*The Marginal Revolution: Rise and Decline, and the Pending AI Revolution*
I am offering a new piece of work — I do not quite call it a book — online and free. It has four chapters, is about 40,000 words, is fully written by me (not a word from the AIs), and it is attached to an AI with a dual page display, in this case Claude. Think of it as a non-fiction novella of sorts, you can access it here. You can read it on the screen, turn it into a pdf (and upload into your own AI), send it to your Kindle, or discuss it with Claude.
Here is the Table of Contents:
1. What Is Marginalism?
2. William Stanley Jevons, Builder and Destroyer of Marginalism
3. Why Did It Take So Long for the Science of Economics to Develop?
4. Why Marginalism Will Dwindle, and What Will Replace It?
Here are the first few paragraphs of the work:
How is it that ideas, and human capabilities, become lost? And how is that new insights come to pass? If eventually the insight seems obvious, why didn’t we see it before? Or maybe we did see it before, but didn’t really know we were on to something important? Why do new insights arrive suddenly, in a kind of flood? How do new worldviews replace older ones?
And what does all of that have to do with the future of science, the future of research, and the future of economics in particular? Especially when we try to understand how the ongoing artificial intelligence revolution is going to reshape human knowledge, and the all-important question of what economists should do.
Those are the motivating questions behind this work, but I will address them in what is initially an indirect fashion. I will start by considering a case study, namely the most important revolution in economics, the Marginal Revolution (to be defined shortly). The Marginal Revolution made modern economics possible. What was the Marginal Revolution? How did it start? Why did it take so very long to come to fruition? From those investigations we will get a sense of how economic ideas, and sometimes ideas more generally, develop. And that in turn will help us see where the science, art, and practice of economics is headed today.
Recommended! I will be covering it more soon.
Solve for the China tech equilibrium
Authorities in Beijing have barred two executives from a Singapore-based AI firm from leaving China amid a review of the company’s $2 billion acquisition by U.S. social media giant Meta, according to a report by the Financial Times on Wednesday.
Xiao Hong and Ji Yichao — the CEO and chief scientist, respectively, of Manus — were summoned to Beijing this month and questioned over a possible violation of foreign direct investment reporting rules related to the acquisition before being told they could not leave the country, the report said.
Here is more from The Washington Post. In my view, the American lead in AI is somewhat larger than a model comparison alone might suggest.
Wednesday assorted links
What should I ask Katja Hoyer?
Yes, I will be doing a Conversation with her. Here is Wikipedia:
Hoyer was born in Wilhelm-Pieck-Stadt Guben, Bezirk Cottbus, German Democratic Republic (GDR), where her mother was a teacher and her father an officer of the National People’s Army. She received a Master’s degree from the University of Jena and moved to the United Kingdom in about 2010.
Hoyer is a visiting research fellow at King’s College London and has published two books about the history of Germany. She is also a journalist for The Spectator, The Washington Post, Times Literary Supplement, UnHerd, and Die Welt.
Her first book, Blood and Iron, about the German Empire from 1871 to 1918, was well reviewed, even though some reviewers suggested that she had played down the negative aspects of the period and of Otto von Bismarck‘s legacy. Her second book, Beyond the Wall, about the history of the GDR from 1949 to 1990, was well reviewed in the United Kingdom, but less well received in Germany.
She also has a new, forthcoming book on the history of the city of Weimar, namely Weimar: Life on the Edge of Catastrophe. So what should I ask her?
An economic framework for space immigration
Large-scale, voluntary space settlement must be economically rational to be viable. Here, we deploy the Roy model, an economic model used to understand immigration, to illuminate the economic factors important for space settlement and develop qualitative understanding of robust features of space settlement that do not depend on the details of the space economy. We find that getting the cost of living in space down by approximately 2 orders of magnitude is necessary to generate a space population on the order of 1 million people and the typical net utility of immigrating will be on the order of this cost. In addition, if the space economy is driven by productive activities of space settlers and there is some correlation between Earth and space skills and income, space settlers are likely to be drawn from the upper tail of Earth income distribution. An ideal way to incentivize immigration by these high-skill, high-income individuals is to declare the space economy free of redistributive taxes. Alternatively, if space settlement is driven by an insurance policy on civilization involving monetary transfers from Earth to space settlers, the space settlers are likely to be drawn from the lower tail of Earth income distribution, and only minimal marginal income beyond the cost of living in space will be necessary to create positive net utility of immigrating for them. The usefulness of the Roy model is demonstrated by its flexibility in providing qualitative insight in these disparate situations.
That is from a new paper by Dorian S. Abbot and Anup Malani.
Ryan Hauser interviews me in print
Here is the link, here is one excerpt:
What was your path into AI, and what are you working on now?
I first became interested in AI when I saw the chess computer Tinker Belle wheeled into a New Jersey chess tournament in I think 1975. I followed the Kasparov matches closely, and the more general progress of AI in chess. I read chess master David Levy telling me that chess was far too intuitive for computers ever to do well. He was wrong, and then I realized that AI could be intuitive and creative too. That was a long time ago.
In 2013 I published a book on the future of AI called Average is Over. I feel it has predicted our current time very accurately. I also taught Asimov’s I, Robot – a work far ahead of its time – for twenty years.
Right now I am simply working to keep afloat and to stay abreast of recent AI developments. I blog and write columns on the topic frequently, and have regular visits to the major labs. I encourage universities to experiment with AI education.
I mention William Byrd and Paul McCartney as well.
Tuesday assorted links
Johan Fourie interviews me at University of Stellenbosch
Physician Incomes and the Extreme Shortage of High IQ Workers
Physician incomes are extraordinarily high in the United States. A new NBER paper finds that U.S. physicians earn roughly two to four times as much as their counterparts in Canada, the Netherlands, and Sweden.
Why? Is it some feature particular to the US health care sector? Probably not. The same paper finds that physicians in the US have about the same relative income ranking as in Canada, the Netherlands, and Sweden. In other words, lots of high-skill workers in the US earn high incomes and physicians don’t look unusual relative to these other high-skill groups.
That is exactly what one would expect in an economy with an extreme shortage of high-IQ, high-skill workers. The US is a uniquely productive economy for high-skill workers which is why the US demand for foreign workers and the foreign demand to immigrate are so strong, especially at the high end.. By one estimate, “immigrants account for 32 percent of aggregate U.S. innovation.”
Immigration of high-skill workers such as with the H-1B and EB-1,2,3 programs, together with stronger U.S. education, is one way to reduce the shortage of high-skill workers. The alternative is simpler: make the economy less dynamic and less rewarding for talent. Then wages would fall and fewer ambitious people would bother coming. A solution but only if your preferred cure for scarcity is decline.
On the Giving Pledge
From my latest piece from The Free Press:
A lot of America’s most effective giving was done by the early “robber barons,” such as Carnegie, Mellon, and Rockefeller. Andrew Carnegie, for instance, helped to create what is now Carnegie-Mellon University, and Carnegie libraries to this day dot the country and encourage literacy and reading. The Mellon and Rockefeller art collections seeded some of America’s highest quality museums.
None of this was done with any kind of pledge. Those great 19th-century industrialists pursued high-quality philanthropic opportunities when they saw them, unencumbered by today’s massive foundation staffs. If a town wanted to set up a Carnegie library, they had to meet some standard criteria, and they started by sending a letter to Carnegie’s private secretary, James Bertram. The Carnegie Corporation, which in later years led much of the philanthropy, had mainly clerical staff and did not have a full-time salaried president until after Carnegie’s death. It remains to be seen whether today’s philanthropists, including the ones who signed the Giving Pledge, will do as well.
There is much more at the link.
The rise of China as a global innovator in pharma (incentives matter)
This paper examines China’s transition from pharmaceutical “free rider” to global innovator over the last decade. In 2010, China accounted for less than 8% of global clinical trials; by 2020, it had surpassed the US in annual registered clinical trial volume. To study this transformation, we compile a comprehensive, synchronized database spanning the pharmaceutical drug development supply chain, covering scientific publications, clinical trials, drug development milestones for China, the U.S., and Europe, alongside drug sales and government policies over the same period. We provide strong evidence that China’s rise was primarily driven by the National Reimbursement Drug List (NRDL) reform, which dramatically expanded the effective market size for innovative drugs. We document a sharp rise in both the quantity (86% increase) and novelty of drug trials post reform, with growth concentrated in reform-exposed disease categories, first- or best-in-class drugs, and among domestic firms. A decomposition exercise reveals that the NRDL reform accounts for 43% of the growth in oncology trial activity, nearly doubling the combined contribution of upstream knowledge accumulation and talent flows (24%), while other government policies play a minor role. Finally, dynamic gains from induced innovation exceed the reform’s static gains in consumer access to innovative drugs by threefold, underscoring the importance of accounting for the reform’s long-run effects on innovation incentives in addition to near-term improvements in drug affordability.
That is from a new NBER working paper by
What should I ask David Baszucki?
Yes I will be doing a Conversation with him. From Wikipedia:
David Brent Baszucki (/bəˈzuːki/ buh-ZOO-ki; born January 20, 1963) is a Canadian-born American entrepreneur, engineer, and software developer. He is best known as the co-founder and CEO of Roblox Corporation. He co-founded and was the CEO of Knowledge Revolution, which was acquired by MSC Software in December 1998.
Roblox (/ˈroʊ.blɒks/ ⓘ, ROH-bloks) is an online game platform and game creation system developed by Roblox Corporation that allows users to program and play games created by themselves or other users. It was created by David Baszucki and Erik Cassel in 2004, and released to the public in 2006. As of February 2025, the platform has reported an average of 85.3 million daily active users. According to the company, their monthly player base includes half of all American children under the age of 16.
So what should I ask him?
Monday assorted links
1. Arbitrage?
3. Minimum wage hikes boost restaurant food prices.
5. Martin Heidegger clip. Not impressive to me.
6. Canvas unrolls AI teaching agent.
7. “This essay has tried to frame what we need to build around AI.“
Oil versus Ice Cream
When Tyler and I were writing Modern Principles of Economics, we wanted examples that were modern, specific, and grounded in the real world. That has been a bit of a headache, because we have to update them with every new edition. Our biggest competitor uses the ice cream market as its central example and never has to revise. Smart! But for us, the extra work has been worth it.
We chose the oil market as our central example. Oil is always in the news, and it works really well across a wide range of textbook topics: the elasticity of demand and supply; oligopoly and cartels; the shutdown condition; shocks; expectations, speculation and futures markets; and oil prices have macroeconomic implications that connect micro to macro.
Yes, keeping the examples current takes more work. But when a student sees that the price of crude has surged past $100 a barrel because Iran closed the Strait of Hormuz—choking off 20% of the world’s oil supply—they have the framework to understand what is happening. Supply shock, inelastic demand, expectations and speculation, the macroeconomic transmission to GDP—it’s all right there in the headlines. Try doing that with the ice cream market.
See the Invisible Hand. Understand Your World. It is not just our slogan. It’s our method.
When will “the research paper” disappear in economics?
Soon enough you will be able to take any published research paper and tweak it, or improve it, any way you want. Just apply a dose of AI.
Using Refine, you already can judge the quality of all past papers, once you get them in uploadable form. We now can rewrite the entire history of modern economics with the mere investment of tokens. Which papers in the 1993 AER were really the good ones? Which are simply false and do not replicate?
Refine, or some service like it, will only get better, and cheaper.
Do we even need the AER any more to certify which are the best papers? Just ask the AIs, including about influence not just quality.
Why not write a program, or have an AI write it for you, that will take your favorite papers and improve them, and change their evaluations over time, as new results come in? Of course people will do this, at least to the extent they care. These papers will keep on morphing.
Will economics become a branch of software engineering? There are important papers in software engineering, but very often the most important advances are embodied in actual software, AI included.
Will the future advances in economics come from producing evaluative systems and producing systems, rather than papers?
What if you submit to a journal a data set and some code? Who needs “the paper” per se? Just issue some commands to the “data set plus code” and get the paper you want. How about “I am Tyler Cowen, what is it you think I will find interesting in this data set?”
Or publish a method for simulating human behavior, to run AI-simulated experimental economics, a’la Horton and Manning? Publish “the box,” and do not worry so much about the individual paper.
Will highly productive researchers, who publish a lot of papers, become far less valuable? The individual paper no longer seems scarce, or will not be in another year or two.
Give tenure to people who build capabilities and who build “boxes”?
How about an economics Nobel Prize for Anthropic and Open AI?
I thank Alex T. for useful discussions on this point.