The Nine Lives of Economic Nationalism – Part One of Four

To say that economists think poorly of US President Donald Trump’s economic policies is to understate matters. Most see him as an unhappy combination of a 19th-hole savant and that student — there is one in every classroom — who insists on the rationality and inevitability of socialism. President Trump differs from the student in that his own guiding star is economic nationalism rather than socialism.

But, as many have pointed out since the administration decided to take a 10 percent stake in Intel and cull 15 percent of Nvidia’s and AMD’s China revenues, economic nationalism and socialism are not so far apart. Each leans toward state self-sufficiency and tends to involve state control of the means of production. Both involve the state imposing its priorities on the market. Economists since Adam Smith in The Wealth of Nations (1776) have seen such state control as less efficient than market allocation of resources. Thus, in part, economists’ anxieties about Trump policy. 

This four-part series will look at how economic nationalism has persisted despite its theoretical irrationality. The question is significant for investors because investments are often based on assumptions about economic maximization in free markets. Economic nationalism confounds such assumptions and complicates investment. It might also make the global economy’s “weaponized interdependence,” in Henry Farrell and Abraham Newman’s phrase, exceptionally dangerous. This series tries to assess that threat.

Adam Smith argued that, whether inside a state or between states, producers should specialize in what they already do best. Trade would then ensure that the best products at the lowest prices would reach customers and the overall economy would produce the most and best for least. Restraining trade would by definition reduce efficiency.

That was a leading reason why Smith and most economists after him were anti-imperialist. To take over territory, people and resources and bend them to making things the imperial center wanted, rather than what they might do best, ran contrary to market economics. The American revolutions, from Buenos Aires to Haiti to Boston, were led by people who wanted to take control of production away from empires. Settler colonialism was, in this sense, a school for radicalism.

It was also, of course, a school for economic nationalism. Newly ex-colonial states like the US appreciated that their former masters had a head start in developing the most productive technologies and business methods. The point of anti-imperial revolution circa 1800 was not simply to exchange formal domination for informal subordination by superior economies. Economic nationalism was animated by the desire for sovereignty: the business of states, so to speak, rather than of businesses. Restraints on trade, in the service of economic nationalism, always operated alongside their opposite, namely free trade. This was true in the 18th century as it is today. It was a feature, not a bug, of modernity.

The first Trump administration, running contrary to modern economic theory, embraced such an economic nationalism and the restraints on trade designed to advance it. The proximate cause was China and its set of policies gathered under the name of Made in China 2025 (launched in 2015). If the state-controlled 18 percent of humanity known as China was going to structure its economy to further its own economic nationalism, then the US was going to do the same. Tellingly, in arriving at Made in China 2025, Chinese economic thought took the anti-imperial US economy of the late 19th century as one model in combining restraints on trade with a conditional embrace of free-market forces, both aimed at the political goal of economic sovereignty and the historical goal of catching up to the modern world’s first movers, which were primarily empires. (Industrializing, imperial Japan circa 1890, one of whose aims was unfortunately supremacy over imperial China, was a similar and powerful model, especially for non-Europeans.)

As Trump’s and then Joe Biden’s economic policies developed, it became clear that China and the US were jointly reconfiguring the global economy to advance their respective economic nationalisms. What neither the US nor China seems to have anticipated was that this dynamic would solidify among other large economies as well, from the European Union to India, to create the global economy we have now, raising up sovereignty and self-sufficiency at the sacrifice of overall economic efficiency. Such an economy is inherently conflictual as well as inefficient. Indeed Adam Smith’s economics was an important inspiration for 19th-century peace movements: a reduction in economic sovereignty was thought to create an interdependence and frequency of cross-border exchange that would tend to reduce interstate conflict. Smith would have seen today’s worldwide rise in military spending and investment as a dead weight on the economy. He would have seen today’s goal of economic self-sufficiency as hopeless and misguided. But the relationship between economic nationalism and economics is complicated. Businesses of many different kinds now find they have to negotiate both simultaneously.

The next post will look at two recent examples of how complicated, and unexpected, such negotiations can be.

What Is “Human” Intelligence?

By Dee Smith

The most common, and probably most important, type of intelligence is known as OSINT (Open Source Intelligence). It involves collecting information in the public domain and in “gray” sources that can be exploited legally but might not have been intended, by the originators of the information, for public access: subscriber-only databases with address and legal-action histories, for example; alumni websites; social media accounts; PDFs on personal websites; websites like Glass Door or RateMyProfessor; conference schedules, or materials on the dark web.

OSINT has always been important. Probably the single most significant intelligence-collection activity in World War I was acquiring, reading, and analyzing newspapers in enemy and neutral countries. After World War II, the new CIA took over the Foreign Broadcast Information Service (FBIS, pronounced “fibbis”), offering invaluable digests of radio and eventually television broadcasts around the world. The Internet transformed the OSINT world: CIA folded FBIS into a new Open Source Center in 2005, recognizing that the channels for OSINT were proliferating. OSINT has become more crucial than ever for both private intelligence agencies like SIG and for government intelligence services. It requires skill and knowledge to find and filter the most important data — “Googling” is only a start — and then know how to put the pieces together to reveal hidden patterns and indicators, the things people do not expect you to know or want you to know.

There are many other types of intelligence collection: IMINT (Imagery Intelligence), which includes airborne and space-borne imagery; ELINT (Electronic Intelligence): SIGINT (Signals Intelligence), including interception of electronic signals during transmissions; and MASINT (Measurement and Signature Intelligence), which analyzes “signatures,” such as the thermal signatures of particular weapons, or the distinctive electronic signals sent by particular technologies. At SIG, we employ any of these techniques that are needed for a specific project that can be legally deployed. SIGINT, for example, is generally not legally permitted in the private sector.

There is one important collection method I have left out, which is HUMINT, or Human Intelligence. Essentially, this means collecting information from people. Sometimes it is also called active intelligence, because it often involves interacting with people, as opposed to passive methods like OSINT or IMINT. Broadly speaking, HUMINT is another way to discover the information environment around a subject and also what is sometimes called their “pattern of life”. It is most useful in combination with OSINT and other intelligence techniques.

HUMINT practices range from discussions, interviews, and interrogations (not necessarily what that word implies in the Hollywood sense, but structured questioning of subjects of investigation using specific methods and techniques), to clandestine elicitation and observation. The latter includes everything from “secret shoppers” to private-eye-type surveillance on the ground to what is sometimes called “cloaked elicitation” — such as discovering and calling “off-sheet” references for a potential employee (that is, finding people they have worked with whom they did not volunteer as references). Surveillance intersects with HUMINT, ELINT, and other means, and is sometimes considered a separate technique, although many people categorically include it under HUMINT, as do I.

HUMINT is the oldest intelligence practice. It is becoming more important, but also more difficult. The reason it is becoming more important is that electronic information is becoming more and more sequestered — for reasons of privacy, security, and state concern for “data sovereignty” — and less and less dependable, due to data pollution.

The reader may wonder why such invasive techniques as HUMINT are used in private business contexts. The primary reason is to avoid costly or otherwise damaging mistakes. A pension plan, for example — investing, say, $100 million of other pensioners’ money into an operating company or fund — wants to know if the principals of that prospective investment have histories of deceptive business dealings, bankruptcies, litigation, or other negative indicators, as well as to understand their general operating characteristics (how they do business). HUMINT is one tool that can provide intelligence on these questions that cannot be obtained in any other way.

There are debates in the industry about what is and is not permissible, even if it is legal. For example, opinion and practice regarding intelligence on competitors can be divided into two camps: “competitive intelligence” and “competitor intelligence”. The latter uses any legal techniques to obtain information. The former places ethical guidelines around certain practices. Imagine that you happen to be sitting on a plane next to someone who works for a direct competitor. If you ask probing questions about their work without disclosing that you are working for one of their competitors, that would not be allowed under the generally accepted rules of competitive intelligence. However, those rules would generally allow some such questions, if you had disclosed your association before asking the questions.

The most confusing challenge is that laws, regulations, and policies and best practices surrounding intelligence vary widely from place to place and are constantly changing. A well-run private intelligence agency has to have one or more employees dedicated primarily to keeping up with these changes as well as other security and best-practices-related matters. Government intelligence operations, as arms of a sovereign state, are typically not so constrained, although in democratic societies there is usually legislative oversight.

HUMINT also includes espionage techniques, for example cultivating contacts (“assets” or confidential informants). These are individuals who knowingly provide information of various kinds for various reasons, including payment, personal beliefs and allegiances, blackmail, and coercion. They have inspired numberless fanciful novels and movies, but  have played important roles throughout history.

Such clandestine operations are becoming much more difficult, however, because of electronic surveillance and tracking. Recruiting and protecting assets is increasingly difficult to do. They have very limited roles in private intelligence, primarily in fraud investigations and when doing fraud prevention through deep dives on the reputations and practices of individuals and companies.

But however challenging HUMINT collection is, increased state control of data, among other factors, is fragmenting and siloing the OSINT data array, leaving HUMINT to rise once again in importance.

The US and Internationalism

A deadline has come and quietly gone for the US State Department’s mandated review of American overseas commitments. Presumably a report will be forthcoming soon. SIG’s view is that the report will be mild in substance, for two main reasons: the political force of the Trump administration’s January attack on the “globalist” agenda within the US government and in multilateral organizations has reached a limit; and the lack of pushback against that attack (by allies and foreign partners, the Democratic Party, or the American people) has revealed the lack of any effective pro-globalist or even internationalist lobby. 

Within days of taking office, the Trump administration issued several executive orders withdrawing from certain international bodies (the World Health Organization, Unesco, the UN Office of the High Commissioner for Human Rights) and putting the whole of US commitments to international organizations under review with a report from State due Aug. 4. Some of this was less dramatic than it sounded. Withdrawing from the WHO is a year-long process and funding remains through the end of the fiscal year (Sept. 30). President Trump in his first term also withdrew from the WHO but the clock ran out before it happened and President Biden reversed the order. Unesco withdrawal would not be effective until July 2026. But the White House’s intentions are crystal clear and were reflected in its fiscal-year 2026 proposal to Congress, submitted at the end of May. This is the “National Security, Department of State, and Related Programs” bill, known as the NSRP. The House Appropriations Committee’s markup of it in mid-July was consistent with the president’s priorities and reduced the previous year’s total spend by 22%.

De-funding of international organizations was consistent with the de-funding of the State Department and the elimination of the US Agency for International Development. The handling of the World Trade Organization is interestingly different. President Trump in his first term wanted to withdraw from the WTO as he believed it unfairly favored China. He embraced and escalated the Obama administration’s blocking of appointments to the WTO’s appellate body. (The Biden administration also did nothing to get the appellate-body issue out of deadlock.) But the EU initiated a workaround, the Multi-Party Interim Appeal Arbitration Arrangement (MPIA), which effectively could do the work of the old appellate body. By June 2025, when Britain joined, the MPIA included 57 WTO members (out of 166) covering 57.6% of world trade. All of the US’s traditional allies are in the MPIA, including Canada and Mexico, as is China. The most important countries staying outside the MPIA are the US, with about 15% of world trade, and, as a political actor, India. (India has long taken a special interest in global trade negotiations.) The WTO provides a valuable measure of stability and rule of law to international trade. The success of the MPIA in attracting most of the world’s biggest national economies is striking, as it is a very curious and jerry-rigged body.

The second Trump administration, rather than attacking the WTO, has sent one of its leading economic advisors, Jennifer Nordquist, to serve as one of four deputy directors-general. (She has been a counselor to the White House Council of Economic Advisors and was Trump’s appointee in his first administration as US executive director at the World Bank.) Trump has also nominated Joseph Barloon, general counsel for the US Trade Representative in his first administration and a former law partner at Skadden, Arps, as ambassador to the WTO in Geneva. In his confirmation testimony to the Senate, Barloon stressed the importance of not accepting large non-market economies, by which he means China, as equal players at the WTO.

President Trump’s tariff policies have been advanced in both his administrations without much reference to WTO rules and practices. They go against the basic idea of the WTO and before it the General Agreement on Tariffs and Trade (GATT), which began chipping away at tariff barriers in 1947. Nonetheless the WTO, as seen in the strange career of the WPIA, does have a purpose in the estimation of most of the world’s industrialized economies. IT also has a place in the struggle between the US and China. And it cannot be accused of wokeness (as was the case in White House criticism of USAID), “ideological” manipulation of science (WHO), or enmity toward Israel (as is the case with the UN Human Rights Council and other UN bodies facing defunding). Of course in one sense the WTO can certainly be described as “globalist” — theorists of neoliberal globalization often root it in economic policy more than politics — but it is not, in the Trump perspective, ideologically or culturally globalist. It is not part of the America First global culture war. And it serves a purpose for US corporations as well as for every other nation’s corporations.

The WTO (along with the International Telecommunications Union and some others) may simply be the exception that proves the rule: the US is nonetheless withdrawing from and de-funding previous long-term commitments to the institutions of multilateral diplomacy and international governance. But the leisurely pace of State’s mandated review, the compliance of the House Appropriations Committee, the uninterest of Democratic leaders, and the almost complete lack of any public or media attention to this US withdrawal suggest that the administration’s anti-globalist fervor has weakened. It might return in the fall for the UN General Assembly, an occasion Trump has used before to attack globalization and defend economic nationalism. But he might also take the moment to declare victory and seize some credit for the reform and whittling down of the UN, which has been going on for many years now but quickened after January. Either way, the anti-internationalist momentum is likely to wane after UNGA closes shop in October. On the US political scene, it is an issue that no one is motivated to fight over. This will leave the next moves in multilateral diplomacy and governance up to other actors.

The Jobs Conundrum, Part Two

The US jobs report by the Bureau of Labor Statistics for July once again proved economists wrong, or appeared to — the number of jobs added, 73,000, was far below expectations. The numbers for May and June (see SIGnal, “The Jobs Conundrum,” July 6, 2025) were revised downwards by an extraordinary 88%. President Donald Trump reacted by saying the numbers were “politically motivated” and firing the Biden-era head of the BLS, Erika McEntarfer, now temporarily replaced by her Obama-era deputy. (McEntarfer had been confirmed with strong Republican support in January 2024, including from Senator J.D. Vance.) Presidents do not often fire agency heads in quite this fashion and the dismissal dominated headlines. But investors pay attention to facts and the facts about the US job market are not very good.

There is really no reason to think that the BLS was falsifying statistics to create bad news any more than it was falsifying them when the news was good. BLS mid-month estimates are based on a somewhat small sample (560,000 business are surveyed) and as the sample gets more complete after the 12th of the month the statistics change and grow more accurate. Sometimes they go up, sometimes they go down. They don’t often stick right at the mid-month estimate, although the May-June revision was of a steepness not seen since 2021.

SIG’s analysis of July 6, for better or worse, has mostly held up. The jobs market was soft then and still is, although the symptoms in July were different than in June. But unemployment as such has been relatively low and steady. The problems are in job creation. In June, job gains were led by state and local government (overwhelmingly in education), “health care and social assistance,” and “leisure and hospitality.” The downward revisions were accounted for mainly (40%) by revised education-job figures; the other 60% was spread across industries. In July, the gains were led by health care and social assistance, retail, and leisure and hospitality. Manufacturing continued its steady decline.

The Trump administration has never aimed at creating more government jobs, so the large downward revision in public-education employment, which is paid for by taxes, should not, strictly speaking, have drawn such a severe reaction from the White House. But the headlines were negative and they drew a headline-based response. The drama masked the deeper problem that the US economy continues to lose employment for American workers “who makes things with their hands,” as Vance said at the Republican convention last year.  It is gaining jobs for those who look after the elderly and the infirm in an aging population and those who entertain and accommodate people who have money to spend. Overall, it is not growing. The pace of hiring is increasing at the slowest rate in a decade, excluding the pandemic.

 When President Trump was elected last year it was greatly on the back of increased support among working and lower-class constituencies, most distinctively black, Hispanic and Asian voters and younger voters. It was an aspirational demographic that did not think Biden policies were good for the economy that mattered to them. Republican politicians hearing from their constituencies over the summer recess will have to explain why their expectations of the economy have not been met.

The president is likely to blame Federal Reserve chairman Jerome Powell for not lowering rates. Presidents blame the Fed on a regular basis. But the pressure on Powell and others on the board is likely to ratchet up significantly. After all, Powell did say on Wednesday that the job market was sound, and two days later the BLS statistics indicated the opposite. Inflation is still relatively steady. The Fed’s dual mandate is to boost employment and fight inflation. So a rate cut seems more than likely. Powell and many others believe this will fuel inflation. If it does, Trump in the fall will have an economy with many of the problems that the Biden economy had, with an increased decline in manufacturing and very little job creation in other sectors. And the economic renaissance predicted by the administration as a result of government support for AI will not have had enough time to occur, if it occurs at all. The huge increase in Big Tech valuations based on AI expectations could very well be a bubble.

The New AI Action Plan

The Trump administration’s AI action plan got a surprisingly warm welcome this week from US tech-industry and foreign-policy experts. The plan was unusual for this administration, and for the Republican Party, in that it advocates complex government-led initiatives, requiring considerable government funds, to advance political goals in a sector that is overwhelmingly made up of private companies. This is Trumpian industrial policy, and on paper at least it is even more interventionist than Biden-era industrial policies aimed at the tech sector. With its invocation of “renaissance” it is also more optimistic about technological innovation than any administration since Bill Clinton’s: “An industrial revolution, an information revolution, and a renaissance—all at once. This is the potential that AI presents.” In announcing the plan Trump also called AI “pure genius.” SIG’s view is that the AI action plan is both inspiring and well done but that implementing it will be extremely challenging.

Some of the challenges are obvious. The Trump administration has been cutting government bureaucracies, including in tech, yet this plan has numerous policy prescriptions that require government bureaucrats to implement them. The initiatives also require funding, which it is up to Congress to give. While there is general bipartisan support for AI investment, primarily as part of the strategic confrontation with China, the new AI action plan revived the White House’s effort to prevent states from legislating on AI. A similar provision in President Trump’s signature tax bill was defeated in Congress by a crushing majority. The AI action plan’s tactic is to say the federal government will withhold funds from any state that regulates AI in a way that would be “burdensome” or “unduly restrictive to innovation” — as judged by the White House on the advice of federal officials. Congress members represent state and local constituencies, not a national one. That is where their power comes from. Many of their constituents have very grave concerns about AI and expect their representatives to do something about it. When the AI section of the tax bill was rejected by Congress, Republicans, who have been much more for states’ rights (for example on abortion) than Democrats, were overwhelmingly against the president’s proposal.  In several senses, then, the AI action plan is primed for conflict with Congress.

The action plan is also primed for conflict with allies. The AI “dominance” foreshadowed by Vice President Vance in his speech earlier this year in Paris is transformed in the action plan to advocating export of the full American-made “AI stack” to allied countries. An American hardware-and-software suite, deliberately cleansed of any technology produced by “adversary countries” (China), would then become the infrastructure for whatever applications companies in other countries might be able to build. In other words, AI infrastructure would resemble the Internet of 2003: an American platform that others could participate in subject to US rules and US intelligence surveillance, and at a tremendous competitive disadvantage to US companies. This is exactly what other countries want to avoid, especially European countries who are still at the core of the US’s alliance structure. Just as the Trump administration wants US AI to be US-made and reflect US values, Europe wants its own AI sector to do the same — just as China insists on its AI companies reflecting “socialist values.” The action plan rightly stresses that for US AI to have maximum strategic benefits it must be on open rather than closed models and build on alliances rather than going alone. But in a geopolitical environment where allies are considering a tech-driven Buy European Act — and in which US tech giants are setting up “sovereign data clouds” just to keep European customers happy — it is hard to see how exporting the US AI stack in toto (once such a stack exists) will be welcomed abroad. China’s more subtle, and affordable, approach seems more likely to succeed.

The most serious challenge to the administration’s AI action plan is the challenge that faces any government regulation of digital technology: the systems are run by private companies according to market logic, more or less. Silicon Valley’s reaction to the AI action plan has been very positive. It is, after all, a strikingly pro-business and pro-technology plan. The plan’s urging of more government and private spending on the electric grid and data centers will certainly boost industry.

But what if capacity is overbuilt, or the wrong kind? Energy expenditures for AI so far have been fantastically high. If AI is to succeed it will need more energy and more data centers. Nonetheless, AI companies also want to reduce costs, which is why a great deal of investment is going into finding less energy-intensive ways to get AI results. (Data-center companies are also striving to find ways to lower their energy requirements.) The government could end up financing with taxpayer money an infrastructure that won’t be what is needed in five or ten years. Investors should be cautious of extrapolating investment opportunities from the areas that the AI action bill is targeting. The obstacles to the plan are many, and the record of government-led innovation policies is decidedly mixed.

The Jobs Conundrum

The US jobs numbers last week were chaotic, to say the least. The 0.1% drop in unemployment was yet another instance in which economists’ predictions were wrong. It is getting to be a habit, and the Donald Trump administration is reaping the political gains. The last few weeks have seen more and more articles attempting to explain why the predicted catastrophe after the Liberation Day tariffs announcement has not materialized. SIG’s view is that, now that the administration’s giant tax-and-spending bill has passed and members of Congress return to their constituencies for the summer recess, the real political work will concern jobs. So it is worth looking deeper into the new numbers.

Jobs in June increased by 147,000. However, the workforce itself shrank by more than that: The number of people characterized by the Bureau of Labor Statistics as “not in the labor force,” and therefore not counted as “unemployed,” grew by 490,000. The unemployment rate went down not just because jobs were added but also because the size of the workforce decreased. 

In sectoral terms, the biggest job adds (73,000) were in government. The biggest source of those jobs was growth in the public education sector, which is mainly K-12 schools. Of the 47,000 state-government jobs gained, 40,000 were in education. Of the 33,000 jobs added in local government, 23,000 were in education. Federal government employment was down by 7,000 for June and has dropped by 69,000 since the beginning of the Trump administration, in line with the president’s commitment to shrink government.

The increase in state and local education jobs should not be a surprise. The 2008 recession hit those sectors very hard. They recovered at a much slower rate than the private sector. When Covid hit, their subsequent recovery, compared to that of the private sector, was even worse. Massive federal aid got schools through the pandemic but it was always going to dry up and eventually did. States, looking to the longer term, realized they needed to increase spending. Populous states like Texas, California, and New York have recently broken records for education spending. Much of it goes into teacher salaries, which have been increasing in response to a chronic teacher shortage. (Credentialing in many states has also become much more lenient to attract more teachers.) In short, the state and local public education sector was overdue for a boost, got it, and jobs have been created.

The other major sectors driving job gains in June were “health care and social assistance” (58,600) and “leisure and hospitality” (20,000).  “Social assistance,” in the world of the Bureau of Labor Statistics, is not governmental but includes services like child care, vocational rehabilitation for the disabled, community food banks, and emergency services. The remaining major gains were in construction (15,000) and transportation/warehousing (7,500).

Overall, the private sector did not do as well as the public sector. Private payrolls were up by 74,000, the weakest growth since last October. An ADP Research study earlier in the week identified numerous indicators of weakening in the private labor market. Job losses in June were concentrated in mining and logging (down 2,000), wholesale trade (down 6,600), manufacturing (7,000), and professional and business services (7,000).

The problem, of course, is that the Trump administration’s goal has been to reduce government and favor the private sector, while the reality of the labor market so far is going in the opposite direction. Meanwhile, CEOs were spreading the word that AI would eliminate jobs on a grand scale. Ford’s Jim Farley thought that AI would “replace literally half of all white-collar workers in the U.S.” Of course, AI could also eliminate jobs in the public sector, including education. But the impetus for the current, very high levels of investment in AI is to increase productivity by making private-sector workers more efficient, not by hiring more of them. Overall, then, AI could well shift the balance of employment in the US economy further toward government.

It is possible that reducing taxes, as the new bill does, on upper-income groups could increase consumer demand, probably in the leisure category, and even free up capital for productive investment. It is also possible that a tariff program could result in increased investment in American manufacturing. However, neither of those results is going to be quick. In the meantime, Congress members will meet their constituencies as private-sector employment weakens and the federal government’s willingness or ability (given extraordinary debt levels) to solve problems, much less provide jobs, is weakening as well. Whether President Trump’s economics will work out in the end might not matter, because the end will be after the midterms, which in political terms could be too late.

Déjà vu All Over Again

By Dee Smith

With his entry into the Israel-Iran war, Donald Trump seems to have gone over to neoconservatism, even invoking the goal of regime change, an old neocon favorite. It remains to be seen at this writing what will happen to the cease-fire he has imposed, but the interesting thing from a policy standpoint is how much this is both in accordance with — and violates — legacy patterns of US foreign policy.

Many Iranians outside Iran are pleased at Trump’s decision, even as they are desperately concerned about their families who remain there. Anne Applebaum cites an article from an anonymous Iranian source published last weekend in Persuasion:

knowing that the men who’ve held us hostage for forty-six years, who’ve ransacked our country, raped and killed our daughters and executed our men for asking for their basic human rights, are finally getting what they deserve—that brings me peace.

That view of the recent American action comes very close a classic element of the liberal international order in its later form: the “Responsibility to Protect” or R2P. Under this doctrine, the international community has a responsibility to intervene inside states that do not protect their populations from atrocities such as war crimes or genocide.

All of this is to say — with apologies to Mark Twain — that reports of the death of neoconservatism and of the liberal international order have been greatly exaggerated. They are gone, but also not gone. They are there, but so radically mutating they are no longer themselves.

That is characteristic of our entire world today. We are living in a time in which ideologies are both more important than ever, and the varieties of thinking and expressing ideologies are more confused and at odds with one another than ever, and in which many people are not sure whether they actually believe what they claim to believe … or want to believe.

This multi-directional confusion is characteristic of most elements of global society and culture: Multiple ideas, trends, and styles from the past are reinvoked and mixed together, often haphazardly. This extends to culture, both popular and “elevated.” It has been said that there is no direction in fashion today: you can wear whatever you want. This is also true in the visual arts. And “serious” or classical music currently includes almost any style—you can compose like Bach, Schumann, Ravel, Prokofiev, Stockhausen, or Glass and be taken seriously, and you can even mix those up in the same piece and get away with it. Beyond that, the lines dividing classical and popular music are dissolving. And popular music has 1001 idioms, genres, and styles, not to mention the almost uncountable “mash-ups.” Really, anything goes.

That is also true in philosophy and even in science, as new and resuscitated interpretations of new and old discoveries create visions and theories that are directly at odds with one another — in areas ranging from particle physics to vaccination science to the study of the nature of consciousness (which is of vital interest to AI) — all claiming to be supported by evidence and each taken seriously by knowledgeable people. It is certainly true in politics, ethics, behavior, and mores. There is simply no overall direction, and certainly no center. That is always true to a degree, but it is much, much more pronounced now.

It is all of a piece only by virtue of being, as Elvis Presley said, “all shook up.”

Some see this as a form of decadence. But it also represents a flailing about to try to find something that works … anything … in the radically divergent situations we face. We seem only to know how to look inside the old boxes we have, and they no longer contain anything fit for purpose. We are all, fearfully, practicing the politics of nostalgia. But the past does not work today, our current systems and ideas do not work, and we don’t see where a future lies that might work. We find ourselves at sea with no life-raft we can grab onto.

Sometimes this is called a “horizon problem” — meaning that the solution is over a horizon beyond which we cannot see from our present vantage point. During the energy crisis of 1979, President Jimmy Carter exaggerated when said we were in a civilizational crisis of confidence. That is no exaggeration today.

In Hemingway’s novel The Sun Also Rises, Mike Campbell answers the question of how he went bankrupt: “Two ways: Gradually, then suddenly.” This is how major change often happens. We would be wise to recall how quickly the Soviet Union fell in December 1991. It had seemed robust, threatening, and indeed almost impervious less than 5 years earlier, and looked reasonably secure even a few months before. But the decay had in fact been eating away at the system for decades.

The old Chinese curse, now repeated with tiresome regularity because it is so apropos to our day, says “may you live in interesting times.” We are indeed there.

Where will our situation lead? And how do we navigate it? These are among the most urgent questions for all of us today, and they extend across all the domains of life. If you have little idea where the future is heading, and you can’t rely on the elements you could in the past, then how do you prepare for it? How, for example, do you ensure the well-being of your family? How does an investor manage, let along hedge, a portfolio in circumstances like this? Aside from intensive vigilance, the ability and willingness to move quickly, and hope, it is very hard to answer these questions.

Writing in another tumultuous time at the end of the 17th century, the English poet John Dryden closed his Secular Masque with:

All, all of a piece throughout;

Thy chase had a beast in view;

Thy wars brought nothing about;

Thy lovers were all untrue.

'Tis well an old age is out,

And time to begin a new.

Investment and Race

Although US President Donald Trump once took some credit for popularizing Juneteenth (June 19), an official national holiday marking the freedom of enslaved Americans, celebrations this week were muted and in some cases canceled. Trump himself did not mention the holiday. Some US businesses also stepped back from it, although not with the speed with which they have moved away from DEI (diversity, equity, and inclusion) programs, which have been explicitly targeted by the Trump administration (see Signal, “The Rollback,” Feb. 28, 2025). It is not hard to tie this deprecation of Juneteenth to the argument that a form of white nationalism is backed by the White House. SIG’s view, however, is that the reality is more complicated, more politically opportunistic, and of more significance to American business.

The racial politics of the current moment seem to pivot around class and social mobility as much as physical appearance. It should be recalled that DEI efforts were losing popularity before President Trump took office, notably among nonwhite Americans. In the brief period from February 2023 to October 2024 (before Trump’s victory), according to Pew Research, Asian-American support for DEI programs at work went from 72% to 57%, while those with a neutral view rose from 18% to 28%, meaning that those Asian Americans who either opposed DEI or preferred not to venture an opinion had reached 43%. Unfortunately, Pew’s summary of the 2024 research did not highlight the same figures for Hispanic Americans, but in its February 2023 survey Hispanic support for DEI had been significantly weaker than Asian support. Given that the 2024 survey also found a broad decline across groups in support for DEI, it does seem unlikely that Hispanic support for it would have gone up while Asian support plummeted.

Dwindling non-white support for DEI might be related to views on the systemic or otherwise nature of racism in American society. The American Communities Project researches American views on a variety of topics based on a 15-part typology of communities, from Aging Farmlands (91% white, strongly Republican, with low unemployment and low education) to Hispanic Centers (more than 50% Hispanic, about evenly split between the two political parties, with low voter turnout and twice the national average of people lacking health insurance) to College Towns (younger, 78% white, 6% black, mildly Democratic) to the African American South (more than 40% black, 3% Hispanic, strongly but not overwhelmingly Democratic). The ACP also includes communities like Mormons (“LDS Enclaves”), Native American Lands, and Military Posts that rarely surface in statistical assessments of the national community. One can find fault with any of these categories but they have the virtue of complicating the straitjacket of race, income, and education.

One ACP question has been to ask whether you agree or disagree with the statement, “Racism is built into the American economy, government, and educational system.” Just 48% in Hispanic Centers agreed with that statement, a tie with Native American Lands. The lowest affirmative share was in Aging Farmlands (38%), the highest in the African American South and Big Cities (both 58%), College Towns (55%), Urban Suburbs (54%), and Military Posts (52%). The perception of systemic racism was highest in areas with large black populations — the US military is nearly twice as black as the national population — and large shares of better-off and better-educated Americans, the last two categories being disproportionately white although also disproportionately Asian. (Asian households are better educated and wealthier than any other racial or ethnic group in the US.) Unfortunately the ACP does not have an Asian community among the 15.

One can reach any number of conclusions from these surveys, including that white Americans do perceive systemic racism, and more so as they climb the social ladder — although there is also a clear partisan divide on how significant it is. The relationship to social mobility does seem relatively clear. In the ACP studies, Hispanic Centers were the community least likely (37%) to feel that “it is increasingly hard for someone like me to get ahead in America” and also the least likely of the 15 communities to agree (61%) that the US is in decline. In both cases, the community at the opposite end of the optimism spectrum was Evangelical Hubs (90% white, with income and education levels below the national averages, poor health care, and low voter turnout). This is the community that least sees itself as upwardly mobile.

In presidential races, the Republican coalition has, of course, become steadily more Asian, Hispanic, and black. (Asian voters in 2024 were 9% of the Republican coalition.) The Democratic candidates’ Asian support dropped from 74% to 61% from 2012 to 2024 nationally and 70% to 57% in 2024 battleground states. About the same pattern held nationally and in the 2024 battleground states for black and Hispanic voters. In a highly partisan political landscape, nonwhite voters, by leaving the Democratic party, have become a crucial swing vote.

If social mobility is a key factor, then these voting patterns might not be much affected by what happens with either DEI or Juneteenth. Republican politicians have consistently stressed that the United States is a land of opportunity more than their Democratic counterparts have. Hispanics and Asians disproportionately reach for that opportunity, far more than their white counterparts. The number of Hispanic-owned businesses grew 44% from 2018 to 2023 while the number of white-owned businesses slightly declined. Meanwhile, Asians, despite their lower numbers, owned more US businesses than Hispanics or African Americans, and had the largest estimated receipts ($1.2 trillion in 2022, the most recent year for which the census has public data).

At the same time, non-white businesses often do find it harder to attract investment than their white counterparts. A Stanford study argued that if “Latino-owned businesses had the same average revenue as white-owned businesses, it would add $1.1 trillion to the U.S. economy.” In short, there is an under-exploited investment opportunity in the non-white parts of the US economy. The Republican party, at times despite itself, discovered this opportunity in political terms. Investors could discover it in business terms as well.

Sputnik, AI, and the Nature of Victory

The US foreign-policy community has been gathering itself around the goal of winning the AI race against China. The problem is that defining “winning” is not at all easy. If winning consists of US companies, in cooperation with the US government, enjoying a monopoly on the best AI technology for some extended period — which does seem to be what is expected — SIG’s view is that winning is nearly impossible. The only way the US could come close is by sharing technology within some type of alliance. But that would entail non-American companies within the alliance having revenues and profits of their own. The US and US companies cannot “win” this alone.

As SIGnal has emphasized before, digital technology has been taking the world’s defense sectors by surprise for some 30 years. Whether it is low-earth-orbit satellite swarms, drones or navigational improvements, technology developed for one use becomes a military must-have for security uses. Proliferation is built into such a process. Military hardware needs software; software lends itself to proliferation, theft, imitation, and improvement. Artificial-intelligence software is no different.

Containment of American AI within US boundaries goes against the nature of the 21st-century technology industry. Most innovation comes from the private sector, whose ability to maximize profit and minimize costs depends on a global marketplace for products and labor. The defense sector is not the private sector but a curious public-private blend. American defense companies do sell a lot to overseas customers, but the customer whose needs shape the greater part of production is the US government. Proliferation of American defense contractors’ products, including software and data, is carefully regulated. Workers need to get government clearances. Contracts have to conform to official bureaucratic standards. There is plenty of red tape. The payoff for defense companies has been the security of long-term contracts and a relatively high level of protection from competition — notably from foreign competition.  The main downside is that profits from such quasi-public business, in the absence of corruption and favoritism, are limited by the obligation of Congress to ensure that government is not over-spending. Innovation within the defense sector thus seems to come up against natural limits. That is not the case in the private sector, which is why so much military innovation comes from outside the defense sector and commonly occurs for reasons that have nothing to do with defense.

This is abundantly true of AI innovation. If the US government wanted to make AI innovation henceforth a government-controlled process, it would amount to turning AI companies into defense companies — which would remove much of their incentive for innovation, defeating the purpose of the exercise. It would not be much of a victory in the race for AI dominance.

By contrast, operating with trusted partner countries would have some of the advantages of globalization — multiple labor and consumer markets to choose from — while preserving the goal of excluding China and other antagonists. Of course, forming some sort of digital alliance structure has been a US goal since the middle of the first Trump administration. Results have been mixed. There has been a contradiction at their core: The US wants partners but insists on being the dominant one. That kind of dominance cannot work in the case of private-sector-led technology innovation.

Fortunately US tech companies, although in their own ways just as hungry for dominance as the US government, have become accustomed in the last decade to competing in markets with foreign companies and not always winning. They have invested huge amounts in overseas markets: to pay suppliers, establish their own production, or attract customers but also to take advantage of the huge and growing innovation ecology that exists outside the United States. And foreign governments and private competitors have gotten used to them as well. The degree to which US tech companies can be profitably active in non-American markets without dominating them is an example of a type of loose alliance. The struggle with China is an important shaping factor but it does not distort everything it touches.

Learning from the success of this private-sector-led approach to the US-China tech contest could lead to a public-sector variant that could help control AI proliferation while accepting that winning the AI race with China, in the winner-take-all sense, cannot be done. A different type of victory might be possible though. After all, when the US, following the Soviets’ shocking Sputnik launch in 1957, went all out to win “the space race” against the USSR, it did not so much prevail as demonstrate its ability to continue to innovate at a pace the Soviet Union could not match. The result, in 1975, was American and Soviet astronauts living together in the International Space Station (as Russians and Americans still do) and the growth of an international scientific subculture that played an important role in bringing the Soviet experiment in oppressive governance to a close.   

AI is Just a Tool

By Dee Smith

There are many problems with AI, some of which I will explore in future posts. But the most basic problem is that, as we have all experienced, computers break.

For computers to continue to run requires multiple people who are capable of fixing them, available all the time.

Remembering this, is it a good idea to give more aspects of our lives over to “intelligent” systems so undependable? The things we rely on to obtain the food we eat, the water we drink, and to make, manage, and spend our money? The systems we use to conduct business, to take care of our health, our critical infrastructure, and our national security?

We already do, of course, but the teams are in place to fix them when they malfunction.

The unreliability of computers is not a passing problem. Computer systems, considered as a whole, are scarcely more reliable now than they were 30 years ago. Hardware is somewhat more reliable, but software is increasingly complex, increasingly unpredictable (complex systems are inherently more unpredictable), and increasingly unreliable.

Relying on AI systems makes us vulnerable in several critical ways. First is their exposure to attack. To cite just one example: discovery of undetected flaws leading to “zero-day exploits” — criminal or terrorist attacks exploiting those flaws.

Second are the continuing “hallucinations” AI experiences, where it gives entirely wrong, and sometimes nonsensical, information, often for reasons computer scientists do not understand. What if it does this while managing an element of critical infrastructure and the problem is “inside” the system, where it cannot easily be detected or fixed?

Third, all computer systems are subject to severe malfunctions due to rare, but potentially catastrophic, single-event upsets (SEUs) or single-event errors (SEEs) caused by cosmic rays bombarding the earth.

Fourth is AI’s requirement for a vast and ever-increasing level of electrical power for operation.

The reason computer systems are so ubiquitous is, of course, money. This works in two ways: the money being made and the money being saved by replacing human laborers. From a social standpoint, the latter may well be a pyrrhic victory: displacing millions of people from their jobs creates a huge social cost, in real money.

Are computer systems, in general, more efficient than humans? There is no evidence that they are. Computers are able to crunch numbers within mathematical operations much faster than humans — although that is discounting the enormous calculational power of the brain of a human, let alone the brain of a bird or even an ant, doing everyday things. There is no real understanding of how these biological intelligent systems work. Computer systems seem more efficient only because of the extremely limited scope within which they are operating.

Consider two alternatives, at opposite ends of the spectrum. One is that computer systems, as they become more and more complex, also become more and more fragile. When a system related to food production, or finance, or national security breaks catastrophically somewhere, the failure cascades through the system.

What if systems could be made substantially more reliable? Perhaps some unforeseen breakthrough will dramatically improve their dependability. Then suppose, as some people insist (incorrectly to my thinking), that AI can and will progress to Artificial General Intelligence (AGI). Imagine that this results in a superhuman intelligence. It could be one that emerges at a critical-mass-type point, almost in an instant (this is called the “singularity” by AGI aficionados). Were this to happen, we have no way of knowing whether such an entity would be benign, neutral, or malicious to humans.

But if such an AGI is trained on the sum total of human knowledge and expression, then that AGI is going to be loaded with all the bad along with the good. Do we really want to live in a world governed by transcendently intelligent and powerful machines trained on the behavior of what are essentially clever, volatile, often enraged chimpanzees? (We share 98.4 percent of our DNA with chimps.) Watching any war movie, or really most any movie, would suggest we might not.

And if the AGI was not trained on human knowledge and culture, what would it be trained on?

Biological systems have had about 4 billion years of evolution on this planet to become reliably dependable in operation. They are generally able, as living systems, to survive constant bombardment by radiation from space, extreme temperatures, rapid changes in climate, changes in atmospheric chemistry — and most important, to survive without someone standing by to repair or reboot them. This is a property known as homeostasis. Life has evolved naturally over an immense period of time through adaptation: trial and error.

One the other hand, our computer systems — based on silicon, not carbon — do have a very fallible creator: us. And they have been around about 70 years, or about two-trillionths as long as biological systems.

The belief in the inevitable ascendence of AGI is an article of faith for many involved in the computer industry and for others outside the industry who uncritically accept this “techno-religious” belief system. In its more virulent forms, it is teleological: a burning faith in an inevitable direction of history, in which AGIs are the successors to humanity. And in which the sacred duty of computer scientists is to bring about the birth of this supremely intelligent “life” form.

If I had told you 30 years ago that you would have in your pocket a self-powered device the size of a pack of cards that could tell you how to drive, turn by turn, from your current address to a building in a city 1000 miles away, you would probably have thought that it must be intelligent to be able to do this.

Do you think of your smart phone that way today? My estimation is that this is how we will think of AI in 30 years: a useful, not entirely dependable tool. Nothing more.

The Rest Is Software

US President Donald Trump’s visit to the Persian Gulf brought the region back into the American camp on artificial intelligence. The White House’s cancellation of the Biden administration’s AI-diffusion regulation was well timed: the message of both the trip and the cancellation was that this administration will not draw distinctions, as its predecessor did, in advancing what Commerce Secretary Howard Lutnick called “Trump’s vision for US AI dominance.” The US is, in a sense, trying to de-regulate AI politically. Washington’s move to block AI regulation by US states is also part of this. In SIG’s view, whether such de-regulation will achieve the goal of AI dominance is a different question.

As with crypto, the current administration’s US’s bias with AI is to let the chips fall where they may, so to speak, while also aggressively using the power of the state — as investor, as enforcer, as customer — to secure American advantages. Trump’s experiences of being deplatformed by Big Tech must have shaped his views: bitterness over the suppression of conservative speech, alongside the supposed promotion of anti-conservative speech, has been a dominant note since his second inauguration. In this scenario, technology and tech innovation were shown not to be autonomous forces, proceeding according to their own logic, perhaps capable of being channeled but not of being controlled. Rather they were the effects of companies run by individuals who could be influenced. That was well within the comfort zone of a lifelong businessman. (See the tariff retaliation against Apple for relocating its China production in India rather than the US.) It is a pro-market perspective in a way, but with the market understood as a place for ruthless competition among a small number of unconstrained players rather than as a mechanism for maximizing the efficient distribution of capital and labor.

Similarly, the role of the state in this perspective is to personify the nation in unconstrained and ruthless competition among states for, in U.S. Commerce Secretary Lutnick’s term, “dominance.” President Trump’s appetite for military confrontation in his first term was low, and that seems to be carrying into his second term. His appetite for economic confrontation was relatively high in term one and has gone to a new level in term two. The tools of the state are the weapons he has for such confrontation. They are directed toward securing dominance. Trump is personifying the powerful idea of economic nationalism.

The difficulty, with regard to “US AI dominance,” is that the AI sector is not like other industrial or commercial sectors. The preferred means for dominating AI has been the control of hardware, as in export controls on leading-edge chips or chip-design lithography equipment. Biden’s AI-diffusion regulations, like his CHIPS Act and much else, were about the geopolitics of hardware distribution. President Trump has opened that floodgate. But once the hardware starts flowing and the data centers are built the rest is software, the diffusion of which is extremely hard to control. Software can be stolen or replicated; more important, it can be developed independently, as DeepSeek has shown. The supply of chips and what is necessary to manufacture them can be choked off, up to a point. The supply of engineers and software-engineering skills really cannot. It will be diffused regardless of what the US or China want.

Among other things, this means US AI dominance depends on the strength and autonomy of US universities, the freedom to innovate in the US tech sector independent of political agendas, the smooth functioning of open global markets, sensible market pricing of resource inputs, the reduction of obstacles to the cross-border movement of labor … all of which run contrary to current US policy.

The Gulf states are investing in US AI infrastructure on the way to building their own systems, which will have the capacity to become independent of US systems (see SIGnal, “The America Stack,” Feb. 5, 2025). The emiratis are not happily volunteering to be hostages to US AI dominance. They are seizing the opportunity to gain access to the best technology that will enable them to maximize their own sovereignty while positioning themselves to be a sort of port for the storage, manipulation, and distribution of data, just as Dubai’s port operates with coffee, tea, and so much else.

The pattern is similar elsewhere, although no one can direct capital with quite the speed, and in quite the volume, that the Gulf states bring to bear. Malaysia hesitated for a moment at new deals for Chinese technology when Washington threatened retaliation against states using Huawei’s latest AI chips, but in the end, the shape of AI is not going to be determined by hardware. The massive computing power required to participate in the search for the grail of Artificial General Intelligence (AGI) is indeed a hardware question, but for sub-AGI artificial intelligence, which might well prove to be most if not all of AI, hardware is only one factor. The rest is software. And US dominance of it is unlikely to be secured using the current means.

The Defense Industry's New Math

Global military spending in 2024 hit a record that will be broken in 2025. Much of the growth comes from the US (which just announced a goal of a $1 trillion defense budget) and its adversaries, but an important part is from US allies that feel they can no longer rely on US security guarantees. For that reason, they seek to build their own defense industrial bases rather than simply buy more American military products. There are opportunities for investors in this global proliferation of military production financed by government budgets, although the peculiarities of military industries make it more important than usual to have the right expertise. Defense-sector exchange-traded funds (ETFs) have, not surprisingly, boomed: the VanEck Defense UCITS Took in $1 billion in March 2025 alone.

In 2024 global military spending hit $2,718 billion, a 9.4% increase over 2023 and the steepest year-on-year rise since the end of the Cold War. The main drivers were the conflicts in Ukraine and Gaza. Israel’s spending increased 65%, to $46.5 billion, which represented 8.78% of GDP, the second highest ratio after Ukraine — which spent nearly 35% of GDP on its military. Russia spent $149 billion, up 28% from 2023 and representing 7.1% of GDP and 19% of total government spending. German spending surged to $88.5 billion, the fourth largest total in the world after the US, China, and Russia, and just ahead of India at $86.1 billion.

All of these numbers are likely to grow in 2025 and into 2026, except perhaps in Ukraine, which might not be able to get above 35% of GDP. But the Ukraine example illustrates a different and more interesting dynamic. According to one report by a former Ukrainian official, Ukraine’s domestic defense sector has grown from $1 billion to $35 billion in just three years. It now produces about a third of Ukraine’s weapons and ammunition, and nearly all of its drones. That is not nearly enough to protect itself against the Russian army, but it is enough to ease some of the country’s dependence on the US

Similarly, Germany in particular, but also France and the European Union, have entered a new era in terms of domestic military production. Germany’s head of state, Friedrich Merz, won a parliamentary vote in March to not apply Germany’s “debt brake” policy to the defense sector. Merz also appealed to the EU to exempt defense production from its own spending rules. (EU member states have their own military budgets but the EU has rules on public debt.) Sixteen of the Union’s 27 members are seeking exemptions from the EU rules so they can increase their defense spending.

What is driving all this spending is principally the desire to, as Merz puts it, “achieve independence from the USA,” which under President Trump he sees as “largely indifferent to the fate of Europe.” EU Commission President Ursula von der Leyen, herself a former German defense minister, declared, “We are in an era of rearmament,” one that requires Europeans to construct their own defense as part of what France’s President Macron refers to as “strategic autonomy” from the US. The EU hopes that new bloc-wide procurement policies will strengthen European defense production at the cost of American materiel.

There is irony in the fact that European NATO members in recent years have spent more, not less, on weaponry produced in the US: from 52% of spending in 2015-19 to 64% in 2020-24. But that very dependence is why traditional US allies are so focused on independence from the US now that the US has abandoned its traditional approach to alliances. It is not just Europe. South Korea has been trying to replace US purchases with its own production for several years, including so that it might export weapons. Japan also seeks to increase domestic military industries. Israel is striving for self-sufficiency in bomb production. Even Australia has been trying to be more militarily independent, although in practice Australian defense production, current and projected, is commonly done jointly with US defense primes.

The proliferation of defense production in a globalized world can lead to curiosities, such as the battle between a Chinese state-controlled defense company and an Australian to buy a troubled Brazilian manufacturer. That in turn points to both the internationalization of military production and the question of what gets done with the products. US military industries and the US military itself have always advanced together. Foreign military sales were integrated into a much larger public-private strategy that was rooted in political alliances. The point was not to sell to enemies. The proliferation of military-industrial production in the past three years suggests a future in which weapons will be available from many sellers, including NATO members, with little or no reference to US policy guidance.

In short, the desire for autonomy from the US is driving a global surge in weapons production that will in turn lead to weapons proliferation on an unprecedented scale. Unless there is a significant increase in war, there will be an increase in excess production. Excess production will need to be off-loaded somewhere. This is the peculiarity of defense production. If you are not simply stockpiling — which is a dead weight on the economy — then you are proliferating. Weaponry ETFs in this scenario would have to be a short-term play. The longer-term returns will be in companies that aim not just at domestic production but at export.

Can AI Make a Country Great Again?

Much recent commentary on artificial intelligence (AI) has focused on the prospect of a company or a country winning a race for artificial general intelligence (AGI) or more-than-human “superintelligence.” However, that goal, which seems rather more religious than technological, is both elusive and, should it ever be achieved, fragile (see SIGnal, “Mutual Assured Malfunction,” March 13, 2025). Investors are focusing instead on “little tech” and firm-level or industry-level AI that uses specific data sets to engineer specific productivity gains. In SIG’s view, this more modest course seems both economically more promising and politically much more sustainable. But it definitely does have risks of its own.

The appeal of “little tech” AI is partly that it leaves to one side the many serious questions about data privacy and other more existential matters that are posed by AGI. Smaller AI systems can run on the contained, often proprietary data sets involved in industrial processes, especially in manufacturing. The goal is not to replicate the human brain but to make industrial processes more efficient, raising productivity. It is a type of automation, using new technology yet still familiar enough from the history of industrial production.

With little-tech AI, startups can focus on specific problems whose solutions will provide a payoff in the relatively short term. In other words, AI would be monetizable. This has an obvious appeal not just to startup investors but also to industrial incumbents whose processes would be improved and whose productivity would be raised in competition with their rivals. Startups are not alone in this sphere. The German giant Siemens, for example, has put industrial AI at the core of its offering.

Politically, this approach to AI is much more appealing to most governments, only a few of which (the US, China) can have much hope of achieving global dominance by winning a race for AGI, at which point they might well regret getting what they wished for. Leaving aside the large question of AI data-center electricity demands, it offers the attractive prospect of raising productivity while reducing carbon use — because your factory in Texas, enhanced by AI, will no longer have to source so many of its components from East Asia, with all the carbon-using transport that entails. The little-AI approach also means states would not have to expose their citizens’ data to foreign tech multinationals, possibly based in hostile or overweening states, in order to participate in the later 21st century. That would be a gain for state sovereignty; and given that so many of the tensions around globalization have had to do with the way it threatens sovereignty and the democratic (or otherwise) accountability of governments to citizens, the little-AI approach could conceivably enhance global stability and the prospects for peace. Little AI, by improving productivity within a given national domestic workforce, could help states that are facing demographic stagnation — which is pretty much all industrialized states and many less-industrialized ones — to nonetheless grow on the basis of domestic labor (see SIGnal, “AI Family Values,” May 3, 2024). As Marc Andreessen and Ben Horowitz wrote in July 2024, “little tech” could make it possible “to reconstruct the American manufacturing sector around automation and AI, reshoring entire industries and creating millions of new middle class jobs” while also having green benefits. Technology could, in effect, provide the “labor” that would solve the biggest challenge facing President Trump’s vision of a more self-sufficient US: the lack of workers operating at a sufficient level of productivity (see SIGnal, “Trade Wars and US Labor,” April 11 2025).

Less carbon use, stabilization of the international sovereign-state system, a growing middle class, a renewal of rich-world domestic manufacturing but with higher wages and less grim manual work…What could possibly go wrong?

AI-enhanced production aimed at reshoring manufacturing to high-wage economies would square the circle of productivity growth and de-globalization. It would revive the pre-1975 global industrial status quo with the crucial addition of China (but not so much India or Southeast Asia). If you have the good fortune to live and work in a benefitting state, this would be a positive outcome. It could, however, also fuel techno-nationalism in the rich world (plus China) and make growth outside the AI-enhanced nations highly problematic. One key issue raised by the US-China struggle — a protected US market deprives non-American producers of consumers, while a protected Chinese economy, likewise deprived, dumps its production for the pre-tariffs US market onto the rest of the world’s economies — would be gravely worsened as the world’s two largest economies reduce their dependence on the rest of the world for both supply and demand.

AI-enhanced de-globalization could, in short, reverse the global redistribution of labor productivity that led to the greatest poverty reduction in human history. In theory, the gains from little AI could be more equally distributed. After all, the AI enhancements that would lift an underemployed person in Oklahoma or eastern Germany into the middle class of his or her domestic economy could do the same for a person in Nigeria or Thailand. But that outcome is not the goal for the people, states, and companies that are driving the growth in AI monetization. Their goal is nearly the opposite. For investors, the greatest gains will come from identifying companies and sectors best positioned to gain from AI-enhanced de-globalization.

A View From Europe

By Dee Smith

I recently returned from 6 weeks in Europe — Austria, Italy, Switzerland, and the United Kingdom. My trip coincided with the build-up to President Trump’s tariff announcement on “Liberation Day” and the reactions that followed it. The most interesting element of the trip was the evolution, or devolution, in views of the United States.

At the end of February, the attitude I first encountered was a mix of perplexity about the changes in the US and sadness that they were occurring. Even people who were disposed to dislike the US discovered that they had nonetheless kept within themselves a kind of hope based on belief in America and its distinctive experiment in democracy and freedom. Even with all its flaws the US seemed, so they said, to represent a possibility that humans might be better than we fear we are. One remark I heard summarized the attitude: “It seems that the lights have gone off in the shining city on the hill.” It was a sense of tragedy, almost of grief. Now, some said, they see that the U.S. is “just another country.”

But as the tariffs were imposed, this recessional mood changed. The attitude of heartache began palpably to transform into fear, and into anger. It was not as if the winds of change had not been blowing, and they knew that. There had, for example, been warning signs over the years that the US was pulling back militarily from Europe. And the Europeans were certainly aware of the fractures in US political structures, as in their own.

However, the tariffs were something different. The universality of them, the suddenness, and the way they were applied — with a chart apparently developed with the help of ChatGPT based on an arbitrary calculation — was disorienting, then frightening, and finally angering.

When the White House suddenly, and apparently temporarily, backed away from the tariffs soon after they were announced, it simply added confusion to the fear and anger around the entire issue and in many minds further undermined the stability of the US governance and financial system. “I really don’t know what to think” was a comment I heard more than once, sometimes followed by “but I’m angry.”

Although they may not have known what to think, they did know how they felt. People have cancelled trips to the US and taken other personally expensive measures, so off-putting have they found the developments.

There was still, amid the feelings of loss and anger, the wish that the old US would come back to something like what it was and an ember of hope that it might. But the dominant note was fear, driven by US actions but not only about them. People fear the Ukraine war continuing while they also fear it being settled: they fear Russia’s intentions once it is loosed from the constraints of fighting in Ukraine. They fear war in other hot spots: Iran, Taiwan, the Koreas. They fear the non-sustainability of their economic situation. They fear having to dial back their social support systems to increase their military budgets. They fear they will be outcompeted by other areas of the world. They fear for their supply chains. They fear more and larger waves of immigration from the Middle East and Africa, particularly if war escalates in the Middle East. They fear for the social and political stability of their countries. They fear unfair competition from China, and they fear what kinds of collusion China and Russia may be up to. And, as a constant, chronic theme, many fear the impact of climate change.

Europe is, like the rest of the world, in the midst of extraordinarily large transformations with unknown trajectories. The changes seem to have come on very suddenly, although of course they have not: there have been harbingers for years. The causes of the changes also elude many. That of course is for history to judge, but I did not find a single person who disagreed with the idea that fundamentally, beneath it all, lie broken promises. I have written about this previously, and will not go into any detail here, but people see that, although they played by the rules, the implied promises they believe were made by the political and economic system — that their children’s lives would be better than theirs, for example — have been irreparably broken.

Most surprising to me, I heard more than a few people in Europe, including investors and businesspeople, say quite seriously that they thought we were at the point of a very big change. And a number said the period between the end of the old and the beginning of the (unknown) new will be very tumultuous and dangerous.

Europe was the birthplace of the Enlightenment, and it was on Enlightenment ideas and ideals that not only the American system but also every system in Europe, and now far beyond, were based. Holding that the world is fundamentally comprehensible, the Enlightenment posited that humans make decisions rationally, in their own best interests, and thus that society can be rationally organized in a purposeful and predictable way. Not just democracy and capitalism, but socialism, Marxism, and communism are all based on different views of how to apply European Enlightenment ideas about organizing society rationally, purposefully, and predictably. Unfortunately, this rationalism simply does not seem to be an accurate take: we make our decisions emotionally.

So I found I was asking myself many times on this trip: if this whole superstructure of concepts does not in the end work — if it cannot work because of the nature of the drivers of human behavior — well . . . then what? That is the largely unspoken fear lying underneath all the other fears, perhaps not just in Europe.

Reversion to Mean

By Dee Smith

About a decade ago, we entered into a period of escalating social and political chaos, increasingly “hot” geopolitical conflict, and growing economic crises — a time that seems uncharacteristic given the previous decades. Unfortunately, the current period may represent a return to the norms of human history. The relatively peaceful, prosperous time we lived through may have been the deviation.

While not halcyon days, the 70 years after 1945 were a period in which great-power conflict was avoided, more than a billion people were lifted out of poverty, life expectancy — due to advances in sanitation, medicine, and living conditions — increased significantly, and norms regarding the value of human life changed dramatically. Murder, for example, was very common in most societies 200 years ago as a means of “solving problems.” Today, it is much less so.

The financial stability of recent decades was also new. There were no true global depressions, and highly disruptive events like sovereign defaults by major economies were absent. This was not true in the past.

Simply put, this relative economic stability was purchased by an overwhelming surfeit of debt. Two occasions on which this debt was used stand out: to rescue institutions deemed “too big to fail” in the financial crisis of 2008, and to stabilize world economies during the Covid pandemic. But debt has mounted continuously in most countries. In the US, public (government) debt is over $36 trillion. Private US debt is between $20 trillion and $30 trillion, depending on how it is counted. The extreme efforts to avert financial disasters mean that markets have never been allowed to clear. Like a forest in which fires are suppressed and undergrowth is never cleared by smaller burns, the fire, when it comes, may be cataclysmic.

After many years of increases in democratic governance in the 20th century, the 21st is seeing considerable backsliding. According to Transparency International:

In every region of the world, democracy is under attack by populist leaders and groups that reject pluralism and demand unchecked power to advance the particular interests of their supporters, usually at the expense of minorities and other perceived foes.

The form of democracy endures. In 2024, more people voted in elections than ever before in history. But with the rise of illiberal democracies, many countries are preserving the form but not the substance of democracy as it has been defined over the past 250 years. It is of particular interest that young people in many places are increasingly dissatisfied with democracy.

Why is all this happening? There are many interacting reasons, but I would suggest that four factors should be singled out.

First, as I have written before, are the broken promises so many people perceive in their lives. They feel that they played by the rules and were promised that their lives would improve and their children’s lives would be even better than their own. If anyone reading this sincerely believes this now, I would be surprised.

Second, the underlying conviction that economic well-being is the primary motivation of almost everyone and the most reliable source of human happiness — and that humans are rational self-interested agents who pursue and maximize their own well-being. This is the basis of not only capitalism, but also socialism and communism.

But, as it turns out, Marx was wrong in his estimation that economics is the moving force of history. It could rather be said that economic forces are moving history away from economics and toward identity politics. As people move or are moved en masse for jobs and economic production, community structures come apart, engendering an urgent need for identity. That need frequently takes the form of a desire to belong to some group that excludes others (social, religious, political, economic, even place-based).

A third factor is technology, particularly the technology of connectivity, and most particularly, mobile visual connectivity (smart phones, tablets, etc.). Not only do these devices demonstrably increase loneliness and affect cognition, as continues to be shown in studies, they also contribute two additional, crucial elements. The first is transparency. People now are intimately aware of how other people live to an extent that has never occurred previously. Whether such accounts are exaggerated, false, or accurate doesn’t matter much, the effects are often the same: envy, sadness, depression, and anger.

Second, mobile visual connectivity allows people with similar interests and thoughts —  including politically aggressive and polarizing ideas or destructive and self-destructive desires — to find one another, create relationships, share and develop ideas, and then act on them. It is perhaps most important that they are all able to do this from a distance and almost instantly. In the past, it was much more difficult for people whose thoughts were outside the norm to find one another and act in concert.

Fourth, much of the avoidance of major wars during the past 8 decades was due to the so-called Pax Americana, a system imposed on the world by the United States and made possible by American military power. Recently, with changes in military technology and the rise of other powers as near peers in military terms, this superiority begun to erode. Other factors are contributing to the eclipse of the Pax Americana, especially the debt load mentioned above. For the first time, the US last year spent more on government debt service than on its military.

All of these factors augur a more conflictual, impoverished, and insecure world. In other words, reversion to the conditions of most of human history. Perhaps some change or series of changes can avert this fate, and we should hope that they do. But if trends continue on their current path, life may be very different.

Mutual Assured Malfunction

The past week has been a lively one for the eternal battle between digital networks and national, sovereign security. After a two-year standoff, Elon Musk’s Starlink was able to reach deals with India’s #1 and #2 telecommunications companies, Reliance Jio and Bharti Airtel, on providing satellite Internet to the subcontinent’s vast and underserved rural market. A few days earlier, Dan Hendrycks, Eric Schmidt, and Alexander Wang — respectively, director of the nonprofit Center for AI Safety, former chairman of Google, and the CEO of Scale AI — released a paper , “Superintelligence Strategy,” arguing that no one state will ever be able to win the AI race.

In the first instance, a technology company with, it is fair to say, its own distinctive geopolitical interests could potentially gain a hold over the telecommunications of the world’s second largest national market. In the second instance, tech industry leaders with, particularly in the case of Schmidt, a strong record of advocating US technology dominance in competition with China are asserting that such dominance can never be complete. Indian digital sovereignty and US digital sovereignty are rendered highly problematic if not impossible. If a state is on the networks, as all powerful states are and will be, then their sovereignty is inherently partial. Taking these two major developments together, the future of digital self-determination can be seen to be rather weak. In SIG’s view, this represents an overdue recognition of the interdependence of states even as they engage in fierce geopolitical competition.

Reliance Jio has, in the past five years, revolutionized India’s telecommunications, particularly mobile communications, bringing huge numbers of Indians online. Bharti Airtel has done a surprisingly good job at catching up, giving Reliance Jio much-needed competition. The Indian state has not been idly observing these developments. Its vigorous advocacy of an indigenous digital infrastructure, often now referred to as the “India Stack,” has become an example to others, including the European Union. (See the SIGnal post “The America Stack,” Feb. 5, 2025.) India is determined to become a major tech power. It has also, with the world’s fourth-largest defense budget after the US, China, and Russia, aggressively advanced its own space program and its own space-based navigational system to rival GPS (US), Glonass (Russia), and BeiDou (China). Balancing US and Chinese telecommunications majors over the past decade-plus, India has artfully and purposefully pursued its desire to achieve digital self-determination.

That made the Starlink deal a surprise. It appears to have been hammered out between Musk and Indian President Narendra Modi during the latter’s recent visit to Washington. The Indian government has an interest in nurturing Reliance Jio and Bharti Airtel, but it also has an interest in good relations with the US under President Donald Trump and in making sure that neither Reliance nor Airtel accumulates too much power domestically. Both the US and China have faced a similar problematic in simultaneously backing and controlling their own tech majors. The deal with SpaceX, Starlink’s parent company, provides one way for India to meet these several challenges. Indian reaction to the Starlink deal has been understandably wary and somewhat confused. After all, the Indian government, at various junctures, has humbled Facebook, Google, Amazon, Microsoft, Huawei, and ZTE, among other foreign firms eager to reach the Indian market. A recent Indian report characterized Starlink as “a technology of geopolitical control,” pointing meaningfully to Starlink’s role as the guarantor and master of Ukraine’s Internet access in that country’s struggle with Russia.

SIG’s view is that Starlink will not be able to repeat its Ukraine dominance in India, any more than its US and Chinese rivals have been able to subdue the subcontinent — not for want of trying. It is nonetheless striking that Modi, Reliance, and Airtel — the latter two have long opposed letting Starlink into the tent — now believe that the advantages of working with SpaceX outweigh the disadvantages. At the very least, Musk has dramatically proved that having the ear of the US president provides enormous business benefits.

While the “Superintelligence Strategy” has been in the works for some time, it is difficult not to read it in the context of the Trump administration’s declared determination to press the US’s AI dominance. One of Trump’s first moves was a $500 billion AI infrastructure project, and Vice President J.D. Vance later stressed in a landmark speech in Paris that the US “will ensure that American AI technology continues to be the gold standard worldwide and we are the partner of choice for others — foreign countries and certainly businesses — as they expand their own use of AI.” Vance held back from a simple declaration of hegemony but the administration’s message has clearly been that US AI should indefinitely be the parent in comparison to the efforts of other nations, especially China.

The “Superintelligence Strategy” has at its core the highly convincing argument that any large-scale AI system, even an American one, will always be vulnerable to infiltration and disruption by rivals. The strategy offers a very worldly solution, based on, but distinct from, earlier strategic arguments about nuclear weaponry. It is called Mutual Assured AI Malfunction (MAIM): the acceptance that there will be a balance of AI power, not a resolution or well-meaning regulation of it. Further, MAIM “already describes the strategic picture AI superpowers find themselves in.” A new Mutual Assured Destruction (MAD), AI version, is already with us. As in the earlier, nuclear version, there can be no victors.

There is much here for China and others to digest. The old, US-led idea of a free and open Internet, so recently repudiated, can be seen as returning, but in a much darker form appropriate perhaps for darker times. How states and companies react is the crucial question for investors. The venerable commercial goal of scaling, ideally to a global level, is not going to be achievable. AI-fueled tech companies, which increasingly means most tech companies, will face geopolitical limits. Commercial cooperation within those limits — and successful digital competition is inherently commercial — seems to be the only way forward. Musk, Modi, and the authors of the “Superintelligence Strategy” are simply ahead of the curve, and showing the rest of us where it bends.

The Rollback

Two tripartite acronyms that came to represent some of the most important policy packages of the post-Cold War West — ESG (Environment, Social, Governance) and DEI (Diversity, Equity, and Inclusion) — are becoming obsolete at an impressive speed. President Trump’s opposition to both was clearly articulated during his campaign. It was part of his electoral appeal to a variety of American constituencies. He has now used his powers to roll them back. European officials are rushing to keep up. Corporates generally welcome all this, although they refrain from saying so publicly. ESG and DEI both added costs. Their repeal is part of the expected package of deregulation and tax cuts that was the foundation for corporate and investor support of Trump’s second candidacy. But a new world after ESG and DEI might not be as commercially liberated as many are anticipating.

The Europeans tend to draw a distinction between the US initiatives, which they see as driven by “ideology,” and their own, which they characterize as driven by a need to compete with US companies that will henceforth be operating by a different set of rules that entails reduced costs. Since, in the European view, the initial impetus comes from US ideology, European governments and companies are rendered blameless as they are only reacting to the US abandonment of what were, until recently, held to be common Western values. For people whose environment, as a result of these changes, is poisoned, or whose workers are returned to labor conditions describable as “modern slavery,” this will seem like a very fine distinction. If one’s values can be overturned in a matter of weeks by a fear of future market pressures, then those values cannot be reckoned to be very strong.

Will abandoning them have the desired effects? Since the US-European playing field is, by virtue of this shared rollback, being not so much leveled as lowered, the strictly economic effects, in competitive terms, are not likely to be impressive. If all firms save the same costs in the same way, then the benefit to any individual firm is not great. What this common downward leveling will do, however, is reduce the barriers to competition for companies from economies that did not much subscribe to Western-led DEI and ESG initiatives in the first place: China, Russia, much of Southeast Asia, parts of Eastern Europe and Latin America. The dominant Western economies, fixated on competition with each other, are abandoning policy levers that, given the importance of their consumer markets, would have given them a type of comparative advantage. Some would say that was what made those levers politically viable in the first place.

This is especially the case with ESG. The DEI situation is interestingly different. One reason the US economy is distinct from those in industrialized Europe and East Asia is that the US has always been a multi-racial and multi-ethnic society dependent on immigration for growth. While DEI as such is quite new, the inclusion of diverse peoples with at least a horizon of equity to aim for — expressed in ideas of Americanization, assimilation, the melting pot, color-blindness, and market-based opportunity, among others — has been a feature of the US from its beginnings, even if it has always been extremely contested. European and East Asian societies, by contrast, have been constructed much more around a central ethnos, the preservation and advancement of which have been seen as constituting much of the purpose of the nation. While there are many, many exceptions to this, the European and East Asian varieties of DEI really have to do with immigration (and gender equality). They are features of just the last few decades. In the US, they are part of a long-established social contract.

Perhaps the distinction is not that important. Ultimately, in both cases, the central question is the supply of labor and its price. Neither the white population in the US nor the Korean or Japanese or German or Dutch labor forces are growing. Robotics and AI and the suite of labor-saving (or job-replacing) technologies may manage to reduce the drag that this lack of population growth has on national economies. Technological protectionism (and other kinds) might also increase employment of skilled nationals. But the demographic and other counter-trends are very strong. The US and other powerful states are expecting capital to be more patriotic, which might create some domestic jobs but could also reduce the returns to capital that were had by outsourcing the rich world’s working class. Meanwhile globalization gave many less-developed economies enough of a middle class to increase domestic demand for domestic production.

The US is, as ever, an outlier. Unemployment is and has been low, unlike in every other major economy. And DEI in the US, unlike in other countries, does not have principally to do with immigration but with the relationship between white and non-white. So does the anti-DEI wave. The Department of Education took the Supreme Court’s ruling against using race as a factor in elite college admissions and decided that it applied, or should apply, to every school of whatever kind in the United States that takes federal funds. The Supreme Court is encouraging white Americans to equate their experiences of racial discrimination with those suffered by non-whites. Missouri’s attorney general is suing Starbucks on charges of discriminating against white men. The secretary of defense, Peter Hegseth, fired senior Pentagon officials he seems to have thought were DEI hires, on a gender as well as racial basis.

All of these moves represent a dramatic change in US social relations, one whose implications can only be guessed at. The unemployment rate for white men is at 3.1 percent. (Its lowest previous rate in memory was 1.7, in December 1968.) White unemployment rates run slightly higher than those for Asians but significantly below those for other groups. If there has been discrimination against white men, and if immigration is held at bay, then employment of white American men is likely to go up at the expense of other groups — perhaps not Asians? — whose unemployment rates are already higher. Over time, the US might return to having an unusually empowered white male working class, recreating to some degree the era when trade unionism, which discriminated heavily in favor of white men, was at its peak and income inequality at its lowest. But it is hard to imagine the nonwhite working class, which is today (unlike in the 1950s and 1960s) the majority of the working class, going along with such a social order. Nor is the unemployed part of the white population likely to jump at jobs that it currently tends not to accept. Corporates and investors have not liked DEI and are abandoning it with impressive alacrity, but the post-DEI world, like the post-ESG world, may not be quite as commercially successful as expected.