2. Ingeborg Bachmann centenary.

3. “Huawei Technologies Co. predicted on Wednesday that global computing demand will surge 100,000-fold by 2035, with AI agents generating over 90% of network traffic.”  And a report from someone who has done AI diplomacy with China (NYT).

4. “US Gov Federal Register use distilled Qwen models in their search mode.”

5. How well do financial economics papers replicate?

6. DeepMind Institute.

The post Thursday assorted links appeared first on Marginal REVOLUTION.

       

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• In reply to anon. How quickly we forget the sea. by MikeP
• In reply to John Mansfield. And if the price of the chips is ... by M
• #3b) A reminder that the international politics of AI is about ... by BC
• In reply to mento. For this to occur, most of the new compute ... by anon
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If COVID began with a laboratory leak—plausible, though unproven—then a research accident has already killed millions. Whatever its origin, COVID demonstrated the scale of the potential damage. AI surely increases pandemic risks. If you have ever used AI to fix your washing machine, you understand the difference between reading a manual and having a tutor by your side helping to troubleshoot each problem. The same distinction matters for biological research at the laboratory bench.

Anthropic’s threat report documents five cases of researchers using its models in ways that “could support biological weapons development.” These included military-linked virus research and plans for work on pathogens with enhanced pandemic potential. Did the researchers intend to build weapons? We don’t know. But some users circumvented access controls and concealed sensitive aspects of their research.

Some safeguards appear to have worked but we don’t know the base rate. And what will happen with open-weight models and AIs not under the control of a large corporation? The safeguards also burden legitimate researchers. We should accept that AI will magnify the power of small groups, ill-intentioned or not.

Of course, AI can accelerate vaccines and treatments too. But faster science does not automatically mean faster defense. Turning discoveries into deployed vaccines and treatments requires institutions that can act quickly. We should not assume those institutions will keep pace with the technology.

That makes the recommendations in my 2025 paper, Pandemic Preparation Without Romance, more urgent (surprise!): wastewater surveillance; prediction markets; pre-developed vaccine libraries; human challenge trials planned in advance; a Pandemic Trust Fund; and temporary Operation Warp Speed–style public–private partnerships.

My paper argues that pandemic policy should not depend on unusually farsighted or wise politicians. Public tripwires and banked resources are what you build when you don’t trust the authorities to move quickly in a crisis hence the value of ideas like wastewater surveillance, vaccine libraries, and ready challenge-trial protocols. None of these technologies is highly expensive nor do they require much in the way of continued investment and attention, hence pandemic preparation without romance.

The post Pandemic Preparation is AI Safety appeared first on Marginal REVOLUTION.

       

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• In reply to Gene de Murro. Lone Ted Kaczynski is probably a ... by tg56
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Annie Lowrey’s new book, The Time Tax, argues that the most regressive levy in American life is the hours each of us must spend on hold, in waiting rooms, and filling out forms a competent state would have pre-filled — roughly fifty a year on average, and far more if you’re poor. Tyler spends much of this conversation pressing the opposite case, asking whether that bureaucracy is quietly serving a useful purpose by rationing knee surgeries that don’t work, deterring fraud, or screening for immigrants with gumption.

So Tyler and Annie hash it out over an hour, covering why TANF and other welfare programs are the worst offenders, the political economy of submerged benefits like the child tax credit, whether the postal service should be zeroed out over ten years the way Denmark did, whether the government should be nudging people out of rural areas, lessons from the COVID unemployment fraud, areas where the time tax is flat instead of regressive, which private sector time taxes are most onerous, whether AI agents will pay these taxes for us within five years, the logic of easy benefits plus randomized harsh audits, the case for less federalism, whether voting should be easier or harder, how the UBI studies changed her priors, where you can find the best moss in the world, her favorite example of Brutalist architecture, tattoos as permanent ephemera, Christianity’s role in liberalism and the post-Christian right, how reporting beats tourism, the time tax of friendship, what she’ll learn next, and more.

Excerpt:

LOWREY: The postal service and Social Security’s retirement programs. Those are both pretty good. Social Security also has other programs, SSI, which is mostly used by very, very low-income seniors with disabilities or who are blind. Disability insurance is run by the Social Security Administration. The retirement program, it’s less than 1 percent overhead. It’s great. It does all the work for you.

COWEN: Isn’t our whole postal service a time tax in the aggregate? Denmark, just this year, abolished its postal service. They don’t have any. Now, I understand we’re not in a position to do exactly the same, but shouldn’t we be moving away from postal service, basically zeroing it out over the next 10 years?

LOWREY: Did they make it so that it’s all digital? Did they digitize things?

COWEN: Well, I don’t know who the “they” is. Direct mail there has gone away.

LOWREY: Oh, yes, that’s interesting. I don’t know. I think in a high inequality country such as ours, where you still have a lot of people who don’t have smartphones and don’t have computers, that’s why I would be very concerned about the postal service going away.

COWEN: That’s why we need 10 years. You want to tax people, tax in the broad sense of the term, living in rural areas, if only because it’s much harder to have government help them, right?

LOWREY: Yes.

COWEN: If rural areas don’t get mail anymore, maybe that’s a good thing.

LOWREY: I don’t think that that’s a good thing for the people in the rural areas, though. There’s always going to be people in rural areas. As a general point, do you want the government to be encouraging people to not live in rural areas?

COWEN: Absolutely, that’s me. Welcome to the show.

LOWREY: That’s feels very nanny state-ish of you, Tyler.

COWEN: I don’t want to subsidize rural areas, and we do it in so many ways, including with our farm programs.

LOWREY: We do. We really, really absolutely do.

COWEN: It gets harder to help people with government. There’s a lot more market power in rural areas, like how many supermarkets are there, how many hospitals, probably just one, if that. Let’s get everyone into the suburbs, or heaven forbid, the cities.

LOWREY: I can’t imagine a less popular policy than that.

COWEN: Absolutely.

Interesting throughout, and full of good spirit.  Again, here is Annie’s very good book The Time Tax: How Government Wastes Our Time — And How to Fix It.

The post My excellent Conversation with Annie Lowrey appeared first on Marginal REVOLUTION.

       

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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.

The post The correct model of AI CEO behavior appeared first on Marginal REVOLUTION.

       

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• One could say.. That if they truly believe the world would be ... by Panderer
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2. Prophets of the Marginal Revolution.

3. The university after AI.

4. Which African nations are spending on education?

5. @mattyglesias: “In an all-or-nothing scenario, bond interest rates would go to the moon. Why lend money at 5% (or whatever) if the two options are not being repaid and stocks going through the roof?”

6. David Schleicher on how property taxes are evolving, underrated yet important ideas.  Good sequence.

7. I just bought the new China Mieville book.

The post Wednesday assorted links appeared first on Marginal REVOLUTION.

       

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• In reply to Wayfaring Stranger. Imagine there was a universal ... by Depends on the tax reduction…
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The post Very good news appeared first on Marginal REVOLUTION.

       

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We also have plenty of evidence that the fears of AI experts are sincere. Amodei, Altman and Musk were all publicly warning about AI risk long before they had AI companies to promote. The worry runs well beyond the executive suite; rank and file researchers share it. And it extends outside the industry altogether, to computer scientists with no product to sell, among them Nobel laureate Geoffrey Hinton. Hinton left a high-paying job at Google precisely so he could speak out and Hinton is not in a Berkeley polycule with Eliezer Yudkowsky, at least as far as I know. Whatever else you may say about the belief that AI presents a serious risk, plenty of AI researchers believe it sincerely.

Similarly, when Amodei recently proposed to slow the pace and install independent safety teams at AI companies many people jumped to the conclusion that this was regulatory capture. Sorry, but no, that theory doesn’t make sense. To see why, we should review the theory of regulatory capture.

Regulatory capture came out of the political science literature especially Marver Bernstein’s 1955 classic, Regulating Business by Independent Commission. Bernstein argues for a regulatory life cycle: Gestation, Youth, Maturity, Old Age. A scandal brings a bureaucracy into existence—or gives an existing one new powers. The public’s attention, like Sauron’s eye, fixes on the issue of the day: something must be done. The thalidomide scandal, for example, helped establish the modern FDA.

Gestation gives way to a youthful burst of reform and the do-gooders come to Washington ready to battle the industry. Inevitably, however, the public’s eye looks elsewhere. But the industry never looks away. It lobbies Congress, hires former regulators, trains future ones, and supplies much of the information the agency needs. As the agency matures, accommodation replaces confrontation. By old age, the regulator has become the industry’s protector. The classic example is the ICC, created to regulate the railroads but it eventually came to shield them from competition from the trucking industry.

Notice that classic regulatory capture takes time, it’s a process of erosion rather than a battle, it happens in the shadows, in the backrooms, away from the public’s eye. As Culpepper argues in Quiet Politics and Business Power, business power goes down as political salience goes up. Regulatory capture and lobbying does a good job explaining why roasting coffee beans was defined as “domestic manufacturing”, thereby lowering Starbuck’s tax rate by 2%. It does less well at explaining big cross-industry issues the public cares about such as environmental regulation or race and gender discrimination regulation. Finally, don’t confuse capture with firms making the best of a bad situation. Philip Morris supported the 2009 Tobacco Control Act not because FDA regulation was Philip Morris’s unconstrained ideal but because it knew regulation was coming and it wanted a seat at the table to nudge the rules in its favor. That’s ordinary political bargaining—or rent-seeking—not evidence that the regulator has been captured.

Now let’s evaluate Amodei’s call for regulation in light of regulatory capture theory. AI regulation is in gestation. Public attention is fixed on the industry, and much of that attention is hostile. The big profits in AI lie in automating work, and job loss is a much more salient fear than extinction. AI politics is now loud–precisely the environment in which Culpepper predicts business power will be weakest. A mature industry can bend regulation to its purposes through revolving doors, longstanding relationships and obscure rulemaking. An industry under Sauron’s eye has much less power and faces much greater risk that politics will bend regulation to its purposes. Political actors are eager for an excuse to redistribute AI rents away from capitalists and toward favored groups (ala Peltzman).

Regulation will reduce AI profits. That doesn’t prove that every rule Amodei favors is innocent of self-interest, an absurd proposition. I suspect that Amodei’s ideal may be something like a single regulated AI monopoly—safe and reasonable profitable, like the old AT&T. But that’s not the profit maximizing outcome. If transformative AI can capture even a fraction of the enormous labor market–the world’s biggest market–laissez-faire would mean vastly greater profits. Amodei may simply prefer a smaller fortune and a safer world. That is perfectly consistent with self-interest playing a role; it is not consistent with the bastardized theory that profit maximization is the only thing that matters or that “capture” is universal.

Go ahead: argue that Amodei and other AI experts are wrong about AI risk. Ask whether his proposals favor Anthropic. But calling “our product might kill you” a clever marketing and regulatory-capture strategy isn’t sophisticated analysis. The facts don’t fit regulatory capture theory and trying to make them fit requires epistemically painful Ptolemaic epicycles. Even a dull Ockham’s razor cuts through that story to the obvious alternative: Amodei actually believes what he’s saying.

The post What Regulatory Capture Actually Looks Like appeared first on Marginal REVOLUTION.

       

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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.

The post The economics of cyber risk appeared first on Marginal REVOLUTION.

       

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• The insurance companies will sue the AI companies, possibly in ... by Tom Meadowcroft
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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).

The post When discussing AI policy, start with China appeared first on Marginal REVOLUTION.

       

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Share prices of cyber firms have jumped around a lot in recent weeks, leading one side or the other to claim victory. But the crucial point is that, relative to the historical norm, the market is not really pricing ANYTHING big to change. There was a much bigger move in cyber stocks in both 2020-22 (up) and 2022-23 (down) but no one read “AI x-risk” into this.

Here is the full post with graph.

Hardly the final word, and I am myself more pessimistic than those numbers indicate.  But at least with this we are getting somewhere concrete and scientific rather than just scare stories.  As for meta-commentary on the discourse itself, you really should be asking who are the people insisting on data here, and who are the people trying to talk you away from focusing on the data so much.

The post Callum Williams on cybersecurity prices appeared first on Marginal REVOLUTION.

       

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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?

3. New David Brooks podcast.

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.

The post Tuesday assorted links appeared first on Marginal REVOLUTION.

       

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• In reply to Kaz Stanczak. Thank you for the pointer on moral ... by dmcharette
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Event key:

1. Dec 31 – China reports the Wuhan pneumonia cluster to the WHO
2. Jan 21 – First confirmed US case (Washington state)
3. Jan 23 – Wuhan locked down
4. Jan 30 – WHO declares a global health emergency (PHEIC)
5. Feb 19 – S&P 500 all-time high, 3,386
6. Feb 24 – Italy outbreak; first big US selloff
7. Mar 3 – Fed emergency 50 bp cut
8. Mar 11 – WHO declares pandemic; Europe travel ban; NBA suspends season
9. Mar 13 – US national emergency declared
10. Mar 15–16 – Fed cuts to zero and restarts QE; worst day since 1987 (−12%)
11. Mar 23 – Fed announces unlimited QE; market bottom at 2,237
12. Mar 27 – CARES Act signed
13. Apr 2 – 6.6 million initial jobless claims in one week
14. Apr 20 – WTI oil futures settle below zero
15. May 8 – April jobs report: 20.5 million jobs lost, 14.7% unemployment

The striking thing is how late the market moved. Wuhan was locked down and the WHO had declared an emergency a full month before the peak. The 34% drawdown then took 23 trading days, and the bottom coincided with the Fed’s unlimited-QE announcement rather than with any turn in the epidemiological news, which was still getting worse through April.

Addendum: Mostly from a query to Claude. You may fill in the missing context.

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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”)…

Here is more from Kristy Alpert at the NYT.

The post Those new service sector jobs appeared first on Marginal REVOLUTION.

       

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While recent research has provided evidence that the Medicaid expansions of the Affordable Care Act (ACA) reduced mortality, there is no evidence on the effect of the Affordable Care Act (ACA) net of the Medicaid expansions on mortality. This is an important gap in knowledge because the ACA significantly increased health insurance coverage in non-expansion states. In this article, we exploit the large increase in health insurance coverage brought forth by the ACA to examine the effect of the ACA and Medicaid expansions on mortality. Unlike prior studies that relied solely on geographic variation in Medicaid expansions to estimate the net effect of the expansion, we use a novel empirical approach that allows us to investigate the effect of the ACA net of Medicaid expansion on mortality, the incremental effect of the Medicaid expansion, and the overall effect of the ACA including Medicaid expansion. We use longitudinal data from the NHIS Linked Mortality Files (LMF) and a nationally representative sample of 40 to 58-year-olds combined with a difference-in-differences and a difference-in-differences-in-differences research design to obtain estimates of the effect of the ACA on mortality. We find no evidence that the Medicaid expansions had a beneficial effect on mortality but do find that the ACA net of Medicaid expansion reduced mortality.

That is from a new NBER working paper by Anuj Gangopadhyaya, Cuiping Schiman & Robert Kaestner.  Via Glenn Mercer.

The post Did the ACA reduce mortality? appeared first on Marginal REVOLUTION.

       

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