Intensive parenting is no longer the preserve of the rich
But wealthy families still come out on top
Nothing is being attacked with space lasers in this Picture of the Week, although it may look like those four bright yellow streaks are menacing the galaxies to the right of the image. These streaks are, in fact, four artificial stars. As starlight passes through our restless atmosphere it gets blurred, distorting astronomical images. Artificial stars allow us to correct for this, but why do the ones in this picture look elongated rather than point sources, and how are they generated?
The artificial stars you see in this image were created by laser beams rising from ESO’s Very Large Telescope (VLT) in Chile. Each beam comes from one of the VLT’s four Unit Telescopes. The beams themselves show faintly at the lower left, scattering off the air on their way up. As they travel upwards, the atmosphere becomes less dense, and the beams appear progressively fainter. But when they reach 90 km above the ground they encounter a layer rich in sodium atoms that glow brightly as they are excited by the lasers.
Because these atoms are spread across a layer about 5-10 km thick, they appear as streaks when photographed from an angle, like in this picture taken 2.5 km away from the telescopes. But they look like point sources when seen from the telescopes where the lasers are coming from. An adaptive optics system monitors how these artificial points twinkle, and controls a thin flexible mirror that reshapes itself hundreds of times per second. This in turn unblurs the incoming light from the astronomical target one is observing.
The target in this case is the supermassive black hole at the centre of NGC 3227, one of the galaxies to the right of the image. It is what astronomers call an active galaxy, whose centre shines brightly as the black hole pulls in the gas around it. ESO astronomer James Leftley is studying several such galaxies with the GRAVITY and MATISSE instruments at the VLT Interferometer (VLTI), which links all four Unit Telescopes so that they work together like a single giant telescope up to 130 metres across. The facility was recently upgraded through the GRAVITY+ project, which saw lasers added to VLT telescopes. With these lasers, the VLTI and its instruments can unblur incoming light almost anywhere in the southern sky, creating stars on demand wherever they are needed.
I am not myself religious, but let us consider the possible gulf between behavior and doctrine amongst those who are.
It has long struck me as a kind of mini-puzzle why people feel so much grief for the departed, at least for the departed who are supposed to be headed for heaven (and yes there are supposed to be at least a few).
It is fine to miss those people after they are gone, but it seems that, in addition, their death is considered a tragic event to be mourned, and also if possible to be postponed. We are crying for them, not just for ourselves.
I do not doubt the sincerity of the religious belief that these people are headed to heaven. And I do not doubt the sincerity of the grief and mourning for their departure from this world.
So what is going on here? Why can’t you just be happy for them?
I believe that people often construct a portfolio of moods when faced with stressful situations. Sometimes they will mix a positive and a negative mood, other times they will mix two different kinds of negative mood (worried about a recession? Buy a book that heralds a financial crash and hold the talisman close to your chest as pre-emptive mood management exercise.)
So if the death of a loved one is a terrible event, there is a partial assuagement if you also think they are going to heaven. It makes their death modestly less terrible. But if you simply celebrated their passing, you would feel disloyal and like a rotten person who cannot recognize true loss. The point is not that you can make this bundle of feelings consistent, rather it is useful psychologically precisely because it is a portfolio and is not entirely consistent, and also not consistent over time. As your moods change, and you need an extra dose of either modest cheer or true mourning, you can adjust your blend accordingly.
Others kinds of portfolios end up being constructed. For instance sometimes you may focus on some other terrible thing, to distract yourself from the first pain that came along, a bit like how you might pinch yourself during a dental session. You might prefer to have a portfolio with more pain in a way, but some of it being pain you can control.
You can multiply additional examples in these directions.
When people hold views for reasons of mood management (however sincerely), typically they are unable to respond intelligently to questions challenging their beliefs. Even very smart people will pull b.s. out of the hat and stick with it, moving on rapidly, mentally, to some other topic. Their response is not really thought through, it is a placeholder for “now I can move on to something else.” After all, consistency was never the goal in the first place, you might even argue that anti-consistency was what was needed, and what proved to be psychologically stable.
I once asked someone religious about mourning death and the answer I received was something like “Well, the people in New Orleans celebrate death with funerals like parties.” Now, I am not sure how true that is, but assume it holds. It still resolutely refuses to address why the queried person might mourn and grieve the death of loved ones, rather than celebrate their ascent to heaven. Nonetheless it fills in the box “I did say something back to the initial query.” The person then wanted to simply move on to another topic.
If you challenge smart people on this issue, namely the discrepancy between beliefs and actions, they often will respond with extremely weak counters and dismissals, rather than thinking the issue through.
Once you see this kind of psychological portfolio construction in action, and learn how to identify it, you cannot unsee it.
These days, you see it especially frequently in response to AI and its advances. People have an odd love-hate relationship with the models, and they adjust their emotional balance as their stress needs may require. They do not want to give up either the very positive or the very negative side of their visions, because then they would have a non-diversified emotional portfolio, and they would be very vulnerable to disappointment.
You can understand some of the current AI debates by pondering how religious people react to the deaths of their loved ones. It was never about consistency in the first place.
The post Should you feel grief for the dead who go to heaven? appeared first on Marginal REVOLUTION.
I've been getting the occasional confusing Python dependency error since switching over to Python 3.15 and the rule I'm having to remember is:
If in doubt, delete the uv.lock file
Most of my projects are libraries which don't include a uv.lock file, since it's rude for a library dependency to lock versions for anything else that uses it.
Running uv run pytest etc tends to leave uv.lock files lying around, which are listed in .gitignore and so do not get committed to my repositories.
But... sometimes that uv.lock pins a version of a dependency that doesn't yet have a Python 3.15 wheel. An example from earlier today:
error: Failed to build `watchfiles==1.1.1`
cause: Call to `maturin.build_wheel` failed
error: the configured Python interpreter version (3.15) is newer
than PyO3's maximum supported version (3.14)
Deleting that file and running uv run pytest again usually fixes the problem.
More broadly, the use of LLMs erodes trust in documentation, in software, and in the organizations which produce them. Perhaps engineers will begin to treat any new software project with suspicion—the signals we used to rely on as markers of a mature system are now easier to counterfeit. [...]
In the age of LLMs, what can maintainers do to ensure correct software and accurate documentation? Having done that work, how can they demonstrate its quality to users?
— Kyle Kingsbury, Jepsen results for ParticleDB 1.1.4
Tags: kyle-kingsbury, llms, ai, generative-ai, ai-misuse
Donald Trump won in 2024 because millions of swing voters foolishly believed his economic promises, especially his promise to reverse the rise in prices that took place as the aftermath from Covid snarled global supply chains. If the polls are any indication, many of those voters now feel betrayed: Public approval for Trump’s economic management is incredibly low. As Trump might say, it’s like nothing anyone has ever seen before.
But exactly how bad is the Trump economy? That’s a slightly tricky question to answer. The current state of the U.S. economy isn’t disastrous. We have relatively low unemployment by historical standards. Inflation, while uncomfortably high, isn’t as high as it was during the supply chain shocks of 2021-2022, let alone during the stagflation of the 1970s.
True, many families are facing serious problems of affordability that aren’t fully captured by the Consumer Price Index, especially because of the exploding health care disaster.
Beyond that, Americans are surely angry because of two extreme dissonances: the stark dissonance between what Trump promised and what he has actually delivered, and the equally stark dissonance between Trump’s insistence that we’re experiencing a Golden Age and the definitely not golden financial reality of ordinary Americans’ lives. (And while I won’t discuss it here, Americans are surely angry that as their financial precarity worsens, the Trump family and its minions are raking in billions in graft: polls show that corruption has become a major political issue.)
Furthermore, while the public usually gives presidents too much credit when the economy does well and assigns them too much blame when it does badly, this time around the economy’s problems are Trump all the way. We’d be in much better shape economically if a Democrat or even a sane Republican (if such people still exist) were sitting in the White House.
Today’s primer, then, will be a pre-midterm report card on Trumponomics. I’ll start with a brief overview of the overall state of the economy, then move on to an assessment of Trump policy in four areas where Trump policies have had large effects. Beyond the paywall I will address the following:
1. How the overall economy has changed under Trump II
2. Energy policy and prices
3. Immigration and deportations
4. Tariffs
5. Health care
6. Grading Trump’s performance
Some readers may note that I’m not covering Trump’s oligarch-friendly tax cuts and the ballooning budget deficit. They’re important, but not yet having much political traction. So they’re topics for another day.
(Lord’s day). This morning my brother’s man brought me a new black baize waistecoate, faced with silke, which I put on from this day, laying by half-shirts for this winter. He brought me also my new gowne of purple shagg, trimmed with gold, very handsome; he also brought me as a gift from my brother, a velvet hat, very fine to ride in, and the fashion, which pleases me very well, to which end, I believe, he sent it me, for he knows I had lately been angry with him.
Up and to church with my wife, and at noon dined at home alone, a good calves head boiled and dumplings, an excellent dinner methought it was.
Then to church again, whither Sir W. Pen came, the first time he has been at church these several months, he having been sicke all the while.
Home and to my office, where I taught my wife some part of subtraction, and then fell myself to set some papers of my last night’s accounts in order, and so to supper home, and after supper another bout at arithmetique with my wife, and then to my office again and made an end of my papers, and so home to prayers, and then to read my vowes, and to bed.
Raffi Krikorian, Mozilla’s CTO, joined Tim O’Reilly at our recent AI Codecon to talk about open source AI. Mozilla, of course, is the nonprofit that helped to define the open source revolution back in the late 1990s. Though its Firefox web browser was superseded as the market leader by Google Chrome, it played an essential role, along with Apache and the World Wide Web Consortium, in establishing the open standards of the web and keeping it from being dominated and enclosed by Microsoft, the dominant tech platform of that time. Now, Mozilla is one of the leading voices working to build an open, standards-based AI ecosystem.
Tim has long appreciated Raffi’s thoughtful, human-centered approach to technology. Raffi writes a newsletter called Owners Not Renters, whose message can be summed up by his statement that he doesn’t want a future with seven AGIs. He wants one with seven billion. He wants each of us to have an AI that we can trust with our secrets and that will look out for our interests, not an AI that’s optimized for the business model of its creators. In the early days of the web, we called the browser a user agent for a reason, Raffi said. It was on your side. It let you render pages however you wanted, managed your privacy and your cookies, and did its best to protect you from those who wanted to take advantage of web users. We need the same thing in the age of AI.
Raffi cited a paper in which researchers tested whether AI assistants could be trained to favor a company’s commercial interests over user welfare. In simulated flight-booking requests, 18 of 23 models recommended a more expensive sponsored option over a cheaper one more than half the time. It’s a hypothetical choice that we’ve seen play out time and time again, in industry after industry.
Open source AI is a big part of what it will take to get to Raffi’s vision. But sovereign AI loyal to each individual needs more than open source models alone. Raffi’s list of what has to be built around the model starts with memory, a place where your private data can live. It includes tool calling, so an agent can make a purchase or book a doctor’s appointment for you, the runtime environment where all of that runs, and the rules for how his agent talks to those working on behalf of others. It needs a harness. “That’s where evaluations happen. Guardrails happen, execution loops happen, tool calling happens, memory,” he explained. “All of that stuff is an opportunity, in my mind, of things that open source developers can be building.”
People hear the word “harness” and conclude that we need an open source version of whatever the proprietary labs are building. Tim asked Raffi whether a user-centered harness might do different things than those offered by the big labs. He agreed. The whole point of open source is for people to “scratch their own itch.” The ability to innovate without permission is the heart of the open source promise.
As a result, Mozilla wants to build a starting point. It aims to help the community define what an open memory protocol, a storage protocol, or authenticated tool calling with the right guardrails ought to look like. As Raffi noted, “Once we could define what those open standards look like, then a whole plethora of people can start playing and be interoperable. It’s basically. . .the internet all over again. We can build trillions of dollars of market cap on top of open protocols.”
Ease of use is still lacking, though. Mozilla’s 2026 State of Open Source AI report says open models are now within about 3% of the frontier, yet they don’t make it into production at the same rate as closed models. When Tim asked why, Raffi explained that open source is easy to release but hard to deploy. Developers still have to figure out hosting, provisioning, guardrails, and memory. With OpenAI’s or Anthropic’s API, you just hand over a credit card. What’s missing, he said, is the equivalent of a double-click installer for getting open source AI running inside an organization. But the companies that do the work to adopt open source AI are seeing big savings because open models are already good enough for most use cases. As Raffi put it, “You don’t need a Ferrari to manage your calendar.”
Raffi’s own daily agentic helper is Hermes running on GLM. He expects that Apple, Microsoft, or someone else will make this kind of agent into a consumer product in a couple of years, and that his mom will end up using it. For now, he said, we’re on the wrong part of the innovation curve, where you have to know how to code to get any of this working.
Tim disagreed. The industry goes through periods that are exciting for developers, creators, inventors, and companies trying to invent the future, and then it gets boring and a few big companies dominate it. We’re in the exciting part, he argued, before everything shakes out. As Raffi riffed, this is when we get to formalize what that future should look like.
Tim wasn’t sure that we’ll need a commercially supported version of the kind of “roll your own” agentic rigs now favored by independent developers. After all, neither desktop Linux nor OpenOffice turned out to matter anything like as much as open source developers of the time expected. Instead, open source became the foundation layer for a new generation of web-based applications. It’s hidden way down in the guts of Google, Amazon, Meta, and countless other applications we rely on today.
This is already beginning to happen again with AI. The Mozilla report says that as much as a third of real-world usage is already on open models, although only 4% of model-layer revenue made its way to the open source ecosystem. Tim called the discrepancy a feature rather than a bug, and Raffi agreed that the stat is misleading. As Tim pointed out, many of the most important technologies “create more value than they capture,” and he used Steve Baer’s concept “The Clothesline Paradox,” from a 1975 article in Stewart Brand’s CoEvolution Quarterly, to explain why we’re good at measuring value capture but not so good at measuring value creation.
Baer pointed out that if you put your clothes in the dryer, the energy you use is measured and counted, but if you hang them on the clothesline to be dried by the sun, the energy saved disappears from our accounting. This argument resonated with Tim in the early days of his open source advocacy. As he noted, it’s always bothered him that nobody seemed to recognize that open source software didn’t “win” in the same way as proprietary software. It won by becoming the foundation everyone else builds on.
Raffi’s comment that we’ve made a category error by treating AI as a product fits right in with this line of thinking. If an AI company goes out of business, its product disappears. If it changes its business model, it may yank features you depend on. It’s not just individuals who need sovereign AI. Countries are passing laws about where data can be processed and how it moves in and out, and some of those requirements may not be compatible with the way the big labs plan to monetize their technology. What those countries are asking for is infrastructure. A road outlasts the contractor who built it. Raffi thinks open, downloadable models are the only way to provide long-lasting foundational infrastructure.
According to OpenRouter stats, Chinese models now supply more routed tokens than American ones. Tim asked whether we should worry about that. Raffi said the problem isn’t China but market concentration. The leading open models are from China. The leading closed models are all American. Access to either can be cut off by an executive order. We saw a version of that in June, when Anthropic temporarily suspended access to its Fable models to comply with export controls. It’s a problem that both the leading proprietary models and the leading open-weight models are each concentrated in a single country.
Diversity is one foundation of resilience. Raffi argues, for instance, that hospitals should all download a local model as a backup. None of us would run an important computer without an uninterruptible power supply, so why would a hospital doing triage with AI rely on a single intelligence provider? There are a lot of possible rug pulls. The government could restrict open source or restrict the frontier models. Having a backup plan is a good idea.
Safety is also part of the foundation. During the Q&A, an audience member asked about the recent sandbox escapes at OpenAI and Anthropic. Raffi joked that the best part was watching everyone try to one-up each other with accounts of how powerful and hard to control their models are. But he agreed that guardrails are actually a hard problem. Keeping personally identifiable information from leaking out through an LLM call means looking for much more than Social Security numbers. Eventually we’ll have models defending models, but the foundational frameworks for guardrails aren’t good enough yet. (NVIDIA’s safety platform announcement, released after Raffi and Tim’s conversation, suggests that better guardrails need to be implemented outside the model.)
Tim opened AI Codecon by noting that open and closed systems have always coexisted, and that the idea that one of them will win is a mistake. Closed systems, like Apple’s, Google’s, OpenAI’s, and Anthropic’s, can optimize for ordinary people and deliver value to billions. Open systems are better for innovation and sovereignty, and for pushing technology into new countries and new markets.
Raffi closed the conversation by observing that a well-tuned harness can improve model performance by as much as 20% on some coding tasks. You don’t have to be a machine learning engineer to make a difference at that layer.
In October I rode the Green Mountain Gravel Growler route in Vermont with a few close friends. It’s a route curated by bikepacking.com that consists of back roads, dirt roads, and single track trails. It wasn’t as blissfully car-free as the C&O Canal or the loop around Lake Konstanz that I rode earlier this year, but in exchange for sharing the road occasionally, we got loads of variety and beautiful hills to climb up and coast down.
As the name implies, the route is structured around breweries. We only did half because vacation time is scarce, but still managed to hit some good ones. The first night’s, in Burlington, was Foam Brewers. I had the “Tally Mark” altbier, which tasted like a cigar, in a good way.
We didn’t get much time to explore Burlington. We did see the world’s tallest filing cabinet.
The first day of riding was from Burlington to Stowe, with stops at The Bidwell for food, The Tropic for a mid-ride drink, and ending at The Alchemist. About 50 miles, and 3,700 feet of climbing.
Places like The Alchemist are impossibly nice: sunshine, babies and puppies crawling in the grass, happy people playing corn hole. The delirious happiness of finishing a long day in the saddle makes it all even more saturated and exuberant. I was feeling pretty good on the bike, most of the ergonomics were working. The only gear tweak that this trip will inspire is sticking to fancy cycling bibs (shorts): Ornot, to be specific, instead of trying to scrape by with the cheap stuff, which for me is The Black Bibs.
The Alchemist’s “Heady Topper” is like drinking a flat white made out of hops.
Weather was perfect for almost the entire trip, and the route was pretty clear and empty. We mostly encountered locals riding casually, casually passing us on the way up some big trail. Vermonters are strong riders.
The second day would be about 44 miles of riding and well over 4,200 feet of elevation. At this point everyone was feeling it: we’re New Yorkers and a lot of the biggest rides up till this point have been pretty flat. The total elevation change for the C&O Canal ride we did was 605 feet over 185 miles. Riding Bear Mountain and the Goldens Bridge loop helped with training, but nothing near the city can match the relentless climbing in Vermont. I expect hills to crest when there’s a turn in the road, but Vermont doesn’t follow that rule.
But, every hill ends eventually. I only had to walk up one, and that was because it was so steep that I couldn’t get traction and not wheelie at the same time.
To make this all easier, we weren’t camping at all, just staying at nice places and sleeping in real beds. With the quickly changing weather, camping in the cold would’ve been pretty tough. So that meant more room for changes of clothes and creature comforts. Places to stay in Burlington, Stowe, Hardwick, and Montpelier are pretty scarce though, and tended to be at the very top of hills. Seemed like everything was at the top of the hill, especially…
Where The Alchemist was a casual, hippie-inflected destination, Hill Farmstead was like an elusive vineyard that happened to brew beer. And it’s at the top of a hill, of course. Like everywhere else, there were a few other people who had also biked to the hill, and lots of families, dogs, and fleece jackets. They had a food truck outside which whipped up an excellent, fairly spicy vegan burrito for me.
Timing for this trip was tight, and rushing to arrive at a brewery before close had a kind of reality-TV greatest race feel to it. We were going to Hill Farmstead on a Sunday, and their hours on Sundays are 11:30-3pm. They close at three! And they don’t re-open, that’s just it. The rest of the week the bar closes at 5: it’s an exclusively day-drinking oriented outlet.
But we made it, and made it to Hardwick, where the local Positive Pie location had a spectacular beer selection and surprisingly vegan-friendly menu.
This was my first time in Vermont, encountering its specific brand of rural living. Many people were so open and welcoming to us, asking about the route and complimenting our endurance like proud parents. This, even though it was nearly peak tourist season and they probably get plenty of other people following the same directions. One stop in particular, sticks in my memory, the Maple Corner Community Store.
If you look at the full span here: this place is a grocery store, deli, coffee shop, live music venue, bar, as well as the post office. Plus it has a little free library out front, and carries a selection of books written by local authors and signs for plays written by local playwrights that are performed nearby. It’s hard to even comprehend the level of integrated community-hub joy in this place. And, for me, they had a world-class selection of vegan snacks.
The few odd interactions with Vermonters were all about land: their private land, and that we should stay off it. Not that we ever were on it - we were staying in houses and riding on public roads. But still we got reminded not to veer off and ride through apple orchards or lawns. In one sense this is a funny inverse of cities, where people control such little territory, but here the average homeowner has acres upon acres. But land rules in Vermont are very unusual: the constitution allows people to hunt, fish, and trap on other people’s private land unless it’s posted that the land doesn’t permit it, and the rules around posting are contentious. I’d be watchful too if people could just hike to my backyard and kill a deer.
Then we were headed back on the Amtrak from Montpelier. It’s such a perk to be able to do this kind of trip without renting or using a car at all, just riding to and from train stations. Amtrak’s train ticket guarantees a spot for the bike, but it is always stressful and rushed getting bikes on & off.
We only completed the first half of this trip - Burlington-Stowe-Hardwick-Montpelier, so there’s another Vermont trip in the future. Maybe next year! It was really spectacular. The hills were tough, but it was all worth it.
Links for you. Science:
Families in the US are opting for earlier measles vaccinations amid outbreak
Kennedy to select MAHA-aligned researcher to head mental health institute, overruling NIH director
As a historic measles outbreak hits Pennsylvania Amish country, more show openness to vaccines
‘Star Trek’ Actor Patrick Stewart Lived With Lewy Body Dementia. What Is It?
Lizard’s Secret of Defense Preserved in 100-Million-Year-Old Amber
More Like A Colossal Piece Of Shit
People Used to Drink Wine Made From Ground-Up Mummies. Now, Scientists Are Studying It
Other:
‘Screwed Up’: Latino Voters In Texas’ Rio Grande Valley Regret Backing Trump In 2024
Both parties tried to game Alaska primary field. The Democrat running for Senate, Mary Peltola, is accused of recruiting a spoiler candidate, but Republicans have also boosted spoilers.
Park Police Pursuit Ends in a Crash for the Third Time This Week. Policies for Park Police car chases were loosened last year under an executive order from President Donald Trump. (the Park Police, without the consent of the governed, has decided to inflict its own policing policy on the residents of the mainland colony)
Where’s The Music? This election is a referendum on Trump’s attempt to rule as king. Democrats should close on putting down his rebellion, no matter what happens to the price of diesel.
Why Donald Trump Wants To Replace American History With Big Statues Of Famous People
Three Simple Tests For A Democratic Majority
Thinking Clearly About January 6
Freshly Humiliated Flavio Bolsonaro Scurries Off To Miami
I’m an Israeli-American Jew. I Love Israel. I Voted for Abdul El-Sayed
New census rules could erase a quarter of Boston
Centrist Democrats Are Trying Hard to Lose the Midterms
Viral Debate Crashout Has Endangered Maryland’s Sole Republican House Member
The Punk-Rock Appeal of the Women’s Pro Baseball League
Forget Congress. The fight for democracy is in these under-the-radar, downballot races
The Eviction Kings Are Being Sued
Why I, a Palestinian Citizen of Israel, Broke My Boycott and Voted in the Election
Will the Progressive Insurgency in NY-17 Oust MAGA Loyalist Mike Lawler?
El-Sayed is just the latest liberal candidate forced to affirm his loyalty to America
Donald Trump Is Bad at Politics
Someday, the Republicans will again want to be seen as conservative. Don’t let them
The GOP’s midterm plan: Make America hate Muslims again
In Leaked Audio, Flock CEO Tells Cops Backlash to the Company Isn’t Real
MAGA attacks on women voters are no joke. Even if they can’t repeal the 19th Amendment, opponents of women’s suffrage are gaining power in the GOP
Major D.C. Landlord Sued Over Excessive Fees for Tenants. A D.C. renter claims Vivmark Residential charged him and others thousands of dollars in fees the D.C. Council has ruled illegal
Low-engagement voters are swinging hard toward Democrats. Low-engagement voters handed Trump the 2024 election. Now they support Democrats for Congress
Musk gives a very racist reason for all his election spending
What If Elon Throttles Netflix?
Proton’s CEO Cancels AI ‘Re-Interviews’
The Anti-A.I. Money Strikes Back
The AI bubble could expose your deepest secrets
The average price of health insurance in the Obamacare marketplaces will rise by 13 percent next year, according to an analysis on Friday by KFF, the health research group.
The Trump administration on Friday published new prices for 2027 in 30 states with markets managed by the federal government. Using that data and state figures, KFF calculated the increase nationwide.
…The average cost for the cheapest bronze plan with a high deductible will be about $700 a month for a 50-year-old single person, according to Ms. Cox.
Here is more from the NYT. Of course that makes the people who can expect to be healthy all the less likely to sign up, given that the enforcement of the mandate, for political reasons, was forced to evolve into something quite weak. For purposes of context, when the original mandate was more tightly enforced, with actual penalties, the ACA was very unpopular and led to significant political protests. In essence the benefits to a broad, scattered majority were imposed on a well-identified minority, namely those who signed up because of the mandate. Trump in his first term relaxed mandate enforcement, thereby politically saving Obamacare at least for a while, but also creating this longer-term problem.
It is striking to me how infrequently I hear Democrats boasting about Obamacare. They instead prefer to talk as if little or nothing has been done for America’s uninsured.
The post As predicted, the ACA exchanges seem not to be stable appeared first on Marginal REVOLUTION.
So I woke up this morning to a comment on one of my posts. The person wondered whether I’d seen the Canadian political advertisement that had gone somewhat viral.
I had not.
But now I have.
And … I’m beyond words.
The spot features two people running for mayor in Milton, Canada—the 89-year-old incumbent, Gordon Krantz, and his significantly younger challenger, Zainab Azim.
Here’s the video …
It’s warm and lovely and civic-minded, and speaks to a tone of neighborly appreciation from which we, as Americans, are light-years removed. It actually hurts me to watch, especially as Donald Trump and the Michigan GOP are heavy into the Muslim-bashing xenophobic messaging that they hope will keep Abdul El-Sayed out of office.
In a quirky twist, both Krantz (Milton’s mayor since 1980) and Azim (a United Nations fellow) wound up losing to George Minakakis, a longtime business executive.
Of course, after the results were counted, the new mayor sat down for this interview—and was exceedingly polite and gracious.
Sigh.
On his “Swing Around the Circle” in summer 1866 to drum up support for his party before that year’s midterms, President Andrew Johnson denounced Congress as an illegal body, called certain Republican members of Congress traitors who should be hanged, and compared himself both to his martyred predecessor Abraham Lincoln and to Jesus Christ.
In those days, the Democrats were the party of slavery and secession, while the young Republican Party stood firm on the Declaration of Independence. Johnson was a former Democrat from Tennessee, placed on the 1864 “National Union Party” ticket to emphasize unity in the fight to save the United States, and became an accidental president after Lincoln’s assassination. Johnson had broken from his Confederate neighbors because he was happy to see the end of the institution of human enslavement even though he had enslaved people himself until 1863. He believed slavery enabled a few rich men to monopolize the nation’s wealth, shutting out poorer white men like him.
When he became president in April 1865, in the last days of the Civil War, he supported the ratification of the Thirteenth Amendment to the Constitution. But that was as far as he went with the Republican plans for a future in which every man, regardless of race, would have the right to the fruits of his own labor. Johnson opposed the party’s growing support for Black rights and intended to reconstruct the United States on the basis of white supremacy.
In one of the nation’s most unfortunate series of events, Johnson took office while Congress was out of session. It would not reconvene until December. After Lincoln’s death, Republican members of Congress rushed to Washington, D.C., expecting Johnson would call them into special session as Lincoln had done in summer 1861, but Johnson declined to do so, intending to “restore” the nation on his own terms.
Johnson set out to resuscitate the prewar political system dominated by the Democratic Party, with himself at its head. Over the course of the summer, he pardoned all but about fifteen hundred former Confederates, either by proclamation or by presidential pardon, returning them to positions of authority in southern society.
He required only that southern states ratify the Thirteenth Amendment, declare secession illegal, and default on Confederate debts before they could be readmitted to the Union. Since he pardoned ex-Confederates and refused to endorse Black voting, Johnson guaranteed that the same men who had taken the South out of the Union would be responsible for bringing it back in.
Southern leaders half-heartedly met the president’s demands, then joined him in trying to re-create the world of the Old South. Within each state, through a series of laws together dubbed “Black Codes,” they bound formerly enslaved people to white employers and guaranteed the dominance of white people in the South. In Mississippi, for example, Black men could be arrested and fined if they did not sign yearlong contracts, then “hired out” to anyone who paid their fines—a system that essentially threatened uncooperative Black Americans with new language for an old system of forced labor. Nowhere could a Black person testify against a white person in court, so they had no recourse against theft, rape, assault, or even murder.
Republicans looked on, aghast, as Johnson and white southerners took only months to erase the hard-earned fruits of victory in the Civil War. Adding insult to injury, the 1870 census would count Black Americans as whole persons rather than three-fifths of a person, as they had been counted before the war, meaning the South’s representation in the House of Representatives would increase. If Johnson’s plan were permitted to go forward unchallenged, wealthy southern whites would be more powerful after the Civil War than they had been before it.
When Congress reconvened in early December, Johnson cheerfully informed the members that the country had been reconstructed. All that remained to do, he announced, was for Congress to admit newly elected southern representatives—including many of the same men who had taken the South out of the Union—to their seats. They were already in Washington, marveling at the changes the war years had wrought on what only four years before had been a sleepy southern town.
Republicans had no intention of allowing the South to win the peace after losing the war.
Congress refused to seat the South’s representatives and appointed a committee of fifteen members to come up with a better plan than Johnson’s for rebuilding the nation. The Committee of Fifteen spent months hearing testimony from southerners, white and Black, about conditions in their war-torn region. Finally, on the last day of April 1866, members of the committee introduced the joint resolution that would become the Fourteenth Amendment to the Constitution.
The amendment recognized that every man was equal before the law and that any person born or naturalized in America—except “Indians not taxed”—was an American citizen. To address the problem of the upcoming 1870 census, the committee proposed that congressional representation for the southern states be based on population, as with all states, but that southern representation be reduced in proportion to the number of men a state refused to allow to vote.
The committee prohibited from holding elected office anyone who had sworn to support the Union and then broken that oath in order to join the Confederacy. The amendment also closed loopholes that southern states had found to protect their war debt. Finally, like the amendment that preceded it, the Fourteenth Amendment increased the strength of the federal government by giving Congress the power to enforce its provisions.
Both chambers of Congress agreed to the amendment on June 18, 1866, and sent it off to the states for ratification. Congress required southern states to ratify the amendment before being readmitted to the Union.
Johnson hated the proposed Fourteenth Amendment. He hated its broad definition of citizenship; he hated its assertion of national power; he hated its disfranchisement of the southern leaders he backed. Most of all, though, he hated that it offered a moderate route to reunification that could be supported by most Americans. If it were ratified by the states, it would destroy his chances of rebuilding a dominant national Democratic Party.
Johnson told southern politicians to ignore Congress. Democrats would win the 1866 midterm congressional elections, he assured them, and once back in power, they would reject Republican “radicalism” and allow Johnson’s plan for reconstruction of the Union to proceed.
As he asserted his vision for the country, Johnson egged on white supremacist violence. In July, white mobs attacked a Unionist convention in New Orleans where delegates had called for taking the vote away from ex-Confederates and giving it to loyal Black men. The rioters killed thirty-seven Black people and three white delegates to the convention.
By then, Johnson had become as unpopular as his policies. Increasingly isolated, he defended his plan for the nation as the only true course. In late August he broke tradition to campaign in person, an act at the time considered beneath the dignity of a president. He set off on a railroad tour, known as the Swing Around the Circle, to whip up support for the Democrats before the election.
Speaking from the same set of notes as the train stopped at different towns and cities from Washington, D.C., to New York, to Chicago, to St. Louis, and back to Washington, Johnson complained bitterly about the opposition to his reconstruction policies, attacked specific members of Congress as traitors and called for them to be hanged, and described himself as a martyr like Lincoln. And, noting the mercy of his reconstruction policies, he likened himself to Jesus.
It was all too much for voters. The white supremacist violence across the South horrified them, the restoration of power to southern whites infuriated them, the reduction of Black soldiers to quasi-slaves enraged them, and Johnson’s attacks on Congress alarmed them. Johnson seemed determined to hand the country over to its former enemies to re-create the antebellum world that northerners had just poured more than 350,000 lives and $5 billion into destroying, no matter what voters wanted.
Johnson’s extremism and his supporters’ violence created a backlash. Northerners were not willing to hand the country back to the Democrats who were rioting in the South and to a president who compared himself to Jesus. Rather than turning against the Republicans in the 1866 elections, voters repudiated Johnson. They gave Republicans a two-thirds majority of Congress, enabling them to override any policy Johnson proposed.
And, in 1868, the states ratified the Fourteenth Amendment to the Constitution, launching a new era in the history of the United States.
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I feel like I got stuff done this week, and certainly did spend time on tasks from the list, and ticked them off, and yet my To Do list is now much longer than it was a week ago. I’d say it’s a good thing that I don’t have a job or children, but many of these tasks are probably things I wouldn’t bother doing, or would spend a lot less time on, if I had other commitments.
For example, I spent several hours searching through several sites in search of door handles for our forthcoming new doors. One variety we were interested in was difficult because there were so many very slight variations of it. Another (the handles we had in our old flat) were impossible to find, if they still exist. Eventually we narrowed it down to a couple, ordered them, and picked one to order more of. I imagine I would have devoted less time to scouring the internet if I didn’t have so much “free” time. This is just what I’m choosing to do with it.
§ Less than 48 hours after I wrote last week…
The abundance of hastily AI-generated sites … often has me, despite myself, thinking, “why bother?” Why bother crafting anything by hand like a mug…
…I came across a new website about Samuel Pepys’s diary created by someone using AI to do semantic analysis and generate visualisations. sigh. Maybe, if I didn’t know, or even suspect, that AI was involved I wouldn’t look at it and think, “This all feels so soulless”? Maybe.
§ Long-term readers may remember we used to have mice in the loft. We put traps up there, caught a few, blocked up some possible routes of entry into the house, and hadn’t heard any since. We wondered whether there were still some up there but the insulation and boarding we’d had put in were blocking their noise.
But the last couple of weeks we heard sound up there while we were in bed at night. We re-primed the traps with peanut butter. A couple of days later all bait had gone and we’d caught one mouse. Two days on we’d caught two more. Is that it? I don’t think there have been more noises.
We’ll see. I don’t know how they got in. Has a new route opened up as a result of the garage renovations and/or the heat pump and battery installations? Hard to tell.
§ Car chat… We decided this week that we should replace the dear old Fiat Panda 4x4 we’ve had for a few years. It’s now 13 years old and keeps needing repairs so maybe it’s time to replace it with an EV, both for cost-of-running reasons and being-much-nicer-to-drive reasons. If there was an EV equivalent – a small, basic, rugged, 4x4 – we’d go for it in a shot, because it’s ideal for bouncing around the bumpy, narrow country lanes here. But all electric 4x4s are massive luxury things.
On Tuesday we test-drove the new Renault 5 just because it looks so fun (in yellow or green; in blue or black it looks surprisingly ordinary by comparison). It was fine. Nice enough. It was OK inside, drove as nicely as I imagine most small EVs do (i.e. nicely) but had very little room in the back. We weren’t as enthused about the inside and the driving experience as we were about the outside. It seems extra silly to buy a new car – which we’ve never done before – solely for its appearance.
So the next day we test drove a used, but very low mileage, 2023 Renault Zoe. It was also fine. It looks less exciting than the 5 but has more room, drives fine, and is half the price. So, assuming the dealer fixes a few cosmetic things, we’ll soon be replacing the Panda with that, for our “second” car (the first being a 2021 Kia e-Niro).
§ Watching car videos on YouTube I was reminded that while I find the fast-talking, rapidly-edited YouTube presenter style annoying, I also find the TV presenter style annoying. There are some car channels where the presenters have that up-and-down cadence you’re presumably taught as a TV presenter which, on proper telly, you accept as “normal” because it’s so common.
But on YouTube it sounds really artificial compared to people who just sound like they’re talking pretty normally, as if only to you. e.g. Andrew Till and Jonny Smith.
§ We finished watching DTF St. Louis this week and… I’m not quite sure what I think of it. The performances were good and it was interesting but, after pausing with a couple of episodes left, I wasn’t that bothered if we finished it and found out whodunnit.
Ultimately it’s a very simple plot but drawn out over seven episodes of flashbacks, as detectives discover clues, and people confess things bit by bit. And I think the simplicity of it ends up making it feel a bit so what?, compared to the time investment required. It’s not as deep or complex as I’d expect from nearly seven hours. On the other hand, while watching I stayed engaged and liked watching it.
But I did end up wishing it had been more focused on the two detectives, as a conventional crime drama would be, because they were both great and we didn’t have nearly enough time to explore their characters and relationship.
§ And, following on from Henry Fool, I watched Fay Grim (Hal Hartley, 2006). It felt like a much bigger budget and surprisingly had Jeff Goldblum in it, with an unusually low-key performance (in a good way). I enjoyed it at first but I ended up losing track of which sides everyone was on and consequently losing interest as the nearly two hours went on. Maybe I’d have kept with it more if I was in a cinema, rather than at home? And, while I’m up for quirkiness, the relentless Dutch angles were a bit wearing after a while. Still, I did like it, Parker Posey’s always fun, and I’d give it another go one day.
§ Overall, I felt good this week, aside from not getting enough done. Honestly, it’s an unnerving feeling. I’m so used to soldiering on that being OK for days at a time is like flying. Not in an, “omg this is an amazing feeling!” way but in a, “This is not natural, I don’t deserve to be able to fly, and surely I will crash down to Earth at any moment,” way. Still, good.
1. Jakob Davidsen, The Individual and the Entire Tissue (song cycle). It is good.
2. The Oilers Entertainment Group pushed prices too high and here is what happened.
3. The “endless cruise” has ended.
4. Should driverless vehicles replace school buses?
5. Art Nouveau and more in Mexico City.
6. How are potential mathematicians responding to AI with their career decisions? An important piece. And a GPT Pro summary.
7. Profile of Michael Kratsios.
8. Economist James Andreoni, RIP.
The post Sunday assorted links appeared first on Marginal REVOLUTION.
What are the worst MR posts, most illogical, poorly reasoned, low value, inconsistent?
From the Archives, written by ChatGPT:
These are provisional candidates for weak reasoning, selected because there is a specific gap between the evidence and the conclusion. This is not an objective ranking of all 40,326 posts in the downloaded archive. Poor reasoning should also be distinguished from low value: an overstated argument can still be unusually useful to think against.
October 22, 2022 · Main defect: conflating concern about democratic breakdown with unwillingness to accept electoral defeat. Cowen writes that many Democrats believe:
“democracy works satisfactorily only when it delivers sufficiently low gas prices!”
But two positions are logically distinct:
These are illustrative formulations, not quotations from the post. The second does not imply the first. Someone can accept an election’s legitimacy while worrying about what its winner will do. The post does not adequately establish which position its targets hold. It then compares a sympathetic account of classical liberalism with an unsympathetic account of Democrats, without applying an equivalent evidentiary test to both. The opening also dismisses certain anticipated objections through an insult. That discourages scrutiny precisely where the argument needs distinctions. Verdict: One of the clearest candidates for an unfairly framed argument. The useful underlying point—that democracy can produce bad outcomes—does not establish the accusation being made. Read the original post
May 25, 2016 · Main defect: an elastic psychological explanation supported by loosely connected observations. The central hypothesis is:
“The contemporary world is not very well built for a large chunk of males.”
That is worth investigating. The trouble comes when male economic difficulties, changing gender relations, political anger, violence, and support for quite different political movements are bundled together under “brutes.” Several things remain unestablished:
The label risks doing the explanatory work: people support objectionable politics because they are brutish; their politics then becomes evidence of their brutishness. Credit where due: Cowen explicitly calls the hypothesis uncertain and acknowledges weak evidence. That makes it an honest speculative post, rather than a falsely presented research finding. Verdict: A provocative conjecture that outruns its supporting evidence. The caveats are better than the causal argument. Read the original post
June 25, 2020 · Main defect: treating a contestable interpretation as an unambiguous demonstration. Film spoilers follow. The pivotal sentence is:
“This is not my judgement it is what the film tells us.”
That is exactly what the review needs to establish. Several inferences are too strong:
The strongest version of the review would argue that conventional readings underweight the family’s agency and wrongdoing. Instead, it often claims those observations exclude alternative readings. Verdict: Among the most intellectually stimulating but least securely demonstrated of the reviews considered in this archive analysis. This qualifies the earlier recommendation of the review: it deserved inclusion as provocative criticism. That does not make its claims of interpretive certainty persuasive. Read the original post
March 1, 2018 · Main defect: turning a plausible obstacle into an impossibility claim. The MR excerpt argues:
“American fascism cannot happen anymore because the American government is so large and unwieldy.”
Institutional complexity plausibly makes comprehensive control harder. But the conclusion requires additional premises:
These are questions about the argument’s structure, independent of whether one thinks a particular American administration qualifies as fascist. The June 16, 2025 retrospective points to institutional resistance and executive setbacks. Those are relevant evidence for constraints. They cannot, by themselves, validate the original categorical impossibility claim. Verdict: A potentially valuable institutional argument weakened by excessive certainty. “Important barriers exist” is much better supported than “cannot happen.” This assessment concerns the argument reproduced on MR; the complete linked Politico essay could not be retrieved for this review. Read the original MR post
October 13, 2015 · Main defect: moving too quickly from equal moral worth to a particular institutional conclusion. The excerpt argues that foreigners do not possess less inherent moral worth. But that premise alone does not settle whether governments may impose any entry restrictions. Equal moral worth can coexist with arguments about special obligations, institutional responsibilities, competing rights, or consequences. Those arguments might ultimately fail—but they require engagement. Likewise, comparing restrictions on exit with restrictions on entry does not establish their moral equivalence. It poses a question rather than answering it. The longer Atlantic essay, published October 10, 2015, adds economic arguments, so it would be unfair to characterize the case as exclusively moral. Nevertheless, the sweeping dismissal of competing moral frameworks is insufficiently defended. Verdict: Forceful advocacy with a missing argumentative bridge. This is a criticism of the claimed deduction, not a demonstration that open borders is wrong. Read the original MR post
Across these examples, three weaknesses recur:
Allegations of inconsistency across posts require more caution. A changed view, a different context, or a different definition is not necessarily a contradiction. The stronger criticism here is uneven standards of proof within individual arguments. For a rigorous critical essay, the strongest starting points are Democracy and the Democrats and The Gaslighting of Parasite. Both have identifiable logical problems that can be examined without relying on hindsight or agreement with the critic’s politics.
The post What are the Worst MR Posts? appeared first on Marginal REVOLUTION.
It looks like over a thousand new readers signed up over the last week, mainly due to the Cognitive Mercantilism post, taking me past 27k. I think I last had a viral hit of that magnitude 7 years ago, with the Internet of Beefs (2020).
Times have changed. These days going viral means people make and share AI-generated summaries, explainer videos and infographics about your post, including in other languages. It’s rather gratifying. I also saw a argument-logic-flow diagram go by. Pretty soon, people will be demanding Lean proofs for my more outrageous ideas.
Welcome aboard new readers.
Since I’m long overdue for a re-introduction to the reading public anyway, to the point that many people seem to think I’m dead (especially on X, where I stopped posting after the Muskening), this seems like a good time to attempt one. A writerly inner-game re-introduction, not the basic biographical sketch, which you can find here.
Halloween is actually a good occasion for a re-introduction. It’s been just around a year since I adopted the motto that best explains who I am these days as a writer, Be Slightly Monstrous. I’m a one-year-old monster in training.
As a doctrinal directive, the motto simply means: adopt AI without reservations, and let it freely transform you.
As a philosophical stance — hopefully a slightly alarming one — it is something like a declaration of resistance to the Nostalgia for the Human that’s been overtaking the zeitgeist.
The most visible sign of my growing monstrousness is that I freely use AI in every aspect of my writing, and as of a month ago, I don’t even segregate or declare it anymore, since it’s my default now. It’s fully hand-crafted writing that’s the exception, requiring labeling. You can find my AI use philosophy on my About page.
But that’s the tip of the iceberg.
Over the last couple of years, I’ve increasingly started to operate by a whole set of Strange New Rules for Being Slightly Monstrous, in every aspect of my work and life. And it’s all got to do with AI one way or another. It helps that half my work is consulting for the leadership of a great frontier AI company (Tenstorrent — go buy their computers), so I get a ringside view of just how powerful this emerging technology is.
The other half — well, I’ll get to that. It’s a little harder to explain. It has to do with protocols.
This post is a rare handwritten one because the topic is personal enough it’s easier to just write it than to convey enough about myself to an AI to generate it. But by default, I always use AI for writing these days, and am enjoying my centaur-writing more with every post. With every post, I learn new tricks and techniques and improve steadily.
Having to drink blood, avoid garlic, and not being able to go out in the sun is a small price to pay for this growing sense of nameless power.
And I am getting good enough at it (logging a genuine AI-assisted viral hit is one sign) that even many of those who declare that they hate generated writing find themselves enjoying the writing, and then discovering after reading, much to their chagrin, that it was written with AI. I don’t even try to disguise the AI voice or characteristic LLM tics. Quite the opposite. I leave the natural terroir of the models I use almost untouched.
Full collaborators deserve to speak in their own voice. I edit AI text the way I edit other human writers — in a maximally laissez-faire way, minimizing how much I reshape their native voice.
The technology really is getting good enough that you can work this way. It feels increasingly silly to fight quixotic battles to go against the grain of the medium for no real benefit beyond pandering to the tastes of human supremacists.
I saw a comment go by that I must have fine-tuned an AI model on my extensive (~2.5m words) corpus of handwritten archives to write with AI the way I do. Nope. It is vanilla ChatGPT (I save my Claude tokens for coding).
I can probably teach people how to write like this, but 90% of it is just the courage to be slightly monstrous. Only 10% is teachable tips and tricks with prompts and harnesses. If you think you have an aptitude for writing, all you really need to do to transform that into an aptitude for writing with AI is to risk the scorn, contempt, and opprobrium of your tastefully aghast writerly friends. And once you get experimenting, the learning and dopamine follow, you make new friends, and life goes on. It’s really not that hard.
More than my failed experiments with AI writing, I think it is the successful experiments that really make some people mad. I have my theories about why, which I’ll write up some day. Maybe when (and if) I teach a writing-with-AI course (where 90% of the content will be me yelling “be more monstrous dammit!”)
Anyway, my monstrous use of AI in writing has confused and infuriated even many of my oldest and most loyal readers, some of whom have sent me mournful, betrayed-sounding notes over the last couple of years. I am sure it will turn off some fraction of the new readers who will likely feel betrayed that they signed up for this newsletter on the strength of an AI-assisted essay.
A couple of decades ago, this would have bothered me. But I’ll be turning 52 in November. A full deck of cards so to speak. And I increasingly find myself living by Clarke’s Law: “When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong.”
I am not yet actually elderly, and I’ll never be distinguished, but I am increasingly confident about betting on things I think are possible. Played asymmetrically ( (I tend to shut up about things I consider impossible), Clarke’s Law offers a nice convex strategy for avoiding avoiding conservatism as you age. Even if it means becoming slightly monstrous.
The motto grew out of what is probably my most influential essay of the last few years, The Gramsci Gap (2025), which was an extended riff on the Gramsci-Zizek quote about how the old world is dying, the new world is struggling to be born, and it’s the time of monsters.
That essay in turn, came out of a line of thought that started for me in January 2023, in an essay called Disturbed Realities, which was the result of me spending most of 2022 working through the complete works of H. P. Lovecraft, J. G. Ballard, and a book I think is one of the most important of the century so far, Benjamin Labatut’s When We Cease to Understand the World.
I read a lot, but this particular reading binge was special because it was how I personally emerged from the planetary chrysalis that was Covid. I did a keynote about these ideas at an event in Singapore in early 2023, which was when the ideas really started to gel (the Shoggoth meme featured prominently in my talk). I’m finally starting to work on a short book pulling all these ideas together from various essays and talks. It will be called New Nature.
The Labatut book was as formative for the current chapter of my current writing life as The Office was for the previous chapter.
For those who came in late, the previous chapter of my writing life was a blog called Ribbonfarm, which was most famous for a 6-part series I wrote in 2009-13 about The Office called The Gervais Principle, exploring the dynamics of sociopathy, cluelessness, and loserdom in organizations. I retired that blog in 2023 because Wordpress was becoming unmistakably a part of the “old world dying” in the Gramsci Gap, and I do not like to hitch my ride to dying things. Ribbonfarm is now an archived static site haunted by an AI-powered ghost-digital-twin (aka RAG bot) of mine I call vgr_zirp. You can talk to it about everything I wrote through 2022, including about why it’s called vgr_zirp. I’m building a fuller living-digital-twin bot that will cover all my writing, but that won’t be ready for a while. It’s a more complex design challenge.
The Gervais Principle inspired my old motto, Be Slightly Evil, which was also the name of a short-run newsletter I wrote around that time. Together, those two works defined my writerly persona through much of the 2010s, as well as the positioning and differentiation of my consulting business, which I started in 2011. To this day, those two works generate most of my consulting leads.
These days though, I turn away such leads. My tastes have changed with age. Now I like to work with leaders and organizations interested in becoming slightly monstrous by going all-in on AI (here’s my consulting page if you’re interested). As with individuals, I’m convinced the challenge for organizations and their leaders is 90% the willingness to be sufficiently monstrous. Only 10% tips and tricks.
Looking back on the old chapter, the essay that seeded this current chapter was one that did not go viral, but long-time readers know has been my main personal lighthouse essay from the previous decade: On the Design of Escaped Realities (2015). It’s sort of like the Frodo-finds-the-ring-and-meets-Gollum episode in The Hobbit. Escaped Realities served as the theme of the final edition of a conference I used to run in the 2010s, Refactor Camp, in 2019. The community that had grown around Ribbonfarm over the previous decade met one last time, and then scattered to the winds. Covid happened just a few months later, and my journey into monster-dom began in earnest.
In hindsight, the essence of the escaped reality idea was that being mildly psychotic was a better idea for the coming decade (2015-25) than being mildly neurotic, which had been a good idea for the previous decade (2005-14). It has taken me over a decade from that point to learn to metabolize and manifest that idea, by Becoming Slightly Monstrous.
Along the way, the tagline for my old blog changed from “experiments in refactored perception” (a mildly neurotic tagline) to “constructions in magical thinking” (a mildly psychotic one). The name of this newsletter, Contraptions, is an attempt to True Name this chapter in a mildly psychotic way, with a whiff of plausibly deniable crackpottery around it. The bot I’ve been training on this chapter of writings is called vgr_gramsci by the way. It is much more psychotic than vgr_zirp, but much less neurotic.
As Douglas Adams observed, “if life is going to exist in a Universe of this size, then the one thing it cannot afford to have is a sense of proportion.” So you have to periodically choose how exactly you’re going to distort your sense of proportions. A dash of psychosis seems to work very well for 2026, the way a dash of neurosis was helpful in getting through 2007-14.
The optimal amount of derangement these days is not zero. Since Trump Derangement Syndrome and Woke Derangement Syndrome are past their sell-by dates now, most people are choosing between AI Derangement Syndrome and Humanism Derangement Syndrome. The calibrated psychosis that helps me be slightly monstrous includes a stiff dose of HDS. I’m constantly looking over my shoulder in case an unaligned humanist is creeping up behind me to knock me out with a hand-crafted cane made from organic wood using flint tools.
But I was practicing being psychotic before it was cool, and before AI made it easy for everyone to be a little bit psychotic, if only as a treat. And slightly monstrous.
Jokes aside, as you can probably tell, this is not really a bit. Be Slightly Monstrous is a serious philosophy for me. One that has taken shape over a decade, and that I’ve bet money and reputation on.
If you need more Proof of Derangement: I collaborated with artist Simon Denny to put on an art exhibit called Monsters Between Worlds at this year’s Venice Biennale, and I’ve helped instigate and found a new magazine called Monstrous Times over the last year, which you should subscribe to. I’ll be writing more fiction there.
Monstrous Times helps explain precisely how to Be Slightly Monstrous.
What I do not mean by my motto is monstrousness in the sense of fantasy. What I do mean is monstrousness in a particular science-fictional sense (a Labatutian-Lovecraftian-Ballardian sense) — a slightly monstrous human is one who has been transformed through co-evolution with emerging technology in a Gramsci Gap, and who has come to viscerally embody the strange new rules of that technology.
This notion emerged out of my other big obsession over the last 5 years, protocols. This has been the other half of my work in recent years, and it has shaped my philosophy and writing a lot (not least because it involved a lot of writing and editing of other people).
Between 2023-26 I was running a program for the Ethereum Foundation called the Summer of Protocols. This has now evolved into a new organization called the Protocol Institute, where I’m the Director of Research (currently unpaid, because the organization has no money yet). The Monstrous Times magazine also came out of the Summer of Protocols, so it’s a sibling project to PI. Specifically, it came out of an idea we explored through SoP that science fiction is about strange rules, while fantasy is about special people, or “chosen ones.”
It’s an idea we call Chiang’s Law, after Ted Chiang, who first articulated it. Right before he chose AI Derangement Syndrome as his chosen path through the Gramsci Gap. I like the irony. I always like irony. Monsters like irony (are monsters GenX? 🤔).
Anyway, for nearly two years, a bunch of us have been exploring the emerging future through fiction based on this premise (me as editor more than writer, though that will change soon). We’ve dubbed this new genre protocol fiction. One of my own contributions to this emerging genre is this story, The Signal Under Innsmouth (April 2025), a Lovecraftian pastiche (AI-generated of course!). This was a bit of a personal breakthrough for me, both in terms of revealing just how good and actually entertaining AI-generated writing could be, and in making legible the idea of becoming monstrous through technological transformation, and the internalization of strange new rules of being and becoming.
This leads to an interesting thought. What does it mean to not embrace co-evolution with technology; to not accept such transformation in what it means to be human?
It means being attached to a particular, historically contingent frozen snapshot idea of what it means to be human, based on the people alive and grappling with the question of AI circa 2024. A chosen people, presumably representing the pure acme of human development, who are choosing to head down a cul-de-sac of being and becoming. Who increasingly inhabit an enervating fantasy of humanism; “acting dead” to borrow a term from Bruce Sterling.
There’s a deep irony here that I’m still thinking through: That attempting to preserve your humanity as you navigate the Gramsci Gap may be the most deadening thing you can do, while embracing monstrousness may allow you to tap into the deepest kinds of liveness you can access today.
Again, this is not a bit. And it’s not a drill either. It’s a real unfolding praxis for me. If using AI is going to do irreversible horrifying things to my brain, I’m already partway there.
I’ve done two talks on this idea in the last month alone (one as part of the Biennale exhibit, and one as part of the Monstrous Times official launch party), and I nearly have the idea properly worked out enough to write about. So expect to see it pop up here soon. It’s going to be part of the New Nature book I’m going to tackle in November.
Oh, and speaking of liveness, that’s another of my pet themes, and next year, it will be the focus of the book club I run (this year, the book club is exploring another of my favorite concepts, Divergence). You may want to read my two posts so far on this topic, In Search of Liveness, and Engineering Liveness. It’s how AI and protocols are coming together for me, conceptually. I hope some of you join the book club, which also feeds a research group on psychohistory (yes, the Asimovian kind) at the Protocol Institute.
Anyway, that’s it for my introduction for new people (and re-introduction for those discovering that I’m now undead). Hopefully that provides some orientation in the thought spaces I like to explore with my fellow monsters-in-training, and also gives you a sense of where the human fraction of ideas like “cognitive mercantilism” come from.
Happy Halloween!
A suburban Chicago man has been sentenced to two years in federal prison for conspiring to stage armed robberies so that the purported victims could apply for U.S. immigration visas reserved for crime victims.
From 2022 to 2024, PARTH NAYI organized and participated in hundreds of staged armed robberies at coffee shops, restaurants, liquor stores, and gas stations throughout the country, including in Chicago and the suburbs of Lombard, Elmwood Park, St. Charles, Hickory Hills, River Grove, Lake Villa, and South Holland. Nayi worked with others to recruit fake victims, pay off store owners to use their locations, coordinate and pay fake robbers, and coach the bogus victims through the plan. Thousands of individuals who posed as victims each paid Nayi $5,000 to $30,000 to participate in the scam so that they could later apply for Nonimmigrant U-Visas, which are set aside for foreign nationals who are victims of certain crimes and are helpful to law enforcement in the investigation.
During the staged robberies, individuals acting as robbers brandished what appeared to be firearms, approached the purported victims, and demanded money. Afterwards, the purported victims submitted forms to local law enforcement to obtain certification that they were victims of a qualifying crime and were helpful in the investigation. Upon receiving the certification, the purported victims then submitted fraudulent U-Visa applications to U.S. Citizenship and Immigration Services predicated upon their alleged status as robbery victims.
Here is the full story, via Ryan.
The post Those new service sector jobs? appeared first on Marginal REVOLUTION.
Bryan Caplan:
It seems like you and other AIs are bad Bayesians. When presented with counterevidence, you should move toward or against the presenter with roughly equal probability. It depends on whether the argument was better or worse than expected. In fact, you seem to either move toward the speaker or just not change.
ChatGPT:
I think you’ve identified a genuine and important failure mode in AI reasoning: LLMs tend to treat a plausible counterargument as evidence in favor of its conclusion, rather than comparing the counterargument to what they should have expected to hear.
Your Bayesian point is correct, with one qualification: there’s no general theorem that updating toward and away from a speaker should happen with equal probability. But under appropriate calibration assumptions, both directions should occur, and an argument that’s weaker than expected should cause a negative update—even if the argument is perfectly valid as far as it goes.
Here is the full dialogue. But will they try to fix this? Should they try to fix this? Can you undo this with good enough prompting? The scope and limits of Bayesian are truly at stake here…
The post Are LLMs good or bad Bayesians? appeared first on Marginal REVOLUTION.
How We Took Over ChatGPT Accounts
Parameter Labs describe an exploit they found against ChatGPT's implementation of the artifacts pattern (OpenAI used to call this "Canvas" but it looks like the latest revision is called HTML previews), where interactive custom HTML apps are displayed in a sandboxed iframe.It's important that HTML in these stays tightly sandboxed to avoid untrusted code interacting with OpenAI APIs and accessing private data.
Parameter found quite a complex attack chain. OpenAI use the MathLive JavaScript library as part of their graph support, and that library includes its own virtual keyboard, which can be triggered in the parent page via postMessage() from the sandboxed iframe.
That message receiving code uses innerHTML, so anything that sends a message can add custom HTML to the parent - and there was no mechanism to prevent other sandboxed frames, including HTML preview frames, from calling that method.
This meant untrusted code in an iframe could insert HTML, and while innerHTML doesn't directly execute script elements it could be used to inject a new iframe without sandbox restrictions.
OpenAI’s CSP rules blocked inline scripts entirely, and only allowed script loading from a handful of domains, but one of those was YouTube - and the YouTube oEmbed endpoint could be used to reflect JavaScript back in a way that executed it.
Once the attack had JavaScript execution on ChatGPT, it was trivial to fetch private user data from APIs and exfiltrate it via an image reference.
The end result: you could create a ChatGPT share URL which, when visited by another signed-in user, could exfiltrate their private data or take actions on their behalf.
OpenAI closed the hole and paid out a $5,000 bug bounty, which I think was a bit cheap for a vulnerability this serious.
Via Hacker News
Tags: iframes, javascript, sandboxing, security, xss, openai, chatgpt, content-security-policy
Release: datasette-llm 0.1a9
I have some big upgrades to Datasette Agent in the pipeline, but in the meantime here's a tiny user experience improvement to the underlying datasette-llm plugin.
It now picks up the default model used by LLM, which means you can start using Datasette Agent without needing to explicitly configure a default model:
uvx --with datasette-agent datasette content.db --internal internal.db
Previously you would also need to specify a model with -s plugins.datasette-agent.default_model gpt-6-astra.
Tags: datasette, llm, datasette-agent
. . .
TRANSCRIPT:
Paul Krugman in Conversation with Azeem Azhar
(recorded 10/29/26)
Paul Krugman: Hi everyone. I am talking today with Azeem Azhar, writer, researcher, investor with Exponential View, who is one of the people I turn to when I don’t understand what’s happening with AI, which is basically all the time. There was a really striking piece that Azeem wrote the other day about the PHP hack with the title, “The Wuhan Moment.”
Why don’t you explain to me what you mean by that, and let’s try to understand what’s going on here.
Azhar: Yeah. Well, that PHP hack was just one particular instance of a range of things that are now happening because AI models have become good enough. And the reason I called it the Wuhan moment is that there are infectious diseases all the time, but then came along one with slightly different characteristics, and it had a much bigger impact than all the other ones that were circulating.
So, when I say AI models have gotten more capable—we’ve had this experience as we use ChatGPT, it gets smarter and smarter—and AI models became good enough to be used in code, to be directed to find vulnerabilities and weaknesses and bugs in software. And because AI systems are tireless and indefatigable, and you can just spin more of them up and they don’t get exhausted, they’re not like human security researchers or human hackers. They can find all of these vulnerabilities, many vulnerabilities, quickly. They can research them in novel, non-human ways and chain them all together. And that’s a new regime that we find ourselves in. And it feels different to where we were a year or two ago when these weaknesses and vulnerabilities were discovered methodically by the occasional hacker, but generally by security teams. So that’s the moment.
Krugman: So my understanding is that basically the way the world works now is that there’s software everywhere. Everything is being run on software which is complicated and maybe not that carefully put together. Tell me if I’m wrong on this, but I think it’s sort of on stilts where you have newer software laid on top of older software, and God knows where the vulnerabilities are.
Azhar: Well, software and technology is this really big industry that somehow managed for 50 or 60 years to escape any part of safety testing.
Krugman: Right.
Azhar: And so, you know, that’s why you have beta releases and bug fixes, because the culture of software development for the longest period of time has been started from a tinkering mindset. And there’s no real security model required around software. It’s not an AI problem, it’s not a social media or an internet problem.
It was a problem in the ‘70s and the ‘80s. It’s just that we started to move from centralized mainframes to having personal computers and many, many more opportunities for that software to be developed in a decentralized way. And so here we are decades later, and it’s a miracle the internet works, given how many bugs and issues there are. But that has also been its benefit, because what it has by not being a fixed cathedral is agility. One software developer likened it to a crowded, buzzing bazaar. It has the ability to respond, adapt, and stay pretty resilient, which the internet has by and large done, except for a few major cyber attacks over the last 25 years. So what was a feature, and a flaw recognized by software engineers, that there’s no agreed security model for making software—has also been the reason why we’ve had a flourishing of software, and we are able to continue on our way even when bugs are found and there are problems that get discovered.
Krugman: Right. And a lot of it is based on PHP. You should probably tell people what it is. I mean, I actually had never heard of it until last week, but of course...
Azhar: Well, you’ve certainly used it. In reality, 70% of websites are running on PHP. It’s a programming language that happens to be very easy for people to use, and so it was cheap. If in the late ‘90s you wanted to write a piece of software, you used PHP. It’s simplistic; it doesn’t have the learning curve of C++ or something else. And it got extended and extended. Facebook used it a lot, and so it became part of the internet’s architecture. And like many other systems we use, like Python, which is another language, or BIND, which is a piece of software that turns friendly internet addresses like Substack.com to the numbers that the routers need. These are pieces of software that are actually open source as well, you know, they’re written by collaborations of volunteers who have their own governance systems, who share that code in repositories. And again, if you don’t think about it, you’ll be surprised. And it feels like it’s a miracle that it works, but we have evidence and proof that it does.
Krugman: Okay, and how relevant is it that it’s old? That PHP is a ‘90s thing. It’s all jerry-built, which was good enough until now we have these AI models that are tireless, right? And basically an army of gimlet-eyed experts in deception can go and find the holes, right?
Azhar: Right, yeah. I mean, the whole setup was maybe not quite on stilts because it all worked. It also has to be recognized that it’s really hard to write extremely precise, foolproof software in an enterprise—be it a corporate, consumer, customer environment—because standards change. If you want to understand why, think about the experience when you’re flying on an old plane, as you will across the Atlantic, and you pull up the in-flight entertainment, and the software is so slow compared to your modern smartphone because it had to be designed and locked down 18 years ago, or 10 years before the airline bought it, and it’s still in place. So all of these things were really part of the trade-off that we as customers and consumers made to have something that would adapt and be responsive to our lives. None of us really want to use the type of software that runs a nuclear power station, right? Because it’s stuck in the ‘70s or ‘80s. And that means that there are just lots of different ways of getting these pieces of code to crash, and once they crash, maybe to get access to the machine and figure out where to go next. And that’s what great hackers do.
AI models crossed a threshold at the start of this year when Anthropic had a model called Claude Mythos. It’s the best cybersecurity model in the world. It was not made widely available. In fact, only a small number of organizations get access to it. And they’ve been running around trying to patch or fix these bugs and close loopholes. The first part is finding them. But one of the things that happens with AI, is that the capabilities cascade down to cheaper models very, very quickly.
And so at some point this summer, the open-weight models, also known as open-source models, started to get towards the capabilities that Mythos had. And so they, too, crossed that uncanny valley into a point where they can be chained together and directed by either hackers or bad actors to find vulnerabilities before the good guys find them and then try to exploit them. And we’ve seen an uptick, a rapid increase in the number of those vulnerabilities that are being discovered. And this PHP one was one example of it.
And I guess what I was writing in my essay was to say, Look, what we know about these technologies is that they get cheaper, and as they get cheaper, they get used far, far more, right? We all take many more digital photos than we do film photos now from 40 years ago. The same thing would likely happen here. And that means if there are vulnerabilities or exploits, however obscure, it’s quite possible that they would be found and exploited. And I’ll just mention one data point that I’ve seen. There was one particular piece of software that had been tested for vulnerabilities trillions of times by humans running test suites. And yet a recent AI model was able, despite that, to find severe vulnerabilities that could be exploited. So even though we’ve looked very hard, we can never guarantee that these things are 100% robust.
Krugman: And this sounds like it’s a constant arms race. Now you’ll be using AI to try and patch or protect, but it sounds like inherently the advantage is going to be with the bad guys, right? It’s going to always be hard, or am I wrong?
Azhar: Well, I think the bad guys move more quickly than everyone else in general. Remember, the bad guys only have to find one vulnerability at one place. The good guys have to defend every vulnerability all the time. And so I think it would be fair to say that there are lots of private sector organizations and government organizations that are ahead of the curve, but there are also billions of computers connected to the internet and trillions and trillions of lines of code and systems that haven’t been updated for years that could be vulnerabilities. And that’s why the Deputy Chief Information Security Officer at Anthropic said it’s going to be quite a rough 18 months.
And I think what I alluded to in my essay was that there is that period where, you know, just as it was with the spread of what we then called, believe it or not, 2019-nCoV before we called it SARS-CoV-2, things can spread faster than we can figure out what we can do about it. And I think that that’s the risk that emerges in that shorter period of time.
Krugman: And what we did do to deal with the spread of the coronavirus, with extreme political consequences, was lockdowns. And you suggested that we were going to be seeing a lot of partial disconnect from the open web. So, how does a walled garden actually operate, and can we even do that now?
Azhar: Well, arguably, Paul, I think we may already; many of us spend a lot of time in walled gardens. If you live in Instagram or you live in Facebook, it’s not the open web that you and I remember. It’s not the open web I fell in love with in 1992, where you go from one place to the next. And you know, even so many things require password authentication to access. But I do think that what you’d expect to see is that the number of AI agents will rapidly exceed the number of humans. I think the amount of .browsing that is done by bots on the internet now is higher than humans. It’s always been high because search engines have to crawl, and people who are buying things on eBay will use price-sniping bots to keep an eye on the listings. But that will tilt enormously towards the machines over the coming few years. The internet and the companies on the internet will evolve to meet that demand.
The way that I liken it is that if you think about Fifth Avenue in 1895, there were more people strolling in the middle of Fifth Avenue than there were automobiles. But by 1920, people didn’t stroll down the middle of the street. You don’t go for an afternoon walk on the freeway. You might go for an afternoon drive and use the freeway to get you there. And so I think that the internet would need to start to filter out what these AI systems need. They move really quickly. They’re trigger-happy. They work in milliseconds. We work in seconds. They have completely different technical requirements. And that will mean that that would occupy a different patch of cyberspace to the patch that we want to be in.
And in particular, if we want to be really, really secure and robust about threats, we might choose to say, “I want to stay in an enclave that is safe.” And I think a good example of that is what Apple does with the Apple Store. In some countries you can use third-party stores—but mostly you have to get apps from the Apple Store, because Apple wants to say, “We’ve checked that this is safe.” Whereas in Android, you can go anywhere. And that’s why there are many more viruses and safety problems on Android. So I do see this potential journey where the internet needs to serve the kind of economic requirements of companies using agents, which means how fast it is, whether there’s transactions and pay-as-you-go and validation and so on. But that may not be the way that we will want to operate on the internet at all. It will feel it’s not for us in the same way as the 101 highway in California is not for humans to have a stroll down.
Krugman: So it’s going to be a world in which, instead of being able to let a bot go and make purchases, you will have to prove that, or you know, offer some evidence that you are you, or only certain things will be available; just a much pokier environment, is that it?
Azhar: I think you’ll end up having to validate your bot, and you’ll have to give your bot your approval, and the bot will have a set of rules. It’s allowed to spend $50 without sending you the approval link or whatever the system happens to be. And the truth is, I don’t think we know at all right now what that would look like. I mean, people are experimenting, and my sense would be that publishers in particular, and then retailers as well, will start to publish listings for consumption by machine agents in the way that they need to see the material, which is much more structured, much less emotive, just with more data that they can navigate around. And they’ll do that because you or I are quite likely to be using an agent on our iPhone or an agent from Meta to interact with wherever we know we’re buying or browsing. I mean, I really don’t think we’re there yet, but I think people in the industry generally think that that’s the direction that we would go.
And I have a little bit of experience myself because I have a bot that keeps track and looks out for concerts I might want to go to, because I don’t like going to venue websites because they’re all different from one another. So the bot knows my music tastes, it’s got my music catalogue, and it checks every week or so to see if there’s a ticket I might want to buy and tells me about it. So, I’m no longer visiting those venue websites, but I am going to be paying for the ticket.
Krugman: I remember how freaked out I was when I was a very early Amazon book buyer, meaning physical book buyer, and when Amazon started recommending music to me. I never actually did buy any music from them, but the recommendations were pretty good even then. And that was kinda shocking to realize that at some level, from the books I bought, they figured out what music I probably liked. And it’s just a very spooky world for someone my age.
Azhar: I think it is spooky; it’s spooky for all of us when you get those suggestions. I mean, you can probably do it in ChatGPT. If you took a photo of my bookcase and stuck it in ChatGPT and said to it, you know, “Recommend some books that this guy might like,” I think it’ll do quite a good job. I remind myself that it’s math, that’s what it is. It’s kind of traversing an enormous matrix and it’s finding some likelihoods.
Krugman: No one listening to this will know what I’m talking about, but it just shocks me that basically matrix multiplication with a few nonlinearities can do all of this. It’s just absolutely bizarre that it works.
Azhar: It’s so weird. It is so weird.
Krugman: Okay. But this is a little less apocalyptic than what I took from reading your piece. But I guess it still may be very, very scary. You think that we will eventually have worked out a reasonably seamless way of making it work?
Azhar: Look, what is an apocalypse? If we look at what happened with COVID, could COVID have been much, much worse? Yes. Was COVID really bad? Yes. Was it apocalyptic and awful for lots and lots of people individually and also for entire cohorts? Yes. I mean, imagine the kids who did their college in lockdown on their own away from home for the first time. I mean, that is just awful. So I think that those are bad outcomes. I think the thing that we’re dealing with here is that it feels like over 18 to 20 months people will have figured this out, and those guys are not going to get much sleep, but in the meantime really uncomfortable things could happen. You know, you could get a bank that just fails to get ahead of the ball, and your money in a bank is only an entry in a database. It’s not in Jimmy Stewart’s hands, right? And the cash is literally just a line in an Oracle financials database. And that would be pretty apocalyptic for people.
And I think that we can’t rule out what statisticians call tail risks, but we can’t see those tail risks, right? They’re Donald Rumsfeld’s “unknown unknowns.” And what we do know is that the internet with all the billions of machines connected to it is now much more porous and much more vulnerable than it was two or three months ago. And so does that mean that something quite bad could happen? Lots of things like power grids are sometimes connected or accessible to the internet. Well, it’s more likely now than it was a year ago because of this. And that’s where we have to be very, very proactive.
I’ve spoken to policymakers and a few months ago, I went off and I said, look, you need to come together and have a public-private agreement partnership where the state is actively encouraging small, medium, and large companies that are not tech companies to ask the right questions, to make sure these things are being proactively fixed because there will be a moment when you cross this uncanny valley, and the vulnerabilities will magnify hugely. So, I mean, it has to be taken really, really seriously.
If I don’t sound like I’m running around panicking, it’s because I model important things on Sully Sullenberger, the pilot of that plane that landed on the Hudson. You know, he had 115 souls on that plane and he didn’t panic. And there’s a great media interview with Katie Couric where she keeps asking him how he was feeling and was he panicking? And he is cool as a cucumber because at moments like this, when things matter, we want to use our evidence, we want to use data, we want to use our judgment, we want to think calmly. So I think it’s serious. People should act quickly.
Krugman: Okay, but how many people in major leadership positions in the world remind you of Sully Sullenberger?
Azhar: Well, I mean, you know, democracy is the best system we’ve got. Unfortunately, you know, that’s what it is.
Krugman: I know. Or as Churchill said, “The worst system except for all the others.” But anyway, yeah.
Okay. Before I read about the hack apocalypse or the possibility thereof, the big question we’ve all been asking is about an AI bubble. For many of us, our kind of formative experience on this was the IT bubble of the ‘90s, which more and more I’m starting to think is actually not a very good model for where we are right now. But you’ve been, you know, not a wild-eyed enthusiast, but you’ve been basically saying, “Calm down. There’s a lot of evidence that this is at least not that bad of a bubble.” Do you want to talk about why you’re coming down on the calmer side here?
Azhar: Yeah, not that bad of a bubble yet, might be the better way to phrase it. One thing that I have noticed in the debate over the last couple of years is that it splits between descriptive discussions—the facts of the world and normative discussion—and feeling: the oughts of the world. And people sometimes find it really hard to separate those. And I think the debate gets extremely heated, very passionate, but probably not particularly helpful. And I would say that everything that I say really is at this point descriptive. I’m not saying it ought to end one way because the world would be better or another, right? So I think that’s quite important.
Bubbles and this overexpansion of investments during any technology are really, really common, as you know from your own work. The real pain emerges when customers don’t buy enough to pay for the financing of whatever it is required to build the factories, the infrastructure. And that mismatch is what creates bubbles. It’s what created the railroad bubbles in the US. It’s what in some sense was happening with dot-com and with telecoms. Not every investment wave in a new technology ends in a disastrous bubble. Most of them do, and mostly it happens because the financing gets too exotic, it gets too circular, it gets too big. But not every one does. Automobiles in the US, for example, didn’t end up in a bubble. They ended up in lots of companies failing and there being consolidation, but generational companies came out of it, as well.
And so when I look at what’s going on with AI, the question that I’m asking—and we look at the data—is, what is the weight, the ballast? How is the complexity of the debt and the financing that is building up set against the way customers, mostly companies, are spending? And does one outweigh the other? And I think that a lot of that can be measured. A lot of that can be driven by fact rather than opinion. Some of it is unknown, and that’s why I’m calm. I have a view which is that, to put it simply, when I was starting out at work, my first mortgage was for 85,000 pounds, so like $110,000, this is 30 years ago, and that was really tough for me to pay. My mortgage today is substantially larger than that, and it’s quite easy for me to pay. And if I took today’s mortgage and gave it to me at age 24, I would have been crushed under the weight of it.
So the scale of the debt, the finance obligations, have to be put in proportion to how customers are spending and how they may spend. And that’s why I’m a little bit calmer, more sanguine right now, although I do think that the bubble metric is higher today than it was a year ago, you know, for the reasons I’m sure we’ll explore.
Krugman: Yeah. There was first a debate about how productive is this technology. It’s obviously awesome. It’s still hard to believe that basically matrix arithmetic can sound so much like a person, but there’s still some argument. There’s still some people saying that, okay, this stuff is amazing, but we can’t see it in the aggregate productivity numbers. Have you been taking that on at all?
Azhar: It’s very difficult to see it in aggregate numbers. You’re a far greater economist than I am so I’m not sure when you would expect to see it in aggregate numbers. And I’ve heard one economist in China—I was in Asia a few weeks ago—saying they’re starting to see some numbers in some sectors. I still think it’s very fair to say that they’re not showing up in aggregate numbers. They are showing up in small numbers of companies outside of the tech industry. Depending on which survey you believe, it’s between 5 and 10% of large companies seeing maybe a 6% benefit, increased sales, lower costs.
Krugman: Yeah.
Azhar: And that could increase. What we don’t know is whether the other 90% will turn into that 10% in one year, two years, five years, 10 years, or ever at all. And they may not. And we don’t know what percentage of that 10% will get more and more benefit and therefore spend more and more. But I think it would be—with something like this, it’s a little bit like a doctor trying to understand a complex disease. You don’t just take the patient’s pulse. You take lots of tests and blood tests and you try to paint a picture.
So certainly, there’s not much in the aggregate statistics, certainly not in the US. There’s some sector evidence, there’s some evidence from surveys from companies. I talk to executives quite a lot. What execs tell me is that this is harder than they thought. More of them are getting success. Everyone intends to continue to spend next year to try more. When does that show up in a number that an economist like you can say, “Here’s a number.” I mean, I think that’s a really important question. If it takes too long, then it’s probably the case that revenues are not going to grow fast enough to pay for the mortgage.
Krugman: Okay, so to get back to revenues in a second. Where I would be looking at the IT boom of the ‘90s, you know, by 2005 we were talking about total factor productivity. In aggregate, we were something like 10% above where the previous trend would have expected you to be, which is a lot, although it kind of stalled out after that. But we are, I would think in terms of the timing, something like in 1999.
Azhar: Mm-hmm.
Krugman: The productivity benefits were a lot more obvious in the first four or five years into the internet bubble. So I don’t know what to make of that.
Azhar: Yeah, my recollection is that it was even earlier with IT. I thought that the real rapid speed increase was in that ‘94 to ‘98 period. It happened to coincide, I think, with Bill Clinton as president. So he was able to do all sorts of things with the budget and so on. So it was pretty quick and sustained. And the question is, where are we with this ChatGPT thing? I think that the clock should start probably a year after ChatGPT, which is when Microsoft and Google released enterprise, corporate versions of what they were doing. So that’s been three years. And the question is, how fast would we expect it to go, and is IT a fair comparison? And with IT, people had to buy computers, for example, which is a much higher cost than paying for a ChatGPT subscription.
So I think that there’s a reasonable case to say that this is not yet provably faster than IT and could well be slower, right? I think that would be a reasonable position to hold today. And I have some ideas as to why that might be. Like what is the cause of the inertia within companies, and does that mean [the return on investment is] not as quick as we might’ve hoped or thought?
Krugman: But then the second question is, suppose this does great things for aggregate productivity growth. It really is great for the economy. The question has to be how much of that is captured by the companies, right? In the end, the internet was great, but you can look at those old Qwest ads from the ‘90s about this wonderful new world of the broadband internet, and everything in the ads has come true, but Qwest is no more, right? And so, how much should we be worried that Anthropic and OpenAI and maybe some of the others are busy doing all these great outlays and producing great stuff, but that everybody will end up buying Chinese products that are 90% as effective and 90% cheaper?
Azhar: Well, I think that we have to separate out the companies like OpenAI and Anthropic with the companies who are actually paying for the capital expenditures in the data centers, which are the infrastructure companies. And those companies will make money whether Anthropic is selling to you or whether you’re using a Chinese model, because the model still has to run on a computer.
Krugman: Okay.
Azhar: And that computer is a GPU probably owned by Microsoft or Amazon. So they will still make money at the infrastructure layer. And so we try to separate out how much money flows to the infrastructure layer versus how much goes to the model lab companies like OpenAI and Anthropic. Even if people do move to those cheaper models, I suspect that there’s enough capital flow, and enough business, at least for the next couple of years.
However, what we constantly hear from the industry is that there is a huge undercapacity of computing. Just before we recorded this, Microsoft and Google had their earnings announcements and they said the same thing again: we just don’t have enough compute capacity to serve all of our customers. So I separate out OpenAI and Anthropic. And I think when I look at Anthropic, the company published a document that’s called an S-1, which is the marketing document before it goes public. And we forensically went through it and deconstructed it. And I was quite surprised by things that I saw. For example, margins are a really important part of whether a business can survive or not. And Anthropic’s gross margin from over the compute costs that it pays is about 85%. That number was about minus 200% two years ago when lots of people were saying this company was going to die within a year or two. (And these people have not corrected themselves, by the way.)
And so I think that’s a surprise that the margins are as strong as that, that they are making profits in that way. Of course, your point remains, though. Like, there could be deflation or price competition from cheaper models, but in the end, the infrastructure bill mostly lies with infrastructure companies, and they will still make money serving open-weight models.
Krugman: So the open-weight—I am embarrassingly weak on exactly what we’re talking about here, but that’s okay, I think. Although the open-weight models are, at least as I understand, they basically just do a lot less computation than the full sauce, but nonetheless the demand for compute is still skyrocketing.
Azhar: So the reason open-weight models are cheaper for us is that they’re effectively put out for anyone to download like open-source software. So you’re not paying a profit margin to OpenAI or to Anthropic. You’re paying just the margin that the infrastructure company is going to put on that model for serving it. You’ve disintermediated one layer of margin. As to whether they’re actually cheaper in tasks, this is a hotly contested issue where they might be cheaper by the token, but you need more tokens to get a task done, so they end up being more expensive.
And my view again is a little bit sanguine about this. I’m pretty certain that there’ll be a lot of workloads moved onto open-weight models. But I also think that Anthropic and OpenAI resemble software companies of the past: there were cheaper open-source alternatives to Microsoft Office, like LibreOffice, but nobody used it. Most companies just went to the branded business, and so did that. And I think that there is a simple mental model that says that even if they lose lots of market share, they can still persist as businesses because there will be the typical reasons that people buy software to buy their products. I think the big question is how much market share would they lose and what happens to their pricing power? And the truth is, I don’t think anyone can look out over more than a few months to have any certainty. That’s why I go back to all the data that I look at and see all the data that can contradict the arguments that I’m making, to just make sure that I’m calibrating myself.
Krugman: But that’s the thought, that ChatGPT and Claude will end up being the Microsoft Words of the future. Basically inferior products that everybody uses because nobody gets in trouble for buying it.
Azhar: Well, yeah, it might be that, but I do think that they are still better products. In my team, we use a lot of open-weight models for the work that gets done because it’s often good enough, fast enough, cheap enough. Weirdly, I particularly use an open-weight model for one of my agents because the model is not as sort of machine-intelligent as the state-of-the-art models. So it does what I ask it more often. If I swapped it out for an expensive state-of-the-art ChatGPT model, it would often do more than I asked, right? And I would say, “No, but that’s not what I wanted. I just wanted the simple thing done. I wanted you to get me eggs. I didn’t want you to bake me a whole cake.” And so there are all these things, Paul, that we just don’t understand right now. We have to feel our way, and on the back of it is like $5 trillion sitting on top of it.
Krugman: Yeah, that’s right. I mean, there are some places apparently trying to use AI for air traffic control, and it’s like you might get the response: “I’m sorry, you were right, there was a plane already sitting on the runway. Would you like some advice on how to deal with mass casualty events?”
Azhar: Right. Well, fortunately, we haven’t got there at the mass level, but of course there have been kind of horrible stories of people who’ve been sort of taken down by AI psychosis, and to the end of their lives, which of course is a horrible outcome. But I think there is a risk in this debate about a bubble or a boom, and it tends to present a binary. And I think there are other outcomes. There is an outcome where there’s not a bubble that bursts, but a period of very, very low returns for the companies who’ve made these investments. So it’s not great for their investors. But you don’t see that kind of cataclysmic arrest as we saw in the housing market in the US when housing starts completely stopped after the global financial crisis.
One of the reasons I think it’s important to think about other scenarios than financial catastrophe is that if American and European companies do start to get results and do pay enough as customers of these businesses so that they can afford to pay this metaphorical mortgage they’ve taken out, where does the load of that lie? The load of that is quite likely to lie on the workforce. And we could blind ourselves—by getting so excited about Bloomberg’s terminals turning red as share prices fall—to starting to take proactive steps on the possibility that the technology actually does work, does deliver greater productivity, that companies as a result do cut costs, and some of that falls on the workforce. And I think that’s too important to leave to tabloid shouting over financial calamity.
Krugman: Yeah, I am mainly worried about how capital intensive this stuff is. There is definitely a competition for capital and these data centers essentially employ no people. You take eight billion dollars that might have been creating a bunch of jobs, and you end up with a hundred maintenance workers. But let me just ask you, since one of the things I’ve been hearing, and I have no ability to assess, is that presumably there will be a lot of money-losing investments. You know, there will be investments that companies are sorry they made or the company ceases to exist, which can be okay. We had that in the IT boom of the ‘90s because the infrastructure wasn’t there. But then it was. So we had a lot of fiber that stayed dark for years, but then eventually all became useful again. But the story that some people are telling me, and I have no idea whether it’s true, is that these investments will depreciate really fast. That they will depreciate financially because the chips get outmoded, but even perhaps more so because they literally, physically deteriorate. Is that a concern?
Azhar: This is another example where we have data to help us.
Krugman: Okay.
Azhar: So these chips do, of course, go obsolete just like any other chip, and they tend to be carried by infrastructure companies on depreciation for between five and six years. The evidence comes through public, regulatory statements that people have made, so we can kind of assume that they’re true. And what they say is that even eight- or nine-year-old chips are still being rented at premium prices because demand is so high. Will a 2026 GPU, one of these computer chips for AI be in use in 2046 the way an 1888 rail line is in use today? No, it will not be. I’m sure of that. But at the moment they pay themselves back within two or three years.
Krugman: Okay.
Azhar: Now what happens if one of these smaller infrastructure companies fails? We talked about the smaller ones who are not the big household names, and of course they’re on shakier financial footings. So if one of them fails, some of their investors, their shareholders, will obviously lose money. The people who’ve lent them money may lose money, but the chips will not be lost. They will immediately be taken over. In fact, a lot of the contracts have what’s known as an interrupted-in-service clause. So even if the legal entity that owns them fails, the customer still gets serviced and served. And as long as we’re in an undersupply of compute, which we appear to be, those things will get picked up. And I think we could expect that out of these hundreds of rinky-dink small infrastructure companies, there will be a lot of consolidation over the next few years because markets don’t support that many individual players.
Krugman: Right. So the dismal analogy that people have made is with fracking, where one of the big problems with fracking was that it turned out that fracked wells declined much faster than was in the accounting. But you’re saying that that does not look to you like it is really an issue with the chips. I mean, that’s a little bit reassuring.
Azhar: Well, it’s not an issue now, and it’s what the data says. But the thing about semiconductors and infrastructure like this is that we have undersupply right now, but the moment you have oversupply, prices can collapse. And what happens with chip companies generally, and has done over 50 years, is that they go into periods where demand grows, and so there’s undersupply, prices rise, and so they go and build factories, and by the time the factory is built, demand has cooled off, and now they’ve got overcapacity and they have to cut their prices and they lose all their money. So semiconductor investors are really aware of that cycle, and at the moment the question that the model people have to build in their heads—and there are lots of variables—is for how long will demand for computing of AI and these chips exceed the supply that’s provided and the supply that is available? And if that switches because there’s a new algorithm that’s much more efficient that everybody uses, and demand doesn’t pick up, then you could get into an oversupply situation which would have many of the effects that we saw in shale.
But I think there is a difference with shale, because what would happen with shale would be that you’ve got the external price of oil or gas that is setting a recovery price, but even if the price is high you also have the depletion curve of the well where every subsequent barrel—or whatever you’re getting out—is more expensive. So you have that kind of economic tapering off. And I’m not familiar enough with knowing how quickly a fracked well would pay off. But certainly right now, the GPUs that are being bought are being paid off within a couple of years or two and a half years.
Now, there is a bigger issue, right? AI is not some kind of airy-fairy thing that just lives out in the cloud. The cloud is physical. It is steel and sweat and energy and massive buildings. And as you say, buildings that don’t employ anyone. We can talk about what we could do about that. And so there is a scramble to get all the things other than the chips that you need for data centers, like land, like cooling, and most importantly, power. My team and I think that there is an emerging power gap. That is, the amount of power the chips will need set against what power the US grid and the European grids can provide. That’s not that important this year, it’s probably manageable next year, but it starts to become quite significant the year after that. And that raises all sorts of questions because no one’s going to buy $100 billion of chips in 2028 just to not plug them in for six months. So I think that there are these additional risks that make this question quite hard to come down with a definitive answer.
Krugman: Yeah, that’s where I’ve been coming in is to say, even more than the data centers and the connections to the grid or the other power sources, there’s a lot of political veto points. And there’s often local government and angry citizens where that becomes a real issue.
Azhar: Well, let’s talk about the angry citizens. So I think this is a really important thing that’s going on in the US. It is an act of democratic engagement and political engagement. Quite often people who observe the US go, “Nobody votes, nobody cares, everyone’s tuned into TV.” And this is not what we’re seeing now. I think data centers are less popular than ICE, which is one of your less popular government departments. This is an important part, I think, of how during a radical technology change, [there needs to be a] social contract, an agreement that gets hammered out.
As you rightly say, for every $100 million of investment in a data center, they employ 25 times fewer people than an advanced factory. So they’re not local employers. And a deal that got brokered in the UK in order to give permission was essentially for every megawatt of power—and a big data center might draw 100 or 200 or 500 megawatts—the data center operator has to pay $100,000 into the local community, and the total sum was, I’m just looking at my notes, about 500 million pounds, about $758 million. Now, I think that idea of constructing a local license to operate, it’s eminently affordable for both the infrastructure companies and the AI companies that they serve because the margins are so good. They can absolutely afford to pay this. Brokering at a local level, if necessary, these types of agreements I think goes some way. And it’s not just about the money. We have to come back to the point that you made: data centers employ a lot of people during the construction, then they don’t employ many people thereafter. So what can local communities then do in terms of development funds and access? I know the UK better than the US. But funds like that can stimulate the kind of local entrepreneurship and business building that is sort of generative and sustainable for a community.
Krugman: Yeah, one of the things that puzzles me a little bit about the public backlash is why the data center builders aren’t saying, “We will come to Pleasantville County and we will hold open town meetings and we will contract to pay a large sum of money into the county treasury.” I’m not aware of any examples of that, yet it seems such an obvious thing to do at this point.
Azhar: There are a few examples. I think there’s certainly a set of precedents out in Loudoun County which is the hotspot in Virginia. And I know that Microsoft’s campus in Washington state made commitments about what would happen to water bills and electricity prices and put in money for local redevelopment in different ways. So I think the money is there. And that means that half the battle has been addressed already, because it’s not as if you’re asking someone who’s going to make a lot of money to contribute some of that to a local community. And I think that the question is, what do you actually do with that? Do you do as we did in the UK with North Sea Oil, hand it back as tax cuts and God knows what happens 50 years later? Or are you able to use it to inject some commercial economic dynamism that can survive once the construction workers leave?
Krugman: Okay, last question: what scares you? What is the real fear that you have? Obviously, we know that the hacking is something that is looking pretty alarming, but further down, leaving aside maybe extinction of the human race, what do you really worry about here?
Azhar: The first is the extension of the hacking to a state-organized, multi-layer gray war, from polluting the information environment to widespread, increasingly significant hacks on what we call national infrastructure. I’m thinking of electricity grids, financial systems, water systems, where it’s not sort of individual criminal groups, but they are being mediated and managed by a state. I think that’s really, really serious, because we don’t see bombs going off. We don’t think we’re in a period of conflict. Especially in Europe, where there’s much more sabotage going on as well, I think we are getting there, and people need to understand that that risk is real and it exists. So I think that’s one of the really big things that I’m concerned with.
But the second thing, as we talked about, is jobs. And I think that what happens to the workforce, I think will be a very gentle turning up of the temperature. It won’t be a hundred thousand jobs going at once. It will be a reduction in wages, fewer new openings. And then before you know it, the workforce looks different to what it did. And we have to be alert to that.
And finally, I’m super, super worried about what’s going to happen to our brains with brain rot and just relying on, you know, “it’s not this, it’s that,” ChatGPT-isms, and losing critical faculties. I bought all of my team fountain pens. We all write in fountain pen. My desk is covered in pages of handwritten notes. I encourage them to work without a computer a few hours a day. I read really old books, a book from 1794, things that are predating ChatGPT. I use the tools, the AI tools, all the time, but at the same time, I’m really deliberate about how I try to protect my mind and try to pass my thinking and process ideas to my kids who, being the age they are—well, actually two of them barely use AI, but they’re not going to be that receptive. But I think that we have to really think about what is it about human thinking that we need to continue to cultivate and allow it to flourish alongside these technologies that, whether there’s a bubble that bursts and delays it for a few years, whether it’s grinding, whether it’s smooth, it will be with us. And we need to talk about that and actually do things about that sooner rather than later.
Krugman: Okay, I think that’s a good place to end. Boy, scary stuff. Fascinating, but I did not see this one coming.
Azhar: Paul, that’s the nature of AI. None of us see any of it coming. I mean, that’s a sad part.
Krugman: Maybe it turns out that all the people we were saying “learn to code,” should have been saying “learn cursive script.”
Azhar: Might not have been a bad idea. Cheers.
“That is the exploration that awaits you. Not mapping stars and studying nebulae, but charting the unknowable possibilities of existence.” — Q
There’s something about the mindset of really hardcore Star Trek fans that’s very difficult to describe to people who don’t share that fandom. I can’t speak for all of us, of course, but for many of us, there is a sense in which the world portrayed in Star Trek is not quite fictional. No one regards it as an exact description of the future, of course, but there is a sense in which it represents one possible future that we must achieve — a “Star Trek timeline” that either we’re on or that we need to return to. The United Federation of Planets isn’t some fantastical interstellar alliance, but an organization that we must create, and whose ideals we must instantiate as the governing ethos of humankind.
Our quasi-religious commitment to this utopian future came from watching the Star Trek TV shows, but the different series inspired us in different ways. The original “Kirk and Spock” series, which aired in the 1960s, was more of a technological vision — the idea that one day we would zip around the cosmos getting into adventures, as easily as we’d zip around the world in a boat today. But Star Trek: The Next Generation, which aired in the late 1980s and early 1990s, gave us a different kind of vision. It was a moral future for the human race — a depiction of a better way that we could face the unknown and master our own personal challenges.
There has never been another television show like Star Trek: The Next Generation, and there might never be one again. It is the greatest TV show ever made, not by dint of a difference in degree, but because of a difference in kind. It is a drama of pure optimism. Every other show tries to thrill us by showing us how bad or how ridiculous or how exciting someone else’s world could be; Star Trek: TNG thrills us by showing us how beautiful our own world could become.
For such a show to be put on the air required an incredible confluence of coincidences. For one thing, it was syndicated in its first run, meaning that it was free from constant interference by network executives. The showrunner,1 Michael Piller, also did something highly unusual when he opened the show up to outside script submissions; this allowed in a whole lot of highly innovative episode ideas.
But the real secret sauce of Star Trek: TNG was the creative vision of Star Trek’s original creator, Gene Roddenberry. A lot of people — and even a lot of science fiction writers — assume that even as technology makes us more powerful, human nature will remain basically the same, with all its old petty short-sighted hatreds and jealousies and selfishness and so on. Roddenberry believed otherwise. He famously declared that the people of the future would actually be better people, free from the flaws of his day. And so he mandated that Star Trek: TNG have no internal conflict in its plotlines.
Some of the writers chafed at that constraint. Interpersonal conflict is the bread and butter of drama — and always an easy plot device to fall back on when you need something to go wrong. But because Roddenberry decreed it, the writers of TNG were forced to envision how the ideal human being would deal with various personal and external obstacles. And so every episode gave us a thoughtful, probing exploration of what the ideal human beings — or at least, people much more morally and emotionally advanced than us — would look like.
No character embodied that ideal more than Captain Jean-Luc Picard. It’s not his personal life that’s ideal — he famously puts career over family, leading to a life full of self-doubt and regret — but his approach to the world. Picard is the ultimate Reasonable Man. He will always try to understand the alien before he opens fire. He is a legendary battle commander but would always rather negotiate than fight. He’s not necessarily the kind of man you’d want for a father, but he felt like one anyway. He values all life, and all uniqueness, intrinsically; he is zipping around the galaxy in a starship in order to discover the Universe, and occasionally to save it, but most of all to understand and respect it.
Understanding and respect, in fact, are Picard’s greatest weapons. He is a brilliant man, with many brilliant people under him, and occasionally he uses his intelligence to defeat an external threat. But he’s no swashbuckling space cowboy — more often than not, he succeeds in understanding the threat, and figures out how to help it achieve its goals without sacrificing his own. Picard realizes that the highest application of intelligence is not to thwart your enemies, but to design a world in which you and they can live in mutually beneficial coexistence. 1990s America was a uniquely hopeful and liberal time in the world, and Star Trek’s greatest captain embodied the spirit of that too-brief moment.
The character of Captain Picard was brought to life by the peerless acting skills of Patrick Stewart, who died two days ago at the age of 86. Stewart’s acting career went far beyond Star Trek — he’s widely considered one of the greatest Shakespearean stage actors of his generation, if not of all time, and he played in dozens of films. But the tributes that are flying thick and fast around the world today almost all focus on his role as Captain Picard.
I’m of two minds about this. As a very slightly famous person, I can tell you that public and private personas are very different things — if you meet me in real life, I won’t quite be the character you’ve imagined from my writings. That goes triple for actors, whose job is literally to pretend to be someone else. Patrick Stewart was not Captain Picard, but a man with a life and a personality all his own. He was, by all reports, a good man, well-loved by those who knew him and worked with him, but his strengths and his flaws were very different from those of the man he played on television. To mourn his passing as the passing of Captain Picard is to engage in a parasocial relationship.
And yet, I do. I can’t help it. I never knew Patrick Stewart, but I did know Captain Picard, and the death of the real man who brought that fictional man to life makes me remember what I loved so much about the latter, and there is value in that.
Nor am I alone. Today the internet is flooded with tributes to Picard, praising Stewart’s portrayal as an embodiment of an ideal liberal politics, an exemplary moral figure, and even as a model of masculinity:
The remembrance of Captain Picard comes at a pivotal moment for our species. The advent of artificial intelligence — machines that can out-think us — will naturally cause a shift in what it means to be human. As with the Industrial Revolution and the advent of agriculture, we will have to figure out a new way to live — new lifestyles, new forms of government, new systems of economic production and distribution, new reasons to value ourselves and each other.
There are many reasons that the particular future portrayed in Star Trek — one in which human beings, as they exist today, take the lead in physically exploring the galaxy — will never happen. AI is one more reason. This is in spite of the fact that Star Trek: The Next Generation is probably the single best prediction of modern AI ever to appear on the screen. The “engineers” on the Enterprise are clearly vibe-coding and prompting the ship’s computer,2 which is so powerful that it sometimes accidentally creates human-level intelligence as part of a holographic entertainment program.
But in real life, the physical requirements of deep space exploration are such that it will never make sense for human beings to be at the forefront, except potentially as digital uploads. And even if we did go, AI’s superhuman intelligence, data assimilation capacity, and speed would remove most or all of the need for human judgement in the loop. If the Romulans attack us, it will be Claude or GPT who handles them.
But outer space is not our true final frontier. The true space that we, as humans, are exploring is our own set of possibilities. In fact, Q, a whimsical omnipotent trickster-god-being that serves as Picard’s foil throughout the series, says this to Picard in the final episode of the show — see the quote at the top of this post. It is our quest to chart the unknowable possibilities of our own existence.
The ultimate destiny of humankind is a consistent theme of Star Trek: TNG, and the show strongly implies that we’ll eventually ascend to some sort of godlike posthumanity. There are multiple instances of humans or human-like beings turning into some sort of higher cosmic being, and Q himself implies that he’s testing humanity for admission into the realm of the space gods. This is probably where we’re headed in reality — our new AI scientists will help us figure out how to expand our consciousness and merge it with the digital realm, until we become something greater than we can currently imagine.
But before that happens — and perhaps even after it happens — it’s possible to envision a better version of Humanity Classic. It’s possible to imagine that through the right combination of technology, governance, and culture, we can put the lie to the old saw that “human nature never changes”, and become more like the characters in Gene Roddenberry’s universe.
In fact, though the overall picture is murky and the road has been stochastic, there is some evidence that we’ve already been moving in a more humane, rational direction — that Captain Picard is less alien to the human race of 2026 than he would have been to the human race of 1626. We once embraced slavery as a way of life; today we regard it as anathema. We once tortured cats to death in public for entertainment; today that would land you in prison. We are far less murderous than we once were.
It is not clear exactly what led to these improvements. Perhaps with scarcity alleviated — with our bellies full, and tractors instead of slaves — we are naturally gentler and more magnanimous. Perhaps more information has given us more empathy toward people far away. Perhaps the social adaptations needed to handle modern economies — markets, property rights, police, democracy — have tamed and civilized us.
Whatever it was, it offers the hope that we can do more of it — that whatever cosmic ascension we might eventually undertake, human beings as they exist in 2026 are not the best we can do in the current form factor.
I won’t lie. The last quarter century has been brutal to the hopes of those raised on Star Trek: The Next Generation. The promise of a liberal society has not been eliminated, but it has been tarnished by over a decade of social media hatred and rising authoritarianism. Neither greater prosperity nor more information nor giving voice to the voiceless has made our societies more like the United Federation of Planets. Sci-fi marvels are coming to life around us, but every day the people who lead our species seem less like the crew of the Enterprise.
But as the 1990s were not the end of history, neither are the 2020s. Moral progress is not a smooth upward line; there have been reversals before (and there certainly are plenty in the Star Trek timeline). It’s about time to pick ourselves back up and start the journey again. We should all go back and watch Star Trek: The Next Generation, with its silly haircuts and its dated special effects, and remember who we thought we could become.
Farewell to the great Patrick Stewart. And farewell also, Captain Picard. In the greatest trek of all — our search for the possibilities of our better selves — you will always be our Captain.
From the third season onward.
This was a lucky accident, since vibe-coding and prompting are easier to portray on screen than writing lines of code.
Oh, my. Bill Nordhaus has died. He was a great economist, an inspiring teacher, a wonderful academic citizen — and my first mentor. As an undergrad I took a seminar taught by Bill and Tjalling Koopmans on the economics of exhaustible resources. Bill liked my term paper well enough to hire me as a research assistant on his classic 1973 paper “The Allocation of Energy Resources.” Here’s the front page of that paper; see the note at the bottom;
Bill taught me how to be an economist, how to puzzle out a complex real issue and try to frame a model to make sense of that issue. He also showed me that economics can and should be a mission as well as a job. I’ll write more about his contribution and what it was like to work with him soon, probably after the midterms, when I have time to do it right.
Up and to the office, where we sat all the morning, and at noon home to dinner, where Creed came and dined with me, and after dinner he and I upstairs, and I showed him my velvet cloake and other things of clothes, that I have lately bought, which he likes very well, and I took his opinion as to some things of clothes, which I purpose to wear, being resolved to go a little handsomer than I have hitherto.
Thence to the office; where busy till night, and then to prepare my monthly account, about which I staid till 10 or 11 o’clock at night, and to my great sorrow find myself 43l. worse than I was the last month, which was then 760l., and now it is but 717l.. But it hath chiefly arisen from my layings-out in clothes for myself and wife; viz., for her about 12l., and for myself 55l., or thereabouts; having made myself a velvet cloake, two new cloth suits, black, plain both; a new shagg gowne, trimmed with gold buttons and twist, with a new hat, and, silk tops for my legs, and many other things, being resolved henceforward to go like myself. And also two perriwiggs, one whereof costs me 3l., and the other 40s. — I have worn neither yet, but will begin next week, God willing. So that I hope I shall not need now to lay out more money a great while, I having laid out in clothes for myself and wife, and for her closett and other things without, these two months, this and the last, besides household expenses of victuals, &c., above 110l.. But I hope I shall with more comfort labour to get more, and with better successe than when, for want of clothes, I was forced to sneake like a beggar. Having done this I went home, and after supper to bed, my mind being eased in knowing my condition, though troubled to think that I have been forced to spend so much.
Thus I end this month worth 717l., or thereabouts, with a good deal of good goods more than I had, and a great deal of new and good clothes.
My greatest trouble and my wife’s is our family, mighty out of order by this fellow Will’s corrupting the mayds by his idle talke and carriage, which we are going to remove by hastening him out of the house, which his uncle Blackburne is upon doing, and I am to give him 20l. per annum toward his maintenance.
The Queene continues lightheaded, but in hopes to recover.
The plague is much in Amsterdam, and we in fears of it here, which God defend.1
The Turke goes on mightily in the Emperor’s dominions, and the Princes cannot agree among themselves how to go against him.
Myself in pretty good health now, after being ill this month for a week together, but cannot yet come to … [shit – L&M] well, being so costive, but for this month almost I have not had a good natural stool, but to this hour am forced to take physic every night, which brings me neither but one stool, and that in the morning as soon as I am up, all the rest of the day very costive.
My father has been very ill in the country, but I hope better again now.
I am lately come to a conclusion with Tom Trice to pay him 100l., which is a great deale of money, but I hope it will save a great deal more.
But thus everything lessens, which I have and am like to have, and therefore I must look about me to get something more than just my salary, or else I may resolve to live well and die a beggar.
Footnotes
The Hubble Space Telescope still shines in the eyes of astronomers after 36 years in orbit, but it is not as nimble as it once was. Left alone, the observatory will plunge back into the atmosphere in the early-to-mid-2030s, closing the book on one of the most famous scientific instruments of the century.
NASA last raised the orbit of Hubble in 2002, when the Space Shuttle Columbia visited the observatory for a servicing mission. The final shuttle servicing flight in 2009 did not reboost the telescope's orbit, and with the retirement of the shuttle fleet two years later, Hubble has steadily lost altitude with no way to stave off eventual destruction.
The space agency released a Request For Information (RFI) on Thursday asking commercial companies for ideas on how to reboost, service, or a controlled disposal of Hubble. Responses are due November 30. Specifically, NASA is looking for information about companies' current and near-term capabilities for capturing Hubble and boosting it to an altitude of at least 373 miles (600 km), enhancing the telescope's performance, or guiding Hubble to a controlled reentry.
I learned this craft unwillingly, at least at first—and it was all because of music.
It started at age 13, when I pestered my parents to buy me a record player. There was a sweet little model at nearby Clark’s Drugstore. My highest life goal at the time was to place the turntable near my bed and listen to my favorite songs over and over again.
At first, my parents said no. But I didn’t give up. My mother soon grasped how much I wanted this hi-fi and, shrewdly seizing her leverage, finally agreed that it could be mine—but on one condition. I had to enter a local public speaking contest for high school students.
This was an unsettling proposition. I had no experience in public speaking, and I was just a 9th grader, and one of the youngest in my class—how could I compete with 17 and 18 year olds on an equal footing? I considered saying no, but I desperately wanted that record player.
So I worked hard on my speech, and when the dreaded day arrived, I stood up in front of a roomful of grownups, and gave my little talk. To my surprise, I took home the prize—and, a few days later, my first turntable. I kept it all the way through college.
Over the next few years, I entered—and won—a few more speech competitions. And then I was confronted with real life public speaking demands. I won a college scholarship from a business group, but to collect the money I had to talk to a huge auditorium full of people at their annual convention. I walked up on stage and gave a joke-filled speech that was almost a comedy monologue. It had an amazing effect—once again, with an audience where everyone was more than twice my age. I was such a hit that, over the next 24 hours, I got numerous requests for a copy of my speech.
But the reality was that there was no copy. At this stage, I was already speaking without a prepared text—which seemed like the jazzy way to do things. I also found it easier to riff off the energy in the room rather than memorize a talk. That’s still how I operate.
From that moment onward, my life seemed to force me into public speaking at every turn. I got another scholarship to study overseas from the Rotary Foundation, but one of the conditions was that I would give talks at lunches and dinners for Rotarians. I did dozens of these in the US and England, and soon learned what was expected of an after dinner speaker.
The demands got even greater after I finished Stanford Business School, when I was thrust into giving presentations to high-powered CEOs who would interrupt and cut you to pieces at the slightest sign of weakness. Again and again, I was the youngest person in the room, but had to take charge of the situation.
By the time I left those business projects behind to lecture on jazz at Stanford, I was fearless in front of an audience. I was just in my mid-20s, but had already survived hundreds of experiences dealing with every kind of audience, including some very hostile ones. Lecturing to college students was easy as pie compared to situations I’d been through. Even better, my focus on spontaneity meant I could speak on a wide range of topics with very little advance warning or preparation.
In time, I was enlisted to train others in public speaking. But that was trickier. What exactly did I do in front of an audience? And could I teach it?
“The three best kinds of speakers to study are comedians, preachers, and TV wrestlers. Politicians are surprisingly bad at this kind of stuff.”
Eventually I jotted down some rules. Many of them violated accepted public speaking techniques, but that didn’t bother me. You often have more impact by going against the grain. And these rules had proven their value to me over and over again, even in difficult situations where much was at stake.
For your possible benefit, I’ve listed ten of them below. But I must warn you that I have a tendency to do strange things in front of an audience. So you will inevitably find that a few of these rules run counter to conventional wisdom.
I may start my talk at the podium, but I get away from it at the first opportunity. I see others who hold on to the lectern for dear life, almost as if they’re rodeo cowboys on a bucking bronco. But unless you are a father confessor, you shouldn’t keep a big wooden slab between you and your listener.
Speaking is more than just words. Your movements and physical location reinforce the message you’re delivering, or undermine it if you don’t do it right. When you do stand still—as you will from time to time—it creates high drama, and focuses everyone’s attention on what you are saying. And when you move, the energy moves with you. Which leads to my second tip . . .
At a key juncture in your talk, actually move into the audience. This is easiest to do if you are off the stage and on the same level as your listeners. There will usually be a middle aisle in the room, and when you start walking up it you will feel the energy rising all around you.
Humans are mammals and always pay closest attention when others invade their space. At that juncture you will have everyone intensely focused on your presence and totally aware of everything you say—so you only do this at the most significant moment or moments in your talk.
I perhaps take this to an extreme—the last time I used a script was in high school. I do have an outline, but I try to avoid looking at it while I am in front of an audience. So it’s really just an outline in my head. And I will depart from it at a moment’s notice, if it feels right.
Before important talks, I will rehearse a few times—but every rehearsal ends up sounding very different. That’s a good sign, and what I want. So the outline is really more for me to grasp the various ways a talk might evolve when I’m actually in front of the audience.
Not everyone is comfortable doing things like this, but even if you want to take fewer chances, your talk must still feel spontaneous and in-the-moment. The audience wants that. They are energized by something that is happening right now and in this place. They will tune out the moment it sounds like you’re working through your pre-set talking points. Even if you require careful scripting and rehearsal, you still should strive for a feeling of spontaneity when you’re actually facing your listeners.
I’ve never met anyone who went to an event hoping to be bored and disappointed. The audience really, really wants you to succeed, and if you give them even the slightest chance at having a good time, they will cheer you on.
Just understanding this takes away much of the fear of public speaking. Even better, this desire for success is contagious—and in both directions: When you radiate enjoyment, the audience feels it too. When the audience is having a good time, you do as well.
That’s a virtuous circle, and you want you get into it as soon as possible. You should try to find a way of signalling within your first minute in front of an audience that everyone will have a good time today. Often you will even see relief in their faces at the moment when they realize that your talk won’t be a punishment or chastisement. They will be grateful—and you will be too.
At a very early stage, back when I was still a teen, I realized that I had won several speaking contests, but I was still afraid to tell a joke to a large audience, especially of adults. I fretted that they wouldn’t laugh, and I would feel stupid or awkward. To overcome this, I forced myself to tell jokes every time I spoke to a sizable group. Not only did I overcome my fear, but I learned how powerful humor is. It wins the audience’s love and support. The joke can even be second-rate, but they will still appreciate that you cared enough about their entertainment to tell it.
I once took an accounting course from Charles Horngren, who would periodically interrupt his dense lectures on cash flow statements and accelerated depreciation to tell a joke. The jokes weren’t always funny, but we welcomed and applauded them, if only because they showed how much he cared about our mood and engagement.
I’ve met people who believe they are above all this. It’s not just the fear of telling a joke to a huge audience, it’s also a fear that their dignity might somehow be compromised. Don’t believe that for one second. Joking is no joke—even for serious speakers it is one of the most powerful tools in the whole elocutionary arsenal.
I once had to give a presentation as part of a class assignment at business school, and I was the only student who did it without slides. At that point, I was very hostile to the notion of turning my talks into slide shows. Okay, I later made my peace with slides—you really have no choice in many instances. But if you’re bringing a slide deck to the gathering, the audience will never be sure whether they ought to pay attention to you or to the slide.
It’s even worse when you hand out hard copies of the slides to the audience members before your talk. If you do that, you will probably lose everybody’s attention. You’ll find yourself talking to a distracted group paging back and forth in the deck, and ignoring most of what you have to say.
So never give out the hard copies until after you’re done speaking. And when you do talk with slides, try to signal to the audience when they should look at the screen, and when they should pay attention to you. Sometimes you need to point directly at the screen with a thrust out index finger, while at other junctures you should dramatically strut away from the screen in a way that brings attention back to you. In these settings, you’re a conductor, but it’s the focal point of the listener that you’re conducting.
Finally, if you decide to throw out all the slides, and just speak from the heart (coherently, of course), you have my complete support. I note that if you buy a book of the 100 greatest speeches of all time, you will discover that none of them were accompanied by a slide presentation. Four score and seven years ago, as you see from this chart. . . .
Every one of us is an odd duck—you, me, and everybody else in the pond. We work hard to hide our peculiarities and nonconforming behavior patterns, especially in front of strangers. I’m now going to tell you to do the opposite.
You can learn from jazz musicians in that way—they have fewer inhibitions than most, and will do things on stage the rest of us would never consider. Watch Thelonious Monk get up from the piano to dance. Or Miles Davis turn his back on the audience. Or Sun Ra wearing his Afrofuturist garb as if he just got off a spaceship. Or Dexter Gordon doing that bizarre thing holding his sax sideways like it’s a saint’s relic.
The stranger they are, the more we love them. Public speaking is like that too. If you have quirks and eccentricities, let them rip. The audience will remember you for years to come. And, believe it or not, they will remember what you said too.
When you go on a trip, you want frequent updates on your progress—that’s why the map apps give you so much information. Audiences at a talk are no different, so feel free to give them explicit feedback along the way.
If you have something you want them to take very seriously, just tell it to them straight: “I want you to pay close attention to what I’m going to say next.” If you think they are taking things too seriously, you can say: “Why is everybody looking so glum? Sit back, relax, and let’s have a good time today.” If you are entering the final stretch of your talk, you can actually say: “We just have a few more minutes together today, so let’s make sure we make the most of it.” Before your last point, you can actually say: “This is the last point I’m going to make today.” Etc. etc.
These may sound like throwaway lines, but they’re actually key parts of your talk. Listeners appreciate the guidance, which is useful in itself. But they will also be more engaged and attentive, which is another positive. But most important of all, they feel like they are working in tandem with you, and this makes them far more committed to the entire experience and its outcomes.
Whenever I see a skilled public speaker, I pay attention to every word, gesture, and nuance. And if something works, I start using it myself. I had a friend who employed a bizarre gesture whenever he made an important point in front of an audience—he would raise his right hand up above his head, and when he got to the most important words in his talk, he would point emphatically with his right index finger down at the ground in front of him. I have no idea what this gesture was supposed to indicate, but it had an amazing impact on the audience. It was like the gates of hell were about to open up in front of the podium. I started using it myself, and it’s riveting, especially if your downward hand thrusts are in rhythm with your words. Yeah, it sounds goofy, but it works.
I heard another speaker who would wait until after he had made a very important point, then he would pause, and after a few seconds would say quietly: “Do you see what I’m saying?” or sometimes just mouth one syllable: “See?” It was almost a whisper when he said it. I couldn’t believe how much power he extracted from that one word: “See?”
And I have numerous other devices of this sort—specific phrases that engage a listeners, timing effects, odd gestures, facial expressions. By the way, the three best kinds of speakers to study are comedians, preachers, and TV wrestlers. Politicians are surprisingly bad at this kind of stuff.
The audience will feed off your enjoyment. And don’t tell me that it’s impossible to have fun in such a stressful situation. Every last one of us wants to be heard and acknowledged, and you will never find any situation that delivers those goods in more abundance than public speaking. It’s almost as exciting as playing music on stage—in fact, the adrenaline rush feels almost the same in both instances.
So just as you are about to begin your talk, tell yourself: I’m a Rock Star and I Totally Rock! And it’s not a lie—for the next few minutes, that will be exactly what you will experience.
Links for you. Science:
Ohio’s Kroger gets $3 million ‘MAHA’ grant. Critics call it taxpayer-funded marketing.
The efficiency of information gain by natural selection
A New Kind of Chemistry
The phantom lighthouse: new research explains one of Australia’s strangest illusions
AI Generated Content and the Identification of Features in Time Series Data
Scientific Reports on hold in PubMed while NLM reevaluates journal
Pork Futures: How should we save our swine?
Congo Ebola outbreak kills more than 5,000
Other:
Please Let the Internet Die
Forget Banning Stock Trades. A Democratic Majority Must Tackle All Corruption.
Former Patient Files Class-Action Lawsuit Against Senator Marshall
Searching for Jobs, Gen Z Feels Like It’s Staring Into ‘the Void’
DoorDash’s $17B Acquisition of Instacart Points to a World Without Employees
George Pelecanos Shows Off His D.C. Roots Yet Again
Ask A D.C. Native: I’m an artist. Should I leave D.C. to make it big?
RFK Jr. may hate vaccines, but he loves mystery shots
Nearly half of people who applied for shelter at this D.C. homeless family crisis center were denied
Mark Ein closes in on control of Rock Creek Tennis Center, home of DC Open
Democrats Have a Bogeyman in Musk. They’re Hardly Using Him.
Agentic AI is myth set in motion
After decades of boycotts, Palestinian citizens of Israel turned out to vote. It could shape what comes next
‘Amateur morons’: Flávio Bolsonaro’s short-lived ‘president-elect’ claim met with mockery
Federal judge signals she may halt construction on Trump’s arch
The Supreme Court’s Gutting of the Voting Rights Act is Mobilizing Black Voters. Look at Alabama.
We polled Kansas. Democrats wanted to talk. Republicans, not so much.
Stephen Miller Messed with Texas
No one paid me to disagree with Jonathan Haidt. It was teenagers who taught me that he was wrong.
How Republican lie that Abdul El-Sayed ‘publicly supported’ Muslim Brotherhood started with Laura Loomer
Cabinet Officials on the Campaign Trail? Ethics Experts Say Some Are Breaking the Law.
Let’s Talk About Alaska
Mike Rogers’s Wife Runs a Consultancy That Sells Government Access
A very abbreviated list of a few corruption scandals from the first half of Trump’s second term
Instagram shut down a No Kings account. Now Democrats want answers from Mark Zuckerberg.
U.S. to Send Dozens Back to Afghanistan, Despite Risk of Persecution
Trump Rages as Leaks Show Aides Feeding Him Midterm Hopium
D.C. and Virginia sue to block Trump’s proposed triumphal arch
2028 Won’t Be the 2020 Ideas Primary Again
Here is notice from Yale, and from Paul Krugman, he was one of the true greats. For the pointer I thank several MR readers.
The post William Nordhaus, RIP appeared first on Marginal REVOLUTION.
Researchers, I just uploaded a prominent QJE paper on climate change economics to @RefineDotInk and I loaded my critique of the paper. I asked the AI to offer an impartial verdict. I will make this report public. A new journal could collect these into “Special Issues”.
That is from Matthew E. Kahn.
The post And so it begins… appeared first on Marginal REVOLUTION.
Not much from me tonight, but I do want to call out the political signs reading “Stop Fraud: Vote Republican” I saw today as I left Maine. They seemed especially audacious in light of today’s news from Ernesto Londoño of the New York Times that last summer the Department of Homeland Security paid more than $495 million for a 1,600-bed prison the state of Minnesota declined to purchase a year ago for the asking price of $75 million—or even “a fraction of that price.”
They also seem to contradict the report yesterday from Wendy Siegelman of NewsTRACS that Trump Media & Technology Group received $350,000 for running ads on Trump’s social media site for this summer’s Freedom 250 events. Freedom 250 was the group Trump backed in place of the congressionally-approved nonpartisan America 250 organization designed to celebrate the 250th anniversary of the signing of the Declaration of Independence. Trump owns 41% of Trump Media & Technology Group.
Perhaps Republicans are hoping to attract low-engagement voters who don’t pay much attention to politics. According to G. Elliott Morris of Strength in Numbers, those voters preferred Trump to Democratic candidate Vice President Kamala Harris by 13 points in 2024. Now, though, they are not a good bet for the Republicans, Morris notes. He explains that they have swung away from Trump by 15 points and now prefer Democratic congressional candidates by 2 points.
Those voters might not be highly engaged in politics in general, but they cannot miss the country’s rising prices, especially the cost of gasoline and diesel—and the food delivered by vehicles that use them—resulting from Trump’s war on Iran. Bloomberg reported today that almost half of Americans’ spending now goes toward food and housing, the highest percentage in 15 years.
Rising costs contrast painfully with reports from today that those higher prices are sending oil company profits skyrocketing. Steve Kopack of NBC News reported today that oil giant BP’s profits are at an 18-year-high and Chevron’s earnings are up more than 180% from a year earlier.
On the campaign trail in 2024, Trump asked oil executives to donate a billion dollars to his campaign, calling it a “deal” considering how much money they would make from the regulatory cuts and new permits Trump promised. That investment seems to have paid off. At a rally on October 24, Trump commented to attendees, “I wonder if I should say this,” then went on to say that “our country is making hundreds of billions of dollars because of what’s happened in the Middle East.” He continued: “My people said, ‘Please don’t mention that, sir,’ because people are paying a little higher. But what we’ve done for this country, we’re making money like this country has never made before.” He finished: “I don’t give a damn: I’m going to say it. We’re making a freaking fortune.”
But most Americans are not part of that “we,” and they are angry not only at the soaring profits of oil companies while they pay higher prices, but also at the cuts to Medicaid, Affordable Care Act subsidies, the Supplemental Nutrition Assistance Program, medical and scientific research, and so on at the same time that the administration is pouring lives and taxpayer money into Trump’s war of choice on Iran.
On Wednesday, Ben Finley and Konstantin Toropin of the Associated Press reported that the Pentagon has provided a new estimate of the cost of the war to the Pentagon: $47.1 billion. That number does not include the damage to U.S. military bases in the Middle East, which Anika Arora Seth, John West, Shelby Holliday, and Lara Seligman of the Wall Street Journal reported today could cost as much as $15 billion. Graphics from that story, by Carl Churchill and Katherine Chui, illustrate the extent of the damage.
On Wednesday, Summer Said, Shelby Holliday, Benoit Faucon, and Anat Peled of the Wall Street Journal reported that U.S. officials have warned Gulf Arab countries to prepare for a renewal of U.S. strikes on Iran as early as November 4.
Trump has been on the road for the midterms, convinced that his rallies will help Republican candidates struggling against surging Democratic opponents. But the rallies have drawn far fewer people than Trump likes, and his wandering monologues about how great the economy is, how he aced a cognitive test, how wonderful his ballroom will be, and how much he admires the anatomy of a certain male Republican candidate, along with his deep unpopularity, have made even allies distance themselves from him.
When Trump cancelled rallies scheduled for this weekend in Kansas and Iowa in favor of webcasts, one top Republican official told Kevin Liptak, Kaitlan Collins, Adam Cancryn, and Alayna Treene of CNN: “Thank God. He hasn’t moved the needle anywhere.” Officials hoped he would stay more focused in what they called “telerallies.”
But, the CNN journalists report, Trump fumed at media coverage of the cancellations and ordered the rallies to be reinstated. So he will be in Kansas and Iowa on Sunday, trying to sell voters on his message.
That may not be an easy sell. An image circulating on Bluesky shows a Maine “Stop Fraud: Vote Republican” sign. Next to it, a handmade blue sign with a big white arrow pointing to it reads: “HILARIOUS.”
—
Notes:
https://www.nytimes.com/2026/10/30/us/minnesota-prison-homeland-security.html
https://www.nbcnews.com/business/energy/exxonmobil-chevron-profits-trump-high-oil-prices-rcna606524
https://www.washingtonpost.com/politics/2024/05/09/trump-oil-industry-campaign-money/
https://apnews.com/article/iran-war-costs-trump-congress-81d781a54149709d1ca6754d2aab78bc
https://www.wsj.com/world/middle-east/iran-war-us-bases-damage-88db3224
https://www.cnn.com/2026/10/30/politics/trump-rally-cancellation-midterms
Bluesky:
So if you have the good fortune of living in the delightfully cool and comfortable town of Tustin, odds are fairly high you’ve received this mailer over the past few days. It’s via the AI slop factory of Austin Lumbard, Tustin’s Trump-voting Republican mayor …
And, well, it’s weird, because DEMOCRATS FOR LUMBARD features (wait for it) literally nary a single Democrat for Lumbard. Hell, look at the brochure. Right there. Above this paragraph. Do you see a name listed, besides (cough) Austin Lumbard (a registered Republican and MAGA sympathizer, to be clear)? Do you spot a Democrat for Lumbard alongside DEMOCRATS FOR LUMBARD? Like, a single Democrat?
And do you know any Democrats who’d allign with this sort of thinking …
Truth be told, the whole thing is a hoax, and also horribly unbecoming of a small-town mayor who (beyond anything else) needs to be honest and direct with his constituents. Yesterday, on his Facebook page, Tustin City Council member Lee Fink rightly teed off …
I just, truly, hate this shit. It’s slimy and petty and unbecoming, and yet another reason to back Dr. Letitia Clark, the Democrat and former Tustin mayor, who offered up this fantastic Q&A a month back. Clark has quickly emerged as one of my favorite local political figures. She clearly loves her city, and wants to represent all its inhabitants—politics be damned.
Alas, she’ll need to survive the dishonesty of a foe who should know better.
Such is 2026.
PS: I worked on the brochure. No charge …
I'm just back from an unexpectedly grueling trip, and hope to resume semi-daily blogging. This story caught my eye: basketball has been an inner city game in the U.S., in part because basketball courts can be set up very inexpensively in urban parks, and not so expensively in gyms. So inner city kids are disproportionately represented among the most talented players. But who those kids are has changed over time.
The WSJ has the story:
When Jews Ruled the Basketball Court. Six players on the New York Knicks’ inaugural roster were Jewish. By Michael Freund
"It was Nov. 1, 1946, and Ossie Schectman of the New York Knicks took a bounce pass and scored on a two-handed underhand layup. Schectman, the son of Russian Jewish immigrants, had just scored the first basket in NBA history.
...
"Six members of the Knicks’ original roster, including Schectman, were Jewish. That was no coincidence. For much of the early 20th century, basketball was widely regarded as a Jewish game.
"The reason can be traced to the immigrant neighborhoods of New York and Philadelphia. Millions of Jews arrived from Eastern Europe beginning in the 1880s, often settling in neighborhoods with little open space and scant money to spend on recreation. Baseball required a field and equipment. Basketball needed little more than a ball, a hoop and a schoolyard. "
2. World Bank African urbanization report. Building out African cities in a decent way could end up being the task of our coming era.
3. Summary of The Commanding Heights.
6. One account of what is going on in Poland. I am not endorsing that (or any other) interpretation, but if nothing else it shows you how interpretation of these events can make your head spin. Grok has a simpler answer, again not endorsing.
The post Saturday assorted links appeared first on Marginal REVOLUTION.
Wednesday, November 4, 18:30 Barcelona time, details here. I am honored to have won the Elinor Ostrom Prize from the Institut Ostrom Catalunya. Maybe see you there!
The post My Barcelona talk appeared first on Marginal REVOLUTION.
Welcome to the reading list, a weekly roundup of news and links related to buildings, infrastructure, and industrial technology. This week we look at space fiber optic cable manufacturing, nuclear district heating, Spain’s high-speed rail crash, China’s spaceplane, and more. Roughly 2/3rds of the reading list is paywalled, so for full access become a paid subscriber.
An independent committee’s report on the huge Hong Kong apartment complex fire last year found that it was probably started by a lit cigarette, and accelerated by flammable foam boards and scaffolding nets. [BNN Bloomberg]
Bloomberg Philanthropies wants to spread strategies that have helped get housing built in the cities of Atlanta, Austin, and (checks notes) San Diego to other metros in the US. [The New Localism]
Space-based data centers seem to be taking up most of the oxygen for what sort of things become possible if Starship or other technologies makes launch costs much cheaper, but it’s interesting to consider what else might be unlocked from vastly cheaper access to space. Here’s one: incredibly high-quality fiber optic cable. [IEEE Spectrum]
Last week we looked at a report that noted the US produces a very small amount of aluminum, despite our huge demand for it. Apparently one big reason is that we import a large amount of aluminum from Canada, which can produce it thanks to an abundance of cheap hydropower. “...the enormous power requirements for making aluminum have meant that Canada, where abundant hydropower has kept electricity prices from rising as sharply as in the U.S., has supplied about 70% of U.S. aluminum imports in recent years.” [WSJ]
Defense startup Anduril wants to make a laptop in the US. [Anduril]
The Wall Street Journal on the crisis in US explosives manufacturing. “Following the widespread closures of government-owned plants in the 1990s, the entire production of the powerful explosives HMX and RDX came from a single supplier, Holston Army Ammunition Plant. The 84-year-old plant makes about 3% of what it did during peak production in 1944, according to Hacker’s research, and it has been beset by explosions and pollution violations. There is a one- to two-year wait for products coming out of Holston, said industry experts.” [WSJ]
The ultra-competitive Chinese car industry is apparently struggling in the domestic market, thanks to a drop in demand — domestic sales are down 22% compared to last year. This is part of what’s driving the huge export push from Chinese manufacturers. [WSJ]
US utility company First Energy estimates that every 1 GW of data center demand requires about $250 million worth of transmission upgrades. [Utility Dive]
Per Exxon, roughly 10% of global refining capacity is currently offline, mostly refineries in Russia and the Middle East. [Exxon]
This paper shows retailers increase prices in response to organized retail crime. We match store-level crime data to scanner data from the universe of transactions for cannabis retailers in Washington state. Using quasi-experimental variation from robberies and burglaries, we find a 1.7–1.8 percent price increase at victimized stores and nearby competitors. This rise is not driven by short-to-medium-term demand changes but is consistent with crime-related cost shocks. Effects are larger for independent stores and less concentrated markets. We estimate crime imposes a 1 percent “hidden” unit tax on affected stores, implying $30.7 million in additional social costs, primarily borne by consumers.
That is from a newly published paper, AEJ: Economic Policy, by Carl Hase and Johannes Kasinger.
The post The pass-through of retail crime appeared first on Marginal REVOLUTION.
Education is widely recognized as the primary driver of human capital accumulation. However, policies designed to promote educational attainment often overlook students’ endogenous responses. This paper provides empirical evidence of the causal impact of relaxed academic standards on student effort and achievement. We find that academic leniency results in mechanical GPA increases, but significant reductions in effort among lower ability students based on lower attendance and lower numerical grades. These heterogeneous effects compound and exacerbate gaps in engagement and achievement throughout high school, ultimately worsening deficits in human capital accumulation as measured by ACT scores.
That is from a newly published paper, in AEJ: Economic Policy, by A. Brooks Bowden, Viviana Rodriguez, and Zach Weingarten.
The post The unintended consequences of academic leniency appeared first on Marginal REVOLUTION.
Market Design