Which are the most common everyday phenomena that we don’t properly understand?
Off the top of my head:
• Lightning (how does it happen?)
• Sleep; dreams (why do they exist?)
• Glass (thermodynamics of formation)
• Turbulence (when does it start?)
• Morphogenesis (how does a creature know what should go where?)
• Rain (it seems to start faster than models would predict)
• Ice (dynamics of slipperiness)
• Static electricity (which material will donate electrons?)
• General anaesthetic. (And the mechanism of a lot of drugs, e.g. paracetamol.)
That is from Patrick Collison. It is a further interesting question how many of those questions will be answered by what is sometimes called AGI. Perhaps none of them? In at least some of those cases, what is scarce is experimental data, not reasoning per se.
Saturday assorted links
1. Do chatbots ever follow the interests of advertisers?
2. Approaching the Star Trek universal translator.
3. Jon Haidt response to the new cell phone study.
4. U.S. electricity prices have been flat since June.
5. Friend Alla Keselman now has a Substack.
6. I am enjoying the new Elizabeth Strout novel The Things We Never Say. It is arguably “too American” for me, and also “too New England,” still it is quite good.
The UAP report so far
I will stick with my earlier Free Press predictions:
The fact remains that, if you talk with insiders, they will confirm that the federal government faces some big mysteries. It seems that we have data on what appear to be craft that move very fast, have no visible means of propulsion, and can accelerate in a surprising manner. Radar, infrared, and other forms of data are cited to varying degrees, plus there are eyewitness pilot reports, broadly consistent with what our instruments are telling us.
And this:
Assuming a reasonable chunk of the data are declassified, I think we will simply see more of the same kind of material we’ve seen in the past: more data on entities that appear to move very quickly and in mysterious ways, but with no real explanations. We will see, as I’ve argued before, that the government itself does not know what is going on, and has been afraid to admit that. That may be the real “conspiracy” and why the veil of secrecy has been relatively difficult to pierce.
As of yesterday, there are plenty of additional videos of what seem to be glowing orbs moving fast and in unpredictable ways. Or try this one. Here is another weird one. Or try this. And another one, near military craft. And what is this?
One thing we can conclude is that the debunkers, who have been suggesting this is all camera tricks, parallax issues, or people not understanding how videos work, are proven wrong in general, even though they are right about some particular cases. On that point we can move on, as I have been arguing for some while. Mick West is not your proper guide here.
Nonetheless we still do not know what it all means, and I do not see proof of anything in particular.
I also will stress my earlier point that we are not going to see alien bodies or alien technologies, or anything meaningful connected to Roswell. That is sheer fantasy, or sometimes locos.
340 million hits in the first twelve hours? More people will be believing in aliens in any case, I suspect. Or will it be demons?
It is fashionable in the comments sections of blogs to call this topic a waste of time, but the serious people in the military and national security — most of whom do not cite alien presence — do not see it that way.
And they will be releasing more materials. These materials are being released because some subsection of “the Deep State” wants to know what is going on. As do I.
Public Choice Outreach!
Just a few spots left! Lots of great speakers including Tyler, myself, Bryan Caplan, Robin Hanson, Jon Klick, Shruti Rajagopalan and more.
Please apply and encourage your students to apply.
Self-fulfilling misalignment?
We started by investigating why Claude chose to blackmail. We believe the original source of the behavior was internet text that portrays AI as evil and interested in self-preservation.
And here is Alex Turner on the topic of self-fulfilling misalignment. I raised this possibility some while ago in a Free Press column, and mainly was met with hostility.
The social return to a positive world view, and avoiding negative emotional contagion, never has been higher.
The social media ban in Australia, how is it going?
In December 2025, Australia became the first country to ban youth under 16 years old from holding accounts on major social media platforms, a policy now under consideration in more than a dozen countries and in numerous states. Because social media use is inherently social, the effectiveness of a ban that is easy to circumvent may depend on whether compliance reaches a tipping point: a share of compliant peers high enough to make it optimal for individuals to comply themselves. We surveyed 835 Australian teenagers four months after the ban took effect and find that only about one in four 14–15-year-olds comply. The social environment around use has barely moved: most banned teens believe that their peers are still using banned platforms and cite social reasons for continuing use. Sustaining high compliance requires two ingredients: the share of compliers must be high enough and those who comply must find it preferable to continue complying. The current ban achieves neither. Teenagers report that they require roughly two-thirds of peers to stop using social media to stop themselves, far above the share currently complying. They also perceive compliers as less popular than non-compliers, so the more influential teens disproportionately stay on the platforms. Together, these patterns suggest that compliance is more likely to diminish than to rise. Sustaining higher compliance will likely require pairing the ban with instruments that act on social norms and individual incentives directly.
That is from a new NBER working paper by
A few days ago I was talking with a very smart fifteen year old in Australia (really). He was of the opinion that it was quite ineffective, though he noted he could no longer access LinkedIn. I would note there are more stringent measures, requiring more governmental monitoring and control of the internet, that perhaps could have a greater effect.
Friday assorted links
1. Eigenism.
2. Steven Nadler, Spinoza, Atheist. A good and very readable introduction to the Dutch philosopher.
3. Neal Katyal talk on what really won the SCOTUS tariff case.
4. “What America lacks relative to Europe is not price-sensitive leisure travelers but routes where almost everyone is a price-sensitive leisure traveler.” From Matt Y.
5. The White House is distancing itself from the very tough AI regulation idea.
6. Musical longevity is reaching its peak this year.
7. Are these the emerging megaregions?
The UFO files
Here is the web site, with some of the files released, I have not yet had a chance to look or to read any reliable summaries. More releases are expected, and as of this moment the Kalshi market is at 25 or so.
A simple point about diversification
In recent times a significant percentage of the S&P 500 run-up has been driven by a small number of tech and AI stocks. Plus the effects of AI can be expected to be further reaching yet for some while.
That makes it harder to diversify against risk, as there is a single dominant variable, namely “AI risk” or something similar. There is AI risk both in your portfolio and on your human capital, though possibly those will offset each other to some degree.
Presumably the equity premium should rise as a result? People will want more portfolio safety as a protective offset, and be gunshy about such a heavy equities bet on one major technology.
If you have a longish time horizon, do you feel brave enough to act on that view?
Or perhaps instead there is some simple way to hedge against AI risk?
One “stupid” equilibrium that no one will want to talk about is the following: buy lots of Nvidia, but if that doesn’t pay off make sure you are doing an MBA and planning a career in non-AI-implementation consulting.
Sentences to ponder
Exposure increases interclass (high- and low-parent-income) marriage but has no detectable effect on interracial (White and Black) marriage. A spatial marriage market model predicts that residential segregation—one of many forms of exposure—accounts for more than one third of marital sorting by class but less than 5% by race.
That is from a new NBER working paper by
How Poverty Fell
The share of the global population living in extreme poverty fell dramatically from an estimated 36% in 1990 to 9% in 2015. We describe how this decline happened: the extent to which changes within as opposed to between cohorts contributed to poverty declines, and the key changes in the lives of households as they transitioned out of (and into) poverty. We do so using cross-sectional and panel sources that are representative or near-representative of five countries that collectively accounted for 75% of global poverty decline between 1990 and 2015. The data show that overlapping birth cohorts experienced the decline of poverty together over time, such that poverty decline can be viewed as a primarily within-cohort phenomenon. Within cohorts, the data reveal substantial churn, casting the challenge of escaping poverty as a “slippery slope” more than a long-term trap. The data also illustrate a diversity of pathways out of poverty: sectoral transitions, migration, and changing occupational choices and female labor force participation can all account for some part of poverty reduction, but in all but a handful of cases, a majority of households exiting poverty did so without experiencing these changes.
That is from a new NBER working paper by
Thursday assorted links
Do Americans really hate AI?
We might be heading towards a populist backlash towards AI, but we’re not there yet. Outside the tech bubble, Americans really don’t care about AI yet.
AI is Americans’ 29th most important issue, according to the fantastic survey @davidshor ran that everyone is rightly looking at.
It’s not surprising that Americans will answer sentiment questions about AI negatively, as they’ve been negative towards tech for a while. But it’s a big leap from negative sentiment to meaningful political action.
Americans have been negative on social media for 10 years, and there has been no meaningful political action. And that’s despite all the other hallmarks of backlash people are saying about AI—violent extremists (people forget there was a shooting at YouTube HQ), protests, etc.
My prediction: we will get real populist backlash to AI when the unemployment moves by, say, 2 percentage points and people see it as caused by AI.
That is part of a longer tweet from Andy Hall.
AGI Could Lower Interest Rates
Standard models predict that expectations of artificial general intelligence (AGI) should elevate long-term interest rates. I show that this prediction need not hold. I develop a heterogeneous-agent asset pricing model in which AGI, or more broadly, transformative AI (TAI) capable of automating most human labor, can lower interest rates even as it dramatically accelerates growth. Under baseline calibrations, the risk-free rate falls to near zero despite growth rising from 2% to 11%, and the equity premium expands from 6% to over 20%. The effect on yields is negative and muted for all maturities, even under aggressive assumptions about the speed of AI adoption. These results advise caution when interpreting long-term bond yields as a signal of market expectations of transformative AI.
That is from a new paper by Caleb Maresca of NYU. Via the excellent Kevin Lewis.
William Stanley Jevons as polymath
In the 1860s Jevons built a Logical Abacus, sometimes called a logical piano, a kind of early computer that could perform (some kinds of) logical operations faster than humans could. It is held in the Museum of the History of Science at Oxford University, and you can think of its structure and operation as broadly akin to a player piano in music. It was limited in its powers, and geared mainly toward replicating Boolean logic, but extreme in its ultimate ambitions. Jevons understood the potential. In his written presentation of the project, Jevons cites the work of Charles Babbage, and noted that “material machinery is capable, in theory at least, of rivalling the labours of the most practiced mathematicians in all branches of their science. Mind thus seems able to impress some of its highest attributes upon matter, and to create its own rival in the wheels and levers of an insensible machine.” Jevons understood that science would be able to tackle some of the most difficult projects, and he wanted to be on as many of those frontiers as possible. He understood that his own work was a mere beginning, and he wanted to press forward as much as possible.25See Jevons (1870, the quotation from p.498), and also Maas (2005, chapter six). For a general background on Boolean logic, see Hailperin (1986).
Jevons also studied molecular motion in liquids and developed the concept of “pedesis,” a precursor of what we now call Brownian motion. That said, Jevons thought his pedesis was an electrical phenomenon related to osmosis, and so he turned out to be incorrect in his fundamental hypotheses. Nonetheless, this topic, like the others, showed he was an observant mind and obsessed with developing theories to explain anything and everything. He wasn’t just a pedant, rather he made real contribution to a number of scientific fields above and beyond economics.26On Jevons on pedesis and Brownian motion, see Brush (1968).
Jevons also was a “born collector” in the words of Keynes, and an extreme bibliomaniac. He accumulated thousands of books, and he lined the walls of his house and attic with them, and also stored them in piles in the attic, which became a problem for his wife upon his passing.
That is from my recent generative book The Marginal Revolution: Rise and Decline, and the Pending AI Revolution.