Category: Uncategorized
The correct model of AI CEO behavior
I agree with Alex that the standard model of regulatory capture does not apply here, but I think he neglects the best model we have. From my recent Free Press piece:
Recently I have been reading my review copy of Kevin Roose’s excellent forthcoming book The AGI Chronicles: The Inside Story of the Race to Create an Artificial Superintelligence. A major theme of the book—I would say the major theme—is how strong and competitive the rivalries have been between Dario, Altman, and Musk. Each believes that the others cannot be trusted to gain super-powerful AI capabilities.
Thus, when you observe these individuals and their companies jockeying for position and preeminence, it is too cynical to think it is just about the money (each of them already has plenty). The actions of each are rooted in the sincere belief that their own company would best serve the world by winning the race toward very powerful AI.
So when these CEOs plead altruism, you should actually believe them, even though obvious selfish motives also happen to align with their plans. One can reasonably argue about who ought to win the race, but I favor the outcome where all of them, including Meta and Google, roughly tie for first place, and the market remains highly competitive.
So they are selfish in a sense, but along the metric of power, where they perceive (correctly or not) “selfish and altruistic” to be quite closely correlated. Note I am using the word “power” in a general capabilities sense, you do not have to believe they intend evil coercive exercise in this context. Furthermore, it is not mainly about “capturing the regulator,” but rather winning in the market and then having an immense ability to achieve ends before the others do. So yes they are sincerely worried about a host of safety issues, but they are all the more sincerely worried about not being the ones to win the race. To the extent we wish to cite those CEOs as authorities, “who gets it is the most important thing of all” would be the takeaway lesson.
Do note that for all the talk of pause, the race to invest in compute is continuing apace and even intensifying. That is the real variable to watch. If a theory does not explain observed behavior toward compute, which of course costs real dollars, the theory is failing to explain what is going on.
Standard competition! I do not flip out about this. But obviously there are some world views where you might view these (and other) actors as evil, and furthermore think they can act without much constraint, and so on. Those are not my world views. I see a lot of competition and a lot of ego, and then I think of Adam Smith. Standard stuff, just at much higher stakes than usual.
METR, EA, and others being attacked
Always focus on what you can learn from people and groups. Criticize in ways where you can learn something from the answer (or non-answer) and from the dialogue. If you attack how people look, their sex lives, their donors, whatever, it will make the critic stupider. It may not even hurt the target of the attack, as it provides valuable publicity and also makes them look powerful. Furthermore, there is nothing per se wrong with being “weird.” What does that really mean anyway? I’ve spent much of my life looking for “the weird,” though I would not frame it in those terms.
Wednesday assorted links
The economics of cyber risk
From Aniket Baksy and Daniele Caratelli, here is part of the abstract:
Because larger firms are more attractive targets but also invest more in protection, the model generates an inverse-U relationship between firm size and attack risk, consistent with the data. Introducing cyber risk reduces firm entry by 3.6 percent, aggregate productivity by 0.6 percent, and total output by 1.8 percent. These effects arise from general equilibrium adjustments in entry, firm size, and spillovers that are absent in typical partial-equilibrium analyses. Policy responses differ sharply: appropriately designed subsidies and minimum cybersecurity requirements can raise aggregate output, while bailouts reduce it.
Note this is not a paper about AI. But it may help us develop estimates of the future costs of AI cyberattacks. We need much more effort in this direction, and I hope this subfield rises in status rapidly.
When discussing AI policy, start with China
Whatever your ideas for regulating AI, I say start with China. Do not put China as an afterthought at the end of your proposal, mentioned in a vague wish that something good ought to happen and that maybe the future of humanity can be secured.
During the 2023 U.S.-China nuclear talks, America proposed missile-launch notifications, a nuclear crisis hotline, and processes to limit the use of outer space for military conflict. China declined all of those. Blame the U.S. if you wish (do we always keep our word?), but that is what happened.
China also broke off meaningful arms control talks. You may think it is their right to play catch-up, and to be cynical of our motives, but that is what happened.
How well did China exchange timely information about Covid, and cooperate with stopping its initial spread?
Get the picture?
If you start with China in your discussion, you will end up with sensible proposals before getting too caught up in your moods of the day. If you are reading proposals or for that matter tweets for AI regulation, and the writer does not deal with these China issues in a forthright and very specific manner, you should be very suspicious indeed.
Here is Ezra and Matt Sheehan, discussing related issues (NYT).
Tuesday assorted links
1. Easy to bioengineer a very dangerous virus?
2. The astrophysicists are getting antsy too. Princeton is also getting nervous. If nothing else, these are huge PR own goals. The guy is a Mill scholars, can you imagine J.S. Mill tweeting that way?
4. One Chinese view of AI risk. And from Richard Hanania.
5. Arnold Kling on Polanyi knowledge.
6. Jeremy Stern profile of Mark Zuckerberg. Great piece.
7. China’s first AI-generated TV series.
8. Introducing Free Press Excursions.
9. Redux of my earlier talk/session at St. Andrews on Effective Altruism as a philosophy.
Those new service sector jobs
Horwitz is in the business of playing a version of mom for local college students. Concierge companies offering student support have existed for decades. But in recent years, a new crop of upstarts — such as Horwitz’s company, MindyKnows; the Bama Mama in Alabama; the GA Mom in Georgia; and Campus Mom in Texas — have met additional demand from a new generation of worried parents…
The specific services vary here and there, but share commonalities. Campus Mom offers “holistic wellness check-ins,” laundry services and sorority recruitment support packages, sent to the sisters to up a child’s odds of acceptance. Carrie Eckhardt, the Bama Mama, will clean students’ dorm rooms and check in if parents haven’t heard from their child in a few days (“just pop in and say hi, and take a picture and send it to their mom”)…
Horwitz, for her part, brings students balloons on their birthdays and chicken soup when they’re sick, sits with them in the emergency room and picks up their prescriptions if they’re busy. She bakes homemade challah, coordinates with the bedbug exterminator, texts photos and updates to faraway parents and doles out recommendations on the best local doctors and landlords.
Here is more from Kristy Alpert at the NYT.
Monday assorted links
1. Will driverless cars increase or reduce urban density?
2. One decomposition approach to why interest rates have been going up.
3. New Guinness record holders.
4. Is there any chance of finding Rembrandt DNA?
6. High school students plus AI solve math problem.
7. “China’s top spy chief has warned that artificial intelligence could pose a direct threat to the Chinese Communist Party’s hold on power, in what is the highest-level and most detailed articulation yet of how Beijing sees the technology’s security risks.” (NYT)
8. Good data: cybersecurity stocks surged today.
Sunday assorted links
A simple model of AI-aided economic growth
The Solow model has its uses, but it fails when it comes to major changes stemming from AI. Consider instead an economy with (at least) two factors of production:
1. Intelligence. Yes, formal smarts. Playing chess, proving math theorems, and doing well on evals. Don’t forget humans can do those things too, though AIs are now a huge boost here.
2. Polanyi knowledge. Michael Polanyi, that is. This refers to knowledge of time and place, inarticulable knowledge, custom and habit, and many other particularities that you can read about in Hayek and Polanyi and in many other social scientists, anthropologists too.
Humans specialize in this. The AIs can aid in its production, but at least so far there is no way you can “bring an AI into your office and have it figure out how that office works.” At least not in the human rather than the purely mechanistic sense.
In the model, intelligence and Polanyi knowledge combine to produce output.
Substitutability is fairly limited. For instance, if you have problems of norms in your office, a mere dose of AI-drenched technocratic knowledge does not usually solve those problems. Sometimes it even can make those problems worse, by empowering rent-seekers further.
Intelligence and Polanyi knowledge are not quite Leontief complements, but they are mostly complements.
Now recently the U.S. economy has experienced a huge positive shock to its Intelligence, with more to come.
The core prediction is that this increases marginal returns, employment, and real wages in the Polanyi knowledge sector. All of a sudden, the inputs into that sector are relatively scarce, compared to the now-larger quantity of Intelligence.
There will also be some transitional unemployment in the Intelligence sector, at least once Centaur models fade. But so far Centaur models are holding, for instance mathematicians did the prompting to do the new math work. Nonetheless some of these Centaur employments will fade, just as they have in chess.
Note that the Polanyi sector cannot be boosted very quickly or with direct and simple efficacy. It is messy by its nature, to cite a term from Luis Garicano. So the wage and employment gains there are slow in coming. But they keep on coming for a long period of time. There are further AI/Intelligence advances on tap, plus absorbing the advances to date, and exploiting them, takes a long time.
In this model, if someone or something could “commandeer” the Intelligence sector, their power over society would be much more limited than it might appear at first. The world does not change that much at first, because the necessary complements are lacking.
The Solow model usually does fine by ignoring these features of the world, in part because it is rare for the Intelligence sector to take such a rapid swing upwards. So the ratios and complementarities across these two sectors usually are fairly constant in the short run, though not in 2026 or in the next years to come.
I recall talking through this model, and debating it with people, when I was seventeen years old. The impetus for that was the Soviet preoccupation with cybernetics, central planning, and possible supercomputers. We were all wondering what kinds of economic improvements that might lead to, or whether it could make central planning successful (no, basically, but that involves some yet further arguments).
Of course this very simple model can be improved upon in many ways, but it is a start.
This very simple model so far is matching up to the data, namely that we have shocking AI and tech advances, the job market is doing fine, markets do not see high risk, and economic growth is robust, not exploding, but likely will rise in the future. These predictions change somewhat as the Polanyi sector, slowly, catches up to and incorporates the Intelligence explosion.
In the meantime, this is the best basic framework for understanding our current situation.
The mathematicians rebel against AI
Here is the statement, signed by Terry Tao among many other math notables, most of you probably have read it by now. I do not accept the most cynical interpretations of this proclamation. Some of you for instance may recall that I made and indeed stressed a similar point in the last chapter of my recent “generative book” on marginalism. In some near future, perhaps fewer economists will carry around marginalist insights and modes of thought in their heads, since you can just get the right answer by pressing the proverbial button on the AI.
I find this future disturbing, and not altogether pleasant for me personally, given how much personal status I have wrapped up in particular modes of economic thought. Yet I also know the Bastiat distinction between the seen and the unseen, and I expect the benefits to economic science from AI will be enormous, even if current practitioners cannot foresee most of those benefits today.
I do very much differ with at least one part of the mathematicians’ proclamation. They write: “…whether these changes ultimately benefit the field or have a destructive effect will in large part be determined by the decisions of the humans in control of this new technology.” There is no actual argument for that proposition, and I would sooner expect that the main “action variable” is how well the mathematicians adapt to the new reality. For instance there is nothing stopping the mathematics community from awarding status, pay, and promotions to people who “fill in the important blanks in math understanding,” even if an AI already has proven or disproven the underlying theorems. If that kind of work is so important, we still can do it and reward it professionally. In the meantime, I expect the funding for mathematics, and the interest in the topic, to rise considerably, at least in the medium term. All of a sudden, math matters much more than it used to, all the more so if P vs. NP happens to go the wrong way, or if the distribution of the primes turns out to be a little too predictable.
The mathematicians may not in every way enjoy being the subordinates or handmaidens of the AIs, but that is a change in status they simply will have to get used to, just as I realize AIs someday will end up as better column and blog writers than I am. I do not look to the companies — which I fully expect to “act like companies” — to somehow manage, moderate, or assuage that pending trend. It really is up to me to parlay my current intellectual portfolio into new, more AI-compatible intellectual and yes also marketing approaches. I’ve been given plenty of “legs up” along the way already, as is true for the Fields Medal winners as well, and it is up to me to figure out how to contribute in the future.
Might someone not invent/discover/prompt a way to use AIs to produce, articulate, and teach “more mathematical understanding” along the way? I get that solving famous dramatic math problems is the current commercial priority of the major AI companies. But as the AI space grows, these other paths hardly seem unlikely to me, and in fact the human mathematicians are the ones who can do the most to lead the way along those dimensions.
In this regard the current manifestation of complaints seems oddly early. “I didn’t like the first week or two of your intellectual revolution” is an accurate, and perhaps better reframed way of putting it. At which point perhaps a bit of patience is needed before anything else? These days, we all have more mathematical resources at our disposal, and so a bit of celebration is in order as well.
The Allocative Cost of War
Why is war so economically costly? Our answer is that modern war lowers output not only by destroying productive factors, but also by making the surviving economy work less efficiently. Using uniquely comprehensive firm-level data collected during Russia’s full-scale invasion of Ukraine in 2022, we document a dramatic collapse in allocative productivity in Ukraine. To sharpen identification and explore key mechanisms (including the role of war intensity, internal displacement, reallocation, and macroeconomic instability), we exploit spatial heterogeneity across Ukrainian districts and comparisons with Russian aggression in 2014 and the 2008 Global Financial Crisis. Our key policy implication is that restoring allocative efficiency–and preparing institutional arrangements that facilitate rapid reallocation in times of stress–is critical for sustaining economic capacity, defense, and national security.
That is from a new working paper by Yuriy Gorodnichenko, Marvin Amann, and Oleksandr Talavera.
Friday assorted links
Markets do respond to AGI news
Here is the link. What are the changes in the other market prices telling you?
Is there now a better trend in youth mental health?
A key U.S. government report on mental health, substance use and addiction showed continued improvements in several metrics, especially among young people.
There was some uncertainty about the future of the National Survey on Drug Use and Health last year, when the entire 17-member team responsible for it was laid off by the Trump administration. But the Substance Abuse and Mental Health Services Administration released the latest report Monday, with data that lets researchers look at trends from 2021 to 2025.
Fewer adolescents aged 12 to 17 reported using tobacco, alcohol, marijuana and binge drinking in the previous month, the survey found.
And in the past year, fewer in that age group reported:
— illicit drug and marijuana use
— starting drinking alcohol, vaping or marijuana
— substance, alcohol or drug use disorders
Adolescents also saw declining trends for major depressive episodes and fewer reported serious thoughts of suicide, making a suicide plan and attempting suicide.
Here is the link, via Chris Ferguson.