Streetwise Professor

Yesterday SecWar/Defense Pete Hegseth made something of a splash with an announcement eliminating tenure at service academies. Well, the headlines were somewhat misleading. What he did was announce that in the future the academies would not offer tenure. This, of course, because existing tenure is a contractual commitment that cannot be revoked absent some rather egregious misconduct.

The effect of the change is also less than it appears because tenured or tenure track civilian faculty are non-existent at the Air Force Academy (USAFA), and a small proportion of faculty at West Point (USMA)–27 percent to be exact. Only at my alma mater, Navy (USNA) are civilians a majority of faculty, and most of those are tenured (about 70 percent). So if anything, this is aimed at Navy first and foremost.

Navy has long had a civilian-heavy faculty, and alums point to it as an indication of the greater academic rigor of USNA relative to its peers. (Perhaps that’s what really exercises Hegseth). Indeed, the “Father of the Naval Academy”-William Chauvenet-was a civilian, and responsible for its academic curriculum and hiring in its earliest days 180 odd years ago.

Chauvenet’s history is illuminating on the subject of civilian instructors. He was hired, as a civilian, to teach math to midshipmen on ships, before there was an academy. So even crusty old salts recognized the comparative advantage of civilian instruction. His dismay at the level of instruction midshipmen received led him to advocate the formation of an academy. Originally a two-year institution, he pushed to make it a full four year school. And he wanted it to be academically rigorous, and hence was a strong advocate of hiring civilian instructors. Chauvenet set the course for USNA (no pun intended), and it has sailed that course ever since. That course is fundamentally different from USMA and USAFA (which reflecting the Air Force’s origin in the Army is far more like USMA than USNA).

Chauvenet’s reputation in American academia was stellar. Yale tried to hire him, but eventually he became the chancellor of Washington University in St. Louis, where he established it as a leading academic institution.*

The age of steam, with its novel engineering challenges, was fundamental in transforming the school and its curriculum. Under steam pioneer Benjamin Isherwood, the Academy became primarily an engineering school. Isherwood was a career officer, but civilian appointments in engineering positions at USNA were common, and remain common today.

So Navy is different, and has always been different. The civilian-heavy instructional staff is reflective of that.

Even at Navy, there is less to Hegseth’s announcement than meets the eye: there is a stock-flow issue. Tenured faculty will decline one retirement (or funeral) at a time, meaning that in the remainder of this Trump term the order will have little effect on faculty composition. Since it well may be reversed under a future Secretary, the effect may be trivial. (I wonder what SecNav nominee Hung Cao, a USNA grad, thinks about this. BTW, there are rumors about that he doesn’t like Hegseth).

The reasons Hegseth gives for his order are eye-rolling:

“To ensure our educational institutions remain firmly focused on this warfighting mission, we must address the structural mechanisms that have allowed civilian academic norms to dilute our focus on lethality.” . . .“academic stagnation, faculty complacency, and institutional inability to adapt to emerging needs . . . . contributes to curriculum that drifts from the mission of educating our warfighters to the research priorities of the tenured academics.”

“Academic stagnation” and “faculty complacency” are things Adam Smith wrote about 250 years ago, and are hardly accurate characterizations of the civilian faculty I knew. Insofar as “research priorities” interfering with curriculum drift and impeding adaption to emerging needs, Hegseth is spouting nonsense. For one thing, the Academies are teaching schools, with heavy teaching loads where research input and output are low as compared to true research institutions. For another, especially with respect to technical fields in particular (which represent the bulk of civilian faculty at Navy), remaining research active actually facilitates, rather than impedes “adaption to emerging needs.” Hegseth’s statement is a slur on civilian profs at the academies.

Hegseth’s references to “lethality” and “warfighters” suggests the reasons his misguided opinions, and how they are particularly misguided with respect to Navy, where many junior officers spend their early careers managing equipment and technology or managing people who operate equipment and technology rather than pulling triggers.

That contributes to lethality. Indeed, the contribution is vital. If weapons or sensors or engineering plant don’t work, even Alexander the Great can’t make them lethal.

The irony here is that Hegseth claims to be technology-focused, with AI being a prominent example. (More on that story in the future). Well, mightn’t it be a good idea to have some officers educated in this? Wouldn’t the quality of this education be improved by faculty who are specialized in the field and who have a long term commitment to an institution where they teach it?

The only thing that saves Hegseth from his own stupidity here is the limited impact it is likely to have.

But of course there are very online Hegseth throne sniffers who offer their own stupid takes on his stupid policy:

Service academies are not, and should not try to be, butched-up colleges.

If you want the college experience as a student, the be like ‘ole Sal and go NROTC.

If you want to get a tenure track professorship, then look elsewhere to pursue that goal. https://t.co/t2Un49MGdf

— cdrsalamander (@cdrsalamander) September 29, 2026

Er, nobody-and I mean nobody-goes to an Academy to pursue an academic professorship. In fact, one pretty much has to leave an academy if one’s interests lie in that direction. Like me, for instance.** So Jeez, if you are going to try to suck up to Hegseth, at least try to make sense.

The more important part of Hegseth’s announcement is not the tenure piece, but this:

He directed the secretaries of the military departments to develop hiring plans prioritizing “institutional flexibility and contributions to the warfighting mission.”

This is problematic because hiring plans are well downstream from curriculum and curriculum design. Given the existing curriculum, there are at least two strong reasons to lean towards more, rather than less, civilian personnel.

The first is that teaching is a skill. My decades in academia have shown me that most people suck in their first couple of years in the classroom, no matter how great their domain knowledge. At the very least, it takes a few years to develop as teachers even if they don’t suck right off the bat. There’s a lot of learning by doing. Rotational military faculty (which dominate at USMA and USAFA) leave just about the time they hit their stride.

The second is specialization. The old adage about those who can’t do, teach, has something to it. Let eggheads specialize in teaching, and warfighters specialize in fighting wars, rather than having warfighters cosplay as teachers–something that is inimical to Hegseth’s stated objective.

Less flippantly, specialization offers other benefits. Specialists in a field have more domain knowledge and are on average more able to convey it than someone who parachutes in from the Rangers or whatever for a couple of years. Even more prosaically, teaching (especially with the heavy loads at academies) involves appreciable prep/setup time. Those costs are largely sunk for experienced civilian faculty teaching the same course for years. Every rotational faculty member has to incur them, and that happens every couple of years. Is that how Hegseth actually wants “warfighters” spending their time?

And just how, exactly, does one advance warfighting in Calc II? Beginning each class with a hearty “ooh-rah”? (My memories of uniformed profs at Navy–mainly in professional courses–are that they were hardly gung-ho.)

So given the curricula at the academies, reducing civilians in the ranks of professors doesn’t make sense. To the contrary.

Meaning that Hegseth should actually be focused on curriculum, rather than who delivers it. But that’s probably expecting too much from our Pete.

So the real issue is: should the academies have curricula that are comparable to rigorous civilian universities and colleges, with a considerable dollop of military-specific courses and training on top? I think the answer is yes, for several reasons.

The first is that rigorous, non-military education offers other benefits. It is a signal for intelligence and diligence. Done right (something increasingly rare these days) it trains people how to think critically and analyze, generalized skills that are clearly applicable in the military.

The second is that although each offers non-technical degrees (I was an econ major!), the bulk of midshipmen and cadets major in technical fields. (The jocks are an exception–but that’s a whole different subject). The very technical change that Hegseth talks about is a compelling reason to retain this orientation, especially since graduates are very technology facing during the early part of their service.

And even the “softer” fields provide things that advance the military mission of “lethality.” Economics, for example. One of the principles of war is “economy of force”–the efficient allocation of scarce resources to achieve objectives. That’s fundamentally a statement of economics generally that applies at tactical, operational, and strategic levels. As a specific example, constrained optimization is fundamental to economics–and directly applicable to military problems. (Linear programming was developed to optimize the allocation of ships to convoys during WWII). Logistics is in many ways applied economics, and logistics wins wars.

Perhaps if Hegseth understood constrained optimization better, he wouldn’t have shot off a goodly proportion of our scarce weapons in fighting Iran.

An appreciation of history is also a vital war fighting skill. Many great commanders (Napoleon among them, but more recently Norman Schwarzkopf) have been students of history and applied the lessons to win battles. And to win wars–something the US has not been particularly expert at in the last 80 years. Maybe having some more liberally educated officers would help address that problem.

I use “liberally” in that sentence in its traditional sense of “liberal education.” But I have a sneaking suspicion that another sense of the word liberal is what really drives Hegseth’s hostility to civilian faculty: specifically, civilian faculty, even at academies, are politically liberal.

There’s a podcast out there somewhere in which Victor Davis Hanson describes his experience as a visiting history prof at Navy, and his shock at learning how politically liberal the faculty were. When I interviewed for the Admiral Crowe Chair at Navy (which I was offered but declined), I was taken aback at the politics of the economics faculty (and their disdain for many Midshipmen).

But here’s the thing. Most of the faculty I interviewed with were my profs when I was a Mid. Yet I had no idea of their politics, although conditional on their cohort (getting doctorates in the 1960s) it should have been pretty obvious. They taught down the middle, and didn’t poison young minds with liberal dogma. (I’m living proof of that!) Classrooms weren’t politicized by civilian profs in the 1970s. Maybe it’s different now, but I doubt it.

In sum, Hegseth’s initiative is mid-witted and ignorant, and wrapped up on bravado. But I guess at this point, that shouldn’t be surprising.

* I seem to have a weird way of following around prestigious USNA professors, Chauvenet being one and Robert Michelson being the other. After teaching at Navy (where he commenced his speed of light measurements) he went to the University of Chicago, where he spent decades. Both men have academic buildings at USNA named for them. They were pretty new when I was there.

**From time to time during a deposition, opposing counsel thinks there is a dark secret underlying my departure from Navy. So when asked why I left the academy, my stock reply is: “Because I figured out I was more cut out to be a scholar than a boat driver.”

AI hysteria has predictably led to calls to regulate! regulate! regulate!, seemingly from all corners except for the Trump administration and NVIDIA’s Jensen Huang. Those baying for “regulation” include frontier model leaders Anthropic and OpenAI.

I put “regulation” in quotes because as is often the case, those calling for regulation are imprecise on just what regulation should entail, and have evidently given little serious consideration to how regulation works in practice. The word is usually more of a magic incantation than a description of something real that has any chance of realizing the goals of those using it.

So what should AI regulation look like? To answer that question, it’s important to start at the basics.

Decades ago Steve Shavell wrote two important articles that speak to the subject: “Liability for Harm Versus Regulation of Safety” (JLE, 1984) and “The Optimal Structure of Law Enforcement” (JLS, 1993). Shavell laid out several criteria for determining the best way to regulate.

Broadly speaking, there are two alternative methods of regulation. Harm-based (“ex post“) sanctions that attempt to deter harmful conduct, and preventative (“ex ante“) regulations. The former includes the common law tort system, and civil and criminal laws. The latter includes things like government approval for the sale of a product, with FDA approval of drugs being an example. Many of the calls to regulate AI fall in the latter category, and some members of the Trump administration basically advocate the former.

So which is best here?

Shavell identifies several factors that determine the optimal legal structure. On balance, these favor ex post/harm-based tort-like approaches.

The first criterion is “is the possibility of a difference in knowledge about risky activities as between private parties and a regulatory authority.” That is, information asymmetry between the regulator and the regulated.

This is quite intuitive. If an actor (an AI firm, in this instance) has better information about the likelihood its actions will cause harm, and the amount of harm it will cause than does a regulator, if it knows it will pay damages commensurate with the harm it causes, it can take the efficient precautions. It will appropriately trade off the cost of mitigating harms (including the cost associated with reduced performance) with the cost of the harms because the prospect of paying damages based on costs and probabilities of harms will induce it to internalize the costs of its actions.

In contrast, an ignorant regulator knows less about the probabilities and magnitudes, and is therefore likely to implement measures that are either overinclusive or underinclusive. That is, regulators are far more prone to Type I and Type II errors.

It is clearly the case with AI that the developers-the labs/frontier firms in particular-will be far better informed about their creations and the risks that they pose than any government regulator would be.

Shavell’s second criterion is “that private parties might be incapable of paying for the full magnitude of harm done.” That is, in the present context, an AI firm might be “judgment proof.” In the event, the actor will not internalize the costs it imposes on third parties, and will tend to take excessive risks and impose excessive harms. Here, external interventions that constrain actions in order to reduce the magnitude and frequency of harms can be superior to deterrence.

The inability to impose monetary damages commensurate with harms is one justification for criminal sanctions, including imprisonment or even execution. These are non-monetary penalties that enhance deterrence.

This is one factor that might-might-favor ex ante regulation. Anthropic or OpenAI (or any other firm) could not pay damages commensurate with harm if that harm is the end of humanity!

But this brings us back to the first issue. In deciding whether judgment proofness is indeed a problem, we need to have some assessment of the distribution of harms, and here the AI firms have a decisive information advantage. And as I discuss below, we absolutely cannot take at face value the pronouncements of Amodei, Altman, Musk, et al, on the potential harms posed by AI, or their likelihood.

And more, even though judgment proofness may preclude AI firms from fully internalizing costs of their products (especially the harms they may create), bureaucrats operating subject to low powered incentives clearly don’t internalize them. Nor do they internalize the benefits of more capable AI. Therefore, although judgment proofness may be a necessary condition for ex ante regulation, it is not a sufficient one.

Shavell’s third factor is “the chance that parties would not face threat of suit for the harms done.”

In the US legal system? As if! Indeed, the likely bigger problem with relying on the tort system to deter would lead to suits for harms not done, i.e., frivolous or baseless litigation.

Shavell’s last factor is the relative administrative costs of the two systems, i.e., the cost of a regulatory bureaucracy vs. the costs of litigation.

Both litigation and bureaucracy are costly. The advantage of ex post, harm-based regulation is that the litigation costs are only incurred when a harm incurs: no harm, no foul, no legal expense (with the caveat related to frivolous litigation mentioned above). In contrast, the bureaucracy must be fed continuously, even in the absence of harms.

And note that regulation would necessarily have to be international in scope. Look at the post-Great Financial Crisis history of banking and financial regulation for a demonstration of the monumental costs and challenges of international regulation. AI regulation would put even that in the shade, especially since it adds China and strategic competition into the mix.

To which, I would add another factor: influence costs, including regulatory capture. It is well known that the regulated exploit their information advantages and financial resources to induce regulators to take actions that benefit some regulated entities, at the expense of other entities and the public at large. This is especially likely to work when the regulated have a big information advantage (check) and a lot of money (check).

Overall, to me the scorecard tilts heavily in favor of ex post, harm-based, liability mechanisms as opposed to ex ante regulation. This is especially true given the radical uncertainty and information asymmetries inherent in such a dramatically new technology. We are learning the harms as we go, and the developers learn more and faster than any bureaucrat can. Indeed, being liable for harms gives the developers a strong incentive to identify those potential harms-their magnitudes and likelihoods. A far stronger incentive than bureaucrats have.

And that provides a segue into a discussion of one of the most fascinating aspects of the ongoing debate/hysteria: the fact that the frontier labs are the loudest and most strident voices calling for regulation. In my opinion, this is overdetermined.

A major reason is that Anthropic et al are deathly afraid of being liable for the harms their products cause. Palantir’s Alex Karp perhaps overstates the case when he says they are effectively calling for nationalization in order to avoid liability, but I think it’s pretty clear that avoiding paying for the harms their products cause is a major driver behind the calls–pleas, really–for regulation.

Which, to be honest, another reason to favor a liability-based system. It suggests they understand that even precluding the end of the world or singularity scenarios, they are aware that their products can do great damage. The only way to get them to act on this knowledge is to force them to pay the costs, and not be able to say “don’t look at me! The regulators approved what I did!”

Another reason-the one that has received most commentary-is that the frontier firms know that they would be able to capture their regulator(s) by exploiting their information advantage and vast wealth. And as George Stigler pointed out long ago, the biggest benefit a regulator can bestow on its industry masters is a reduction in competition, including by the erection of entry barriers. As I’ve written with respect to financial regulation, regulatory costs are largely fixed and therefore benefit large incumbents at the expense of new, smaller, disruptor entrants.

There is another reason that is laid bare by some of the specific rhetoric and actions of Amodei, Altman, et al: a belief that intense competition between the frontier firms, let alone between them and open weight models, small models, etc., will be ruinous to them.

The cabal has been negotiating in public for “pacing,” i.e., a coordinated slowdown of model development. Competition on the capability dimension is hugely expensive, especially with respect to training. I view the various public statements-including the apocalyptic rhetoric justifying a slowdown-to be “cheap talk” intended to coordinate reduced investment. A way of cartelizing the industry.

Which leads to another motive for favoring regulation–protection from antitrust laws.

A coordinated slowdown would also address something else that I think looms over them. The whole AI sector is a bet on future demand, future prices (which depend on demand and competition from non-frontier implementations), the costs of production (e.g., data center investment and operational costs, including notably electricity), and the execution timeline (e.g., will bringing data centers online be delayed by supply chain bottlenecks or local political opposition?) Doubts have been increasing on all these dimensions, and I strongly suspect that the industry insiders fear that their massive investments (at all levels of the value chain) will not pay off if the current pace and growth are maintained. That is, the “pause” is not driven by safety fears, but by fears of a financial bloodbath.

It reminds me of Stalin’s pausing collectivization because he was “dizzy with success.” AI has been so successful that it has led to dizzying excesses that need to be reined in.

So there are many reasons for AI executives to want a pause. I think all are operative, and all push in the same direction–regulation by means other than liability.

But the nature of the industry and the product and the economics of harm reduction mean that a liability mechanism is the best way to address the safety concerns surrounding AI. That mechanism would give AI developers the strongest incentive to control the risks that they lecture us about daily. Anthropic doesn’t need OpenAI to mitigate the risks of its models, and vice versa. Internalize costs via a liability system and they will unilaterally have the incentive to do so.

Elon Musk enterprises are deeply embedded in the US national security establishment, most notably via SpaceX’s space ventures, but now via its xAI subsidiary and its Grok AI. The Department of War’s/Defence’s set-to with Anthropic demonstrates that an AI enterprise’s interests can potentially conflict with the Department, which could pose a security issue if the enterprise attempted to hold it up by restricting use in some way. The same risk could arise with Grok.

The embedded documents, prepared by @LibertyLynx and I, analyzes in detail the holdup potential for Grok. The basic conclusion is that the DoW has access to multiple AI providers, and can switch out at short notice–but not immediately. That matters, because in war, mere moments can count (what Patton called “the unforgiving minute”), meaning that even a fleeting withholding or even degradation of Grok (or another AI) could have dire consequences. In an optimistic case, a switch out would take 96 hours–pretty much the time that the ground campaign in Desert Storm lasted. A military eternity, in other words. That is, there are acute “temporal specificities.”

As the US military becomes more reliant on AI, especially for operational functions (e.g., targeting), the model relied on will become a potential single point of failure. As we analyze in the attached documents, failures can arise for purely technological reasons, or because of human interference with employment of the models–the latter being the holdup problem.

The reason that the Pentagon attempted to axe Anthropic was that the company demanded the power to withhold deployment of its models for purposes that it deemed incompatible with company values. That is, a deployed model posed holdup risks that the Pentagon deemed unacceptable.

It is troubling enough to extend someone as mercurial and megalomaniacal as Musk serious holdup power that the Pentagon assumed unacceptable in the case of Anthropic. If Anthropic’s values are problematic, what about Musk’s?

What is even more troubling is that Musk is deeply embedded in China. Specifically, Tesla is very dependent on China, to an extent that is barely appreciated in the United States–in large part because Musk hardly says anything about it, in contrast to his pontifications on pretty much every other subject known to man.

A majority of Tesla production is in China. Tellingly, Tesla’s output per unit of fixed assets is far higher in China than in the US. Moreover, Tesla gets appreciable funding from China. It hardly seems prudent to give an individual with such conflicting interests as Musk control over a vital defense function that requires complete reliability 24/7, and which is characterized by acute temporal specificity.

There is a fundamental economic challenge here. The government does not have a comparative advantage in developing these models, and is inherently reliant on the developers for continuous support of their operation. But given the specificity of these assets, what contracting and governance mechanisms can be put in place to protect the government against opportunistic behavior by the model developers? It’s an inherently daunting challenge, and those challenges are particularly acute when the counterparty is one of the world’s most egregious opportunists who is known for using his leverage to benefit himself. Of all the people to give leverage to . . .

Some problems could be mitigated by requiring Musk to sever his China connections. That would change his incentives, but would not change him.

Our research also raises questions about how disinterested Secretary of War/Defense Hegseth and his Chief Technology Officer, Emil Michael, were in their Anthropic decision, and their subsequent embrace of Grok.

The embedded documents analyze these issues in detail, and highlights issues that have received too little attention amidst the ongoing hype over space, digital data centers, and AI. Not that those are unimportant, and will the the subject of future similar posts.