Christopher Nolan, Straussian?
When asked what secondary literature Nolan consulted in working on his epic magnum opus masterpiece, he said none. None save Benardete’s The Bow and the Lyre. “It was my muse” —Christopher Nolan,
, April 2026.
Here is the link.
One way to benefit adolescents
Have school start later:
We examine the impact of California’s Senate Bill 328 (SB 328), the first statewide mandate requiring later school start times for middle and high schools, on adolescent sleep, mental health, and academic outcomes. Using difference-in-differences and eventstudy designs across five data sources, we find that SB 328 increased the share of students sleeping at least 8 hours per night by 13%, meeting the CDC-recommended minimum for this age group. Average mental health effects are imprecisely estimated, but boys show significant reductions in sadness, hopelessness, and suicidal ideation, and Hispanic students, who experienced the largest sleep-timing shifts, show parallel reductions in difficulty concentrating; together these patterns are consistent with a dose-response relationship between sleep improvement and mental well-being. Math and English scores in grade 8 improved by approximately 0.08–0.10 standard deviations, with the largest gains among Hispanic and economically disadvantaged students. A within-state analysis using teachers’ commute arrival times as a proxy for pre-policy school start times corroborates these findings, and shows academic gains accumulating over 2023–2025 alongside a suggestive decline in high school dropout rates. The absence of effects on chronic absenteeism rules out an attendance-driven mechanism, pointing instead to the direct cognitive benefits of aligning school schedules with adolescents’ biological rhythms.
That is from a new NBER working paper by
Meta-papers in science (from my email)
From Brennan Plaetzer:
Hi Tyler,
Your post yesterday argued AI will replace papers with meta-papers that synthesize, re-run, and extend prior work. I built one in oncology last month, before reading your post.
I ran my friend Omar Abdel-Wahab’s (MSK) last ten papers through an AI synthesis layer. This came out on top: an integrated, falsifiable hypothesis bridging two of his 2025 papers, one in Cancer Cell on a refractory MEK1 mutation, one in Cell on splicing-derived neoantigens. It comes with seven testable experiments his lab can run today. The move generalizes to any field: surface the questions hidden in plain view, the ones the source papers could answer with their own data but never asked.
https://page56capital.com/writings/cross-paper-synthesis
The “box” you described already exists in biology. It just doesn’t have a name there yet.
Brennan
Note that if you, in the future, do not do this kind of thing yourself, someone else, or their AI agent, will do it for you. Solve for the equilibrium!
MIT fact of the day
Outside of Sloan and the EECS MEng program, still in the midst of admissions, compared with 2024, our departments’ new enrollments for next year are down close to 20%.
That means that, in total, outside of Sloan, we could have about 500 fewer graduate students. Which means we’ll have many fewer students advancing the work of MIT, and undergraduates will have fewer grad students as mentors in their research.
That is from the president of MIT in a recent speech. It is time to put aside denial about the tsunami coming for higher education.
Thursday assorted links
How Much Has Shale Gas Saved U.S. Consumers?
Every US president since Nixon has called for freeing the US from ‘dependence on foreign oil’ (within ten years!). Every president has failed. Fracking, however, has delivered the goods. Fracking has reduced the price of energy, reduced net emissions of greenhouse gases and turned the US into an energy exporter.
In How Much Has Shale Gas Saved U.S. Consumers? Lucas Davis compare LNG prices in the US ($5.3 Mcf), Europe ($14.4 Mcf) and Japan ($16.1 Mcf) to offer some plausible back of the envelope calculations:
Advances in hydraulic fracturing and horizontal drilling caused U.S. natural gas production to increase significantly, and the U.S. went from being a net importer of natural gas to being the world’s largest exporter. This paper calculates how much shale gas has saved U.S. natural gas consumers. Using price differences between the United States, Europe and Japan, we calculate that U.S. natural gas consumers have saved $4.5-$5.3 trillion between 2007 and 2025, equivalent to $237-$276 billion annually. Access to low-price U.S. natural gas has been particularly valuable during major supply shocks such as the war in Ukraine, and the benefits of shale gas have been experienced broadly across sectors and states.
The Impact of AI-Generated Text on the Internet
The proliferation of AI-generated and AI-assisted text on the internet is feared to contribute to a degradation in semantic and stylistic diversity, factual accuracy, and other negative developments. We find that by mid-2025, roughly 35% of newly published websites were classified as AI-generated or AI-assisted, up from zero before ChatGPT’s launch in late 2022. We also find evidence suggesting that increases in AI-generated text on the internet bring about a decrease in semantic diversity and an increase in positive sentiment. We do not, however, find statistically significant evidence supporting the hypothesis that an increased rate of AI-generated text on the internet decreases factual accuracy or stylistic diversity. Notably, our findings diverge from public perception of AI’s impact on the internet.
That is from a new paper by Jonas Dolezal, Sawood Alam Mark Graham, and Maty Bohacek. Via Glenn Mercer.
My excellent Conversation with Bob Spitz
Here is the audio, video, and transcript. Here is the episode summary:
Bob Spitz has written major biographies of the Beatles, Led Zeppelin, Bob Dylan, and now the Rolling Stones — but also, somehow, Ronald Reagan and Julia Child. In rock, his credentials were hard won: he started out hustling gigs for an unknown Bruce Springsteen for six years, moved on to handling Elton John’s American business, and spent long enough in the world to find himself jamming with Paul McCartney and chatting with Bob Dylan on a stoop in the Village. The Reagan and Julia Child books are harder to explain, and perhaps that’s the point—Spitz seems to do his best work when he has no business writing the book at all.
Tyler and Bob discuss how the Stones became so great so quickly, what they added to the blues, how their melodies stack up against the Beatles’, whether Exile on Main Street deserves its canonical status, which songs are most underrated, what Charlie Watts actually got out of playing in a rock band, the rise and fall of Brian Jones, how the Stones outlasted nearly everyone, the influence of Mick’s London School of Economics training, why popular music has lost its cultural influence, what we should still be asking Paul McCartney and Ringo Starr, whether the Beatles’ breakup was good for the world, how senile Reagan really was in his second term and whether he was ever truly a communist, how good a cook Julia Child actually was, his next book on Lennon’s second act, and much more.
Excerpt:
SPITZ: Mick, from a very early age, was an exercise freak.
As we know from my investigation in the book, Mick’s father was the Jack Lalanne of the United Kingdom. He had a television show, an exercise show like Richard Simmons, and he always had a great person to show off the exercises, young Michael. He would say, Mike, get down, show him 50 pushups. Mike, do 100 chins, and Mick would jump to it and do it. That man still has a 27-inch waist at the age of 83.
Keith, on the other hand, is a medical miracle.
And this:
COWEN: Mick once said his favorite economist was Friedrich A. Hayek. Do you know anything more about that?
SPITZ: I do not, actually. I think it’s incredible that Mick had favorite economists. We do know that Mick was a scholarship student to the London School of Economics, and that for two and a half years, he attended and got pretty good grades. He did fairly well. The one thing that amazes me about Mick coming out of that London School of Economics is this. After 1967, when Andrew Loog Oldham stopped managing the Stones, they have never had another manager. They’ve had some money managers, but as far as managers go, Mick Jagger was their manager.
And:
COWEN: How good a cook was Julia Child? That’s another of your biographies. Actually, how good was she?
SPITZ: She was great. She was a wonderful person, but here’s the little secret. Julia was a great cooking teacher, but not a very good cook. There were people who left her house—and John Updike told me this. He was a frequent guest with her. Corby Kummer, who was a wonderful food writer, told me this as well. They’d leave Julia’s house. They’d go to a little park around the corner, and they’d get physically ill. They’d get sick. Julia used too much butter, too much cream. She really had no reins on her when it came to using things like that.
Bob was excellent throughout, and I very much enjoyed his new biography of the Rolling Stones.
Xavier, Nick, and Tristan podcast with me
All three are from Queens College, I thought they did a great job, and mostly fresh material. They describe the episode as such:
Xavier, Tristan, and Nick talk about everything interesting under the sun, including aesthetic convergence, the probability that Tyler lives for many centuries, if Spain was the most culinarily optimal culture to colonize Mexico in the 16th century, if Tyler would have joined the fellowship of the ring, why we don’t yet have a GMU lunch podcast, and much more. We hope you have as much fun listening to it as we had recording it!
Recommended, this is a good argument for sometimes doing podcasts with semi-random people, though choose them wisely.
Wednesday assorted links
Some non-obvious reasons why AI will create some transitional problems in employment
I do not find the mass unemployment hypothesis persuasive, and I have covered this extensively in the past. But here are three other problems which may end up being noticeable in the short run, though likely absent longer term:
1. Many of the new jobs to be created may come in highly regulated sectors, and that will slow their creation. Energy and health care — especially biomedical trials — are two examples I have in mind here. Let’s say we opt for more nuclear power to ease constraints of compute — how long will it take for most of those jobs to come on line?
2. At least initially, job search and matching might be less efficient. We have lots of practice judging which workers are best for which jobs in a pre-AI world. But say most jobs involve working with AI in some manner? How well can actual HR departments judge who is good at that? Are the HR departments themselves even decent at that?
So expect slower matches, though at some point AI itself might give us better and faster labor market matches.
3. Government fiscal policy might be less effective at putting people to work in an efficient manner, given that the government is likely, at least for some while, to be a poor judge of who is good at working with AI. That may slow hiring, or lead to quicker dismissals and quits, or simply result is less output from the fiscal policy investments, thus making them less effective.
These features of the problem all could use a bit more consideration, and likely there are others I have not thought of.
Data centers are good
Data centers are the physical infrastructure behind cloud computing, artificial intelligence, and enterprise software. The rapid diffusion of artificial intelligence (AI) is intensifying demand for compute, accelerating investment in data centers, and raising concerns about the local economic and environmental footprint of these facilities. Their expansion creates a local policy tradeoff. A data center can bring capital investment, construction activity, and specialized employment, but it can also increase demand for electricity, land, and grid capacity. This paper studies these effects at the U.S. county level. We assemble a facility-level panel of global data centers with precise coordinates, scale metrics, and annualized revenue. We map facilities to U.S. counties and combine them with County Business Patterns, county-level IRS income, county-level house prices, and electricity prices. To address endogenous siting, we instrument for data center growth using two shift-share instruments, which leverage pre-existing proximity to InterTubes long-haul fiber nodes and the 1980 county share of U.S. urban college population as shares, and both Chinese and rest-of-the-world data center revenue growth as shifts. The IV estimates show positive effects on total employment, data-processing employment, construction employment, establishments, house prices, and electricity prices at different horizons after data center growth. We also find positive effects on tax returns, adjusted gross income, and wages, while annual payroll responds less robustly. The results suggest that data centers create measurable local activity, increase house prices, and affect local electricity markets through higher prices.
That is from a new NBER working paper by
Hollis Robbins on AI and higher education
There’s a growing idea I’ve seen in some circles that college could be replaced by conversations between an A.I. tutor and a student. When I think about your model, I wonder why college even needs to exist. If I can just seek out a tutor, somebody that I like, and they just charge me a little bit, and we go through these edge-knowledge cases together, what’s the degree for? Couldn’t you, as Hollis Robbins—not only a specialist in African American sonnet traditions but also an idiosyncratic thinker on the subject of A.I. and the future of the academy—just set up your own shop?
I was in Austin, Texas, a couple of times in March with a bunch of twenty-five-year-old billionaires. This is what they’re looking at. Instead of having the credential from the institution, why not have the credential from the professor? If you have a Hollis Robbins education, what would that signal? What would that credential mean as opposed to a degree from a university? There was some conversation about what that would look like, and one guy at the end of the dinner said, “Instead of OnlyFans, it’s like OnlyProfessors.”
Here is much more from The New Yorker.
Tuesday assorted links
1. Is it too expensive to sell a house? (NYT)
2. Sumner on Halperin on macro.
3. Why progress under Milei has stalled (WSJ).
4. Why is Latin America so violent?
5. Diet Coke parties are the rage in India.
6. Optimizing AI models for creativity. “They simply have not done it yet” is one of the most useful phrases to keep in your mind these days.
Ideas Behind Their Time: Part Two
In 2010 I wrote about Ideas Behind Their Time:
We are all familiar with ideas said to be ahead of their time, Babbage’s analytical engine and da Vinci’s helicopter are classic examples. We are also familiar with ideas “of their time,” ideas that were “in the air” and thus were often simultaneously discovered such as the telephone, calculus, evolution, and color photography. What is less commented on is the third possibility, ideas that could have been discovered much earlier but which were not, ideas behind their time.
I gave experimental economics, random clinical trials and view morphing (“bullet time”) as examples. Jason Crawford has a list discussing the wheel, the steam engine and bicycles among other possibilities. In some cases, further exploration indicates that an idea required precursors and so was not as behind its times as first suspected, in rare cases, however, good ideas really could have been invented much earlier.
Using Claude, Brian Potter has significantly expanded the list by looking systematically across a wide range of inventions and asking could they have been invented earlier? Most could not. Put the other way, most useful technologies tend to be invented quite quickly once they are possible–this is reassuring. The airplane, for example, could not have been invented before a high power-to-weight engine, which happened circa 1880 making the late 1880s the earliest feasible date for powered flight. Thus, the Wright Brothers (1903) were only just behind the earliest feasible date–and that is true for many inventions.
The ideas very far behind their time include the stethoscope, general anesthesia and reinforced concrete and quite far behind are the Jacquard loom and canning. Is there a pattern here?
Addendum: Brian’s Github with the full prompt and output for each invention is here.