New from @Stripe Economics today:
One of the biggest labor market uncertainties is whether AI will displace human work at scale. Evidence so far is still early & mixed. The story of travel agents—a clear case of tech displacement—is instructive. And not entirely bleak. 🧵 /1
Just begging everyone to recall that "how to win elections in New York City" is not really a problem that Democrats have.
This essay by @alexolegimas is the best thing I've ever read on why AGI won't lead to mass unemployment. A compelling argument backed up by substantial empirical data.
The results of the Renters Rights Act:
- mass evictions as landlords sell up
- huge fall in the number of properties available to rent (flat hunting is worse than ever)
- landlords/letting agents intensely vetting tenants
- mega-landlords taking over the market
- traditional student lets effectively banned
Good for renters with £50,000 in the bank ready to buy. Bad for just about everyone else.
The consequences were obvious to anyone who has studied economics and yet Ministers just didn’t listen.
And now we have politicians calling for full rent controls. It beggars belief.
https://www.thetimes.com/life-style/property-home/article/renters-rights-act-uk-2026-m2bd9l97g
It's become common lately to hear people say that rising attainment in English schools has been bought at a terrible cost - that of rising mental health problems.
How true is this? Is it fair to blame Gove-era curriculum & exam reforms for increased anxiety & unhappiness?
I dig into the international data to see what it can tell us...
https://substack.nomoremarking.com/p/do-knowledge-rich-curriculums-cause
NEW ODD LOTS:
@tracyalloway and I talk to @alexolegimas about what economists might be getting wrong about AI and white collar disruption, and how to most clearly understand what jobs are at risk https://podcasts.apple.com/us/podcast/alex-imas-on-why-economists-might-be-getting-ai-wrong/id1056200096?i=1000762116378
Strikingly, young women are *a lot* more negative about the opposite gender than young men.
✴️U30 women are 3x as likely to hold a negative view of young men than the other way around
✴️Just 35% of u25 women hold a positive view, only 11% a very positive view
ANGRY YOUNG WOMEN by @emilylawford and @Scarlett__Mag
It was a Wednesday night and seven members of the University of Leeds’ feminist society had invited me to join their book swap. I asked how they felt about the young men they knew. “I don’t care for them,” said a girl called Ruby imperiously. “They’re not bad people, but they refuse to call out their friends who make other girls uncomfortable. They’ll laugh at jokes that are sexist, racist, homophobic, they don’t care about political issues… I don’t think they like women a lot.” If a man is attracted to you, she said, he might talk about things like toxic misogyny. If he doesn’t fancy you, he won’t bother. “I feel like a lot of it is quite sexually motivated with men.”
I asked if they’d consider dating a man with different political views. They all immediately said no. “I don’t think I’d even be friends with one,” said one girl. “They don’t see you as human.” Only one woman, Evelyn, admitted to having male friends (though she was worried this made her a “pick me”, trying too hard for male attention). Evelyn was concerned about what the men she knew were watching online. “The stuff that’s being said about women is crazy,” she said. “They’re getting all these reels, talking about, like, bad stuff about women. And I get reels of women saying bad stuff about men. I try to think, not all men are like this, but…”
On the internet, women and men have never been more alienated from each other. While the toxic, often hard-right politics of the manosphere have been exhaustively documented, the new generation of female influencers are nearly as extreme – just on the other side of the political spectrum. The “femosphere” spans a range of tones: there are misandrist dating coaches who urge women to reject men altogether, and more explicitly progressive content creators who cover global and domestic politics.
Exclusive polling by Merlin Strategy for the New Statesman reveals that young women, aged between 18 and 30, are by far the most progressive demographic in the UK. Young women are 26 percentage points less likely to feel positively about capitalism than young men, and much less likely to feel the economy works in their favour. Gen Z women are more likely to support causes such as feminism, environmentalism and anti-racism than young men. They also feel much more negatively towards young men than young men feel about them.
I spent the last few months in search of the new left-wing young women. It wasn’t difficult – they were everywhere. But it all felt impossibly bleak. They weren’t excited about their futures. They didn’t like the men they knew, or the idea of those they didn’t. Men were just a threat who had the potential to harm or trap them. This will almost certainly make relationships harder: fewer than half of young women feel men understand them. Young women are much less likely than men to date people who disagree with their politics. People will get lonelier, and angrier. Young women are twice as likely to not want children as young men. And it’s getting worse. Women under 25 are most likely to believe things are “stacked against me, no matter how hard I try”.
A significant majority of young women feel isolated from the rest of the country. The two main political parties aren’t reaching out to them specifically. Many women told me they feared a Reform government pressuring them to have babies. Many say they will vote for the Greens in the upcoming local elections, but few seem to believe that will make a difference. They don’t feel represented by mainstream politics, and they don’t think anyone cares.
Cover art by Carl Godfrey
I'm joined by @jburnmurdoch to discuss AI's impact on the economy, the widening ideological divide, declining birth rates, and the affordability crisis that's creating some of the most extreme demographic distributions of wealth & opportunity in history.
https://hiddenforces.io/podcasts/who-wins-and-who-loses-in-the-ai-economy-john-burn-murdoch/
An increasingly coherent picture of the impact of AI on jobs, by @jburnmurdoch @ft:
1. New Fed paper by Crane and Soto now confirms with official labor force survey data what private payroll analysis was showing: roughly 500,000 fewer coders are working than pre-LLM trends would predict.
2. Argues evidence consistent with my work (with Lin and Wu, link in my pinned post) on weak/strong bundles: junior developers and contractors hold "weak bundles" (their work is mostly standalone coding that AI can substitute directly), senior developers hold "tight bundles" where coding is combined with domain expertise, judgment, and cross-functional responsibilities, making substitution much harder.
3. Freund & Mann and Gans & Goldfarb add a second lens: what matters is the value of the tasks that survive automation. Remove coding from a senior role and you free up time for higher-value work; remove it from a junior role and almost nothing remains.
https://www.ft.com/content/b69f8599-eaf1-477a-a5a8-60a715e56a04?syn-25a6b1a6=1
“Rather than being primarily about ideology, the manosphere is a contest over who gets to define success for a generation of boys actively searching for an answer.” Superb weekend piece by @S_VanTeutem @FinancialTimes
https://www.ft.com/content/a00cba0a-3218-49a7-bb59-2fa968d49db1 via @ft
Very happy to share a new paper with Guido Friebel, Yao Huang, Jin Li, and Andrew Zhang on how AI could change the structure of internal labor markets.
We show that cutting junior hiring when AI arrives may weaken the pipeline that creates future seniors and lead to “lost cohorts” of juniors and cycles of shortage and glut over time.
The AI job loss story is all about bundles by @jburnmurdoch @madhumita29 in @FT's great The AI Shift newsletter.
"Between the now-consistent picture on junior coding employment and the expanded framework of jobs as bundles of tasks, it feels to me like we’re developing an increasingly coherent picture of AI job displacement." writes @jburnmurdoch.
One important nuance I'd add is that task bundling is important not just for thinking about "job displacement" -- it also implies many workers can experience "job disruption" even absent full-scale displacement as wage returns to different skills shift as AI leads to work tasks being reorganized.
With shout-outs to the recent papers by @crane_leland&Soto, @lugaricano-Li-Wu, @joshgans-& @avicgoldfarb and @lukasfmann& myself on Job Transformation (thank you!).
This is correct. Extraordinary that we have this game changing moment unfolding in front of us and most elite discourse is still fake news about AI water usage or three-year-old angst about hallucinations.
Important new Fed paper on coding employment https://www.federalreserve.gov/econres/feds/files/2026018pap.pdf
One of the largest spills of untreated wastewater in American history happened while an environmental review process held up sewer line repairs because they were studying risks to a flower and a bat.
We now have an answer to the question of "is NYC just doing good social media posts about service delivery, or is service delivery actually changing?"
While social media is polarising, evidence suggests AI may nudge people towards the centre.
This holds true of all studied models. Grok is more right-leaning than other models, but also has depolarising effects.
By @jburnmurdoch.
The FT is hiring a correspondent for our Investigations team. Contact me if you want to discuss the role. Deadline is April 12 https://job-boards.eu.greenhouse.io/financialtimes33/jobs/4824783101
I’ll admit - i was sceptical about the idea of AI psychosis. Not the specific cases, which were all too believable, but about the scale. How much was this happening? And anyway wouldn’t better models make it go away?
Then I read a paper by Anthropic and the University of Toronto which has strangely received very little attention
We need a tax on self-driving cars.
Beneath eight states of the American Great Plains lies the Ogallala Aquifer, one of the largest bodies of groundwater on Earth. For centuries, extraction was constrained by the modest capacities of wind and hand power. At that rate, this 'fossil water' resource was effectively limitless. Farmers could draw as much as they wanted without ever running it down.
https://worksinprogress.co/issue/escaping-the-ogallala-trap/
But in 1949 Colorado Farmer Frank Zybach invented centre-pivot irrigation. Combined with electricity and the centrifugal pump, farmers could now draw thousands of gallons per well per minute, enough to irrigate 40 acres at a time. Since then, the aquifer has gone down 10%, losing a Lake Erie's worth of water. It is down 50% in the dry parts, where it recharges just 0.02 inches per year. Without intervention, modern pumps will bring about the total end of irrigated farming in the arid parts of the Great Plains in 20-30 years.
This is what I call the Ogallala Trap. Technological change can create a new tragedy of the commons. The telegraph enabled the destruction of the passenger pigeon; sonar, radar, and diesel enabled the industrial trawling that devastated the North Sea cod in a decade; chlorofluorocarbons came close to destroying the ozone layer.
Self-driving cars are about to do the same thing to roads. When you can sleep, work, or drink with friends in a moving vehicle, you will take many more journeys by car. Roads, which are free at the point of use almost everywhere, will grind to a halt. People who have to go to the office or the hospital will be stuck sharing the road with people having beers, working remotely, and taking naps.
There is a fix, but it depends on acting now, before autonomous vehicles go mainstream. Voters balk at being charged more for something they already depend on. The tax needs to come in as soon as possible. Waymos are already in dozens of cities and do millions of journeys per month. We have very little time left. If we want to save our roads from omnigridlock, we must introduce road pricing for autonomous vehicles.
This is a brilliant - bleak - piece about the broken local politics of Birmingham. First class on the ground reporting by @alexrogerssky @JoshGafson1
These pieces aren’t easy - you only get footage like this with skill, graft and luck - please watch:
We often think that the effects of class background are washed out by education. But we show that two people who did the same subject at the same university at the same time, and got the same grade …. end up earning quite different amounts when they enter the labour market
Today we launch a new @BritishProgress report to fix one of the dumbest parts of the UK tax system: the £100k cliff-edge, which encourages some of the highest taxpayers to work less.
Huge thanks to @DanNeidle for giving us such positive coverage in @FinancialTimes!
We find a way to fix the cliff edge, incentivise work and make it net-positive for the Treasury.
Full thread from @Ezra_Cohen_ below. He and @matthewg_stubbs did amazing work on the report.
Hmmmmmmmmmm. https://www.ft.com/content/1171d623-3709-4f6e-8ded-a5df4ec57696?shareType=nongift
The deterrent effect of gathering DNA from people arrested for felonies is large, and illustrates something important about crime. 1/2
The paper I’ve been most obsessed with lately is finally out: https://www.nbcnews.com/tech/tech-news/ai-changing-style-substance-human-writing-study-finds-rcna263789! Check out this beautiful plot: it shows how much LLMs distort human writing when making edits, compared to how humans would revise the same content.
We take a dataset of human-written essays from 2021, before the release of ChatGPT. We compare how people revise draft v1 -> v2 given expert feedback, with how an LLM revises the same v1 given the same feedback. This enables a counterfactual comparison: how much does the LLM alter the essay compared to what the human was originally intending to write? We find LLMs consistently induce massive distortions, even changing the actual meaning and conclusions argued for.
This is second time we've used Anthropic Interviewer and the first time we've deployed it at scale. Quite accidentally, we ended up conducting (what we believe is) the largest qualitative study ever
I'm a mixed-methods social scientist by training. Traditionally, when it came to understanding what people think, that meant quantitative analysis of lower resolution data (polls, surveys, etc.) or hand-wavey analysis of in-depth qualitative data. Using Claude to conduct *and* analyze interviews bridges that tradeoff between breadth and depth
AI also makes access much, much easier. Had we run this study in person, in the real world, it would have taken hundreds (if not several thousand) enumerators many 1000s of hours to conduct. It also affords us access to places we could otherwise never go. I once led a five-person team in Tanzania that reached a few hundred people. It took 3 weeks. In this study we heard from people 80,000 people in 159 countries, in cities and rural areas, in daily life and in war zones, and more, in just one
I'm still, even after months, beginning to wrap my head around the scale of this work. Like, to a social scientist, it's quite unbelievable. This could produce dozens of dissertations! It is also, of course, imperfect—certainly speaking to an AI is different than speaking to a person—and as a team we're all still figuring out how to make this research as useful as possible: what questions to ask and how, what to analyze and why, and how that all feeds back into what we do as a company. This is, as we say in the blog, a brand new form of social science
Hat tip to @saffronhuang for leading this for the past few months. Here's one of my favorite quotes
Excited to be on Odd Lots to talk about the politics of AI.
AI today is less important than it will ever be.
Over the past year, AI rose in issue importance faster than any issue we track — it's now more important to voters than climate change, child care, and abortion.
Today in @TheArgumentMag, Milan Singh and I do a deep dive into the data on who is ordering food delivery.
https://www.theargumentmag.com/p/whos-really-ordering-all-that-doordash
What that viral Anthropic jobs chart really means, by @jburnmurdoch and @sarahoconnor_
• Task vs. Job Automation: The chart distinguishes between theoretical AI exposure and actual real-world usage. It emphasizes that LLMs typically automate specific tasks rather than entire occupations; if AI handles low-value tasks while humans focus on high-value ones, the technology may augment and enhance a profession rather than displace it.
• Subjectivity of the Data: The metrics used are inherently "fuzzy." The theoretical exposure is based on subjective assessments by researchers and GPT-4, which often ignore regulatory, legal, and organizational hurdles. Meanwhile, Anthropic’s real-world data reflects Claude's usage logs, which don't always clearly distinguish between AI helping a worker (augmentation) and AI replacing a workflow (automation).
• The "Rorschach Test" Effect: Despite high theoretical exposure in fields like computing, there is currently no evidence in labor market data of increased unemployment in those sectors. Consequently, the chart acts as an inkblot test: optimists see it as "hype-busting" proof of AI's limited reach, while pessimists see the vast gap between theoretical and actual use as a sign of massive disruption yet to come.
https://www.ft.com/content/2cd79c2c-d1f0-4417-a06f-2572868ee858 vía @ft
Alarming story from @georginaquach:
At one UK university, the scramble to attract lucrative international students to the new London campus saw thousands admitted without the necessary English or academic skills, widespread use of ghostwriters, and fraudulent attendance logging
R to @jburnmurdoch: Arguably the most eye-opening stat:
After tightening its recruitment processes, the campus only took on 31 students this year, down from 1,624 (a fall of 98%).
Full piece: https://www.ft.com/content/aa845112-58a6-48c5-9278-35e809465607
This week's column: choose your university wisely
Post-1992 providers have been rapidly expanding business, law and computing courses. Yet the returns for students 5 years after graduating from these courses have, to date, been woeful
1/4
New newsletter: THREE REASONS TO BE A PARENT
Britain’s politicians have pushed through a number of well-intentioned policies that have been ultimately disastrous.
Another great column by @jburnmurdoch
The AI Shift is the @FT’s latest newsletter, from the fabulous team of @sarahoconnor_ and @jburnmurdoch
Do we really know which jobs are most at risk from AI?
https://as.ft.com/r/c1791cf8-710c-48c9-95ef-8b8d114e6b79
The graduate premium is falling in the UK but rising in the US.
However even if the grad premium was rising everywhere, it still might have nothing to do what students learn at university. It could be the result of the "signal" sent by university attendance - a signal that could be replaced by something far cheaper and less time-consuming.
Even in America, where the grad premium is rising, there are plenty of people who would argue that it's still the result of a signal - not the result of the human capital gained from being at university.
There is a huge academic debate about this which is very hard to settle one way or the other, partly because we have such poor assessment data on universities.
I don't think the value of university is 100% signal. I think it's a mix of human capital & signals.
If we want to tilt it more towards human capital, we need better assessment data. We need to know which universities are the best at teaching certain skills (and which skills are most valuable in the job market).
Graduate earnings data cannot tell you this.
I just don't think it's good enough for the graduate premium to be the sole measure of university impact. You wouldn't measure a hospital by the later earnings of the people it treats! We shouldn't measure universities that way either!
https://substack.nomoremarking.com/p/does-a-university-education-help