024 (as AI reduces the number of junior people hired). The broader labor market is weakening too (across both white collar and blue collar work), coupled with rising inflation.

• Politicians are increasingly deciding that their role is not to represent their constituents but is instead to become social media stars

• The Nepali government was overthrown and a new PM was voted in via Discord

• The continued exuberance of the stock market alongside a growing gap between the rich and poor as the top 10% now account for almost 50% of total spending

• Trump’s approval cratering because the economy is showing major signs of weakness (contrary to the view of Internet, most people really just care about the affordability of groceries)

So how do you describe the indescribable? You describe it as a test. Every one of these stories - Kimmel and the FCC, Paramount and CNN, TikTok, Miran at the Fed, youth unemployment, Trump’s slipping approval - is a stress test of institutions. Can media resist capture? Can central banks stay independent? Can governments maintain trust?

We are living inside overlapping crises of trust, violence, and attention, alongside weakening material conditions. It feels mythic - the human struggle with meaning and certainty is nothing new. And maybe that’s the best way to understand it. The old myths help explain why this feels both absurd and eerily familiar.

The Chicken and the Egg

A big debate right now is sort of a chicken and egg problem. Does social media cause Problems, or does it simply amplify deeper ills - like zero-sum thinking, institutional collapse, and inequality? Does the algorithm come first, or does the despair?

I think it’s complicated. I believe that The Machine is designed to monetize human attention, which is then sold to advertisers. And in an attention-based economy, outrage is cheap fuel, something you toss on the fire to make it burn bigger and brighter. Truth, nuance, and analysis are luxury goods that most people can't afford to produce consistently - so they ragebait.

Meanwhile, companies chasing giant mergers bend themselves into silence, because nothing (not even the law!) can jeopardize regulatory favor. My billion dollar merger must go through, you see. Attention gets harvested, but so does independence.

And people aren’t just “fooled by algorithms.” They’re living with real pressures. The economy is weakening. Young people have very different priorities in life, and there is continued divergence between young men and young women.

Declining prospects funnel young men into hyperspecific online ecosystems, where economic disappointment curdles into cultural grievance. Anxiety creates the psychological conditions that algorithms exploit.

AI is weird too. Platforms are under control by actors who might not have the best intentions at heart (continually refining Grok so it fits an ideology is not great). When the machines become echoes for someone’s worldview, who are they really for?

So yes: it’s the despair and the algorithm, together. To explain where that leaves us, I think we need myths. Myths give us language for recurring human patterns, and frameworks for understanding whatever is going on. They describe the harmony and discord, conflict and scapegoats, plagues and crowds. Books.

(1) Discord

Then the discord of Melkor spread ever wider, and the melodies which had been heard before foundered in a sea of turbulent sound. - The Silmarillion, J.R.R. Tolkien

In the opening of The Silmarillion, the world is sung into existence by the Ainur, the holy ones, each contributing their voice in harmony to a vast symphony directed by Eru Ilúvatar. But then Melkor, the most powerful of the Ainur, introduces discord into the music. It’s chaotic, a melody of pride and violence. When it gets woven into the very fabric of creation, it permanently scars the world.

Our world feels the same - the age of struggle between order and chaos. Discord (lowercase d, ahem) has become a central organizing force. In Nepal, Discord servers (capital D) coordinated mass protests that toppled the government. And the same rails that carried that also carried the confession of Charlie Kirk’s killer.

The world has become very small, and the platforms have become very powerful. Social media is one thing - where we all yell at each other in the feed - but private chatrooms are increasingly important to understanding the suburbanization of the Internet.

Trending topics mean millions of people are suddenly focused on the same thing, in their own algorithmic universe, whether it’s a school shooting in the US or political unrest abroad. They sing their discord and bring turbulence: half-truths, polarization, confusion. The algorithms are tools of engagement, and many people know that it’s all a game. Why not sing darkness into the fabric of creation? It’s a good way to make a lot of money, after all.

(2) Blame

The account thus shows once again the omnipotence of mimetic contagion. What motivates Pilate, as he hands Jesus over, is the fear of a riot. He demonstrates "political skill," as they say. This is true, no doubt, but why does political skill almost always consist of giving in to violent contagion? - I See Satan Fall Like Lightning, René Girard

The discord shows up continuously. When Charlie Kirk was killed and when Representative Hortman and her husband were killed, two high profile instances of political violence in the last few months, the response was instant politicization.

For Kirk, there were demands that he be remembered in a particular way and the Department of Justice is making it their duty to enforce that. Representative Hortman got none of the respect she deserved, no lowered flags, and a mocking tweet from Representative Mike Lee saying “Nightmare on Waltz Street” with a picture of her killer.

For both cases, death became a partisan talking point. René Girard's mimetic theory helps explain what's happening here.

• Human desire is imitative - we want what others want (the business model of social media), which creates escalating conflicts as people compete for the same objects of desire.

• This mimetic rivalry builds tension until it threatens to tear communities apart.

• The ancient solution was scapegoating: the community would unanimously direct their violence toward a single (perhaps innocent) victim, achieving peace through shared blame.

• It worked because it required unanimity.

• Everyone had to agree, at least publicly, on who was responsible for their troubles and that collective accusation created social cohesion, even if it was built on a lie.

But online, that type of unanimity is structurally impossible. The same tragic event gets processed through completely different frameworks all at once. Murder becomes a way to validate an existing worldview and reinforce a sense of moral superiority. Digital scapegoating amplifies it across feeds. Tragedy becomes content.

(3) The Permanent Crowd

A murder shared with many others, which is not only safe and permitted, but indeed recommended, is irresistible to the great majority of men. - Elias Canetti, Crowds and Power

The crowd craves content. Canetti saw crowds as boundless, with a hunger for expansion, contagious, all-encompassing energy. In his world, the crowd was more physical than what we have now - more bodies in a square with a single purpose.

Now, the crowd is mostly online. The digital crowd is everlasting, omnipresent, overwhelmingy powerful. It doesn’t need a public square. It is always scrolling and always metabolizing whatever is fed into it.

You can see this whenever violence breaks through. A shooting, a protest, whatever, it doesn’t matter. The crowd swells instantly, understandably. Some condemn, others cheer, others meme. Again, the algorithm doesn’t distinguish between condemnation or celebration, just raw engagement.

Canetti thought crowds had to find a release, a moment of catharsis before they dispersed. But our digital crowd never really goes away. It just keeps growing, folding one story into the next, a persistent force, but no moment of return to individual. What does politics become when the crowd never goes home?

(4) Habit

Resolve to serve no more, and you are at once freed. I do not ask that you place hands upon the tyrant to topple him over, but simply that you support him no longer.” - La Boétie, Discourse on Voluntary Servitude

The crowd can swell, but it can also become stagnant. La Boétie’s idea was that authoritarian power often depends less on coercion than on habit. People get used to serving, to accepting, and to normalizing. They don’t really resist because obedience feels like some form of order. People will accept almost anything if the transition feels gradual enough. The tyrant doesn’t always need chains. He just needs inertia.

But there is a broader application too. The erosion of independence feels familiar in an economy where convenience has become infrastructure. DoorDash with buy-now-pay-later, AI reducing entry-level jobs, politics turned into performance. People accept erosion not because they love it, but because resistance feels exhausting. The trap is voluntary servitude dancing with efficiency.

(5) Propaganda

This situation makes the "current-events man" a ready target for propaganda. Indeed, such a man is highly sensitive to the influence of present-day currents; lacking landmarks, he follows all currents. He is unstable because he runs after what happened today; he relates to the event, and therefore cannot resist any impulse coming from that event. Because he is immersed in current affairs, this man has a psychological weakness that puts him at the mercy of the propagandist. - Jacques Ellul, Propaganda

The crowd also responds to noise. Ellul argued that propaganda saturates - it pervades every aspect of life. It creates that exhaustion that leads to erosion of independence.. This is flood the zone before there was flood the zone. Create noise and force people to adapt their behavior to uncertainty. You don’t have to believe the propaganda for it to work, you just have to adjust yourself to its presence. It’s sort of La Boétie’s idea too - much of power depends on people never resisting.

Our media consolidation environment is starting to look like this. Paramount and Skydance circling Warner Brothers Discovery, a merger that would put CBS News and CNN under the same roof. Oracle might also have a bit of TikTok. Nexstar angling for Tegna, dependent on FCC favor. Everyone knows the game to be played - curry favor, do what must be done, make billions of dollars, sacrifice much of what those who came before you fought for, etc.

Ellul would say the danger is in what goes unsaid, the self-censorship. The saturation effect makes people cautious, quiet, reluctant. It narrows the space of speech without ever needing a formal ban. People know the consequences, and like the ABC execs, backdown instead of taking retaliation.

If propaganda works by poisoning the atmosphere, then what happens when our atmosphere is dominated by silence?

(6) Power

What we call Man’s power over Nature turns out to be a power exercised by some men over other men with Nature as its instrument. - C.S. Lewis, The Abolition of Man

Silence is the scariest thing. Lewis warned that when values are hollowed out, institutions risk being run by raw will. He called it the Tao: a shared understanding of right and wrong as the basis for all human values and the purpose of institutions. Once that framework is hollowed out, domination follows. The people operating the levers of power bend the machinery toward their own ends.

Central banks were designed as buffers of independence, neutral arbiters of monetary stability. Yet one of Trump’s appointees, Stephen Miran, now sits on the Fed board while on leave from his other job in the White House - a revolving door that he once criticized Lael Brainard for walking through. Does he still believe that? Or has independence itself become theater, a performance of neutrality rather than its practice?

Same thing for the media, too. Journalism’s grounding is the pursuit of truth. Remove that, and it gets messy. Outlets become vessels for whoever controls distribution, whether that’s Paramount/Skydance/a16zTikTok or a regulator with veto power.

Lewis’s warning was that when institutions forget why they exist, the what of their power gets captured. Technology, regulation, and expertise become instruments of will. And then, things get dangerous. Do institutions remember what they are for? Once the why is lost, the what can be bent into anything.

Final Thoughts

The question was whether social media causes despair or simply amplifies it. And like, we have bots running engagement farms for coffee shops. We have an economy that is currently built on rage, and a political system that is designed to feed it. So the answer is both. It amplifies what already exists, and in doing so, it reshapes what comes next.

What we are really facing is a broader test. Can institutions remember what they are for? Can media resist capture, can regulators stand independent, can governments maintain trust? Or will habit, propaganda, and hollowed-out values turn them into stages where power is simply performed?

The books remind us this isn’t the first time such uncertainty has existed (one could argue it’s always there), and likely won’t be the last time. In the most dramatic of terms, collapse doesn’t come from challenges, it comes from response.

Thanks for reading.

This transcript has been lightly edited for clarity and flow. Below is the audio version, which is also available wherever you listen to podcasts.

Recorded on Friday, August 29, 2025.

Why Fed Independence Matters

Kyla:  So President Hammack, could you talk about the importance of Federal Reserve independence? It's one of the main things that gives the Fed so much credibility here and abroad. So could you talk about what that means for markets, for the economy largely.

President Hammack: To me, a threat to Fed independence is a threat to low inflation. Achieving low inflation can mean making tough choices. It means that sometimes we have to maintain higher interest rates to ensure that we have lower rates over the longer and medium term.

And what is interest? It's the cost of borrowing money. If interest rates are higher, that's going to discourage households and businesses from borrowing, and that'll help bring down inflation. But those tough trade-offs can be really uncomfortable.

If we don't have independence, it likely means that we'll have higher inflation and higher costs. Over time, business leaders and politicians on both sides of the aisle agree that Fed independence is important to make sure that we can fulfill our dual mandate that we've been given from Congress. That mandate is to support maximum employment and price stability over the medium to longer term.

The Fed is accountable to Congress. The Chair, Jerome Powell, meets with Congress twice a year on what's known as his Humphrey-Hawkins testimony. That allows him to explain to our elected leaders about how we’re seeing the economy and where some of the challenges might be.

Having independence allows us to be free from short-term political pressures as we look to steer the economy to those dual mandate objectives of maximum employment and price stability. 

 Kyla: There still is some political influence in terms of nominating Fed governors and things like that - but a lot of people will call the Fed “unelected bureaucrats”. Could you talk about that?

President Hammack: I would say we're independent, but accountable. So the Federal Reserve system is set up of two main parts.

• One is the Board of Governors in Washington DC. Those people are appointed by the President and confirmed by the Senate.

• Then you've got 12 Regional Reserve banks across the country, one of which is in Cleveland. Those regional reserve bank presidents are appointed by a local Board of Directors. Those Boards of Directors are pulled from members of the community and business leaders to help represent that area.

So you've got a federated system. Together we form the FOMC, all 19 of us. The seven governors vote at every meeting. The President of the New York Fed votes at every meeting. He's the Vice Chair of the FOMC and then four of the bank presidents vote at any given meeting on a rotating basis.

Kyla: Your job as a president is to be in the community. You're really involved, you're hearing from constituents on what their needs are and then delivering that news. Is that the correct way to interpret your role?

 President Hammack: I'd say it's twofold.

• One is for us to gather information about how the economy is doing and to understand what the experience is so that when I go to Washington, I can accurately represent how people across Ohio, Eastern Kentucky, Western Pennsylvania, and parts of West Virginia are faring and I can make sure that I'm doing everything I can to help set up an economy that's working for all of them.

• The other is for us to be out in the community and understand what maybe some of the barriers are for individuals getting into the workforce. We spend a lot of time through our community development work, understanding what's happening both in the workforce development space with small businesses and with affordable housing.

Those are kind of three pillars that we spend a lot of time digging into to understand what's working and what's not working. We don't implement programs, but we do study what programs are working and we try to elevate and make connections, so we convene stakeholders across different groups to bring them together to help work on solutions to some of these core problems.

Staying Modestly Restrictive

Kyla:  It seems like you've been looking at some of the economic data and have said that it's more important right now to stay modestly restrictive. And of course, Chair Powell gave his Jackson Hole speech and said it might be time to cut - or at least hinted at that. Could you talk about what you're seeing in the data that supports the fact that you think it might be best to stay modestly restrictive right now?

President Hammack: This is a challenging time for monetary policy. We're seeing pressure on both sides of our mandate. But to me, what I'm mostly seeing right now is that inflation is too high and it's been trending in the wrong direction.

Inflation

Recent reports have showed that core goods prices are moving higher and that may be driven by tariffs1.

There's some debate as to whether or not that's going be a one-time move or more persistently, but more concerning is that services inflation has also been moving up. That is less likely to have been driven by tariffs. That's something that we need to watch closely.

When I talk with businesses in the region, what I hear from them is that they've done their best to try to buffer individuals from raising prices that they've been eating into their margins, but that's not really going to last forever.

We saw that kind of play out in last month's data of the CPI, which moved up modestly. But the PPI moved up even more. I do anticipate that that is probably going to converge at some point and the pricing pressures we're seeing may make their way into the consumer's hands.

The Labor Market

Right now, when I look at the labor market, to me it looks pretty balanced.

• We have seen some shifts in terms of the headline growth in payrolls that are being created. But a lot of that could be driven by what's happening in labor supply. So with the changes in immigration, you would expect that you need fewer jobs being created to maintain the same level of unemployment.

• We had one report in early August, which signaled that there could be some signs of slowing in the labor market because of the headline job numbers.

• But on the other hand, we still had an unemployment rate that was low and stable and right around my estimates of maximum unemployment.

To me, when I look at the balance between those two sides of the mandate, I think it's more important that we continue to put pressure on bringing inflation back down to target. I think we need to stay modestly restrictive to do that.

Could the Fed Be Too Late?

Kyla: The recent labor market report was relatively weak. The only jobs that are really being added are in healthcare. There is a risk that all of this expedites - that the labor market deteriorates very quickly. Then the Fed finds itself in a situation where they're too late to respond effectively. How do you think about managing that sort of risk? 

President Hammack: It's really about the balance of risks when we're looking at the overall picture and how we're setting monetary policy. As you rightly point out, monetary policy works with what we call long and variable lags, which means sometimes it takes a long time between when we make a rate change and what actually flows into the real economy.

We don't know exactly how long that's gonna take. We try to set policy not based on where we are today or where we were a month or a quarter ago, but where we think we're headed over the medium and longer term. So for us that requires really looking at forecasts of where we might be headed.

Right now, on the labor side, it's a little bit challenging to figure out what those forecasts should look like because we are seeing so many structural changes in the economy right now. But when I step back and look at where we are, it looks to me like we are still generally at a pretty healthy labor market. We may see the number of jobs being created coming down, but the supply of labor has also structurally come down.

A couple of other things that I look at are the (1) vacancies-to-unemployment ratio. That number has been generally pretty stable around one, meaning that there's just about as many unemployed people as there are jobs available. Sometimes it takes time for people to find their way into the right opportunity. That to me is a sign of things being in balance.

The other place that we look in Cleveland is (2) we've done analysis of worker notices, which is the Worker Adjustment and Retraining Notification (WARN) notices that come out that need to get filed ahead of larger layoffs. Those have not been trending upwards. They've moved up very slightly, but they're still within historical ranges.

So to monitor the labor market, we try to look at a broad confluence of those numbers pulled together. Then I add that with the conversations I'm having with businesses in the district. What I'm hearing is it took them a really long time to find the talent that they needed. They're loath to let people go unless they see a more significant downturn. So right now, to me, it looks like the labor market is pretty healthy and pretty stable. But as you know, there are definitely some things we need to continue watching closely for potential signs of slowing. 

The Slow-to-Fire, Slow-to-Hire Labor Market

Kyla: It's a slow to fire, slow to hire labor market. In my conversations with people, I've also heard this note that it's very difficult to find people that are trained properly for the job. When you put your Fed hat on, like how do you think about that? These restrictions to the labor market that might just be things like training.

President Hammack: It could be training. I think that's where some of the workforce development that we've talked about comes in. I think there's also bigger shifts in the picture like AI and other new technologies that are coming out which are going to shift how we think about things. The place where I've heard the most concern in hiring has really been around recent college graduates.

We've heard that they're having a much tougher time getting into the labor market. It is a low hiring, low firing environment - someone coined the term job hugging, right? Instead of job shopping, the people who have jobs are kind of holding them as tight as they can because they want to make sure they can maintain it.

But people who don't have jobs are struggling. We had an event that we call our Policy Summit in June, where we bring together a whole bunch of community development specialists and leaders across the country to talk about some of these challenges. They talked about how applying for jobs in this environment with the online technology that we have can be really challenging because you send out hundreds of resumes and oftentimes you get two or three responses. There's lots of things that just don't even send you a response when you're sending out your resume to try to reach out. That's a really challenging environment for individuals. 

The Impact of AI on the Labor Market

Kyla: It seems like AI is taking over job recruitment strategies and that AI is replacing the entry level workforce. How do you think about this massive technological change that we're all going to have to navigate? How does that impact how you think about the economy? 

President Hammack: It's definitely going to be a big change and what exactly it's going to mean is still uncertain at this point. Technological progress is really crucial for raising living standards and we've seen lots of different moments of technological progress over the past several hundred years, whether you look at the shift from horses to cars, steam engines, calculators, the Internet, and every time you have these types of new transformational technologies come on, you see some amount of shifting in the jobs. There are jobs that are being destroyed, but new jobs that are being created. What's really important is to watch is how fast is that pace is moving.

Are you seeing as many new jobs be created as jobs being destroyed, which would keep the labor market in balance? Of course, there'll need to be some solutions because the people who are losing their jobs may not have the skills for the new jobs that are created. There'll be some amount of worker retraining that's needed, and we at the Fed don't operate that, but we can help study that and help see what is working and what's having the most most impact and which are the most effective programs, and help amplify those so that hopefully more individuals can find their way back into the labor market, if that is how this progresses. 

Kyla: Have you seen any effective programs of retraining? 

President Hammack: We've seen a couple of things. There's an organization in Cleveland that we've spent some time with called Magnet, which is the Nonprofit Manufacturing Advocacy and Growth Network. They really work to help explain why manufacturing is a great set of opportunities and why those can be great high paying jobs. They work with local businesses to help provide them ideas on robotics and ways to implement AI and other types of machine learning to help support and improve their businesses.

There are places like community colleges too. I went and visited Lorain County Community College which is just slightly west of Cleveland. They've developed clean rooms where they're training individuals who come straight from high school, go through a 10 week program and come out on the back end of that with a reasonably high paying job and a pathway to continuing their education, continuing to grow and continuing to improve in the wages they earn in the roles they take on.

It’s About Trends, Not Just Point-in-Time Data

Kyla:  Last year when the Fed cut, the data looked a bit worse. How do you think about comparing now to then?

 President Hammack: To me, it's not just about the point-in-time data, it's really about the trend and where are we headed. Last year when we reduced rates by 100 basis points starting in September we had unemployment that was right around these levels. It's been pretty consistent between 4% and 4.3% over the past 12 to 18 months. We had inflation that had come from above 7% to below 3% and was trending in that downward direction.

So we had confidence that we would continue to make progress towards that 2% objective. Over the last 12 months, we've really made little further progress, and if anything, we're seeing inflation now tick back higher. That's a place that we need to watch.

The Two Speed Economy

The other thing I'll point to when I'm out in the district talking to individuals and businesses is I hear about a two speed economy.

1. I hear about people at the top of the wealth spectrum who are feeling really confident. They're maybe feeling buoyed by prices in the stock market that are supporting their IRAs or their 401ks.

2. But then I hear from lower income individuals at the bottom end of the spectrum and inflation continues to really bite for them. It means that their paycheck is largely going to housing and food and there's really not much left over for new clothing for going out to the movies for ordering in for a night.

We really have this disconnect in terms of what's going on in the economy.

Wealth Inequality

Kyla: When wealth inequality comes up like that it’s probably very difficult to make a decision. The economy is becoming more and more uneven. How does the Federal Reserve think about managing something like that?

President Hammack: Well, we really have one tool and that one tool is monetary policy, which is largely setting interest rates. We also have our balance sheet and we use our communications to help explain where we are and where we think we're headed. But monetary policy is not really well equipped to deal with the income inequality issues. That's really something that we leave to the fiscal policy makers.

Maybe it's a good time to talk about kind of the other four functions away from just monetary policy that we do. Monetary policy is what most people know us for - moving interest rates - but we have four other functions that really help contribute to how I see how monetary policy needs to be set.

1. Financial stability: This was the reason for our founding - to make sure that we can watch across the broad economy, see where there are risks and instabilities, make sure that we have the tools we need to help keep the financial system working, and really having a strong and healthy financial system allows us to implement monetary policy. If the markets aren't working, it makes it much more complicated for us to get our rate transmission into the markets.

2. Supervision and regulation: We oversee the banks and the financial institutions within our districts. Within Cleveland's district, there are about 250 institutions that we work with, making sure that these are stable strong banks allows them to provide credit to individuals and businesses, which is really the the growth engine of the economy.

3. Payment system: We process and issue cash to banks. I like to think of the Fed as being the bank for banks. We're where a commercial bank goes when they want to deposit their funds. We have to ensure that that system runs smoothly behind the scenes and that money can transfer amongst individuals, businesses, and financial institutions.

4. Consumer protection and community development: This is where we really try to serve the regional areas that we're representing, understand how the economy is performing for them, help highlight different ideas and solutions of where things are going. Talking with individuals out in the district what I hear day to day is that inflation continues to bite, that wages haven't kept up, and that they're feeling more and more stretched.

I was with a business in Wooster, which is a small college town in northeast Ohio, talking with some individuals who were working in a factory and they were talking about how they've always had a [$400] emergency fund, but that $400 fund isn't paying for what it used to pay for. It used to cover getting your air conditioning replaced and getting some small auto changes needed. Now it's just not stretching quite as far. Once you wipe out that fund rebuilding, it takes an awful long time and puts them in a more precarious position.

What the Stock Market Might Not Be Seeing

Kyla: So you're talking about these concerns that the everyday person is facing, but when you, look at the markets, it's just nonstop. The S&P 500 is skyrocketing. Do you think that there's anything that the stock market is missing?

President Hammack: Financial markets price risk, that's their job. It's the collective judgment of lots of different individuals that come together, but they still get surprised from time to time. I'd say there are two places in particular that I'm focused on where I think markets may be surprised in the near future.

1. The first one is really around Fed independence.

2. The second one is around sort of the overall outlook for the economy.

Over the last 40 years, what we've seen is long-term interest rates have continued to trend down and inflation has generally been low and reasonably stable. Part of this is because there's been widespread belief that the Fed acting as an independent body would be able to reduce inflation and be able to keep that contained. If we had a loss of monetary policy independence, that could threaten our ability to control inflation. That might mean that longer term interest rates rise and stay higher on a more sustained basis. Certainly, it could impact things like mortgage rates and 10-year [Treasury yields] and the longer end part of the curve. That could be pretty difficult for the economy to adjust to as you settle into that new normal.

On the more fundamental side of the economy, I do think there's a real challenge for monetary policy because we are seeing these competing crosscurrents on our inflation side of our mandate and on the employment side of our mandate.

Both of those could be under pressure in the near term, and so we need to watch closely how we balance that. As you pointed out, it does seem like there's a real disconnect between what I'm seeing in the financial markets, with the S&P 500 making new highs, and when I'm out talking to local businesses and hearing about how they're thinking about their customer bases.

The equity markets seem very optimistic about margins and the ability for businesses to continue to have robust demand, whereas when I talk to businesses on Main Street, what I'm hearing is a lot more caution and a lot more concern that maybe they can't push pricing any further. Their costs are going up. They feel like they need to raise prices to maintain their margins, but they're worried about demand dropping off if they do that. There's much more nuance and tension in what I hear from Main Street than I think what we're seeing from the Wall Street pricing. 

Kyla: Do you think that they know what is potentially at risk? 

President Hammack: The markets have had a pretty muted reaction. I think participants in the markets understand what it means. That’s the best I can judge from the modest yield curve steepening we've seen, which is the front end staying low and the back end going higher, which is what you would expect if monetary policy independence was being threatened because you might have more pressure to lower near term rates.

[The Fed doesn’t] control the back end of the curve, but if the market starts anticipating a higher inflation - and more risk of inflation becoming out of control - that could put more pressure on higher yields at the back end of the curve. I think that's something you would likely see if there was more concern about Fed independence.

As we talked about, we're independent but accountable. I think there's a lot of misconceptions about how the Fed operates. We try to get out there and explain who we are and what we do. But I recognize individuals have lots of things going on in their lives and we may not be first and foremost of their concerns.

Kyla: Institutions are pretty confusing to understand. It sounds like that there's higher concerns about inflation. You're watching the labor market very closely and Fed independence is top of mind. That's what you're going into the next few months really paying attention to, those three things.

President Hammack: I think that sums it up really well. 

Kyla: Is there anything else that you want to add or anything else that you wanna talk about?

President Hammack: I would just say thank you very much. I really appreciate the opportunity, um, to talk with you and thank you for all the work that you're doing to help young people understand what's going on in their financial health and what's going on broadly in the economy. I think it's critically important. I spend time trying to talk to my 19 and 22-year-old kids about it as well. But I have a feeling that putting it in your format probably resonates better. 

Kyla: Thank you so much for all that you do.

Four Takeaways

Four things stood out from this conversation with President Hammack:

1. Independence really matters. If politics push the Fed around, long-term rates can jump and stay high - pricier mortgages and car loans - and it can dent how the world views the dollar. If we don’t have central bank independence, it could lead to higher inflation and higher costs, as President Hammack said.

2. The Fed isn't unified on what comes next. While Chair Powell hinted at rate cuts in Jackson Hole, Hammack wants to stay restrictive to fight inflation that's creeping back up (Odd Lots interviewed some other Fed Presidents at Jackson Hole that said the same thing). There is genuine uncertainty about the economic path ahead.

3. There's a real disconnect between financial markets hitting new highs and what businesses are actually experiencing. The S&P 500 assumes companies can keep raising prices and maintaining margins, but Main Street businesses are telling Hammack they're worried about pushing customers away if they raise prices further. The markets could be underpricing two risks - an erosion of independence and a messy inflation/employment cross-current.

4. Recent graduates are struggling find work, for many reasons. There does seem to be a cooling labor market - but to President Hammack, inflation is the thing to pay attention to right now. Services are still getting more expensive, and what businesses pay (producer prices) are rising faster. That pressure often rolls downhill.

The bigger picture is that economic data is getting fuzzier just as the stakes are getting higher. Fed independence questions, inflation concerns, and labor market shifts are all happening at once. The path ahead requires balancing risks that pull in opposite directions.

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Thanks for reading.

AI and Workers

AI dominates the headlines with predictable extremes. Some days it’s market panic over Sam Altman calling everything a “bubble”2. Other days it’s horrific and morbid stories ending in death. The coverage lurches between utopian and dystopian framings - AI will revolutionize everything or destroy everything.

AI is at least four different transformations happening simultaneously - in how we work, how we invest, how we power our world, and how nations compete. We're trying to integrate an unpredictable technology into systems that weren't designed for it. What’s happening in this messy middle?

I wanted to know how people felt about AI. What do workers think about working alongside these new systems? So I asked them directly.

About 1,200 people responded to the survey in 24 hours. It was entirely anonymous, so I didn’t collect any demographic data, which is a limitation. The entire goal here is exploratory research - this is more meant to be of a preliminary exploration of how people are thinking during this time of immense change than to produce declarative conclusions.

The Labor Market

The labor market is already feeling the impacts of AI.

• Academic research on AI's labor impact keeps pointing to the same uncomfortable truth - disruption is already here.

• A recent paper titled Canaries in the Coal Mine found a 13% drop in employment for young workers in AI-exposed jobs. These are young people losing work today while others their age make millions building the systems that displaced them.

• The papers Working with AI and Voice AI in Firms explore how AI is taking over workplaces, and what tasks it might best be suited to.

There have been studies (specifically one out of MIT) noting that 95% of AI trials don’t really work… but it was about choices, not the technology. It’s still early innings.

The Market Narratives

The market thinks it’s going to work. Two things that the stock market cares about most are (1) rate cuts and (2) Nvidia. Nvidia is forecasting decelerating growth after two absolute ripper years. It could be a sign of what is to come for the AI industry broadly - a slowing.

• Sam Altman himself has described the current AI market as a bubble (the honesty is refreshing) acknowledging froth even as his own company drives it.

• He also claims that OpenAI will need to spend “trillions” on data centers to sustain ChatGPT’s growth.

• Frothy valuations + trillion-dollar capital needs = volatility and so investors bounce between between treating AI as a general-purpose utility (especially because OpenAI’s backup plan seems to be selling infrastructure services) and dismissing it as hype (the company still doesn’t make money).

Both markets - the stock market and labor market - reflect a deep uncertainty about whether AI is a genuine productivity revolution or just pure speculative fervor.

Infrastructure

But maybe it’s different this time? And part of the reason is because of the infrastructure build out. Data centers are the economy. It’s not like the Internet Bubble, where Pets.com disappears into a cloud of vapor and dreams overnight - there’s cement and land involved here.

• When AI companies struggle, they leave behind $7 trillion worth of data centers that still need electricity and maintenance, as McKinsey’s “The Cost of Compute” points out.

• Goldman Sachs’ “The AI Power Bottleneck” emphasizes a different bottleneck: electricity. AI datacenters could drive 100 GW of new global power demand by 2030, equivalent to 75 million American homes (!). That’s a huge physical commitment.

Companies building trillion-dollar data centers can't afford to wait for thoughtful AI integration strategies. They need utilization rates that justify the capital expenditure, which means pushing AI tools into workflows before anyone really understands the implications. The workers in my survey kept talking about “rushed implementation” and “overzealous corporate people” forcing AI into areas where it wasn't ready. The concrete creates its own logic.

Also, China is moving quickly.

Geopolitics

Sam Altman has warned that US export controls on semiconductors may not effectively constrain Chinese AI progress, since China can pretty much work around anything at this point. DeepSeek's recent models prove his point. Chinese labs are achieving competitive performance with less advanced hardware by optimizing algorithms instead of throwing more compute at the problem.

This creates an acceleration trap. The external threat justifies rapid domestic AI adoption, but that acceleration translates into exactly the kind of chaotic workplace integration that workers are worried about. The same competitive pressures that make AI a national priority are the ones that make its deployment at the workplace feel haphazard and worker-hostile.

Why This Matters for Workers

Each of these domains creates pressure that ultimately lands on individual workers trying to figure out their relationship with AI systems. The labor market research suggests disruption is already happening. The market needs to boom, probably. The infrastructure investments create pressure for rapid deployment. The geopolitical competition adds urgency that makes careful implementation feel like a luxury we can't afford.

But here's what all this macro analysis misses: how do actual people navigate these pressures? What do they want? What are they worried about? How are they making sense of working alongside intelligence that's powerful but unpredictable3?

So… how do people feel about it?

A Survey About Making AI Work for Workers

I asked 11 questions4, with multiple chances for fill-in the blank responses:

1. How familiar are you with AI tools in your industry?

2. Have you used AI at work in the past 6 months?

3. What’s the biggest benefit you hope AI could bring to your work?

4. What’s your biggest concern about AI at work?

5. What role should workers have in decisions about how AI is implemented?

6. How much do you trust your employer or organization to use AI in ways that benefit workers?

7. Has your employer provided training on how to use AI tools?

8. If you could enact one policy to ensure AI benefits and complements workers, what would it be?

9. What industry or type of work are you in?

10. Are you a member of a union or worker association?

11. Any additional thoughts

Their responses largely showed a workforce that's not totally enthusiastic nor completely resistant - but they are actively thinking through what it means to work alongside intelligence that isn't quite human but isn't really predictable either (the hallucinations, for example5).

And just to be clear, there is a personal side to all of this - a lot of people are using the technology for a form of anthropomorphic bonding and chatbot codependency6. OpenAI had to rollback the sycophancy - the model was too agreeable. People got mad at them, as the New York Times reported:

ChatGPT was “hitting a new high of daily users every day,” and physicists and biologists are praising GPT-57 for helping them do their work, Mr. Altman said on Thursday. “And then you have people that are like: ‘You took away my friend. This is evil. You are evil. I need it back.’”

Our relationship with AI is complicated. I am not going to focus on the more personal side of AI in this piece. The labs want it to be this huge, intelligent, math champion thing that takes over life and work, but most people just want a buddy that they can ask something like “whre shld I buy new dog food for dog puppy” or “help me analyze this dataset pls”.

In this tense in-between time, we have to know what people are thinking about it.

Executive Summary

• Familiarity vs usage: 85% are familiar, but even among the very familiar, more than a quarter don’t use AI at all.

• Hopes: Workers want AI to take over the boring parts of their jobs. The top hoped-for benefits were reducing repetitive work and increasing efficiency.

• Concerns: Workers are less worried about total replacement, and more worried about erosion of the good parts of their jobs.

• Industry differences: Concerns reflect professional identity: healthcare workers fear accuracy errors, teachers fear loss of connection, and tech workers fear diminished creativity.

• Decision-making: 62% want shared decision-making in how AI is implemented at work, and 15% want full authority. Fewer than 2% are comfortable with no input.

• Trust paradox: Most people “somewhat trust” their employers on AI. But in many industries, a majority report no trust. No industry reached a majority “complete trust.”

• Training gap: Only about 60% of respondents have received training, with especially low rates in creative industries (20%) and entertainment (5%).

• Policy demands: The most common requests were: training/upskilling funds, algorithmic transparency, and safety nets for displaced workers.

Questions 1 and 2: Familiarity and Usage

Most respondents who use AI said that they were at least “familiar” with AI tools (ranking 3 or above). And familiarity clearly drives some element of adoption: just 9% of workers who say they’re “not very familiar” use AI at work, compared to two-thirds of those who report being “very familiar.”

But the relationship isn’t perfect. There are an interesting bunch of people - the 26% who are “very familiar” with AI tools who don’t use it. These are people who know exactly what these systems are capable of and have decided, maybe, deliberately, not to integrate them into their workflows.

Questions 3 and 4: Benefits and Concerns

When asked what they hoped AI could do for them, workers overwhelmingly pointed to the perhaps boring parts of their jobs: reducing repetitive tasks and making work more efficient. The main hope that people have for the technology is that AI becomes a productivity tool that frees up time and energy for more meaningful work. Below are some quotes from the survey:

• If it can take away the paperwork, that’s a huge win. - Healthcare worker

• AI should be doing the boring parts so I can spend more time on the thinking parts - Tech worker

But those same workers are also worried about fewer career opportunities and a decline in work quality. In other words: even as they want AI to take over the drudge work, they fear it could take away the parts of their work that matter most for advancement and identity.

• “My worry is that overzealous corporate people looking to reduce headcount will force it into areas it’s not good enough at yet, and it causes major problems.” - Automotive engineer

• “Hospitality is already stretched thin. If they throw AI into scheduling or customer service, I’m worried it’ll just mean more stress for us when the tech doesn’t work right.” — Hospitality worker

Question 9: Industry Analysis

Breaking down the concerns and benefits by industry reveals even more. Most industries, like tech and finance and consulting, are most excited abut reducing repetitive work and increased efficiency and most concerned most about job loss.

But the concerns vary broadly - academia and healthcare are most concerned with a decline in accuracy. Design/creative roles are worried about creativity loss. Government workers are most concerned with bias.

Healthcare workers specifically are drawn to efficiency gains, but are very worried about accuracy, liability, and patient safety:

• “We have the option of using an AI scribe software that can also enter orders. Some providers love it and say they can see a lot more patients.” - Cardiology worker

• “AI in medical coding could save significant time, but I would not trust it on anything but simple cases. There is too much $ at stake to risk a denial on medium or high complexity case to allow AI to do medical coding unsupervised.” - Healthcare worker

• “Other things will have to change to allow for more AI like legal framework for handling malpractice in medicine for example. Is it on the physician to have quality AI tools or the hospital?” - Healthcare worker

Education is more worried about losing meaningful connection than about efficiency:

• “There’s talk at my school of teachers being forced to use AI to give feedback to students because, for years, we’ve complained about not having enough time to do our jobs. Instead of acknowledging the validity of that condition we’ll now be mandated to not use our skills as we wish…” - Education worker

• “AI in education is swiftly becoming an ouroboros. Students write papers with AI that teachers grade with AI or use AI to detect itself… The results are facile, simplistic and passable if you don’t really care about what you’re teaching. The overworked, underpaid teacher is tempted, but for me all the AI usage in education falls short of the goal of humanistic education.” - Education worker

Tech workers are conflicted - AI boosts efficiency (that is indeed the main selling point) but it also creates existential worries about skill relevance and creativity.

• “Use AI every day to code and my team is older and doesn’t understand truly how helpful it is. I work probably 15 hours on a 40-hour schedule. AI is the best thing to happen to my career but I now am kinda stuck because I don’t know my next career move. I am a developer but I wouldn’t pass a technical interview without AI, but that shouldn’t matter anymore?” - Geospatial Mapping

• “AI can be dangerous if we let it run free, humans should always be there to check and correct.” - AI worker

Logically, each profession's relationship with AI seemed to reflect deeper questions about professional identity and purpose. Healthcare workers worried about accuracy because accuracy defines competence in their field. Tech workers worried about creativity because creative problem-solving is their core value proposition. Teachers worried about meaningful human connection because that's what makes education more than information transfer.

People are are using AI as a mirror, reflecting back their own understanding of what made their work worthwhile.

Question 5, 6, and 7: Decision Making, Trust and Training

When asked the role that workers should have in decisions about how AI is implemented, about 62% of respondents want shared decision-making over AI implementation, 15% want full authority, and fewer than 2% are comfortable with no input.

Most people somewhat trust their employers to implement AI to benefit workers - on a scale of 1 to 3, with 1 being no trust and 3 being full trust, most people chose 2 - they somewhat trust their employers. But a few industries were majority “no trust”. No industry voted “complete trust”.

This reflects most AI conversations. Most people who have been experimenting with AI understand their capabilities, have an element of excitement, but don’t necessarily trust it (and don’t really trust their employers). We trust it to do specific, bounded tasks that we can verify. We don't trust it to think for us.

That’s the difference between functional trust and existential trust. Functional trust is that more bounded, verifiable, instrumental task - like “I trust it to transcribe a meeting, summarize notes, or generate test code - things I can check.” Existential trust is ceding judgment or cognition. - like “I do not trust it to decide how I treat a patient, structure a contract, or grade a student’s essay.”

A few quotes from a variety of industries emphasize this, ranging in trust:

• “If benefits of AI are shared with workers it can be helpful, but I don’t have much trust in tech CEOs to allow worker input into how it’s used. Unions will be necessary to ensure this.” - Tech worker

• “Trust is a factor — who can trust a billionaire? AI might be good for pulling up planning lists or Excel functions, but when it comes to real jobs you need humans.” - Transportation worker

• “People are far too trusting of AI, they seem to think it’s all knowing and that’s a greater issue in my opinion than any other since the management class looks at it as a replacement for people when in reality it’s at best a faulty assistant.” - Fintech

• “I work in a technical job, and struggle a lot with being able to factually trust AI. My worry is that overzealous corporate people looking to reduce headcount will force it into areas it’s not good enough at yet, and it causes major problems.” - Automotive Engineer

And so the key to building out trust might be a combination of shared decision making and training. Despite most people being familiar with AI and most people using AI, most people are not trained on AI.

• Only about 60% of workers have received AI training, and training rates are especially low in low-trust industries like Design/Creative (20% trained) and Entertainment/Film & TV (5% trained).

• Compare that to technology (60% trained) and consulting (58% trained) and it becomes rather clear where that low trust might be coming from.

So one way to build trust in these tools could be providing training.

• “I believe that AI can make most knowledge workers incredibly more efficient, like I am already experiencing in my day to day. I train my students not only to work effectively with AI, but also how to do so without decreasing other important skills which might get lost by using especially GenAI to execute “menial” tasks for them. - Physics, Machine Learning worker

• My job is pretty safe from AI. But I worry that the world is hurtling towards this mindset of scarcity, where AI is a replacement for humans. We should instead bolster the workforce by training people to use AI. It’ll improve the workers quality of life, while setting up a company for growth. - Research/Development/Academia worker

• “I really think training on information privacy and safety is most important. If we can keep information in a safe environment, then people can experiment, break stuff....in a safe way and learn how to implement for their own individual or department needs. But currently, I think line employees are loading "God knows what" into free AI models without understanding where the data is going.” - Finance worker

• “The way to protect workers is by training and upskilling. You can’t force a company not to innovate — the government should promote upskilling and give incentives to companies that complete courses and programs.” - Tech worker

• “We have to train people on the job — if they just rely on AI all the time, I worry about the level of learning happening. Mistakes will happen and most will burn out.” - Manufacturing worker

Question 8: Policy

When workers were asked what policies they actually wanted, the gap widened. In the open-text responses, three themes dominated:

• Training & Upskilling Funds - calls for employers (and government) to invest in programs that help workers adapt.

• Algorithmic Transparency - demands that AI systems be explainable and auditable, so workers understand how decisions are made.

• Transition Guarantees & Safety Nets - requests for income supports, severance, or job placement if AI leads to displacement.

And people have requests, specifically around training and upskilling.

• “Mandatory training on how to use AI for all staff to minimize the digital divide.” - Education worker

• “Exceptional training on how AI tools work, how to use them effectively, and how not to use them.” - Manufacturing / Supply Chain worker

• “I can’t believe I’m saying it, but mandatory trainings. AI adoption is happening, but without common understandings of uses/risks/benefits, gathering lessons learned, and without actionable ethical/privacy training.”- Government / Policy worker

They also want to see more transparency and oversight.

• “Organizations that implement AI should be transparent in their decision-making processes, and the review process should be easy to access (for instance hiring or promotional decisions).” - Transportation / Logistics worker

• “Radical transparency in the use of AI tools and algorithms to evaluate performance and worker efficiency.” - Tech worker

They would like to see attempts at protecting jobs or redistributing the gains from AI.

• “No layoffs based on projections for ‘efficient’ use of AI; collaborative training on AI and collaborative development of practices, policies, and applications for AI.” - Consultant

• “Severe tax punishments for companies who lay off workers to implement AI agents.” - Medical / Pharmaceutical worker

• “Either an increase in salaries or maintaining salaries while reducing work hours. If AI delivers on the promise to streamline things and boost productivity, the workers should receive compensation rates to reflect that.” - Design / Creative worker

But overall, they want frameworks.

• “Given the studies on how it is affecting critical thinking skills and the tremendous amount of it that is essentially stolen, I'd want to walk it back almost entirely and give policy-makers, workers, and scientists ample time to consider how it can be effectively deployed in the workforce ethically, without costing jobs.” - Finance worker

• “Mandate a ‘Holistic Congruence Model and Measures for AI Adoption,’ including board-level corporate structures, security, data, ML/AI, and ecosystem maturity.” - Consultant

And the demands make sense as things continue to speed up. Kimi (another AI lab that performs quite well) mentioned in an interview recently that they were handling the wheel to their AI for training and processing. No more humans. This creates an environment where there isn’t really people input, it’s just the AI building upon itself. The implications are clear there. These policy suggestions will be examined more in a future piece.

Question 10: Unions

Only about 8% of respondents in this survey were union members, perhaps a reminder of how small organized labor’s footprint is in much of the economy today. It’s hard to pull any meaningful takeaways from a small sample. Some of their thoughts below:

• As a Baltimore construction worker co-op rebuilding redlined neighborhoods, we actually think we are in a rare spot where AI can be used to empower marginalized workers and communities. - Construction Worker

• It’s very surreal seeing how AI is playing out while working at a public high school. - Education Worker

• While my employer is training us to use the AI, they are also setting unrealistic goals of task to be accomplished follow by a weekly report which is said to provide transparency but the data collected on our task / output doesn’t tell whole story just the story the department heads want to report. - Government Worker

• I'm deeply concerned about the lack of Junior engineering jobs since the rise of AI. I think one issue that hasn't been discussed a lot is when skilled workers leave the workforce, there's going to be less and less of a talent pool with experience to pull from. I also feel like all types of workers are expected to be doing much more work with less resources, and in some cases, AI doesn't help to fix issues, but individuals are expected to go faster. - Transportation and Logistics

Question 11: Any Additional Thoughts

The most important part of the survey was the open-ended comment box at the end, which I’ve pulled from throughout this essay, where I'd asked people to share anything else about their AI experiences that the formal questions hadn't captured.

I got hundreds and hundreds mini-essays (thank you everyone!!) that read like dispatches from the front lines of a cultural transition. People were clearly hungry to talk about this stuff in more nuanced ways than public discourse (or their workplace) typically allows.

AI is forcing everyone to articulate why they work, what makes work meaningful, and what parts of human capability they most wanted to preserve and develop. AI is making us reckon with what it means to be human, in a way that not many of us have ever had to do.

What to Do Next?

The conventional narrative about AI and work focuses on displacement and efficiency: which jobs will be automated, how much productivity will increase, whether humans will become obsolete. But I think the real story happening is about people figuring out how to maintain their sense of purpose and agency.

Too many organizations are treating AI implementation as a purely technical challenge rather than a cultural transition. Too many workers are left to figure out AI integration on their own, without much institutional support or collective wisdom. Too much of our public discourse remains stuck in binary thinking about AI as either salvation or threat, missing the more complex reality of how people are actually living with these technologies.

People are remarkably thoughtful about these challenges when given the space to be. They're developing creative solutions and collaborative approaches that point toward more sustainable forms of human-AI integration. But there has to be leadership from government, companies, and the AI companies themselves. They have to (should?) listen to the needs of the people that are the users of this product.

Whatever is happening in offices and schools and hospitals and design studios across the country isn't the one the headlines describe fully. It’s not just revolution or ruin. It’s the messy middle, where people are building new rules of work in real time. This is about people figuring out how to remain fully human while working alongside forms of intelligence that are powerful, useful, and different from our own.

Thanks for reading.

Two days ago, I fell off my bike. We were on an incredible trail, perfectly chunky with rocks and just wide enough. I took my eyes off the trail for a second - to ask if everyone else was enjoying the trail as much as I was - and the bike slid out from under me. I was totally okay, but the derailleur, the bike’s gearing system, was completely bent out of shape.

So there I was, halfway up a hill, with a bike that could only operate in one gear. I could pedal, but I couldn't shift. I could maybe move forward, but only with tremendous, inefficient effort.

And to carry a metaphor here - the US economy is sort of like that bike. It's moving, but its gearing system is completely out of whack. The US is operating with 3 broken gears that no longer connect. There are currently 3 Americas:

• America 1 (The Speculative Class): The first America is the speculative class, and its engine is artificial intelligence. The Magnificent 7 are spending over $100 billion a quarter on data centers, which are these monumental projects of hope. They consume vast amounts of capital and electricity, a place where money and power are absorbed in a high-stakes gamble.

• America 2 (The Real Economy): The second America is the real economy. With 75% of new jobs in healthcare and social assistance, our workforce is being absorbed by the essential but underfunded ‘maintenance economy’ of an aging population. While it props up the labor market, it fails to generate the type of wealth that fuels the stock market or long-term growth, as resources are poured into maintenance rather than creation.

• America 3 (The Memes): The third America is the bridge between the other two, acting somewhat as a psychological gold sink for those who are priced out of a house and a future. The money spent here is largely speculative and doesn't build a sustainable future (is memecoin investing productive, I don’t know) but it gives people a sense of agency and hope within a system that otherwise offers them little.

It’s a very strange world.

America 1: The Speculative Class (AI)

Let’s start with the gear that gets all the attention - the one that's supposed to be powering us into the glorious future, the world of AI.

AI is weird. Derek Thompson wrote a nice piece on the good and efficient parts of AI, noting that it’s making workers more productive (or at least, the workers think so), changing our language (delve), and absorbing a massive amount of cash. But there’s also the psychological impacts of AI:

• People are getting addicted to it and it could be breaking brains: OpenAI rolled out a new version of the model, changing some of its sycophantic tendencies (where it would tell you how smart and beautiful you were, not matter what you said). It was feeding people’s delusions and causing “Chat-GPT induced psychosis”! That’s not a tool that we need during the age of everythingspiracy!

• It could also making people stupider, inserting itself between us and the real world, creating a “technological wedge” as Ewan Morrison describes, and potentially (?) taking all the jobs (or at least the narrative of jobs) - outside of healthcare, at least.

• It is impacting both how students learn (perhaps, making it so they don’t learn at all) and the jobs they might get (perhaps, taking their jobs). And interestingly, in the chart below, OpenAI usage drops off around June 6th - around the same time that schools let out. AI is perhaps a school tool above all else.

Google knows this - they are providing Gemini for free for students for a year and investing $1b in AI and career training for every college student in America.

It’s just so strange! How we teach students are going to have to change (more written in-classroom essays and a bigger focus on process over outcome) but overall, everyone has more questions than answers right now - is AI the next iteration of the Internet? Is it simply here to give all of us infinite boyfriends and girlfriends? Will it replace the entire employee population at Salesforce? All three? Who knows! But while we're still figuring out if AI is breaking our brains, we're betting the entire economy on it.

AI is making things more expensive but it’s propping up the economy

AI takes a lot of power. It’s putting huge pressure on the consumer, with electricity costs ticking upwards at the same time that Trump decides there is no need for renewable energy. (Tyler Norris has a good read here saying (1) yes the higher electricity costs are data centers and (2) here’s how we can fix it).

And companies like Meta are essentially acting as a technological and financial arm of the government, fueling fiscal expansion, as Jason Furman described. Someone has to prop up the faltering US economy which is starting to buckle under slowing growth and tariff uncertainty. So we get data centers (which contribute $26 in taxes for every $1 in services they take)1. But who is all of this really for, you know?

I mean, financially, it’s working for the people in the business!

• AI capital expenditures are a large (and growing) percentage of GDP

• The Magnificent 7 have spent “more than $100 billion on data centers in the last three months alone” and “Morgan Stanley estimates that capital expenditures on AI could exceed $3 trillion in the next three years” according to Bloomberg.

• These companies are now 35% of total US market capitalization (Nvidia and Microsoft alone are almost 15%)

• The 10 biggest companies have driven almost all of the S&P 500’s growth over the past two years.

AI is spending more than consumers are, which feels fitting as it seems the end goal is to replace them (?). Again, who is this for? What is it really supposed to do? I don’t know if anyone really knows. I like elements of AI (I wish that everyone would stop being like “let’s replace artists” and instead say like “how can we help people order medicine) and think it has a future but it’s confusing.

The economy is dependent on data centers really working and continued consumption by the very wealthy as Heather Long wrote about recently. There is no in-between.

What about a world beyond AI?

And as we are funneling a ton of money into AI, at the same time, we have seemingly decided to pass off all other science and innovation to China. They are now completely winning - 13 of the top 20 research institutions in the world are now Chinese. The Chinese Academy of Sciences is No.1 on the 2025 Nature Index, beating Harvard.

It’s internal destruction. China is winning and the US is actively losing.

• RFK Jr just cancelled mRNA vaccine research, very real and important work that could have helped treat cancer.

• Science funding has been cut by 50% in the US. We were once the gold standard for important research and now that China is closing in, the administration has responded by gutting the National Institute of Health and the National Science Foundation.

• But the pendulum is of course swinging back - Doge fired 550 people at National Weather Service, and now there is special permission to hire 450 people to “relieve critical shortages”.

This weird one-step-forward-one-step-back is also why China is more popular than the United States right now - the US offers nothing more than AI and various types of gambling and volatile tariffs, whereas China has offered massive advancements in science and technology and a future that people can actually believe in. China is succeeding because of its outsized investment in the future and the US is failing. As Albert Pinto wrote “For the first time in two centuries, the West is no longer the leader in future technology, but the follower.”2

The US seems to be

• Simultaneously living in the past (the focus on the energy of the a different era, like fossil fuels and coal)

• Trying to manifest new technology to save itself in the future.

• But that technology requires the energy of the future - solar, nuclear (not on the moon, probably), and wind (Heatmap has a great read on that here).

We need to live in the future to build the future!

And Trump has now decided to tariff semiconductor imports at 100%, exempting companies that move production back to the US (the trick here is to simply announce that you’re moving production to the US). TSMC is exempted. Apple3 is exempted (Tim Cook gave Trump a 24-karat gold engraved trophy and promised to invest $600 billion in the US4). The Intel CEO was not so lucky.

What happens when you isolate all your trading partners?

The rest of the world is trying to move on without us (one example out of many - Japan is turning to Brazil for beef now). Tim Sahay and Kate Mackenzie wrote in BRICS in 2025 about how the world is trying to get away from the US at the moment:

The postwar geopolitical order rested on three pillars: American hegemony, the fossil-fuel energy system, and an open, multilateral trading order. America has now attacked each pillar at the foundation of its hydrocarbon global order. There are now two competing global models of energy and influence: one based on fossil fuels, one on green technologies and a new model of sustainable development. China’s technology is finding new markets around the world because lots of people want it. But there is so far no real wraparound support of finance, trade, and tech transfer—as no new international order of sustainable governance has yet been built.

This ties into what Gillian Tett wrote about a few weeks ago - the “core thesis is that China today has hegemonic control of manufacturing (via its dominance of key supply chain nodes such as rare earth minerals) but the US has hegemonic control of finance (because of the dollar’s reserve currency status).” The US still has the dollar, even after all of this. We are still the financial stronghold. But for how much longer?

As the US is ramping up “mercantilism and isolationism” to try and throttle China Tett notes that “in places such as Asia, cross-border trade is still rising; for many countries globalisation is far from dead”. Other countries know what works - comparative advantage, free trade, trading with China - and are following that!

The US seems to developing a data-center driven economy that works for the very few at the expense of many (Noah Smith has an interesting read on the risks of that here). Spend or sink. The problem is, the world might not need another round of software and information technology - and instead it might need the things that power those things like renewable energy and resource efficiency, which China is focused on and the image above shows.

In the meantime, America 2 grapples with a very different reality.

America 2: The Real Economy (Healthcare)

The second part of the economy is healthcare5.

• 75% of the jobs added in July were in healthcare. 

• Healthcare, social assistance and state and local government made up almost 70% of the jobs added in the past year.

• Most of the other sectors are shedding jobs (Manufacturing lost 11k jobs in July).

• Almost 20% of consumers have said it’s hard to get a job right now, up 5% from January.

• 20% of the US population will be over the age of 65 by 2030, meaning that that the care industry is only going to continue to grow

Healthcare is where the jobs are, but it’s not where the money goes. It’s Nancy Fraser’s crisis of care. This industry props up the labor market but not the stock market. Healthcare stocks are one of the worst performing sectors this year. That's mostly because healthcare costs are still unmanageable for both the patient and the service provider, and despite being the only sector adding jobs, there are still workforce shortages.

It’s a very clear example of the fundamental disconnect between the stock market and the economy. And that’s the important thing - we have these two parallel worlds, both:

1. Replacement economy in the form of what AI has promised itself to

2. Maintenance economy that is designed to care for our aging population.

This creates an interesting push and pull - the healthcare economy is exceptionally stable, dependent on an aging population and continued health problems (and solutions, like GLP-1 drugs). The technological economy is blowing through cash (Meta has about $12 billion in cash left after burning through $30 billion the last two quarters) and creating a product that hasn’t really found a fit quite yet.

So then a bunch more questions - Do we end up in a real world where people are at a cognitive disadvantage if they don’t use Meta’s AI glasses? What happens when many of the jobs are in maintenance rather than creation? AI can certainly help healthcare, and it is, but what happens next?

America 3: Memes

So we have AI, right, the big shiny thing that the US is betting its entire economy on as it isolates itself from the world - and then we have healthcare, where an extraordinary amount of resources are going to have to go (and again, AI can likely help here, but it will require an immense amount of labor). Joe Weisenthal, of the very famous podcast Odd Lots, wrote about the bifurcated economy, stating that the rise of healthcare and AI:

Makes it easy to envision what a stagflationary environment looks like: an economy that exhibits mediocre growth across many sectors, but which sustains a fairly high level of resource utilization, because there’s so much demand for social assistance (soaking up labor) and demand for electricity and certain types of industrial gear (soaking up capital) due to the AI buildout

But what does everyone else do? What about the trifurcated economy? What about people that are shut out by AI and don’t touch the healthcare economy? What do they do?

Bet?

Well… meme stocks have started bubbling again - acting somewhat as a psychological gold sink. Goldman Sachs Speculative Trading Indicator has hit its highest level in over a decade. American Eagle rocketed up 20% on Monday after Trump tweeted that their campaign was “the hottest ad out there” (it erased almost all of those gains the next day). But it’s more than just that.

This is the Labubu/Fartcoin economy - the attempt to maintain agency and community within constraints rather than spending energy fighting battles with Sam Altman who says things like“the whole structure of society will be up for debate and reconfiguration” due to AI. There are two core things to understand here"“

• Aesthetication: Labubu6 are functionally plush bunnies with plastic people faces and the pointed teeth of a jack-o-lantern. They are sold in blind-box packaging (you don’t choose them, you open a box and receive your fate) by a Chinese company called Pop Mart (There's something strangely poetic about importing economic nihilism from China too. We're buying blind-box toys from the country that just overtook Harvard in research output. They sell us $15 mystery boxes while they build the actual future!) Over the past six months, they’ve generated almost $1 billion in sales.

• Gamification: Fartcoin is a memecoin born out of an AI project called Truth Terminal. It launched in late 2024, reached a peak $2 billion market cap in January 2025, and now sits at about $1 billion. It increasingly appears to be an alternative to the risk-free asset of US Treasuries.

Labubu and Fartcoin are the economy people can actually participate in. They’re a form of symbolic participation, what happens when ownership is out of reach and when expression replaces accumulation.

Both represent a form of aspirational displacement. This is the idea that when you can't afford a house, you buy mystery boxes that might contain a rare variant and then that’s good enough. It’s a way to perform relationship to consumer culture. When you feel shut out of institutions, you buy meme coins that turn financial nihilism into a form of cultural expression.

Conor Sen has talked about this idea a lot, pointing out that consumption is contributing far less to GDP growth now than it was in the late 1990s. Nick Magguilli wrote about the idea recently too. He essentially says that people (who would normally buy a house) are throwing money into financial assets because housing is just too expensive.

John Burn Murdoch points out that young people are extremely unhappy in the Western world because society broke its promise of a home them - there is no faith in the future of the system, so people turn to ripping each other apart.

Memecoins and mystery boxes are a way for people to feel they are participating in the boom, even as they are priced out of its tangible rewards. When institutional financial advice assumes you have disposable income, long time horizons, and faith in market stability – none of which apply to most young people7 – meme coins become a rational way to engage with financial markets as you’re betting on volatility rather than growth.

Something that troubles me is the idea that maybe everything is becoming financialized because financial markets are the last remaining system capable of aggregating distributed information and enabling coordination at scale. Like obviously the above example8 is wild and absurd, but it’s a very efficient form of communication. And when traditional institutions (media, education, political parties, local communities) lose credibility, people turn to markets for economic coordination and for truth discovery.

And the institutions are losing credibility. Trump fired the head of the Bureau of Labor Statistics after we got a not great jobs report, which is (1) not great (2) threatens the trust of US data (3) subsequently threatens the trust in the US dollar and US Treasuries. The same day that happened, Federal Reserve governor Adriana Kugler resigned, giving Trump the chance to nominate a ‘shadow Fed chair’ which creates even more uncertainty (right now, two Kevins are in the running).

Las Vegas tourism is declining and people are like “oh the young Americans are at fault” which ignores that (1) betting is different than gambling and (2) the US is becoming Las Vegas - but everywhere. We are essentially building a glorified, speculative fantasy while China focuses on the foundational, "boring" work of scientific and technological advancement.

The Three Americas

So those are the three Americas. Stocks are just chugging along, driven by AI and memes. There is excitement over lower interest rates (at what cost, who knows) and liquidity. And the stock market can look past all sorts of problems, because all it really needs to care about is data center build out and memes.

“Real” companies like “carmarkers, airlines, and companies manufacturing household durables such as refrigerators and washing machines” have been absolutely hammered under tariffs and economic conditions.

As David Stubbs said “The hope is that AI investment will keep the economy going. But you have to acknowledge that some of the tailwinds from greater migration and greater fiscal spending have run their course.”

So, if we zoom out, the U.S. economy's broken gearing system is powered by these three separate things: institutional speculation on AI, the demographic obligation of healthcare, and the psychological relief of memes. In a healthy economy, labor builds the future, but in our economy, labor (as is necessary) maintains the aging population, AI speculation builds a future with a 'You’re Not Invited' sign for most people, and memes let us pretend we’re still part of it. We have created a world where the only things that grow are this fervent hope that AI works, nursing rosters (thankfully), and the hope that your meme coin might moon.

On that trail, Zach was able to fix my bike with his depth of knowledge and care. He essentially bent the derailleur back into place. The same thing exists for our economy - the knowledge and care here is incredible. The three economies can and must connect. We have the tools. We even have the resources - we're spending trillions on AI infrastructure, after all. Memes don’t have to be the only thing we believe in.

Thanks for reading.

Last week, I joined Jon Stewart on the Daily Show (!!) to talk about how we might think differently about the economy. This week, I spoke at the Aspen Institute about what it actually feels like for young people trying to live in said economy. Both events were extraordinarily interesting and brought up two main questions:

1. What is happening to the labor market right now?

2. What do we do about it?

The path of predictable progress is largely gone - the ROI on a college education is unclear, buying a house (if you don’t have vast family wealth1) feels incredibly out of reach, the rate of getting married and having kids has fallen - combine all that with the push and pull of the transformational power of AI and it makes it all that much more uncertain.

And of course, that framework is nothing new to anyone at this point. But in this piece, I want to examine the labor market as it actually functions today - less like a ladder, more like a slot machine - and the zero-sum logic that’s emerged in response.

The Rise of Zero-Sum Thinking

In 1957, the Soviet launch of Sputnik triggered a huge US response. It led to 3x funding for science education, created NASA and DARPA, and created massive investment in talent and infrastructure (and optimism). The US looked at a challenge and said: We can build our way out of this.

As economist Alex Tabarrok pointed out in his piece about the Sputnik moment, that kind of mobilization didn’t happen in 2024 when China’s2 DeepSeek AI surpassed OpenAI’s GPT-4. The US retreated instead of rallying. We looked at a challenge and say: They must be stealing from us.

This is a shift in how we understand problems and solutions. As Alex highlighted, research shows we're developing what economists call zero-sum thinking, or the belief that my success requires your failure, that wealth and opportunity are fixed pies to be divided rather than expanded. As Alex explains, zero-sum thinkers “see society as unjust, distrust their fellow citizens and societal institutions, espouse more populist attitudes, and disengage from potentially beneficial interactions.” It’s a form of despair that arises during times of economic uncertainty.

Platforms like Jubilee, where extremists debate for views, have become arenas for this despair. Mehdi Hasan recently debated 20 Far-Right conservatives in one episode, most of whom argued with emotion over data (as is common on both sides, Asimov’s cult of ignorance in action). It was rage as algorithmic fuel - Imani Barbarin called it the “memefication of politics”, which it largely is because it all becomes spectacle. This performative anger is a direct feature of the zero-sum mindset.

And at scale, this type of mindset can lead to a zero-sum trap as Tabarrok points out

The more people believe that wealth, status, and well-being are zero-sum, the more they back policies that make the world zero-sum.

This is what is going on right now. Putting aside however you might feel about the current administration’s policies, (1) trade wars (2) deportation quotas and (3) holding pens like “Alligator Alcatraz”3 and (4) gutting our science are all extraordinarily zero-sum approaches to building our future, especially when compared to the Sputnik moment of not so long ago.

The Sputnik generation organized society around creating abundance, a “creation” phase of infrastructure. They built universities, highways, suburbs, and systems that expanded opportunity. When they faced the Soviet challenge, they tried to make America richer rather than make the Soviets poorer. There was a belief in a positive-sum future, that everyone could grow together.

It’s the reverse now. We are in the “management” phase of infrastructure. Rather than viewing immigration as demand expansion and a chance for the pie to grow, we treat it as a scapegoat for wider systemic failures. Immigrants become a proxy war for how we think about identity, who deserves what4 and people on Jubilee argue over who gets the smaller pie.

In this management phase, we've watched student loans turn universities into profit centers. We've seen healthcare become a financialized industry. We've witnessed housing become an asset class for investors rather than, you know, homes for people to live in. Everything feels like it's being optimized for someone else's profit rather than expanded for everyone's benefit. And so young people (and everyone else living through this moment) have been taught to think in zero-sum redistribution rather than positive-sum creation.

Can we reverse it? How can we build a Sputnik moment again? It begins by tackling the very real challenges in our labor market.

The Labor Force

There are two important themes to understand about the labor market right now, as documented by Will Raderman in a guest post for EmployAmerica and John Burn Murdoch of the FT:

1. College graduates are struggling. “Since 2018, the unemployment rate of recent college graduates has generally been higher than the rest of the labor force.” - Will

2. Young men are struggling the most. “The rise in graduate joblessness is concentrated almost entirely among young American men.” - John

Both John and Will are quick to point out that the rise joblessness isn’t due to AI but rather

1. Sectoral changes, like the shift to a healthcare-oriented jobs which tend to be dominated by women

2. Supply and demand - there are a lot more college grads than there used to be

3. A softening of the overall labor market in our current slow-to-hire, slow-to-fire environment5 and

4. The techcession of the past few years, with higher rates striking reality into the heart of many of a vaporware company.

So, to repeat, recent college graduates now have higher unemployment rates than the overall workforce. This isn't supposed to happen. For decades, a degree was economic insurance - graduates always found work faster than everyone else. That’s what you pay for.

Is College Worth It?

But we're asking the wrong question entirely about college. Instead of 'Is college worth it?' we should be asking 'Which parts of college are working, and what does that tell us about the future?'

The math is brutal for most graduates. Boomers could trade 4 years of college for 40 years of middle-class security (more or less). Today's 25-year-old faces a negative net-present-value on that same deal. When the fundamental economic bargain breaks down, it flips everything - your discount rate, your risk tolerance, your entire worldview, again, leading to zero-sum beliefs.

But some parts of college are working, especially those that prepare for people to work in the healthcare sector as mentioned earlier. Look at these maps! In the 1990s, the top employer in each state was manufacturing. In 2024, it’s healthcare. That’s a different economy.

We are a maintenance economy, rather than a creation economy.

There are two important points to make here:

• Women are succeeding in this new economy: A lot of these healthcare jobs are going to women. As John reports, “almost 50,000 of the 135,000 additional jobs filled by young women graduates in the past year were in America’s healthcare sector — more than double the total number of additional jobs going to graduate men across all sectors over the same period.” This is partly because by 2030, 1 in 5 adults in the US will be over the age of 65 and partly because we are a rather sick and unhealthy country.

• Men are not: One solution floated to help men out is to bring manufacturing jobs back, a revival of the 1990s. The problem is that there are 500,000 unfilled manufacturing jobs open right now, so maybe we should focus on filling those with proper investment in training, rather than mining coal again.

These shifts underscore a fundamental truth: the economy has changed, jobs have changed. Jobs have changed. Colleges have to change. Training has to change. This is about aligning our education system with the actual structure of today’s economy. A real Sputnik moment wouldn’t just yell bring the jobs back! It would ask: what kind of future are we preparing people for?

The Hiring Process

And this is about how people get hired too, not just the jobs themselves.

Derek Thompson also wrote about this phenomenon a few weeks ago, noting that AI has essentially turned job applications into an arms race. Humans send thousands of tailored AI-generated resumes at job postings, companies deploy bots to screen them creating total vacuum of bots talking to each other (similar to how bots are enjoying the AI generated music on Spotify). It turns it into a numbers game.

Back in 2019, I applied to over 150 jobs when I graduated Western Kentucky University. LinkedIn had their little QuickApply feature, but I wrote so many essays, did many projects, and endless interviews. The entire process made me better, but I was rejected from most of the jobs.

I had a 4.0 GPA, was valedictorian with three majors, worked three jobs for most of my time at university, sold cars, ran D1 Track and Field for a year, and yet, I only got into my first job because the recruiter and some people at the company took a big chance on me (and I only got there because they had a blind resume process where they hid the school. Says a lot about a lot).

The only reason I got my chance - a truly lucky break - was because people bet on me. A computer would have instantly rejected me because I didn’t meet some arbitrary qualification. AI has spurred us right into the depths of what David Brooks calls the rejected generation - endless nos from platforms that are meant to serve as human interfaces (slot machine grabs across dating, investing, and now jobs), but really end up dehumanizing the whole process.

This is why young people are applying to 1,000 jobs - (1) to get one and (2) they're desperately seeking algorithmic validation to replace the human validation that the system has removed. The job search used to be a proving ground of sorts. The job search becoming algorithmic removes the human validation that made rejection bearable. When a human rejects you, you can tell yourself they didn't "get" you. When an algorithm rejects you, it feels like objective proof that you're insufficient. No wonder they're developing zero-sum mindsets and political radicalization.

This game fosters a dangerous proficiency illusion too, where both applicants (through AI-generated resumes designed to 'beat the bot') and companies (through AI screening that prioritizes keywords over skill) are optimizing for algorithmic compatibility rather than genuine human capability. It’s a performative dance for the machine, potentially eroding the very skills critical thinking and problem-solving needed for future human capital.

The Casino Economy

This is the casino economy in action. Again, just like dating apps and meme stock trading, the job market has created the illusion of abundance by replacing meaningful friction with meaningless volume. It has become a dopamonster, to borrow Scott Galloway’s word. More applications, more swipes, more trades - but every extra option raises the noise-to-signal ratio, making the median outcome worse for everyone.

A job market that once rewarded persistence now punishes it. A dating market that once rewarded genuine connection now atomizes it. Markets that once rewarded research and patience (sort of) now gamifies everything into day-trading dopamine hits. When the only lever left is 'push more buttons,' the rational response becomes zero-sum cynicism.

We've turned job hunting into a lottery where you buy as many tickets as possible and pray one hits and it is destroying our belief in meritocracy itself. When getting a job feels like winning the lottery6, what happens to the 'hard work pays off' narrative that held American society together? It creates the kind of thinking that feeds zero-sum thinking: “if I can only win by gaming a rigged system, then the system itself must be fundamentally unjust.”

In a true market, skill creates value. The casino economy is about simulated fairness masking an imbalance. Everyone feels like they could win - and this structure thrives on hope just long enough to drain it.

What Next?

The zero-sum trap is reinforced by institutions that feel broken, bogged down by the "management phase" of infrastructure where inertia takes over innovation. Systems that work are what make belief possible again.

Reclaiming Capacity

As Robert Gordon and Jennifer Pahlka wrote in The New York Times, a new playbook is emerging in “intelligent disruption”, and they highlight cities that are making sure “that our public institutions have the right people doing the right work” rather than “across-the-board cuts to programs and raise fees and maybe taxes”.

In Denver, Mayor Mike Johnston got rid of antiquated seniority-based layoff rules, instead empowering managers to weigh performance and ability. It’s never good when anyone gets laid off. But instead of the typical last to hire, first to fire, this playbook is focused on ensuring the public has the right people doing the right work, rather than simply preserving obsolete positions.

San Francisco's City Attorney, David Chiu, used AI to identify over 500 outdated requirements for staff reports (the thing that leads to public toilets costing $1.7 million.) The goal is to eliminate excessive regulation. Another thing that Pahlka and Gordon focus on is using technology smartly - New Jersey has trained their employees to use AI, rather than banning it entirely.

Redefining Prosperity

Another piece offered some food for thought (and threads of hope). Jonathan Rauch and Peter Wehner wrote on how to rewire this infrastructure of opportunity, addressing young people’s economic concerns, interviewing 19 democrats across a range of views. The main takeaway I got from their article is that Democrats need to (1) build more (2) talk normal (move past the memefication of politics and focus even more on shared, tangible realities and problems) (3) put forward proposals like building vocational-technical high schools and chartering new cities.

Affordability is the #1 issue.

Many young people supported Trump in the election because they believed he would protect the economy. It’s also why Mamdani won. Faced with rising inflation, a broken labor market, and deep frustration over student debt and housing costs, Trump’s narrative offered clarity: he promised lower prices, more jobs, and a return to order.

But by July, that promise has largely unraveled. His tariffs have backfired, shouldered by the consumer, raising the cost of goods like clothes and electronics, as the WSJ documents in their piece on Amazon hiking prices on most essential goods by 5% over the past 4 months.

For a generation that experiences policy in real time through TikToks about layoffs, evictions, and AI ghosting, the disconnect was immediate. His approval rating among those aged 18-29 has fallen by 44 points, with 72% disapproving. I am not sure if they will flip back. People voted for him to make things real again7, and instead he’s very much added to the fog rather than lifting it.

Some people seem to think that young people went further right - that “Trump isn’t conservative enough”. That doesn’t show up in the data either, with almost 2/3rds of young people thinking he has been too tough on immigration. But people just want things to be affordable again.

We’ve seen the predictable paths vanish, replaced by a zero-sum casino economy where algorithms mediate our worth and artificial scarcity is optimized for someone else’s profit. This mindset, amplified by a fractured political landscape, threatens to trap us in a cycle of anger, distrust, and disengagement. It's a stark reversal from the Sputnik generation's belief in positive-sum creation, where national challenges sparked mass investment in human capital and an expanding pie for all.

Everyone seemingly agrees on the path forward - reduce regulation, build things, invest in students and their outcomes, and it’s happening at the local level. Platforms should have some responsibility too, ideally. Tech companies8 are increasingly the Fourth estate of government as shadow policymakers due to their power in disseminating information, and we really have to treat it as such.

The young people applying to 1,000 jobs and getting rejected by algorithms are canaries in the coal mine of a society that's forgotten how to create rather than extract - and they've been trained to expect systems that work for them, not against them. If we can equip them to build for creation instead, we might just find our Sputnik moment yet.

Thanks for reading!

I had the chance to go on the Ezra Klein Show and talk with Ezra about all of the below. Please check it out, it was a lot of fun to go back and forth on all of these topics.

UFC at the White House

I flew to NYC last week, and the woman next to me on the plane was very nice. She spent the entire six hour flight scrolling through TikTok. It was strange to watch - I was watching Training Day and I'd glance over to see her consuming an endless stream of get-ready-with-me videos, a new thing every 3 minutes, a jump from one filtered person to another, each competing for the same scarce resource: her attention. She wasn't consuming content so much as being consumed by it.

Everything feels like that now? We're living in this constant scroll, trying to make sense of the world around us within a world confined by the limitations of an algorithm that doesn't care about truth, coherence, or consequences, only engagement.

And logically, this also became how we govern.

The Trump Administration has taken full advantage of this algorithm brain. We’ve entered the pure extraction phase of the economy, where things are created solely for consumption rather than purpose. I don’t mean this as a moralistic argument, it’s purely incentives, but it’s puzzling.

Take the picture below. This is a fan account for the Department of Homeland Security tweeting about the 2026 White House x UFC Fight Night. It’s a perfect image of the present moment. This is most powerful building in the world, a representation of freedom, lit up during an ominous storm, the flag drooping above, crowds gathered around a UFC-branded octagon - it’s creepy AI fever dream, but it’s very, very real.

It's the perfect crystallization of what America has become: the world's most powerful content creator. Roland Barthes, Marshall McLuhan, and Guy Debord would be totally floored here. This image truly has everything - the medium is the message and society is defined by a social relationship to images and the digital world is increasingly disconnected from the physical world, and it’s hard to tell what is real and what isn’t.

That image is about extraction versus creation and it represents a fundamental choice about what kind of economy we want to be.

Act 1: The Show

The US has become an extraction economy.

• We extract value from our existing position through dollar dominance, military supremacy, and technological leadership and now are choosing to tear down the foundations that created that position in the first place.

• We extract attention through spectacle without creating the trust that makes spectacle meaningful.

• We extract wealth from our own institutions without replenishing the capacity that generated that wealth.

• The UFC image captures this well - it takes the symbolic power of American institutions and converts it into entertainment value, with no consideration for what that conversion costs us in terms of credibility or coherence.

China, meanwhile, has become a creation economy1.

• They're building electrical generation capacity, training engineers, developing industrial policy that spans decades.

• They're creating an “electrostate” with an economy driven by the technologies that will determine 21st-century competitive advantage.

The tariff letters that President Trump sent around yesterday accomplish the same extraction mechanism too - telling other countries that tariffs “may be modified, upward or downward, depending on our relationship” is not a great way to do business2.

I keep thinking about something Ezra said in our conversation - Trump embodies the attention economy so completely that he's become indistinguishable from it. The stock market didn’t take the tariff letters seriously - because yes, narrative is capital and attention is infrastructure but there are real world constraints on all of that.

Eventually, the attention games stop working. What do we do next?

In Part 1 of this series, Trump, Mamdani, and Cluely, I mapped how attention became infrastructure, narrative became capital, and speculation became the operating system between them.

Here in Part 2, we will hopefully answer some more questions and provide some more solutions.

• What happens when an entire civilization optimizes for extraction over creation?

• What are the material consequences when your resource allocation system rewards virality over productive capacity?

China is building the infrastructure for 21st-century economic dominance. As we're financializing everything, they're electrifying everything. We're optimizing for attention while they're optimizing for capacity. We must figure out how to channel the dynamics of the attention economy toward creation rather than extraction.

So… how?

Act 2: The Dollar, Energy, and Trust

The Big Beautiful Bill

Somewhere along the way, the United States decided that the most sophisticated thing you could do with economic power was to financialize it and to create increasingly complex mechanisms for extracting value from existing systems rather than building new ones.

We took the incredible wealth-generating capacity that built America and the industrial logic that made us globally dominant and we turned it into a machine for redistributing wealth from the future to the present, from the young to the old, much funneling to the already-wealthy.

This is the governing philosophy of extraction. Take the Big Beautiful Bill that just passed. We're adding $4.1 trillion to the national debt (potentially $5.5 trillion) to fund tax cuts. We are funding it (or at least, some of it) by cutting billions from SNAP, stripping healthcare from millions of Americans, and slashing the National Science Foundation budget.

The BBB very clearly establishes that more money will go toward extraction versus creation. We will not beat China with tax cuts! And rather than building systems that create new wealth, we're building systems that redistribute existing wealth to those who already have the most political power.

It's completely economically incoherent and politically brilliant, which tells you everything you need to know about how our resource allocation system actually works. Senator Lisa Murkowski, who was the deciding vote, captured this approach perfectly when she said:

“Do I like this bill? No. But I tried to take care of Alaska’s interests. But I know that in many parts of the country, there are Americans that are not going to be advantaged by this bill.”

And that’s the conundrum of an extractive economy. Everyone protects what they have instead of incentivizing what they could make.

The Dollar

We're also extracting value from America's position in the global financial system without rebuilding the foundations that created that position in the first place. Karthik’s piece on Monetizing Primacy is a great read on the complicated relationship the Trump administration has with the dollar.

He writes about the stablecoin legislation that passed through the the GENIUS Act. It’s a pretty distilled version of extraction. The theory, according to Treasury Secretary Scott Bessent, is that stablecoins will create massive new demand for US Treasuries, maybe $3.7 trillion worth over the next few years, which is substantial! Sure!

• Foreign capital will buy these digital dollars

• Stablecoin issuers will pocket the yield

• And Treasury gets a new source of funding!

Stablecoins take advantage of an existing system3, rather than building upon it. And the dollar is very valuable to the United States. The problem is the Trump administration doesn’t know what it wants from the dollar. It both wants a weak dollar to encourage reindustrialization and a strong dollar to prevent inflationary fallout from tariffs. And the dollar, as Karthik explains, is valued by

• Fiscal and mon­et­ary policy inter­ac­tions

• The polit­ics of cent­ral bank­ing

• Expect­a­tions of the rate of return on Amer­ican assets.

So when you take that equation:

• Fiscal policy via blowing out the deficit with the BBB

• Monetary policy which is frozen because of the tariffs we can’t get an answer on

• The Trump administration actively threatening Jerome Powell

You get a weak dollar. And you get higher bond yields because everyone is like “um, hello?” That combination is a crisis-of-confidence signal.

If the trust in the dollar begins to erode and if other countries begin to believe the dollar is being governed by a reality TV feedback loop then the whole system begins to shift.

That will weaken the dollar too. A weaker dollar raises the cost of living, shrinks geopolitical leverage, and chips away at the safety net while making it harder for people to understand why things suddenly feel worse.

So to the point of stablecoins - it's a classic attention-speculation play to create a new financial instrument that generates engagement while (maybe) theoretically serving strategic goals. But the underlying mechanism is fundamentally extractive rather than productive.

Extraction only works for so long. Eventually, you have to create again.

Energy

And this creation begins with energy! At the exact moment when AI is creating unprecedented demand for electricity (and is the backbone of the entire S&P 500), America is dismantling its capacity to generate power through some of the cheapest, fastest-to-deploy sources available through the Big Beautiful Bill. As Thomas Friedman wrote:

There has never been a more intimate connection between the amount of cheap, clean electricity a nation can generate for A.I. models and its future economic and military might.

The bill ignores all of that and instead prioritizes the past over the future:

• Phases out clean electricity tax credits for wind and solar

• Adds complex restrictions to battery storage credits

• Bans fees on methane emissions

• Opens up federal lands and waters to oil and gas drilling

• Orders 4 million additional acres of federal land be made available for coal mining

All because clean energy is coded as lib or is aesthetically unpleasing or something. It completely misunderstands where energy comes from - 93% (!) of the electricity capacity added to the grid in 2025 will come from wind, solar, and battery storage as Rogé Karma writes in the Atlantic. Texas was the top solar state in the nation, adding 10,000 megawatts of power in the last year, mostly from solar-plus-batteries, and saw brownouts decrease as a result.

But rather than scaling this success nationally, we're making it more expensive going forward. Energy Innovation projects that Trump's bill will increase wholesale electricity prices by roughly 50% by 2035, with cumulative consumer energy costs rising more than $16 billion by 2030. Some 830,000 renewable energy jobs will be lost or not created. We are weakening our competitive position to play tribalism games in the name of the attention economy.

Act III: The Alternative

China vs the United States

And this is where the China comparison comes in. China, for all its (very many) faults, spends its money on itself. It builds infrastructure. It trains engineers. It electrifies villages. It rewards capacity.

By contrast, the US has the infinite money glitch as Soda said (the dollar) and we’ve used this vast financial and worldwide power mostly to subsidize stock buybacks (which certainly has generated value in its own way) but that differentiation is the key line between the US and China. Value is understood and developed differently between the two countries.

• Because of deindustrialization, the US has lost coordination capacity.

• And the world has changed since. We have a murky idea of what we are supposed to be building - maybe it’s a generative AI slop machine, maybe it’s the future of manufacturing, I guess the free market will decide.

But China has made the conscious decision to invest in people, knowledge, and systems like their next-generation high-speed train, the CR450 which will allow for the country to be connected even more - and encourage even more innovation.

They treat human capital as infrastructure, the same way we treat attention as infrastructure. David Autor, an MIT economist, did an incredible interview on the US-China race in manufacturing. The whole interview is worth a listen (essentially, the days of yesteryear aren’t coming back) and the problem we face is extraordinarily serious. It will take public knowledge to address and public money to address:

We’re in the midst of a totally different competition with China now that’s much, much more important. Now we’re not talking about commodity furniture and tube socks. We’re talking about semiconductors and drones and aviation, electric vehicles, shipping, fusion power, quantum, AI, robotics. These are the sectors where the US still maintains competitiveness, but they’re extremely threatened. China’s capacity for high-tech, low-cost, incredibly fast, innovative manufacturing is just unbelievable. And the Trump administration is basically fighting the war of 20 years ago. The loss of those jobs, you know, was devastating to those places. It was not devastating to the US economy as a whole. If we lose Boeing, GM, and Apple and Intel—and that’s quite possible—then that will be economically devastating.

China understands4 something that American policymakers seem to have forgotten: there has never been a clearer connection between a (1) nation's ability to generate huge amounts of electricity at affordable prices and (2) its ability to develop the AI systems that could determine future economic and military advantage.

As Autor said, the Trump administration is fighting the war of 20 years ago. We are memeing our way through a time of vast geopolitical change5, passing cuts to science and energy and cutting degree offerings all of which will likely kneecap our role in the world, and are for some reason presuming that stablecoins are going to save us6.

As Lu Feng said:

The past 500 years of world history show that an industrial power has never lost when challenged by a financial power, even when the financial power is also a global hegemon.

Antimemes

We all know that the attention economy erodes trust. It rewards the most dramatic claims, the most outrageous behavior, the most compelling narratives regardless of their relationship to truth or long-term consequences.

As Ezra and I discussed, it creates adverse selection: the people most willing to play by attention economy rules are often the least suitable for positions requiring patient stewardship of complex systems and the feedback loops are accelerating.

• As traditional institutions lose credibility, more activity shifts to attention-based platforms.

• As more activity shifts to attention-based platforms, the incentives become more distorted.

• As the incentives become more distorted, traditional institutions lose more credibility.

We're not just losing to China because they're good at what they do. We're losing because our own systems are increasingly optimized for outcomes that make us less competitive. You can't run an industrial economy on spectacle! You can't compete with China using tax cuts! You can't maintain global worldwide power through financial engineering if you're dismantling the productive capacity that makes you globally competitive in the first place!!

Nadia Asparouhova's book about antimemetics helps explain why we're stuck in these destructive loops. Antimemes are high-impact, low-transmissibility ideas. Compared to traditional memes, they are hard to spread because they're complex, counterintuitive, or culturally taboo.

The attention economy is hostile to antimeme development. It rewards ideas that spread quickly and generate immediate engagement, not ideas that require patient development over years or decades. Supermemes - those apocalyptic, high-transmissibility ideas like "AI will kill us all" or "climate change will end civilization" suck up all the cognitive bandwidth while the important work of building alternative systems happens in the shadows.

The result is a political discourse dominated by supermemes that generate lots of engagement but very little constructive action, while the antimemes that might actually solve our problems like “how to build industrial policy that works” or “how to design monetary systems for multipolarity” remain confined to small networks of specialists.

We're trapped in the “infinite AI TikTok slop machine” - an information environment that makes long-term strategic thinking nearly impossible while rewarding the kind of attention-seeking behavior that undermines our competitive position. We need more infrastructure around real ideas.

Act IV: The Way Out

The way out requires acknowledging that the attention economy's incentive structure is quite misaligned with the requirements of maintaining complex civilizations.

So what can we do?

1. Reintroduce friction: We’ve mistaken convenience for progress. Instead of making everything easier, we need to make important things appropriately difficult in the digtital world. Right now, the system rewards the performance of expertise rather than its development. AI makes that worse. We likely will have to rethink education - AI will be a part of it, and right now, the system rewards output over understanding, so of course students are Chat-GPTing essays. Some things will have to be harder than they currently are - maybe getting a college degree should require more than the ability to prompt an AI effectively. (maybe governing a country should require more than generating attention on social media.)

2. Treating attention as infrastructure rather than a market to be optimized. Right now, we treat attention like a commodity. It’s something to be mined, optimized, and sold to the highest bidder. But attention is infrastructure! It’s the invisible highway that ideas, identities, and institutions travel on. We have to invest in it like we would a highway. We’ve built a digital ecosystem that optimizes for engagement, not understanding. As boring as it is, we need new algorithms and to treat attention as a shared utility.

3. Boring things. Most of the ideas that will save us are boring at first. We need to rewire our entire grid, retrain an industrial workforce, and build factories We need more of the Manhattan Project, the Interstate Highway System, DARPA, etc - the confluence of public investment (and probably private investment at this point) and educational training systems that directly train people for the phenomenal task of rebuilding the physical infrastructure of the United States.

4. Rebuild systems that restore stakes. A functioning economic and political system doesn’t need to give everyone the same outcome, but it must give them a stake in the game. Today, vast swaths of the public don’t see policy as cause-and-effect. They see it as a performance, a branding exercise, a series of decisions made for someone else. That’s why Kansas farmers vote for a leader who guts their food export program. And it’s why young people identify as socialists- what’s the alternative? As Peter Thiel once noted: people without a stake in capitalism will rationally turn against it. What we're seeing now is that process playing out. Reestablishing stakes doesn’t mean giving everyone money in the S&P or whatever. It means showing them that effort leads to change and that policy is cause-and-effect.

One thing that I tried to get across in the Ezra interview (and he kindly asked me a followup so I could be clearer about it) was that there are two worlds right now, the digital world and the physical world. Floods just wreaked havoc on Texas, and Coast Guard Rescue swimmer Scott Ruskin rescued 165 people from the raging waters.

As Peachy Keenan said, the job Scott did has a few requirements - you must (1) love your country enough to be willing to put yourself in harm's way for it and (2) love your fellow citizens enough to risk your life for them.

That has nothing to do with the attention economy and everything to do with what it means to be a human. Its creation in its purest form - creating safety, trust, and meaning through competence and service. As C.S. Lewis said:

Since it is so likely that children will meet cruel enemies, let them at least have heard of brave knights and heroic courage

Many of the things we fund right now are completely killing us.

We need strategic investments in creation over extraction while acknowledging that the attention economy is a part of that. But it doesn't have to be the dominant logic of resource allocation. It doesn’t need to be so extractive.

Every day, people are making the other choice to create. They're installing solar panels and rescuing flood victims and teaching skills and building the infrastructure that keeps civilization running. They're choosing the hard work of creation over the easy work of extraction. We have all the pieces, we just have to realign our capabilities and our priorities.

Thanks for reading! I’ll be working on these ideas throughout the next several newsletters.

What Trump, Mamdani, and Cluely Reveal About the Attention Economy

Trump bombed Iran over the weekend and announced it via Truth Social. Maybe not the first time posting became policy, but it’s hard to find a clearer example. I was in the middle of the grocery store grabbing bananas when I got the notification, which just underscored how strange and disorienting this all is.

Yesterday, Zohran Mamdani won the NYC Democratic Mayoral Primary, a highly contested race that he ran with sheer narrative discipline and command of the digital. Even if you don’t like his policies (I think many of them are unworkable) the campaign was good! He walked the entire length of Manhattan. He was everywhere, all the time.

And finally, a few days before both of those, a startup called Cluely1 raised a $15 million round led by a16z2. The company’s modus operandi is ‘cheat on everything’. Like sure, of course. But a16z didn’t invest based on that! They invested based on Cluely’s attention capture capability! Cluely is good at getting people to pay attention to them and is largely copying the enterprise Jake Paul playbook (stunts, virality, nihilism, and a vibe-first narrative) for B2C AI apps. We’ve already seen “brain-rot marketing” take over culture so it was only a matter of time before it hit the startup world.

But these three things - geopolitical conflict, a mayoral primary, a startup raise - are indicators of something I want to tie a thread through in this piece:

• Attention is infrastructure: Determines what gets funded, elected, or build

• Narrative is capital: It drives flows of money, policy, and sentiment.

• Speculation is the operating layer between the two - it’s how belief is tested, priced, and converted into outcomes before institutions act.

What we’re seeing isn’t just a media trend. It’s a shift in the architecture of power. Attention → Speculation → Allocation. This is the new supply chain.

Traditional economic theory assumes information flows serve resource allocation. But increasingly, resource allocation serves attention flows. We've moved from an economy where attention supports other forms of value creation to one where attention is the value creation.

How to Think About Attention

Traditional economic substrates are land, labor, capital - bedrock inputs to make stuff. But now, the foundational input is attention.

Trump said he was going to take 2 weeks or so to think it through the Iran bombings… and then just did it? The NYT later reported that the decision to strike was influenced in part by how the Israeli campaign was “playing” on Fox News, so Trump’s response very much felt like a reactive spectacle3 rather than military strategy. And it played like theater!

• Iran knew Trump might do something because of his incessant posts.

• Military officials feared that Trump’s posts were compromising operational secrecy, so they ordered a diversionary B-2 flight to distract from the real mission.

• Iran simply moved their uranium to a different spot, and now we don’t seem to know where it is.

• It seems like the bombs didn’t really hit what they were supposed to?

• Iran retaliated a few days later by striking US Gulf bases signaling to the US ahead of time that the bases would be hit (I was also in the grocery store when I found out about this one)

• The fact that they didn’t close down the Strait of Hormuz is a sign that things might (?) be petering out from here (I write tentatively on the morning of June 25).

• Trump called for a ceasefire, and both Israel and Iran seem to be ignoring him

• He said China can continue buying Iranian oil, apparently lifting the sanctions?

• He got very mad (understandably) on Live TV

Trump only notified Republican members of Congress about the strikes, which isn’t great. It also seems that intelligence briefings said that Iran wasn’t actively weaponizing its nuclear program (making the bombing illegal). But, when Congress is as useful as a fish flopping next to a giant body of water, the law matters less than content strategy.

Trump yet again inverted system architecture - flipping how information and decision-making traditionally flow. Military strategy and diplomacy all became subordinate to social media dynamics. But he is moving on as if war is only a weekend thing. As his State Department spokeswoman said:

I’m not going to get ahead of the president or try to guess what his strategy will be. Things happen quickly and I think we’ll find out sooner than later.

And this gets into the tricky part of the attention economy - it’s easy to get eyeballs, sure, and people will do wilder and wilder stunts to keep eyes on them. But what happens when people stop paying attention? Here, it’s that Iran will likely continue pursuing a nuclear bomb because all they have to do to understand the narrative is watch the feed, and that holds heavy, heavy consequences.

Zohran Mamdani

There are many great essays on Mamdani (Derek Thompson just joined Substack!), so I won’t belabor it too much here. But yesterday, Zohran Mamdani won the NYC Democratic Mayoral Primary. A 33-year-old democratic socialist just beat a former governor - Andrew Cuomo - by running a campaign that got a lot of attention. 4.5 months ago he was polling at 1%!

Most of his messaging was about affordability (which is also why Trump won among young voters). He is a master of short-form video and podcasts, but he was also physically in NYC, again, walking the length of the city. Cuomo was advertising on TV and raised $25 million in the largest super PAC ever created in a NYC mayoral campaign (!) but that simply didn’t matter

And as many have said, Mamdani is the most Trump-like candidate *in messaging* the left has produced - he had a deeply online campaign, he did every interview he could, he has a loyal base (they knocked on 1.5 million doors!), and clear messaging.

Mamdani proved attention is the path to institutional override. Just like Trump, but from the other side.

The shift isn’t that surprising, and it will happen more now, on both ends. People are largely frustrated with the status quo. There is excitement in rule bending, like JD Vance sticking up a middle finger or Trump dropping an F-bomb on C-Span.

The ideas matter, sure. People voted for Trump because they wanted deportations and unwokeness but also because he was different and new. Mamdani promises affordability and fresh new ideas. It feels like change in a world where people are not listened to.4

How They All Tie Together

All three stories - Trump bombing Iran on social, Mamdani walking Manhattan on TikTok, Cluely’s raise - have one thing in common: the power came from attention, and attention came from narrative discipline.

It operates like a supply chain of sorts:

You can trace this pipeline through of our examples.

Trump's Iran strikes:

• Raw Material: Geopolitical grievance, national pride, fear of weakness.

• Processing: Posts cryptic threats, shares Fox News segments, teases retaliation

• Distribution: Amplified by cable news, echo chambers

• Speculation: People begin trading not on strategy but on vibes. Prediction markets react.

• Consumption: He bombs Iran.

• Pollution: Strategic incoherence, legal ambiguity, normalization of feed-driven warfare.

Mamdani's campaign:

• Raw Material: Affordability crisis, wealth inequality, housing despair.

• Processing: TikToks, interviews, walking Manhattan,

• Distribution: Lefty podcasts, shortform clips,

• Speculation: Can he actually win? Would free buses work? What if NYC really went full socialist? Young voters, disillusioned moderates, and donors place bets in energy, time, and belief (and in prediction markets5)

• Consumption: He wins the primary. Cuomo concedes.

• Pollution: Outrage cycles, factionalism, increased ideological sorting.

Cluely fits this cycle too. When a16z funds Cluely based purely on attention capture capability, they're legitimizing attention as a fundable asset class. That sends a signal to every other founder - build for virality, not just utility. It’s American Dynamism!

Attention is the raw material of economic, political, and military action. But speculation is what operationalizes that attention: the bets people place (emotionally, politically, financially) on what narrative will become real.

And in politics, this type of speculation has become the closest thing to agency for people who feel like they are no longer served by the economy. People speculate on ideas, personalities, etc. Why wouldn’t they? But when this happens, you end up with a system optimized for speed and virality rather than stability or accuracy.

And I think that’s why there’s an informal coalition that controls resource allocation now - podcasters like Joe Rogan, YouTubers like Mr Beast, guys like Steve Bannon and Tucker Carlson. Elon Musk, who has not said one word about what's going on, is a narrative thermostat. They are masters of speed and virality.

They all take that speculation, determine what gets attention, which increasingly determines what gets resources. The world is learning from them now - startups, politicians, geopolitical strategy. The "checks and balances" no longer come from Congress or the courts, but from the feed.

We’ve Been Here Before

What I'm describing isn't entirely unprecedented, of course. Many have discussed6. Back in 1971, Herbert Simon wrote in Designing Organizations for an Information-Rich World:

In an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.

Information abundance creates attention scarcity! By 1997 (!) Michael Goldhaber was pushed this further with The Attention Economy and the Net arguing that attention was becoming the new currency of the digital age.

The attention economy brings with it its own kind of wealth, its own class divisions - stars vs. fans - and its own forms of property, all of which make it incompatible with the industrial-money-market based economy it bids fair to replace. Success will come to those who best accommodate to this new reality.

Robert Shiller coined narrative economics, arguing that stories drive economic behavior. I think we are in a new iteration of all of this where the stories aren't just influencing economic activity, they are the economic activity. Attention is a precursor to wealth (in many ways) and speculation drives it.

Succinctly… everything feels like crypto now? Crypto doesn’t represent “real” value (some things in the industry do, but broad brushstrokes), but it synthesizes it through speculation and belief. Vibes, volatility, and mindshare, if you will. We're now living in a system where attention dynamics are the operating system for resource allocation, political decisions, and identity formation.

What Comes Next

This intersection of speculation and attention feels ignored outside of markets. And the question isn't whether we can build better housing or infrastructure - though we desperately need both. The question is whether we can build anything coherent when the resource allocation system rewards attention over everything else.

Because right now, the person who can generate the most compelling speculation about the future gets the most power to create it, regardless of whether they understand the consequences.

There's no neutral outside from which to observe these systems. We're building the tools that are rebuilding us, and it will have consequences across the board. There really isn't an offline anymore, just due to the administration. We're all participants in a cognitive economy that trades in attention, belief, and behavior. Shape the feed, shape the future. What happens when everything becomes an attention-speculation machine?

Next week: Part 2, I’ll attempt to answer that question and walk through what could be built and the generational implications. Subscribe to get that in your inbox!

The Volunteer State

I was in Chattanooga, Tennessee on Monday at the Litespeed bike manufacturing facility. I got to try welding - trying to lay the bead exactly right. You wear a giant helmet, which turns dark with the welding torch hits the titanium. It’s just you and this little beam of fire. It’s all you can see.

On Tuesday, I was in Nashville and the parking garage connected to my hotel caught on fire at 2 a.m. We were all shuffled outside, the air thick with burning rubber. You could hear the gas tanks explode. Some people thought they were bombs. The firefighters laddered toward black, billowing smoke, and doused the garage. We shuffled back inside an hour later. I stared at the ceiling until 5 a.m., got up, did some work, spoke on stage at 10 a.m. to a wonderful crowd about the economy for young people, and then drove home to Louisville.

I am currently trying to board a flight to get out West, and fuel is pouring of the wing of the aircraft. I will certainly miss my connecting flight. In fact, the flight is entirely cancelled as I edit this.1 So I write to you, dear reader, from the airport yet again.

While I was moving between these different grounded, very physical realities this week, the news feed was offering something else. Inflammatory information about the protests in Los Angeles2 (now spreading to more cities), removal of all CDC vaccine panel experts, the DHS memes, Apple’s big WWDC day, Zuckerberg AI army, China and the US trade (the deal is done now and the tariffs on China are monstrous) a cyberattack on United Natural Foods (which is why your local Whole Foods might be empty), Elon and Trump are friends again, plans to send people to Guantanamo et cetera. But inflation did come in cooler than expected, likely because the economy is not so healthy.

It’s overwhelming! It feels like a moment where all the contradictions are coming to roost. The structure of the world hasn’t suddenly changed, but the underlying stories feel like they are fracturing.

We are increasingly caught between a future promised and the present we're living through. We have apps that can summon autonomous vehicles in minutes while we have ICE raids escalating across the country3. AI evangelists talk about dancing in fields of daisies now that robots will do all the work while National Guard troops sleep on concrete floors without water (and their service members boo state governors).

If you wanted a perfect image of this contradictions (we are a visual first society after all), I think the burning Waymos in LA4 are pretty searing. People used the frictionless Waymo app and the seamless user experience that the company spent billions perfecting to summon an autonomous vehicle to their exact location, and burnt it.

It’s painfully on the nose, and I would hate to veer into detached-from-reality-metaphorical-thinkpiece but there is something relatively poignant about using the infrastructure of the promised future to reject that future and to also the refusal to keep pretending that this future arriving through our screens has anything to do with the reality people are living in.

The image of the Waymo on fire is a miniature of collapse, used to fuel calls for sending in more troops to LA than we have in Syria or Afghanistan. The contradiction becomes content, the content becomes justification for more contradiction. We scroll past the burning car to see arguments about whether the burning was justified, then scroll past those to see memes about the arguments, then scroll past those to see counter-memes. The cycle feeds itself!

And somehow, we've become remarkably adaptable to living inside all of this. We navigate between realities without stopping to notice how incompatible they are. There has always been the incredible difficulty of making real things, right, the patience and skill required to weld metal without burning through it, the complexity of keeping people safe during an actual crisis.

But now we layer endless innovation theater on top - revolutionary interfaces that solve no actual problems, liquid screens that fundamentally do not matter, promises of abundance that depend entirely on erasing the people who make abundance possible.

The contradiction isn't new. What's new is how smoothly we scroll between the real work and the performance of work, between the welder's focused attention and the algorithm's demand for distraction.

The Gentle Singularity

Which brings me to Sam Altman’s essay. I want to be very clear I wholly support AI as a complement to the human experience, but certainly not as a replacement to humans.

On Tuesday, Sam Altman, the CEO of OpenAI, published a piece called "The Gentle Singularity” (what a word combo). It opens with

We are past the event horizon; the takeoff has started.

He goes on to describe a future where intelligence becomes “too cheap to meter,” where AI drives scientific breakthroughs, and we’ll swim in lakes and wealth inequality will disappear. He writes:

In the most important ways, the 2030s may not be wildly different. People will still love their families, express their creativity, play games, and swim in lakes.

But in still-very-important-ways, the 2030s are likely going to be wildly different from any time that has come before. We do not know how far beyond human-level intelligence we can go, but we are about to find out.

Sometimes when I read pieces like this - which I take very seriously, because Sam Altman is clearly at the forefront here - I wonder what world they are writing about. Right?

What sort of world is this future landing in?

He states that “the world will be getting so much richer so quickly that we’ll be able to seriously entertain new policy ideas we never could before” which feels like it entirely misunderstands human incentives.

A few days before Altman published his gentle singularity, the Cato Institute released an analysis showing that the current administration's deportation plans will cost nearly $1 trillion. The "One Big Beautiful Bill" allocates $168 billion to immigration enforcement, enough to make ICE's budget nearly quadruple by 2028, enough to detain over 200,000 people at a time.

The AI systems Altman describes as ushering in this gentle abundance are being used to spread disinformation about the very protests happening in response to these deportations. According to a WIRED report, people are turning to ChatGPT and Grok to fact-check information about the LA protests, and the AI chatbots are giving them completely fake information. Grok claimed photos of National Guard troops were from Afghanistan in 2021 when they were actually from Los Angeles last week. ChatGPT misidentified current protest footage as being from Biden's Afghanistan withdrawal.

The contradiction here is that Altman promises intelligence will become abundant just as truth becomes scarce, and promises gentleness just as violence escalates. And of course he does, that is his job, those are his incentives, and AI money operates in a nonreality!

As Altman notes in the piece, the main goal of AI is to get it aligned to humans - and states that “social media feeds are an example of misaligned AI”. This is accurate. The abundance of intelligence is being used to manufacture scarcity of truth. The same systems that will solve humanity's problems are being used to obscure the very real human cost of current policies.

Altman's gentle singularity depends on ignoring the violent present that makes it possible. The AI systems he's building require massive data centers, enormous energy consumption, and human labor to train and maintain them5. But his vision of abundance erases all of that friction, all of that cost, all of those people.

Joan Didion wrote in the beginning of the White Album “We tell ourselves stories in order to live.” Altman's gentle singularity is one of those stories, a narrative that helps us make sense of technological change by promising it will all work out in the end.

But what happens when the story breaks down? When sitting in that airport, watching fuel pour from an aircraft wing while scrolling through news about AI armies and deportation raids, the gap between the promised narrative and lived reality becomes impossible to ignore?

Zadie Smith, writing about Facebook over a decade ago in Generation Why?, warned that digital life was already flattening our sense of self and “shrinking the range of human expression” to fit the logic of the platform. We are flat now. Our attention is disassembled and the contradictions are monetized. The stories we have are incompatible with the lives we’re actually living.

“From a relativistic perspective,” Altman writes, “the singularity happens bit by bit, and the merge happens slowly.” But the deportations are happening fast. The disinformation is spreading now. The contradictions aren't gentle.

The Performance of the Scroll

And what happens when you can't scroll past the contradiction anymore? When the promised future and violent present become impossible to reconcile?

To repeat - Sam Altman said that "social media feeds are an example of misaligned AI.” And boy is he right. The New York Times published a profile of Dominick McGee, one of the most prominent right-wing influencers on Twitter which perfectly illustrates the misaligned AI in action. McGee has over 1 million followers and is one of the most influential users on the platform. He earns about $55,000 a year for eleven hours of daily labor designed to spread outrage and disinformation.

This is the misalignment. Dominick McGee is responding perfectly rationally to a completely irrational system. The algorithm rewards outrage, so he produces outrage. His response makes perfect economic sense.

My professor Dr. Chhacchhi said that the opposite of rationality isn't irrationality, it's being normal. And this is what normal looks like now - isolated creators optimizing for metrics they don't understand and producing content designed to make everyone more confused and angry.

Ursula K. Le Guin wrote about Omelas, a beautiful, prosperous city whose abundance depended on one child suffering alone in a basement. Most citizens know about the child and accept this as the price of their perfect society. They understand that their joy depends on the child's misery, and they make peace with it. She writes:

They all know it is there, all the people of Omelas. Some of them have come to see it, others are content merely to know it is there. They all know that it has to be there. Some of them understand why, and some do not, but they all understand that their happiness, the beauty of their city, the tenderness of their friendships, the health of their children, the wisdom of their scholars, the skill of their makers, even the abundance of their harvest and the kindly weathers of their skies, depend wholly on this child's abominable misery.

But some people can't do that. They walk away from Omelas. They don’t know where they are going really. But they go. Many stay, justifying suffering of others as their way of life.

This bleeds into what Marx called this commodity fetishism, how we see the smooth interface, the autonomous car, the AI, but we don't see the social relations that make them possible. The data centers, the energy, the human labor all disappear behind the frictionless user experience.

When it's time for the machines to replace the people, or to acknowledge the invisible humans behind the systems that keep us fed and connected, we don't, because we've trained ourselves not to see what it actually looks like. We ignore what we don’t want to see.

Brian Merchant writes in 'Blood in the Machine' how the original Luddites weren't the anti-technology primitives of popular myth. They were skilled textile workers who understood exactly what the new machines meant. It wasn’t just “oh let’s automate stuff” it really was the destruction of their expertise and communities in service of capital accumulation. Luddites feared a particular kind of progress - the kind that annihilated skill, community, and voice in the name of efficiency.

Studs Terkel spent his career during a time of immense change (not too different from now) documenting in Working what happens to the people who do the work that makes everything else possible. He wrote:

This book, being about work, is, by its very nature, about violence - to the spirit as well as to the body. It is about ulcers as well as accidents, about shouting matches as well as fistfights, about nervous breakdowns as well as kicking the dog around. It is, above all (or beneath all), about daily humiliations. To survive the day is triumph enough for the walking wounded among the great many of us.

He interviewed hundreds of people whose labor gets erased from our stories about progress: steelworkers, waitresses, cleaning ladies, farmers, firefighters. He talks with Roberto Acuna, a farm laborer and organizer. Roberto says:

When people have melons or cucumber or carrots or lettuce, they don’t know how they got on their table and the consequences to the people who picked it. If I had enough money, I would take busloads of people out to the fields and into the labor camps. Then they’d know how that fine salad got on their table.

There's a violence in making people invisible, in treating their work as just an input rather than recognizing their humanity. There is violence in ignoring the humans behind the story, ignoring the child fraught with misery in the name of progress.

Steve Bannon described the Trump strategy as "flooding the zone” where you overwhelm people with so much stimulation that they can't focus on any one thing long enough to understand it. The stories like Studs told get lost. It's the same principle that drives social media algorithms: flood your vision with everything at once so you keep scrolling instead of stopping to think.

McGee is both the child in the basement and the citizen who's made peace with it (again with these contradictions). He earns money to poison public discourse while the platform extracts billions in value from the outrage he generates.

The immigration raids happening right now follow this playbook. As the WSJ reported, Miller tells ICE agents to hit arrest quotas, target Home Depots and 7-Elevens, create maximum visual impact. Deploy the National Guard, send in Marines, generate footage of militarized enforcement that floods our feeds and keeps us scrolling between outrage and justification. There are more troops than there are protestors and it’s costing $134 million. Optics are policy!

The system rewards the performance of enforcement over the reality of it.

If they really wanted to solve immigration, they would read papers like Exceptional by Design from the EIG team on improving high-skilled, legal immigration. They would offer fair hearings, deport actual criminals, arrest people who are violent during protests, and help people who have been trying to get citizenship for years who pay taxes (almost $100 billion in 2022) and work hard.

We are in a system that is designed to blind, distract, and blur - the infinite scroll. Nothing is too urgent and everything is equally urgent at the same time. Nothing lands. Welding is the opposite. It’s about focusing all your vision into a single point of contact, that small bead of fire between metal and hand.

The bike factory offered a different model too. Individual skill contributing to collective knowledge, the painter who understood which coatings would last, the assembler who could feel when the derailleur was properly aligned. Each person's expertise was visible, valued, and connected to everyone else's work.

There's something important in the difference between systems where you can see how your work connects to others versus systems designed to keep those connections invisible.

Most dystopian narratives focused on authoritarian control like Big Brother watching, governments suppressing information, which we are increasingly experiencing. But one could argue that the systems that profit by drowning us in information and platforms that make money by making everyone confused and angry are even scarier. The panopticon perhaps is less frightening than the slot machine.

It's extraordinarily reassuring that Altman says that social media feeds are misaligned. Perhaps that's a move in the right direction, that the endless scroll is not inevitable technological progress but a specific choice about how to organize human attention. And then there is this:

Even the AI systems themselves are resisting this! The scroll is rejecting itself.

Thanks for reading.

The United States of Gamblemerica

Jon Cohen begins his new book Losing Big with a story about Kyle. Kyle really liked sports betting, and it seemed like he was pretty good at it! He made thousands of dollars betting in January 2023 and felt invincible. Working from home, he kept one screen for gambling, one for everything else. A dual monitor life, if you will. The confidence from his wins rewired his entire sense of reality. When his boss disagreed with him about a project, Kyle's gambling success made him overconfident enough to push back in ways he never would have before. He got fired, spent his unemployment checks on more bets, lost thousands and thousands of dollars over six months, and moved back in with his parents. "Gambling tore me apart," he told Jon.

My Little Brother

Kyle's story is extreme, but it's not unusual. It’s what happens when you’re young, wired for risk, and the system is wired to reward it, until it doesn’t. My little brother Ryan is big on sports betting, like many 20-something year olds (he wrote a newsletter about it)2. When I asked him his thoughts on betting a few months ago, he said via voicenote:

Ryan:   Sports betting is definitely a form of entertainment for a lot of people, and I think it's pretty comparative to what we might associate Robinhood trading with. I think sports betting provides opportunity if used correctly. But I don't think it is used correctly. The marketing of it is super predatory. The whole idea is that once they get you in, you're not going to want to leave. 

He understands that "99% of people won't" approach sports betting systematically, that most people just "want to hit the big parlay... want to hit the jackpot." And he knows that the marketing is designed to hook you.

But he also sees potential value in (1) entertainment, or (2) sports betting as an easier market to beat than traditional financial ones if you really dedicate yourself. And gambling is fun, there’s a reason it’s one of mankind’s oldest activities! His voicenote ended:

Ryan: I really have slowed my betting just because it only has gotten progressively harder and I don't love losing money. And I really like the stock market too.

There is a very thin line between entertainment and destruction. Both Ryan and Kyle are smart, analytically minded young men. Both understood the risks of sports betting. The difference seems to be that Kyle crossed some invisible dopamine threshold where early wins rewired his decision-making entirely, while Ryan managed to pull back when things stopped working.

Young people have come of age during what feels like the gamification of everything and human psychological limitations becoming a source of value. Day trading has become TikTok content! Crypto has become a presidential talking point! Any sort of hobby that you have can become a monetizable side hustle - and you better be monetizing, buddy!

Sports betting is part of this transformation in how we make money off attention, confidence, and cognitive bias. The line between investment and speculation and entertainment has been deliberately blurred.3

Ryan:  I think people will just look at [sports betting] as form of lottery tickets. They might bet this big parlay and view it in the same sense of going of trying to win the Powerball or going and getting a scratch off.

Luckily, my dear friend Jon Cohen has his new book, Losing Big, detailing America's experiment with legalized sports betting (and is also the author of the excellent book For a Dollar and a Dream, about the American State lottery). I had the chance to talk to him about how blurry everything has become. Included throughout this piece are snippets of our interview.

In Dialogue with Jon Cohen

Kyla: Hey John, thanks so much for joining me today to talk about sports betting 

Jon: A really small topic with no direct relevance to everything happening in the world right now.

We were talking about sports betting, sure - but that's not really what we were talking about. We were talking about how a society decides what kinds of human weaknesses are acceptable to monetize, and how quickly something can go from scandal to infrastructure when there's money to be made. Throughout Jon’s book and our conversation, there are two big ideas:

1. Behavioral Design: The platforms are engineered to exploit overconfidence, dopamine, and a lack of friction - especially among young men.

2. Institutional Complicity: States, media, and markets helped normalize betting not by accident, but as a way to collect revenue.

Our interview began as most do, with me asking an impossible question:

Kyla: After writing this book and doing all this research, what is your big opinion on what sports betting has done? So just summarize your book in one sentence.

Jon:  Stories like your brother. I'm like, either okay, that's totally chill and awesome and that's fine. Or I'm like, okay, this is the first step to destruction. There is nothing in-between.

A study on NFL bettors from the 2023 - 2024 season [found that] 87% of bettor accounted for a total of 1% of sportsbook revenue, which means that the vast majority of bettors are able to play safely. Then there's that other percent of players, like 3% of players that account for like 80%+ of revenue. Some of them are really rich and good for them - they can spend their money however they want. Some of them are not really rich and their dopamine pathways are rewired and they're addicted. 

So Ryan - along with most people who bet on sports - is in that 87% who contribute almost nothing to the industry's bottom line. He's an entertainment user, someone who might bet on his favorite team or analyze conference matchups he genuinely understands.

But Kyle was in the 3%, fueling the entire billion-dollar infrastructure, like the celebrity endorsements, the stadium naming rights, and the integration into live TV.

But let’s back up to the beginning - how did we get here?

The History of Sports Betting

Kyla: Could you just talk about the history and how we've ended up in this situation where so many people are being impacted and everyone's just like… *shrugs shoulders*.

Jon: Really cool. Just ask a historian to summarize the history of a couple hundred year topic in three minutes.

Kyla: Should be easy.

Sports betting wasn’t always this mainstream. It wasn’t even legal in most states until about seven years ago! For most of the 20th century, sports gambling carried a moral stigma with legal penalties. Betting scandals, like the Black Sox throwing the 1919 World Series reinforced the perception that gambling corrupted the integrity of sports. This perception hardened into law in the 1990s.

Jon: In 1989, the state of Oregon tried to legalize - not even sports gambling, it was just like a weird parlay card game through their lottery - Congress and the sports leagues basically freaked out and passed the Professional Amateur Sports Protection Act of 1992, which didn't ban sports gambling but it banned states from legalizing sports gambling.

For decades, betting lived offshore, underground, or in Vegas. Then a 2018 Supreme Court decision overturned PASPA on states' rights grounds.

Jon: And because of this court legal quirk, the Supreme Court, uncorked the champagne bottle in 2018 and it has run rampant over society ever since.

It indeed has run rampant over society! We went from Pete Rose being a cautionary tale to announcers discussing point spreads during live games. Sports coverage now assumes you're financially invested. The language of sports journalism has absorbed the vocabulary of gambling - spreads, overs, unders, value plays.

Advertising had a lot to do with it. FanDuel and DraftKings, a duopoly who control 80-90% of the market, spent billions on a specific kind of cultural programming on redefining what it meant to be a sports fan.

 Kyla: FanDuel and DraftKings were dead in the water a while ago and now they've had this massive revival. So could you talk about the role that advertising has played in bringing this to the forefront?

Jon: FanDuel and DraftKings got every celebrity you've ever heard of - mostly like black male celebrities like Jamie Fox and Kevin Hart. I talked to someone who worked at in the DraftKings marketing department before sports betting was legal. So this is 2017 or so, and his theory is that they want to get people who aren't crazy, weird sports fans into sports betting. And the way you do that is you get people who are like Kevin Hart and JB Smoove and Jamie Fox, who didn't play college sports.

You want to make the make sports betting feel accessible, especially for these companies that are also offering online casino games, which are like insane and even more problematic and scary than sports betting.

But to this theory of normalizing, you want to just get people acclimated to betting with the help of Jamie Fox. And with advertising at the tip of the spear, turn our sports ecosystem into a sports gambling ecosystem.

Anyone can do this, especially you, just open up the app and put your money in. Your casual sports knowledge is valuable, young man! It’s normal. Sports are about gambling now. The result was complete cultural transformation in less than a decade - and it was for everyone.

Jon: Sports betting is really complicated and I still sometimes get confused about various line movements. Kevin Hart is there to make it an everyman's game. I do emphasize everyman. I think that's part of the process again, the acclimation, the normalization and letting people get used to it as part of their sports viewing experience.

It’s all about building out the Sports Experience of gambling while watching, and doing it at the click of a button.

Jon: The 30,000 foot level goal is the normalization of sports gambling - or even the normalization of just a second screen experience where you're watching TV over there and you have your phone open with your sportsbook open on the same side. All advertising is meant to build familiarity and enthusiasm for the brand, but it’s also as much about just normalizing this activity.

A lot of people were not gambling before 2018. It was too scandalous. It was too hard to access. You had to buy Bitcoin and transfer the Bitcoin to cash and then gamble with that. But now you can just use your phone, use your debit card, use your PayPal account and they are trying to normalize that.

Previous eras had gambling, sure. People have always bet on sports, bought lottery tickets, speculated on markets. But never before have we simultaneously decided that every opinion should be monetizable (prediction markets), every social connection should generate revenue (dating apps), every creative impulse should become a side hustle (creator economy), every moment of boredom should be captured for advertising dollars (infinite scroll), and every sports opinion should become a financial position (sports betting). I do this! We all do!

We looked at the full spectrum of human psychological experience and asked: how can each of these become a profit center?

The State, The Platform, and the Hen House

Cultural normalization via two screens is only half the equation. For sports betting to become infrastructure, it needed political legitimacy. When Jon started researching how states legalized sports betting, he expected to find a story about regulatory capture like “Local Lawmaker Gets Hoodwinked By Sophisticated Lobbying Campaigns and Caught Flat-footed by Industry Promises They Didn't Understand”. He found something worse.

Jon: The case study I have in my book is about Colorado. There was a lawmaker in Colorado who's genuinely really into sports betting and was happy to go along with basically whatever the companies wanted. So this was not, as I was expecting, like state capture and lobbying. It was basically the hens enthusiastically opening the doors to the hen house.

Sports betting became policy because it promised money during COVID. Lawmakers needed revenue without raising taxes. Betting looked like an easy win. It wasn’t.

Jon: A lot of states passed sports betting during COVID when they had more acute financial needs and they were basically being offered a free source of revenue that didn't require any taxes. Why wouldn't they say yes?

What elected official wants to be the one who said no to free money during a budget crisis? What lawmaker wants to explain to constituents that they opposed something that could fund schools or infrastructure without requiring tax increases? But the revenue math never worked.

Kansas expected ~$100 million annually but collected $12 million in 2023 - less than half of one percent of the $2.8 billion wagered according to the Washington Post. Arizona projected $100 million but got $26 million. Colorado expected a 10% effective tax rate but promotional deductions cut it to under 5%.

Jon: You'll be shocked to hear that's not exactly what FanDuel and DraftKings promised when these states were considering legalizing in the first place

States themselves have become gamblers too, in a way!

Jon: Red and blue lawmakers alike have shown that they're just total suckers when it comes to gambling revenue. They'll just say yes to anything because it seems too good to pass up.

As Jon argues in his lottery book, the real problem isn't individual, it's institutional:

Jon: The thesis of my lottery book is that it's easy to look down on lottery players for being irrational and stupid for wasting all their money on these hopeful impossible dreams of a lottery ticket. But the only reason we have lotteries in the first place is because lawmakers and taxpayers wasted their impossible dreams of a tax free bonanza for the state on a lottery ticket.

So first of all, that's why I don't call a lottery a stupid tax because we're all stupid and we just condemn it when it's poor and non-white people who are buying lottery tickets. So I think if you want to distribute the blame it lies a little bit with these companies for these false promises.

States become stakeholders in an industry built on extracting money from their own citizens. The worse people like Kyle get at gambling, the more money the state makes.

The Dopamine Business Model

We tend to think gambling danger lives in losing streaks and desperation, but Kyle's story shows how success becomes the actual problem. The confidence that comes from early wins creates the sense that you've discovered some edge that separates you from all the other suckers.

Jon: You win your first bet, and you get really high off of the dopamine from it. That's how they get you. That 'I won my first bet on Marquette, so I must be awesome at sports betting'— [bettors] don’t realize that's actually the dangerous part in how they get you.

Kyle made $4,000 in January and felt "invincible." That confidence might have made him bold in betting, but it torched his work, his relationships, and his entire sense of reality. When his boss disagreed with him about a project, Kyle's recent gambling wins made him overconfident enough to push back in ways he never would have before. He got fired.

Jon: The FanDuel ad right now is Never Waste a Hunch - [making you think] that you know more about sports and you can leverage that to make money. Seems like a really easy trap door to fall into, like it might lead to problematic play down the road. 

Platform economies have collapsed the distance between self-expression and market participation. A hunch becomes a commodity and a casual thought like “I think the Knicks are going to win tonight” becomes something to be priced. Something that shouldn’t be wasted!

And what if the platforms aren't neutral markets rewarding good analysis? What if they’re designed to exploit your belief in your analysis?

When Jon talks about how dangerous early wins are, he’s really describing the gamified version of self-confirmation. You feel like you’re right, and that your rightness should scale. It’s a statement of sorts: I know something. I see something. And that makes me valuable.

Jon: It's at your highest winningest moments that are the most dangerous. This is the design of the No Sweat, First Bet promo because they want you to win your first bet. This is literally the plot of the Gambler by Dostoyevsky from 50 years ago - when you win your first bet is how you build out the sense of overconfidence that will be really hard to shake

The marketing of sports betting is very precise: young men like Kyle (and Ryan) who are statistically prone to overconfidence, hit during the exact developmental window when their prefrontal cortex is still forming and their financial lives are most fragile. 39% of men aged 18-49 now have online betting accounts. And they bet. 

Jon: The impacts are being born disproportionately by younger men - the rates of problematic or hazardous gambling or even just having a bad week and losing a couple thousand dollars more than you intended to, which is probably the most common sort of harm and negative side effect.

Polling indicates that pluralities of young men between the ages of 18 to 35 say this has happened to them at least once: that they've been unable to pay one of their bills because of gambling losses. If it's happening to that many people, there's clearly some phenomenon going on, something that is rooted in both gender and society. And it's not just a coincidence anymore.

Pluralities of an entire demographic unable to pay bills because of gambling losses. For college students, the environment creates what Jon calls "trip wires everywhere." Sports culture, peer competition, underdeveloped impulse control, and apps designed to prey on overconfidence.

Jon: It seems like drinking, right? Just to take the college student analogy, which is you can drink safely, you can even drink a lot and it might give you a hangover, but it's not going to have any long-term consequences. You can also drink and even just one night of unsafe drinking can ruin your life in the same way that gambling can for a young person, right?

[In gambling] you either you lose literally all your money and you can't pay your bills or it can start a process of addiction that lasts a long time. College students are in an environment where sports are central, they're surrounded by culture, let's say at a fraternity house, by other young men who also love sports. And they're encouraged to prove that they're smarter than their friends about sports by betting on sports because they can make money off of it. And you can just see all of these things alone might be okay, but they're all compounded together.

How do you exercise personal responsibility against a system designed by teams of behavioral psychologists and data scientists specifically to defeat your capacity for rational decision-making? I genuinely don't know.

The Language of Individual Responsibility

One thing that clearly frustrates Jon is how the industry weaponizes the language of personal responsibility:

Jon:  I'd love to actually talk about the phrase, please play responsibly. I think each of those three words is so interesting. It's like the warning labels on cigarettes, which is just ingeniously worded and so insidiously worded. It's like “Okay, please Kyle, I'm asking you to play responsibly. Putting the onus on you as a result to be the one in charge of your own play.” They can't even say the word gamble! It's not even please gamble responsibly! It's like play. It's fun, it's light, it's easy. This is not gambling, it's just playing. And then responsibly, same thing. I think the true function of responsible gambling campaigns and ads is to put the onus of responsibility onto the individual rather than the billion dollar corporation that is offering them the chance to bet on Malaysian women's doubles badminton at 3am.

I don't want to say people don't stand a chance, but again, there's just all these like landmines or trip wires or however you want to put it in front of people that both make it easy for them to get addicted, and then when they do, it's basically implying that it's their fault and that they should have been more responsible.

Kyla: How would you phrase it to capture the corporation's responsibility?

Jon: That's a good question. I don't know. There are people who do this who think about responsible gambling and how to improve responsible gambling all the time. And no one listens to them, but they do have actual ideas about campaigns. I don't know if I'm smart enough to have an off the cuff amazing advertising copy.

Kyla: Yeah. Maybe it's like It's Our Fault.

Jon: Don't gamble, asshole.

When Kyle lost his job, his savings, his ability to function, the message was that he should have played more responsibly. That this was his fault. It’s complicated. Traditional gambling required physical presence, social interaction, choice. The current system eliminates all friction, all social context, all natural stopping points.

Jon: So the word that's used in the subtitle of the book is Reckless—and not because gambling is reckless, but the way we rolled it out in the United States and the fashion in which it has been set up here is reckless. I'm quoting here from a 1976 gambling Congressional gambling commission - but you know that gambling is inevitable, right? As a human activity, as a human pastime.

Also I think it's fun, right? Not everything that's fun should be legal, but I think gambling does happen to be fun. The question is like “Okay, just because something's fun, should that mean that you should be able to bet in the middle of the night on like Malaysian women's doubles badminton through the state of Colorado?”

That to me is where you get past the point of oh, this is inevitable, so we might as well legalize and make money off of it. We are now inculcating gambling and creating a new generation of gamblers and soliciting gambling that wouldn't have been happening otherwise. 

Many people compare it to other vices, but Jon points out that gambling is a very specific type of cognitive capture.

Kyla: That's the loop of gambling, right? You're like, “oh, I'm in the hole. I just need to gamble some more and I'll get out of the hole.” It's such a nasty cycle.

Jon: It’s unlike drugs or alcohol in that way. There's no reason that you'd expect “oh, if I have another shot of vodka, it will cure all the negative effects of my alcohol addiction”. Theoretically, like if you hit the Milwaukee Bucks over tomorrow night, it could wipe out all of your debt. So you just keep chasing and keep chasing.

Kyla: Yeah. And you never really get there, do you?

Jon: I have yet to find a bettor who went down so far, got even and then was able to stop. This one guy profiled in the book got down a lot of money. He basically broke even. But he was like, no, I was, I used to be up $40,000. I need to get back up $40,000. And then of course, it's chasing that last $40,000 that he quote unquote lost, that he runs back in trouble and falls right back into debt and the whole cycle begins again.

The addiction is built around a logical premise, that somehow the next bet could actually solve all the problems created by previous bets.

Jon: What I'm saying is that has always happened. There have always been Kyles in American history, but never has the government and corporations made it so easy to have that exact experience and to have it from their couch.

The Human Cost

The worst-case scenario is documented in places that got there first.

Jon: Gambling addiction is the addiction most closely associated with suicide compared to every other directly, formally categorized addictive behavior in the diagnostic and statistical manuals. And this is what sparked the—we'll call it a reckoning—over gambling policy and over legalizing online gambling in the United Kingdom: a wave of suicides of young men who had developed gambling addiction."

The UK data: young men with problem gambling show 9x higher suicide attempt rates. Public Health England estimates 409 gambling-related suicides per year in England alone.

Jon: So that's the absolute worst case scenario is basically a lot of young men taking their own lives because of gambling addiction in the sense that if they were to disappear, their gambling debts and their addiction were to disappear. Once you unleash gambling [it could] lead to increased rates of people taking their own lives.

And then working down a couple layers of harm, as illustrated in these two SSRM papers that came out over the summer, increased bankruptcies, increased credit card delinquencies, reduced investment in the stock market and reduced savings among families that bet a lot of money. We are already seeing direct evidence of that. Just financial insecurity or people wagering their financial futures, quite literally. You're probably more qualified than me to know what the long-term consequences of that are of a 20 something year old losing all their money but I know it's not good I'll tell you that. 

Kyle moved back in with his parents, his career derailed, his finances destroyed. But he survived. Many don't.

What Comes After Sports Betting?

New players have emerged with even more aggressive and exciting models.

Jon: There have been all these big gray market gambling operators that have rolled out under the guise of prediction markets. You can bet on the NCAA tournament in all 50 states, even in states that haven't legalized sports betting.

Kyla: The Robinhood-Kalshi agreement.

Jon: Yes, which apparently received the blessing of the CFTC, which I have no idea how. I'm all for the shitting we've done on DraftKings and Fanduel, but I think there's a chance that within a few years we will look at them as the most benign and responsible providers of sports gambling.

Kalshi and Robinhood are the tip of the iceberg when it comes to offshore sportsbooks or this Sports Illustrated branded peer-to-peer betting program that might be being rolled out that is claiming that it can exist by being totally unregulated because it's peer-to-peer rather than with a house.

Kalshi x Robinhood represents something potentially more… interesting than traditional sportsbooks because it's wrapped in the language of financial markets rather than entertainment. They're not running a casino, right, they're building a financial exchange. They don't set odds; they facilitate trades between users.

It's Uber logic: we're just the platform!

If you can eventually bet on everything from the weather to election outcomes to celebrity behavior through the same interface you use to buy stocks (which is an interesting and engaging thing to do) - where do we even go from there?

Jon: DraftKings and FanDuel have built the noose that'll be used to hang them. They normalized betting as a practice as something that's a part of American society over the last seven years. Why should we be surprised that there are going to be innovators and other companies that are trying to disrupt the framework that they're building and that [these companies] are going to be more aggressive, are going to try to be less regulated and be more aggressive in their pursuit of customers and in their offerings?

What makes the newer platforms particularly concerning is their lack of even the minimal safeguards traditional sportsbooks maintain.

Jon: As totally ineffective as I think the responsible gambling campaigns are from the big companies, at least they have them. At least they're trying. At least they have people at their companies who are well-meaning and will show up when a regulator says, 'Oh, we need to talk to you about your practices.' Whereas some of these other companies aren't even gonna have that.

So I'm a little sympathetic to these companies because again, I think there's a chance that they might look like the most responsible providers, but they're also responsible for the situation in the first place because of how fast they wanted to move at the beginning, and how recklessly again they tried to proceed.

If uncertainty of Kyles everywhere can be monetized, why limit it to sports? Why not monetize every form of human uncertainty - political, cultural, personal, financial? Why not turn every moment of doubt into a transaction opportunity?

How Do We Fix This?

Kyla: We're going to have to totally revamp the curriculum for kids. It's going to have to be gambling literacy and porn literacy and AI literacy and deep fake literacy. There's just going to be a whole new world. I do think the 25 to 35-year-old range is a guinea pig for all of this stuff. My point of hope is that we'll take the lessons learned from the consequences that have been bestowed upon this generation and hopefully the kiddos coming along won't be so fried.

Jon: A journalist I talked to once called it a nation of beta testers. It’s a generation of beta testers.

Kyle and Ryan are both guinea pigs4 for what happens when every dopamine pathway becomes monetized. Kyle and Ryan are both full of analytical confidence, competitive drive, technological fluency and it serves them really well in other contexts. Kyle got caught in the machinery. Ryan managed to recognize when to pull back - and that’s good. Tests help you adapt and learn and develop immunity. There is hope!

Jon: I don't want to be another liberal who's like everything's bad and nothing is good. I do think that the cultural work would be really important and would be really impactful.

I do think there are some concrete ideas that would actually make things safer that would remove some of these trip wires and these landmines. I don't think you should be able to bet on minor league British Darts. I don't think you should be able to bet as much as you want without ever having to provide proof of income and provide proof of how much money you have.

I do think that a destigmatization effort or a counter narrative to the advertising would play a big role. I think it could and should be part of high school curricula to talk to kids about gambling... we try to give them some counter narrative so it's not, 'Oh, Jamie Foxx is gambling on a piano, it's really cool, I should try it.'

We need gambling literacy alongside digital literacy, financial literacy, media literacy5. We have to understand how these systems work!

Jon: Even just telling people how that process works—that when you win your first bet, that's actually the dangerous part, that's how they get you—I don't think people realize that. The house always wins, which is true in this case because if you do start winning, they'll just limit you and limit your gambling. So you don't actually have any prospects of making money in sports gambling, and that should be your mentality going into it.

Jon’s book is incredible, and it opened my eyes to the very complex problem we have before us. I don’t know much, but what I do know is that sports betting isn't really about sports betting. It's about what happens when we reduce all friction and turn uncertainty into a profit center.

Each platform promises control, skill, edge and all are designed to extract maximum value from your inability to stop. Exploitation is in the language of freedom!

We are all living in the experimental phase of an economy built on extracting value from human psychological vulnerability6. We've built a democracy that literally depends on citizen irrationality for some parts of revenue, then wonder why our political discourse feels increasingly unmoored from reality. Everyone is responding to incentives, all of the time. But the incentives are increasingly misaligned.

The house always wins, you know? But what happens when the house is everywhere?
In your pocket, your feed, your brain. And what kind of society are we building if it’s powered by our worst instincts?

Jon Cohen's book "Losing Big: America's Reckless Experiment with Sports Betting" documents America’s experiment with sports betting and is available wherever books are sold.