When I posted a piece on the latest failure of the US Navy a while back, I predicted that I wouldn’t be changing any minds. That was one of my safer predictions, confirmed almost immediately by  Robert Farley at Lawyers, Guns and Money,Farley declined to respond, saying “whatever his other virtues, Dr. Quiggin is not a serious voice on naval questions” .

I wasn’t surprised by this. Farley is the epitome of the navalist view that serious expertise on the technology of naval warfare is a crucial requirement for commentary, whereas being right is irrelevant.

Given this respect for credentialed expertise, however, I was a bit surprised, to see Farley endorse a piece by Bret Devereaux making the claim that that “the United States Navy is a load-bearing component of the global economy” You might think that the relevant expertise here included at least some knowledge of both transport economics and the global economy. Devereaux, who is an “ancient and military historian” has neither.. Still, I’m not going to pull academic rank here. Let’s see what Devereaux has to say and how well it stacks up as a piece of economic analysis.

I take the architectural metaphor to mean that the global economy depends critically on the supposed role of the US Navy in protecting maritime trade. This is stronger version of a claim commonly made by navalists, to the the effect that US naval expenditure is a form of global foreign aid, offsetting the notorious stinginess of the US in ordinary aid (now massively exacerbated by Trump and Musk).

The recent panic about a breach of Medicare computer security by an “AI agent” contrasts sharply with other recent cases such as the Telstra and Optus outages that left many Australians unable to reach Triple Zero. In those cases, no one blamed the computers involved. The mistakes were clearly sheeted home to the corporations that operated them.

This wasn’t always the case. When the term “artificial intelligence” was coined some 70 years ago, the first mainframe computers (absurdly primitive by modern standards) were viewed with the same awe and concern as the AI agents of the present day. There were even “algorithms” (though the term wasn’t used in that way at the time) that were supposed to pick ideal dating matches.

Failures were inevitable, and blame-shifting became routine. “The computer made a mistake” was the 1960s equivalent of “your email must have gone to junk”. Gradually, however, we realised that the problem was not with the computer but with incorrect information fed into it or badly written programs invoked as a result.