On Thursday, February 29, I’ll be giving my talk “Towards a New Philosophy of Progress” to the New England Legal Foundation, for their Economic Liberty Speaker Series. The talk will be held over breakfast at NELF’s offices in Boston, and will also be livestreamed over Zoom. See details and register here. This is a talk I have given before in other venues. The description: Enlightenment thinkers were tremendously optimistic about the potential for human progress: not only in science and technology, but also in morality and society. This belief lasted through the 19th century—but in the 20th century, after the World Wars, it gave way to fear, skepticism, and distrust. Now, in the 21st century, we need a new way forward: a new philosophy of progress. What events and ideas challenged the concept of progress? How can we restore it on a sound foundation? And how can we establish a bold, ambitious vision for the future?

In December, I went to the Foresight Institute’s Vision Weekend 2023 in San Francisco. I had a lot of fun talking to a bunch of weird and ambitious geeks about the glorious abundant technological future. Here are few things I learned about (with the caveat that this is mostly based on informal conversations with only basic fact-checking, not deep research): Cellular reprogramming Aging doesn’t only happen to your body: it happens at the level of individual cells. Over time, cells accumulate waste products and undergo epigenetic changes that are markers of aging. But wait—when a baby is born, it has young cells, even though it grew out of cells that were originally from its older parents. That is, the egg and sperm cells might be 20, 30, or 40 years old, but somehow when they turn into a baby, they get reset to biological age zero. This process is called “reprogramming,” and it happens soon after fertilization. It turns out that cell reprogramming can be induced by certain proteins, known as the Yamanaka factors, after their discoverer (who won a Nobel for this in 2012). Could we use those proteins to reprogram our own cells, making them youthful again? Maybe. There is a catch: the Yamanaka factors not only clear waste out of cells, they also reset them to become stem cells. You do not want to turn every cell in your body into a stem cell. You don’t even want to turn a small number of them into stem cells: it can give you cancer (which kind of defeats the purpose of a longevity technology). But there is good news: when you expose cells to the Yamanaka factors, the waste cleanup happens first, and the stem cell transformation happens later. If we can carefully time the exposure, maybe we can get the target effect without the damaging side effects. This is tricky: different tissues respond on different timelines, so you can’t apply the treatment uniformly over the body. There are a lot of details to be worked out here. But it’s an intriguing line of research for longevity, and it’s one of the avenues being explored at Retro Bio, among other places. Here’s a Derek Lowe article with more info and references. The BFG orbital launch system If we’re ever going to have a space economy, it has to be a lot cheaper to launch things into space. Space Shuttle launches cost over $65,000/kg, and even the Falcon Heavy costs $1500/kg. Compare to shipping costs on Earth, which are only a few dollars per kilogram. A big part of the high launch cost in traditional systems is the rocket, which is discarded with each launch. SpaceX is bringing costs down by making reusable rockets that land gently rather than crashing into the ocean, and by making very big rockets for economies of scale (Elon Musk has speculated that Starship could bring costs as low as $10/kg, although this is a ways off, since right now fuel costs alone are close to that amount). But what if we didn’t need a rocket at all? Rockets are pretty much our only option for propulsion in space, but what if we could give most of the impulse to the payload on Earth? J. Storrs Hall has proposed the “space pier,” a runway 300 km long mounted atop towers 100 km tall. The payload takes an elevator 100 km up to the top of the tower, thus exiting the atmosphere and much of Earth’s gravity well. Then a linear induction motor accelerates it into orbit along the 300 km track. You could do this with a mere 10 Gs of acceleration, which is survivable by human passengers. Think of it like a Big Friendly Giant (BFG) picking up your payload and then throwing it into orbit. Hall estimates that this could bring launch costs down to $10/kg, if the pier could be built for a mere $10 billion. The only tiny little catch with the space pier is that there is no technology in existence that could build it, and no construction material that a 100 km tower could be made of. Hall suggests that with “mature nanotechnology” we could build the towers out of diamond. OK. So, probably not going to happen this decade. What can we do now, with today’s technology? Let’s drop the idea of using this for human passengers and just consider relatively durable freight. Now we can use much higher G-forces, which means we don’t need anything close to 300 km of distance to accelerate over. And, does it really have to be 100 km tall? Yes, it’s nice to start with an altitude advantage, and with no atmosphere, but both of those problems can be overcome with sufficient initial velocity. At this point we’re basically just talking about an enormous cannon (a very different kind of BFG). This is what Longshot Space is doing. Build a big long tube in the desert. Put the payload in it, seal the end with a thin membrane, and pump the air out to create a vacuum. Then rapidly release some compressed gasses behind the payload, which bursts through the membrane and exits the tube at Mach 25. One challenge with this is that a gas can only expand as fast as the speed of sound in that gas. In air this is, of course, a lot less than Mach 25. One thing that helps is to use a lighter gas, in which the speed of sound is higher, such as helium or (for the very brave) hydrogen. Another part of the solution is to give the payload a long, wedge-shaped tail. The expanding gasses push sideways on this tail, which through the magic of simple machines translates into a much faster push forwards. There’s a brief discussion and illustration of the pneumatics in this video. Now, if you are trying to envision “big long tube in the desert”, you might be wondering: is the tube angled upwards or something? No. It is basically lying flat on the ground. It is expensive to build a long straight thing that points up: you have to dig a deep hole and/or build a tall tower. What about putting it on the side of a mountain, which naturally points up? Building things on mountains is also hard; in addition, mountains are special and nobody wants to give you one. It’s much easier to haul lots of materials into the middle of the desert; also there is lots of room out there and the real estate is cheap. Next you might be wondering: if the tube is horizontal, isn’t it pointed in the wrong direction to get to space? I thought space was up? Well, yes. There are a few things going on here. One is that if you travel far enough in a straight line, the Earth will curve away from you and you will eventually find yourself in space. Another is that if you shape the projectile such that its center of pressure is in the right place relative to its center of mass, then it will naturally angle upward when it hits the atmosphere. Lastly, if you are trying to get into orbit, most of the velocity you need is actually horizontal anyway. In fact, if and when you reach a circular orbit, you will find that all of your velocity is horizontal. This means that there is no way to get into orbit purely ballistically, with a single impulse imparted from Earth. Any satellite, for instance, launched via this system will need its own rocket propulsion in order to circularize the orbit once it reaches altitude (even leaving aside continual orbital adjustments during its service lifetime). But we’re now talking about a relatively small rocket with a small amount of fuel, not the big multi-stage things that you need to blast off from the surface. And presumably someday we will be delivering food, fuel, tools, etc. to space in packages that just need to be caught by whoever is receiving them. Longshot estimates that this system, like Starship or the space pier, could get launch costs down to about $10/kg. This might be cheap enough that launch prices could be zero, subsidized by contracts to buy fuel or maintenance, in a space-age version of “give away the razor and sell the blades.” Not only would this business model help grow the space economy, it would also prove wrong all the economists who have been telling us for decades that “there’s no such thing as a free launch.” Mars could be terraformed in our lifetimes Terraforming a planet sounds like a geological process, and so I had sort of thought that it would require geological timescales, or if it could really be accelerated, at least a matter of centuries or so. You drop off some algae or something on a rocky planet, and then your distant descendants return one day to find a verdant paradise. So I was surprised to learn that major changes on Mars could, in principle, be made on a schedule much shorter than a single human lifespan. Let’s back up. Mars is a real fixer-upper of a planet. Its temperature varies widely, averaging about −60º C; its atmosphere is thin and mostly carbon dioxide. This severely depresses its real estate values. Suppose we wanted to start by significantly warming the planet. How do you do that? Let’s assume Mars’s orbit cannot be changed—I mean, we’re going to get in enough trouble with the Sierra Club as it is—so the total flux of solar energy reaching the planet is constant. What we can do is to trap a bit more of that energy on the planet, and prevent it from radiating out into space. In other words, we need to enhance Mars’s greenhouse effect. And the way to do that is to give it a greenhouse gas. Wait, we just said that Mars’s atmosphere is mostly CO2, which is a notorious greenhouse gas, so why isn’t Mars warm already? It’s just not enough: the atmosphere is very thin (less than 1% of the pressure of Earth’s atmosphere), and what CO2 there is only provides about 5º of warming. We’re going to need to add more GHG. What could it be? Well, for starters, given the volumes required, it should be composed of elements that already exist on Mars. With the ingredients we have, what can we make? Could we get more CO2 in the atmosphere? There is more CO2 on/under the surface, in frozen form, but even that is not enough for the task. We need something else. What about CFCs? As a greenhouse gas, they are about four orders of magnitude more efficient than CO2, so we’d need a lot less of them. However, they require fluorine, which is very rare in the Martian soil, and we’d still need about 100 gigatons of it. This is not encouraging. One thing Mars does have a good amount of is metal, such as iron, aluminum, and magnesium. Now metals, you might be thinking, are not generally known as greenhouse gases. But small particles of conductive metal, with the right size and shape, can act as one. A recent paper found through simulation that “nanorods” about 9 microns long, half the wavelength of the infrared thermal radiation given off by a planet, would scatter that radiation back to the surface (Ansari, Kite, Ramirez, Steele, and Mohseni, “Warming Mars with artificial aerosol appears to be feasible”—no preprint online, but this poster seems to represent earlier work). Suppose we aim to warm the planet by about 30º C, enough to melt surface water in the polar regions during the summer, and bring Mars much closer to Earth temperatures. AKRSM’s simulation says that we would need to put about 400 mg/m3 of nanorods into the Martian sky, an efficiency (in warming per unit mass) more than 2000x greater than previously proposed methods. The particles would settle out of the atmosphere slowly, at less than 1/100 the rate of natural Mars dust, so only about 30 liters/sec of them would need to be released continuously. If we used iron, this would require mining a million cubic meters of iron per year—quite a lot, but less than 1% of what we do on Earth. And the particles, like other Martian dust, would be lifted high in the atmosphere by updrafts, so they could be conveniently released from close to the surface. Wouldn’t metal nanoparticles be potentially hazardous to breathe? Yes, but this is already a problem from Mars’s naturally dusty atmosphere, and the nanorods wouldn’t make it significantly worse. (However, this will have to be solved somehow if we’re going to make Mars habitable.) Kite told me that if we started now, given the capabilities of Starship, we could achieve the warming in a mere twenty years. Most of that time is just getting equipment to Mars, mining the iron, manufacturing the nanorods, and then waiting about a year for Martian winds to mix them throughout the atmosphere. Since Mars has no oceans to provide thermal inertia, the actual warming after that point only takes about a month. Kite is interested in talking to people about the design of a the nanorod factory. He wants to get a size/weight/power estimate and an outline design for the factory, to make an initial estimate of how many Starship landings would be needed. Contact him at [email protected]. I have not yet gotten Kite and Longshot together to figure out if we can shoot the equipment directly to Mars using one really enormous space cannon. Thanks to Reason, Mike Grace, and Edwin Kite for conversations and for commenting on a draft of this essay. Any errors or omissions above are entirely my own.

This is the written version of a talk presented to the Santa Fe Institute at a working group on “Accelerating Science.” We’re here to discuss “accelerating science.” I like to start on topics like this by taking the historical view: When (if ever) has science accelerated in the past? Is it still accelerating now? And what can we learn from that? I’ll submit that science, and more generally human knowledge, has been accelerating, for basically all of human history. I can’t prove this yet (and I’m only about 90% sure of it myself), but let me appeal to your intuition: Behaviorally modern humans are over 50,000 years old Writing is only about 5,000 years old, so for more than 90% of the human timeline, we could only accumulate as much knowledge as could fit in an oral tradition In the ancient and medieval world, we had only a handful of sciences: astronomy, geometry, some number theory, some optics, some anatomy In the centuries after the Scientific Revolution (roughly 1500s–1700s), we got the heliocentric theory, the laws of motion, the theory of gravitation, the beginnings of chemistry, the discovery of the cell, better theories of optics In the 1800s, things really got going, and we got electromagnetism, the atomic theory, the theory of evolution, the germ theory In the 1900s things continued strong, with nuclear physics, quantum physics, relativity, molecular biology, and genetics I’m leaving aside the question of whether science has slowed down since ~1950 or so, which I don’t have a strong opinion on. Even if it has, that’s mostly a minor, recent blip in the overall pattern of acceleration across the broad sweep of history. (Or, you know, the beginning of a historically unprecedented reversal and decline. One or the other.) Part of the reason I’m pretty convinced of this accelerating pattern is that it’s not just science that is accelerating: pretty much all measures of human advancement show the same trend, including world GDP and world population. What drives acceleration in science? Many factors, including: Funding. Once, scientists had to seek patronage, or be independently wealthy. Now there is grant money available, and the total amount of funding has increased significantly in the last several decades: American Association for the Advancement of Science People. More scientists (all else being equal) means science moves faster, and the number of scientists has grown dramatically, both because of overall population growth and because of a greater portion of the workforce going into research. In Science Since Babylon, Derek J. de Solla Price suggested that “Some 80 to 90 percent of all scientists that have ever been, are alive now,” and this is probably still true: Eric Gastfriend Instruments. Better tools means we can do more and better science. Galileo had a simple telescope; now we have JWST and LIGO. Computation. More computing power means more and better ways to process data. Communication. The faster and better that ideas can spread, the more efficient and effective scientific communication can be. The scientific journal was invented only after the printing press; the Internet enabled preprint servers such as arXiv. Method. Better methods make for better science, from Baconian empiricism to Koch’s postulates to the RCT (and really, all of statistics). Institutions. Laboratories, universities, journals, funding agencies, etc. all make up an ecosystem that enables modern science. Social status. The more science carries respect and prestige, the more people and money flow into it. Now, if we want to ask whether science will continue to accelerate, we could think about which of these driving factors will continue to grow. I would suggest that: Funding for science will continue to grow as long as the world economy does Instruments, computation, and communication will continue to improve along with technology in general I see no reason why method should not continue to improve, as part of science itself The social status of science seems fairly strong: it is a respected and prestigious institution that receives some of society’s top honors In the long run, we may run out of people to continue to grow the base of researchers, if world population levels off as it is projected to do, and that is a potential concern, but not my focus today. The biggest red flag is with our institutions of science. Institutions affect all the other factors, especially the management of money and talent. And today, many in the metascience community have concerns about our institutions. Common criticisms include: Speed. It can easily take 12–18 months to get a grant (if you’re lucky) Overhead. Researchers typically spend 30–50% of their time on grants Patience. Researchers feel they need to show results regularly and can’t pursue a path that might take many years to get to an outcome Risk tolerance. Grant funding favors conservative, incremental proposals rather than bold, “high-risk, high-reward” programs (despite efforts to the contrary) Consensus. A field can converge on a hypothesis and prune alternate branches of study too quickly Researcher age. The trend over time is for grant money to go to older, more established researchers Freedom. Scientists lack the freedom to direct their research fully autonomously; grant funding has too many strings attached Now, as a former tech founder, I can’t help but notice that most of these problems seem much alleviated in the world of for-profit VC funding. Raising VC money is relatively quick (typically a round comes together in a few months rather than a year or more). As a founder/CEO, I spent about 10–15% of my time fundraising, not 30–50%. VCs make bold bets, actively seek contrarian positions, and back young upstarts. They mostly give founders autonomy, perhaps taking a board seat for governance, and only firing the CEO for very bad performance. (The only concern listed above that startup founders might also complain about is patience: if your money runs out, you’d better have progress to show for it, or you’re going to have a bad time raising the next round.) I don’t think the VC world does better on these points because VCs are smarter, wiser, or better people than science funders—they’re not. Rather, VCs: Compete for deals (and really don’t want to miss good deals) Succeed or fail in the long run based on the performance of their portfolio See those outcomes within a matter of ~5–10 years In short, VCs are subject to evolutionary pressure. They can’t get stuck in obviously bad equilibria because if they do they will get out-competed and lose market power. The proof of this is that VC has evolved over the decades—mostly in the direction of better treatment for founders. For instance, there has been a long-term trend towards higher valuations at earlier stages, which ultimately means lower dilution and a shift in power from VCs to founders: it used to be common for founders to give up half or more of their company in the first round of funding; last I checked that was more like 20% or less. VCs didn’t always fund young techies right out of college; there was a time when they tended to favor more experienced CEOs, perhaps with an MBA. They didn’t always support founder-led companies; once it was common for founders to get booted after the first few years and replaced with a professional CEO (when A16Z launched in 2009 they made a big deal out of how they were not going to do that). So I think if we want to see our scientific institutions improve, we need to think about how they can evolve. How evolvable are our scientific institutions? Not very. Most scientific organizations today are departments of university or government. Much as I respect universities and government, I think anyone would have to admit that they are some of our more slow-moving institutions. (Universities in particular are extremely resilient and resistant to change: Oxford and Cambridge, for instance, date from the Middle Ages and have survived the rise and fall of empires to reach the present day fairly intact.) The challenges to the evolvability of scientific funding institutions are the inverse of what makes VC evolvable: They tend to lack competition, especially centralized federal agencies such as NIH and NSF They lack any real feedback loop in which a funder’s resources are determined somehow by past judgment and the success of their portfolio (Michael Nielsen has repeatedly pointed out that failures of funding from “Einstein did his best work as a patent clerk” to “Katalin Karikó was denied grants and tenure before she won the Nobel prize” don’t seem to even spark processes of reflection within the relevant institutions) They face long cycle times to learn the true impact of their work, which might not be apparent for 20–30 years How might we improve evolvability of science funding? We should think about how we can improve these factors. I don’t have great ideas, but I’ll throw some half-baked ones out there to start the conversation: How might we increase competition in science funding? We could increase the role of philanthropy. In the US, we could shift federal funding to the state level, creating fifty funders instead of one. (State agricultural experiment stations are a successful example of this, and competition among these stations was key to hybrid corn research, one of the biggest successes of 20th-century agricultural science.) At the international level, we could support more open immigration for scientists. How might we create better feedback loops? This is tough because we need some way to measure outcomes. One way to do that would be to shift funding away from prospective grants and more towards a wide variety of retrospective prizes, at all levels. If this “economy” were sufficiently large and robust, these outcomes could be financialized in order to create a dynamic, competitive funding ecosystem, with the right level of risk-taking and patience, the right balance of seasoned veterans vs. young mavericks, etc. (Certificates of impact, such as hypercerts, could be part of this solution.) How might we solve long feedback cycles? I don’t know. If we can’t shorten the cycles, maybe we need to lengthen the careers of funders, so they can at least learn from a few cycles—a potential benefit of longevity technology. Or, maybe we need a science funder that can learn extremely fast, can consume large amounts of historical information on research programs and their eventual outcomes, never forgets its experience, and never retires or dies—of course, I’m thinking of AI. There’s been a lot of talk of AI to support, augment, or replace scientific researchers themselves, but maybe the biggest opportunity for AI in science is on the funding and management side. I doubt that grant-making institutions will shift themselves very far in this direction: they would have to voluntarily subject themselves to competition, enforce accountability, and admit mistakes, which is rare. (Just look at the institutions now taking credit for Karikó’s Nobel win when they did so little to support her.) If it’s hard for institutions to evolve, it’s even harder for them to meta-evolve. But maybe the funders behind the funders, those who supply the budgets to the grant-makers, could begin to split up their funds among multiple institutions, to require performance metrics, or simply to shift to the retrospective model indicated above. That could supply the needed evolutionary pressure.

A ~monthly feature. Recent blog posts and news stories are generally omitted; you can find them in my links digests. All emphasis in bold in the quotes below was added by me. Books Finished Lynn White, Medieval Technology and Social Change (1962). Last time I talked about the stirrup thing. The second part of the book is about the introduction of the heavy plow in agriculture, and how it enabled the shift to a three-field crop rotation. Among other things, this provided more protein in the European diet, which made for a healthier population. The third part is a survey of medieval power mechanisms, including water mills, crank shafts, and clock escapements. Very interesting overall, perhaps a bit dry and technical for casual readers though. Note also that since it is from the ’60s it is not up to date with the latest research. Also finished Ian Tregillis’s The Alchemy Wars. I can now definitely recommend this sci-fi/fantasy trilogy, even if the cast of characters and the way the conflict unfolded isn’t exactly how I would have written it myself. Browsed Derek J. de Solla Price, Science since Babylon (1961), while preparing for a talk. Some very interesting charts such as this: Science since Babylon, p. 97 New on my reading list: Venkatesh Narayanamurti and Toluwalogo Odumosu, Cycles of Invention and Discovery: Rethinking the Endless Frontier (2016), and Venkatesh Narayanamurti and Jeffrey Tsao, The Genesis of Technoscientific Revolutions: Rethinking the Nature and Nurture of Research (2021). These have actually been on my list for a while, but got bumped back up after meeting Venky and Jeff at a recent workshop on metascience. (The latter book is required reading at Speculative Technologies.) Also mentioned at the workshop: B. Zorina Khan, Inventing Ideas: Patents, Prizes, and the Knowledge Economy (2020); and A Michael Noll and Michael Geselowitz, Bell Labs Memoirs: Voices of Innovation (2011). Also: Pedro Domingos, The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World (2015) Robert Martello, Midnight Ride, Industrial Dawn: Paul Revere and the Growth of American Enterprise (2010) Jessie Singer, There Are No Accidents: The Deadly Rise of Injury and Disaster—Who Profits and Who Pays the Price (2022) Ursula Le Guin, The Dispossessed (1974) (sci-fi) Articles Ray Kurzweil, “The Law of Accelerating Returns” (2001). Kurzweil strikes me as a grand theorist but not a careful scholar—a risky combination. For instance, he writes: “Homo sapiens evolved in a few hundred thousand years. Early stages of technology—the wheel, fire, stone tools—took tens of thousands of years to evolve and be widely deployed.” Stone tools, fire, and the wheel are often depicted in cartoons featuring cavemen. But stone tools evolved over millions of years; the controlled use of fire is something like several hundred thousand years old; and both predate Homo sapiens. The wheel came much later, well after agriculture and settled society. Details like this are a warning to tread carefully. That said, I was interested to read this essay because I am starting to see the truth and significance of its core idea: that human progress accelerates over time, following a super-exponential curve. This phenomenon has been documented more broadly in the economics literature, such as by Jones and Romer (2010), who refer to “accelerating growth” as one of the key stylized facts that growth models should attempt to explain. I have described acceleration as resulting from the compounding of multiple feedback loops: increases in wealth, population, science, markets, institutions, and technology allow us to invent more, improve institutions, expand markets, advance science, grow population, accumulate wealth, etc. Kurzweil sees the phenomenon as not merely technological, but biological—a feature of evolution as such (and he sees technological evolution as simply a continuation of biological evolution by more efficient means). In his telling, as evolution progresses, it sometimes evolves better mechanisms for evolving. This is a very intruiging idea, but he doesn’t argue it with any rigor or present much evidence for it, and I don’t know enough about biology or evolution to evaluate it. He mentions “cells” as the “first step” in evolution, and then refers to “the subsequent emergence of DNA” (but wasn’t DNA present from the origins of life?) He indicates that evolution sped up during the Cambrian Explosion, and credits this to “setting the ‘designs’ of animal body plans”, but doesn’t elaborate on the causal connection except to say that this “allowed rapid evolutionary development of other body organs, such as the brain.” Presumably sexual reproduction should be a major event in this story, since it allows for more variation through genetic recombination, but he doesn’t mention it. So, it’s very unclear to me what to make of this story (although if it’s right, it would extend the “accelerating progress” pattern backwards by more than three billion years). Ray Kurzweil Grand theories aside, I was very interested in his analysis of computing power. He plotted the computing speed per dollar of dozens of devices, all the way from late 19th-century mechanical calculators through early 21st-century microprocessors, and claims to have found a increasing cost-performance curve running through five generations of computing technology: purely mechanical, electromechanical, vacuum tube, transistor, and integrated circuit. Moore’s Law is only the fifth and most recent segment of this much longer trend, one exponential portion of an overall super-exponential curve: Kurzweil, The Law of Accelerating Returns I’d like to check the data and sources on this one, but it’s a very intriguing pattern. The full essay is very long and covers many not-super-well-connected topics, which I don’t have time to comment on; the core idea is in this 2004 Edge question, but doesn’t contain all the most interesting details (such as the computing trends just mentioned). The same accelerating curve, and the same basic explanation based on feedback loops, seems to be the gist of David Roodman, “Modeling the Human Trajectory” (2020), which I have only skimmed but plan to return to. Others: Deirdre N. McCloskey reviews Acemoglu and Johnson’s Power and Progress (2023). If you know anything about the book, and anything about McCloskey, you won’t be surprised that she is critical: The invisible hand of human creativity and innovation, in the authors’ analysis, requires the wise guidance of the state. … This is a perspective many voters increasingly agree with—and politicians from Elizabeth Warren to Marco Rubio. We are children, bad children (viewed from the right) or sad children (viewed from the left). Bad or sad, as children we need to be taken in hand. Messrs. Acemoglu and Johnson warmly admire the U.S. Progressive Movement of the late 19th century as a model for their statism: experts taking child‐citizens in hand. Robert Tracinski, “We Are All Philosophers Now” and “The Dilemma of Choice” (2023). Modernity has replaced a narrow, limited set of social roles and life choices with a smorgasbord of options. This is liberating, but the price of the freedom of choice is the responsibility of choice, which is now everyone’s to bear. Not everyone is happy about this. Rob’s pithy summary: “If Socrates said that the unexamined life is not worth living, well, now it’s not really an option.” Virginia Postrel, “What ails American culture?” (2023). On similar themes: Human beings need to feel purpose and meaning in their lives. But I am not entirely sure that the current discontent is a product of material abundance, that people did not feel similar discontent in the past, or that the “economic problem” loomed so large in the past that it dwarfed all other problems. Ben Landau-Taylor, “The Vocabulary Of Power” (2023). “Power” can mean many things; here are four more precise terms. Not only will this help clarify your concepts, it will also fulfill your daily quota of thinking about the Roman Empire. Tanner Greer, “Where Have All the Great Works Gone?” (2021): Spengler … repeatedly describes Tolstoy (d. 1910), Ibsen (d. 1906), Nietzsche (d. 1900), Hertz (d. 1894), Dostoevsky (d. 1881), Marx (d. 1883), and Maxwell (1879) as figures of defining “world-historical” importance… Spengler began writing Decline of the West in 1914. Tolstoy was only four years dead when Spengler started his book; Marx was only 30 years deceased. … Is there anyone who died in the last decade you could make that sort of claim for? How about for the last two decades? The last three? Gideon Lewis-Kraus, “They Studied Dishonesty. Was Their Work a Lie?” (2023). A case study of scientific fraud. Stephen Wolfram, “Are All Fish the Same Shape If You Stretch Them? The Victorian Tale of On Growth and Form” (2017) I just thought this idea was kind of hilarious: D’Arcy Thompson, On Growth and Form