The New Pessimism

Talks in South Korea between US President Donald Trump and China’s President Xi Jinping on Thursday went as expected: the two leaders negotiated away from confrontation rather than toward it. The transactional nature of current US foreign policy is sometimes over-rated, but in the case of China it is clear, and China’s leadership is more than ready to behave similarly, transaction by transaction. Given that China has for many years been identified by Trump as the leading challenge to American status globally, his reconciliation with Xi suggests that moral arguments about the US’s duty to lead its allies in opposing authoritarian government and promoting free markets are being left behind. This was the contention of two important commentaries last week by Michael Beckley and Ian Bremmer. SIG’s view is that the domestic crisis Bremmer identifies and the US’s “rogue superpower” behavior (Beckley) will last well into 2026 but then moderate. The reasons are the same as the ones that led Trump to make a deal with Xi: a lack of better options.

Ian Bremmer, founder and head of Eurasia Group, sees US President Donald Trump as leading a domestic “political revolution” that could involve “the kind of political chaos, realignment, and violence that America saw in the decades after the Civil War.” On the international side, Beckley, of Tufts and the American Enterprise Institute, sees the Trump administration as caught up in “the same logic of raw power that helped spur two world wars…What looms is not a multipolar concert of great powers sharing the world, but a reprise of some of the worst aspects of the twentieth century.” These are loud alarms from highly credible people.

Bremmer and Beckley are both what American political science calls “realists,” with political views somewhere on the center-right. Ian Bremmer started Eurasia Group in 1998 in Manhattan, just four years after earning his doctorate in political science at Stanford. (His dissertation was on the ethnic politics of Russians in Ukraine.) In his 2015 book Superpower, Bremmer wrote, “I’m proud to be a political scientist, one who takes seriously his responsibility to offer unbiased analysis. I’m also intensely proud to be an American….I love my country.” Growing up in a rugged part of Boston, with multiple and varied heritages in his ancestry, Bremmer, like numberless Americans before him, developed a profound sense of the US as uniquely a land of opportunity for all. He also saw it as having a unique and positive international role, although by 2015 he had turned against a “superhero foreign policy.” He mainly thought the US should lead by democratic example, rooted in the constitution. (“Congress is the guarantor of our security and our liberties. The president, every president, must respect its authority.”) Although in 2016 he called Donald Trump “a buffoon…willing to use racism, xenophobia, and all of the worst and basest impulses” to gain power, Bremmer generally stuck to foreign rather than domestic politics. Nonetheless, a certain type of constitutional democracy at home was seen as the essential basis for leading by example overseas.

It is the “replacing” of “the rule of law with the rule of Don” that led Bremmer to write last week that “a constitutional crisis before the next elections looks increasingly likely.” If the American system has become personal rather than constitutional, then it can no longer lead by example. So Bremmer now speaks of a “post-American order” in which other nations cannot expect American leadership, even by example.

Michael Beckley made his name with Unrivaled: Why America Will Remain the World’s Sole Superpower (2018). He had been advised as a PhD student by America’s international-relations royalty: Richard Betts, Andrew Nathan, and Robert Jervis. Beckley offered a very compelling argument that China’s prospects were over-rated and the US’s strengths were under-rated. It was read as an argument against US defeatism. Beckley, like Bremmer, was against US military problem-solving abroad. His worry, two years into the first Trump administration, was partisan division leading to the loss of “America’s purpose”: compared to fighting fascism or communism, “maintaining the liberal order may seem like an underwhelming call to greatness….But it is just as virtuous and just as vital.”

Seven years later, writing in Foreign Affairs, Beckley finds that, “As liberal democracy corrodes at home, liberal internationalism is unraveling abroad. In a world without rising powers, the United States is becoming a rogue superpower, with little sense of obligation beyond itself…. U.S. strategy is shedding values and historical memory, narrowing its focus to money and homeland defense. Allies are discovering what unvarnished unilateralism feels like, as security guarantees become protection rackets and trade deals are enforced with tariffs.”

Bremmer and Beckley are determinedly level-headed, experienced, deeply engaged political scientists at the top of their games. They both conclude that the US is falling apart at home, which in turn means that its status as a world power is also falling apart.

How does the Trump-Xi meeting look in this light?

They talked for two hours. Trump said Taiwan did not come up and that China signaled a desire for cooperation on Ukraine. The Chinese readout mentioned neither. The public takeaways included a US reduction in tariffs (and threatened tariffs) in exchange for additional Chinese measures to hinder exports of ingredients in fentanyl, an opiate that has become a leading killer of Americans who use it recreationally. China agreed to lift its ban on imports of US soybeans, returning them to roughly the same quantity as before the recent trade war. The US indicated it would ease restrictions on exporting to China advanced silicon chips, notably those produced by Nvidia. The Chinese readout said that the US had agreed to suspend for a year the implementation of a new rule targeting subsidiaries or affiliates of companies on the US Commerce Department Bureau of Industry and Security’s list of proscribed companies (Entity List) and military-related end users (MEU List). The first list is about 70% Chinese companies; the second is entirely Chinese companies. China in turn suspended for a year its export controls on rare earths and associated products going to the US. 

In all of these, the US seems to have been at a disadvantage. On soybeans, US farmers suffered the loss of a market while China diversified its soybean suppliers; the result of Thursday’s talks was at most a possible return to pre-tariff US soybean export levels.

Fentanyl-related tariffs were announced by the White House on February 1 under the authority of the International Emergency Economic Powers Act (IEEPA). They were paired with “illegal aliens” as twin aspects of a “national emergency” invoked in order to apply tariffs to imports from China, Canada, and Mexico. The declaration of a national emergency was necessary in order for the executive branch to gain the authority to impose the tariffs. (The administration cited the same emergency IEEPA authority for the April 2 “Liberation Day” tariffs, with high US trade deficits said to constitute a “threat to the national security and economy of the United States.”) Now the fentanyl tariffs are to be reduced in the case of China.

What was missing from the statements and readouts on Thursday was anything about fentanyl use itself — which is the legal basis for the White House’s imposition of the tariffs. Non-fatal fentanyl overdoses actually ticked up from January to June 2025 then declined into August, but they remain where they were when the tariffs were first applied. By contrast, fatal drug overdoses, the majority linked to fentanyl, have been dropping steadily since August 2023 and are now at about the same number as in April 2020. On the first figures, the fentanyl tariffs have been a failure, so why revoke them? On the second measure, the overdose emergency itself has been abating steadily for two years, with the pace seemingly unaffected by the tariffs, so why retain emergency powers at all?

On silicon chips, export controls have been based on national-security grounds, as were Liberation Day tariffs. The same was true of the proposed expansion of BIS Entity List and MEU List powers. These measures have now been suspended or possibly rescinded. So is China now less of a threat to the US?

China’s suspension of its rare-earths export controls was its only significant move and it seems provisional. (China did not suspend its rare-earths controls from April, only the new rules announced in early October and not yet implemented.) China’s strategic management of its rare-earth resources and capabilities has been a consistent feature of its foreign policy since it suspended such shipments to Japan in 2010 over a maritime dispute. A one-year suspension of a new export protocol again, as with soybeans, represents a return to the status quo more than a concession. And as Rush Doshi said on Bill Bishop’s Sinocism podcast yesterday, the rare-earths sector is mainly controlled by a tiny number of Chinese companies that defer to government direction. That tap can be turned on or off at any time.

The import of the Xi-Trump negotiations, then, is not so much in the rather insubstantial terms themselves but in what the talks imply about the Trump administration’s power. It was playing a weak hand from the beginning. China still controls 90% of the rare-earths supply chain. The US was bargaining with soybeans that could be purchased elsewhere, tariffs that are already being priced in and hurt US firms and consumers as well as Chinese suppliers, and technology exports that have already proved difficult to control and for which China is very energetically developing substitutes.

But Trump’s hand was also weak in a different, possibly more important way that puts the grim prognoses of Bremmer and Beckley in an interesting light. It isn’t just that the national-security justifications for presidential tariff powers and export controls have been revealed as opportunistic. It is that Congress has begun to push back in this slow-burn constitutional crisis. As the White House is keenly aware, the Senate resolved, on the heels of the Xi-Trump meeting, that the “national emergency” invoked on Liberation Day was over. This followed two earlier Senate resolutions to oppose tariffs imposed by the White House on Brazil and Canada. In short, Trump was bargaining with Xi partly on the basis of powers that a Senate majority said the president did not have. (Those powers will be reviewed by the Supreme Court as well, on November 5.) It is worth recalling that it was also the Senate that rejected (by 99 to 1) the White House’s bid to forbid states from regulating AI. Senators this week will have noted that the president’s approval ratings have slipped and, perhaps more important, independent voters have swung toward blaming the president and the Republican party for the government shutdown that just reached its thirtieth day. (The record is 35.) At the same time, there is no indication that Congressional Republicans or Democrats have concluded that China no longer poses the threat to national security that inspired BIS and other tech export controls or that Xi has been cowed. Or that China’s control of the rare-earths supply chain has really been weakened.

Bremmer and Beckley were abundantly justified in raising the alarm over America’s ongoing constitutional crisis and its implications for US foreign and economic policy. But they might have called the fight a bit too soon.

The Market for Tech Containment

Recent moves by Microsoft and the Chinese government marked a new stage in the years-long process of tech decoupling, a SIGnal preoccupation. Meanwhile, the US and China are moving toward what might be significant high-level talks — and the US bull market continues, fueled by AI valuations that are dependent on American dominance of the AI future. None of these three elements seem at all stable. Even tech decoupling could be upended if US President Donald Trump decides to favor a megadeal that would bring Chinese investment into the US. The markets and the politics are both frothy indeed. SIG’s view has long been that AI technology as such will transform industrial processes and much else. A related but quite separate question is whether the massive investment into data centers, understood as the infrastructure of AI, is really necessary for the AI future. “Infrastructure” has a reassuringly solid sound, but if the much-anticipated burst of the AI bubble occurs then data-center capex is where the deflating is most likely to happen.

Microsoft’s withdrawal from China received less attention than it deserved. Bill Gates and his company have long been more pro-China than most of Big Tech. Microsoft’s China labs were crucial to China’s acquisition of AI expertise and experience. That is much of why China’s leader Xi Jinping mischievously greeted Gates as an “old friend” in Beijing in 2023, seven years into a bipartisan consensus that China was the pacing challenge for American security and the US economy. Microsoft’s withdrawal began late in 2024 and has continued through this year. The shuttering of its Shanghai AI lab early in 2025 was done very quietly but it reversed decades of company policy that had done much to create China’s AI industry in the first place. In short, when Microsoft decouples it really means something.

At the same time, China made a strategic shift this month with comprehensive restrictions placed on Chinese companies to prevent use of US silicon chips. This hit Nvidia particularly hard. Its share of the China market plummeted from 95% not long ago to 50%. Nvidia’s CEO, Jensen Huang, has done everything he can to hold on to what he still has. He is said to have the ear of President Trump. But the reprieve Huang secured in July seems to have been eliminated by China’s new moves. When China decouples at this scale, it really means something. 

Tech decoupling is a secular trend. It is the central force behind the current trade tensions, which both China and the US have been escalating, each placing the blame on the other. President Trump’s retaliatory tariffs, set to take effect November 1, responded to China’s weaponizing (not for the first time) of its tight grip on rare-earths production. All these moves revolve around the perceived centrality of AI to victory or defeat in the geoeconomic struggle between China and the US.

The two countries are nonetheless continuing talks. China hawks in Washington and elsewhere are genuinely worried that President Trump’s love of the grand gesture will combine with the influence of Jensen Huang and others to undermine the structure of tech containment built up in recent years. They might well look to Trump adviser Peter Navarro for reassurance. He has been ringing the bell about the China threat for 20 years. And indeed at the Council on Foreign Relations on Friday Navarro spoke of how the president’s tariff negotiations have already resulted in “19 trillion dollars” of promised investment: “foreigners are going to be paying to fix the vulnerabilities in our supply chain,” and once they have done so there will be a global “level playing field.” He also said that the US pre-Trump had “shipped 19 trillion dollars of our wealth” overseas. Nineteen trillion out, 19 trillion back in, and balance is restored. That is the idea. Navarro believed China’s new rare-earths policy is showing the world that China is everyone’s enemy: “The world will not go back to sleep on this.”

But if a three-year bull market, grounded in speculative bets on building data centers to set the infrastructural stage for future AI-driven productivity gains, wobbles enough, trade wars with China could lose their appeal. Tech containment and tech decoupling, though, will continue.

Changing Patterns of Foreign Direct Investment

The McKinsey Global Institute has published a report on patterns of foreign direct investment (FDI), specifically greenfield (new project) investment. It is both a thorough and  a methodologically innovative report. Interestingly, the report rather buries its headlines. This might well be because the MGI, like McKinsey itself, to the limited degree that it has a political perspective, is for efficient global markets based on mainstream economics, and therefore “for” globalization. It is not the McKinsey Institute for Successful Economic Nationalism. Given that this is an era dominated by economic nationalism, the MGI’s commitment to political neutrality probably makes it hard to rank its findings by significance.

For example, is it good news or bad news to show that announced greenfield FDI flows into China have decreased by 70 percent since 2022, in the teeth of Chinese policy? Is that finding more, or less, important than the related finding that Chinese outward FDI investment is dominated by what MGI calls “future-shaping industries,” which mainly means AI data centers? Similarly for the US, the report finds that announced inward greenfield FDI has soared but it is mainly in semiconductor manufacturing and, again, AI data centers. The report also notes the huge role of Gulf Cooperation Council countries such as the UAE and delicately acknowledges that much depends on “the ultimate form of trade deals between the United States and its partners.” It would take a brave investor to decide with confidence what that form would be or indeed whether those deals will ever have an “ultimate form.”

Another possible headline might have been built around the finding that FDI announcements in advanced economies other than the US have been anemic since 2024, with data centers barely picking up the slack from drop-offs in energy and advanced manufacturing.

Yet another headline is in the finding that announced greenfield FDI investments in 2025 (to May) “in each of the emerging Asia, Latin America, MENA, and sub-Saharan Africa regions are at 20-year lows….FDI investments across these regions have fallen by 50 percent from their levels during the 2022-24 period, on an annualized basis.” So while total global FDI has grown, it has gone down in all the poorer parts of the global market, as well as barely straggling along in most advanced economies.

This could be seen as a victory of sorts for the US and the Trump administration, if victory is measured by the signing (not execution) of deals in AI data centers and semiconductor manufacture. However, the Trump administration gained power with promises to bring back traditional manufacturing, and the MGI report finds investment in that sector plummeting nearly everywhere in the world, including the United States.

There are several other possible headlines that could be gathered from the MGI report, which amounts to a map of the intentions or hopes of mega-scale capital. (The corporate drivers in the report are dominantly major multinationals signing megadeals — yet another headline.) In a crowded field, SIG’s own choice would perhaps be that investments in low-emissions technology, which doubled from the 2015-2019 period to 2022-2024, have fallen by 70 percent in 2025 for low-emissions hydrogen and offshore wind. Other energy forms have remained about the same or, as for conventional fossil fuels, gone down. Geothermal and nuclear announcements have more than doubled but from such a relatively low base that “they hardly dent the aggregate energy FDI numbers.”    

What this suggests is that even the biggest investment decisions made by the largest corporations having (as with energy companies) the longest and deepest experience of greenfield FDI are being decisively shaped by political developments, above all in the US and China but also in the Gulf. If the political winds of January-May 2025 were to change, as they almost certainly will, then further massive shifts in FDI flows will also occur.

So both investment capacity and policy influence, when it comes to global greenfield FDI flows, are being concentrated and profoundly politicized. That clearly does not mean that they are becoming more predictable, only that there are fewer decision-makers. In the global struggle for political-economic power, this could mean that victory will go to the major power that is most stable and predictable, which is presumably China. The high degree to which Chinese multinationals, as the MGI found, are engaging in greenfield investment outside China — as well as, of course, outside the US, where they are not currently welcome — also suggests as much.

The Nine Lives of Economic Nationalism – Part Four of Four

Earlier posts in this series considered the multi-century trajectory of economic nationalism in reaction to empire, the resurgence of import substitution and major-power resource competitions, and the ways in which major-power economic nationalisms have made non-market-based economic development policies more popular than they have been in decades, almost regardless of levels of industrial development or economic size.

This final post considers some likely near futures of economic nationalism and economic sovereignty, with particular attention to AI.

First, the United States. The US was born in a determination to end external imperial dictation of economic policy and has, for the most part, guarded a relative autonomy from other economies ever since. The unification and then expansion of the 13 colonies across the continent integrated conquered territories into a “domestic” economy in a way that had few comparators elsewhere in the world. The resulting extent of US natural resources, from fresh water to arable land to natural gas, also proved to be unique. The US was peculiarly well suited to economic sovereignty, and with large-scale immigration it was able to grow on domestic demand better than anywhere else. Exports therefore accounted for a relatively smaller share of GDP than was the case in other industrial countries.

The constraining factor in the US case was not a lack of petroleum or fresh water or food but labor productivity. This was addressed through numerous means, from transport infrastructure to compulsory public education to industrialized agriculture. It helped that the US economy, unlike other industrialized economies, benefitted from both world wars. Productivity entered a crisis in the 1970s. It was eased, in a way, by the Internet and industrial globalization: your wage might be stagnant but it bought much more. But that improvement depended on production outside the US under working conditions that would be rejected in the US itself.

The extraordinary US investment in artificial intelligence comes from this.  AI holds out the promise of increasing productivity. But will it be global productivity or national productivity? Differently put, will the gains be captured by transnational capital and consumers or by tax-paying domestic markets and citizens? Will it be international or nationalist? Low unemployment, very slow job creation and high government and corporate debt all suggest that, absent an AI productivity miracle, the US will head into recession. That might well make the American people more nationalistic and insistent on economic sovereignty, but economic nationalism will not be able to solve their problems.

Chinese economic nationalism faces other constraints. A shrinking workforce and resistance to immigration mean productivity gains will have to come from labor-saving technology and investment in the non-Chinese global workforce. The first would be economically nationalistic. The second would be more like what US companies did in the 1980s and 1990s, and it could hollow out the Chinese jobs market as it once did the American. This would fuel the popular appeal of economic nationalism but, again, economic nationalism is not likely to be able to solve China’s labor productivity problems. An AI productivity miracle would help China as it would help the US. But it would be a miracle.

AI looks different outside the US and China. Those two countries thoroughly dominate the AI space. In AI terms, most other countries are takers, not makers. Africa’s population, a bit larger than China’s, captures 2.5% of the global AI market and is expected to attract 0.3% of global AI investment. The European Union attracts 7%. Britain, Canada, Israel and India also have significant investment, with Britain’s spend twice that of Canada’s. Nonetheless, the US and China attract 80%, with four fifths of it in the US. If an AI productivity miracle occurs in the existing economic-nationalist environment, it is difficult in political terms to imagine the benefits being rapidly diffused across the globe, since the goal of the investment is roughly the opposite.

AI aside, the resurgence of discredited 1960s-era development economics, from “national champions” and import substitution to infant-industry protection and tariffs, is becoming widespread. These policies were celebrated by the Left half a century ago as a way to withstand US corporate domination. Today their appeal is close to universal. They are even seen in the US as ways to ensure the US domination that they were once meant to block.

The essential point seems to be sovereignty. It is a phenomenon rich in paradox. The US-led Internet boom made possible a globalization that dramatically increased the wealth of once-poor countries, above all China but also India and others. These states could then afford to oppose what had just made them wealthy and to revive policies that had not helped them at all the first time around. China, India and other once-colonized nations wrap this in a rhetoric of anti-imperialism while hurrying to lock up poor-world resources before their once-imperial competitors do.

This is the central reason why China’s alternative global-governance schemes will go only so far: they are motivated by economic nationalism. Yet the same is true of US, Indian and European efforts, although European economic nationalism plays out on two levels at once, the national and the supranational. The major EU reform initiatives of 2024 were all premised on consolidating nation-based sectors into a super-nation capable of competing with the US and China.

For investors, at the national (or for the EU, supra-national) level, the play is in policy arbitrage, which is also political arbitrage. At the global level, as between major economic-nationalist actors like China, the US, India and the European Union, it makes sense to hedge with presences in at least two, navigating the relationship in each market among affirmative industrial and financial policy, protection, and market-based competitiveness. (A simpler way to do this, of course, is to invest in multinationals and funds with the proven capacity to do this kind of multi-market navigation themselves.) Beyond that, in countries like Nigeria and Ethiopia, which aim at economic sovereignty but lack much of what is necessary to achieve it, there are opportunities in the state-favored sectors themselves, the import and domestic sectors that provide the necessary inputs (such as electricity and raw materials), and the export sectors that ultimately make imports possible.

Little of this was featured in business school and Adam Smith would be appalled, but for the time being economic nationalism is the way of the world. 

The Nine Lives of Economic Nationalism – Part Three

Part one of this series discussed the roots of modern economic nationalism in anti-imperialism, then went on to consider how US-Chinese economic nationalism has scrambled established ideas about both empire and economics. Part two examined two cases in Africa: the first involved two formerly colonized countries (India and China) competing for dominance of resource extraction in other formerly colonized countries; the second focused on the successful import-substitution (oil refining, cement, fertilizer) companies of Nigeria’s Aliko Dongate and his new, $2.5 billion fertilizer-production deal with Ethiopia. In both posts, the through-line was the defense of national economic sovereignty in a world deeply interconnected through trade.

The third post in the series looks at the blowback created by US-China economic nationalism.

The first case of blowback must surely be the US reaction to Made in China 2025 itself. The original Chinese program was a sovereignty play. China did not want its economic future (green energy, smart manufacturing, biotech, etc.) to be dominated by US companies with massive first-mover and other advantages. Made in China 2025 was a project aimed at economic self-determination. It did not cause much concern at first in the US: President Barack Obama met China’s President Xi Jinping for positive talks in 2016, after the project had been launched, and visited him again in Beijing in 2017 after leaving office. But Trump’s signature economic nationalism, once he settled into the White House in 2017, gradually fastened onto Made in China 2025 as a legitimizing opponent. Much of corporate America and the Democratic Party went along with this, for reasons of their own. The economic nationalism of a still relatively poor country — Chinese GDP per capita in 2015 was less than a third of what it would be in 2025 — begat the economic nationalism of the dominant economy in the world.

The US elaboration of economic nationalism in reaction to, and often in imitation of, Chinese economic nationalism inspired similar reactions elsewhere, most notably in the world’s most populous nation, India. In May 2020, while Trump was still in office, Prime Minister Narendra Modi launched a Made in India campaign. He made free use of a term, swadeshi, deeply resonant of the anti-imperial movement a century before. It was probably Modi’s move, combined with the breakout of border conflict with China (also May 2020) and the ensuing expulsion of Chinese tech companies from the Indian networks they mostly built, that led China to reframe Made in China 2025 in a longer history of anti-imperialism and attempt to rival India as a leader of the Global South.

The die was cast. An economic nationalism, including import substitution and “food sovereignty,” that had seemingly left the world stage in the early 1970s was back, led by the two dominant economies in the world and its most populous nation.

At the same time, the US, China and India all knew that actual isolation from the global economy was impossible in any imaginable near term. Modi’s atmanirbhar (“self-reliance”) coincided with much closer relations with the US and US companies, for example, including military and tech cooperation, right up to Trump’s sudden and wrenching disenchantment with India in August of this year. US economic nationalism was also not just about autonomy in North America. It involved, for example, throttling Chinese export industries and doing whatever was necessary for “locking in dollar supremacy,” in Treasury Secretary Scott Bessent’s words, to preserve “extraterritorial power.” Similarly, Chinese self-reliance (zili gongsheng) developed alongside a lengthening list of quite internationalist projects, from the Belt and Road Initiative to promoting the Shanghai Cooperation Organization as a pseudo-NATO. Each of these large economic powers preached economic nationalism but also practiced internationalisms of various kinds and showed no actual desire to stay contentedly within its borders tending its own gardens.

Yet if major-economy economic nationalism in practice had a strong internationalist cast, it was nonetheless nationalistic in terms of the barriers erected against foreign participation in domestic economies. It was also exceedingly transactional, before Trump’s re-election and all the more so after. Friendly meetings at the beginning of September of this year among Modi, Putin, and Xi were often spun — not least by China — as evidence of an emerging international unity when faced with US trade and security policies. But there were no principles involved beyond sovereignty itself, and each of these actors, as well as Trump, has shown himself able to switch sides at will, and to switch back again.

So the sensible conclusion for countries in the rest of the world is to avoid alignment with any of these changeable states and to pursue their own self-sufficiency (“economic sovereignty”) — because you really never do know any more when your foreign supply chains will be reshaped by political policies over which you have no influence.

Economic nationalism fosters more economic nationalism. The unpredictability created by economic nationalism among major players — including the European Union with its quest for “autonomy” and resistance to becoming a US tech “colony” — has come to outweigh the profound efficiency costs. Better to slog through building your own fertilizer or cement industry or AI “stack” than give up what autonomy you have to politicized global markets.

The fourth and final post in this series will consider the future of economic nationalism.

The Nine Lives of Economic Nationalism – Part Two

Part one of this post discussed the roots of modern economic nationalism in anti-imperialism, then went on to consider how US and Chinese policies of economic nationalism over the past decade have scrambled established ideas about both empire and economics. The US-China model of economic nationalism, combining a desire for economic autonomy within the state’s borders and one for the projection of economic power outside them, has been embraced by powers both formerly imperial and formerly colonized. It is an episode in a very long history.

Two recent developments exemplify this. The first has to do with Indian-Chinese competition and Africa. India (and others ) now aims at securing African resources to compete with, and avoid dependence on, China. Writing in The Hindu, Samir Bhattacharya of the Observer Research Foundation argued, “African nations are growingly asserting their rights to value-added development. The old model of raw resource extraction in exchange for infrastructure or investments is no longer tenable in a region demanding agency, accountability, and economic sovereignty. … By challenging opaque contracts, enforcing environmental standards, and demanding value addition, they are redrawing the terms of engagement. If these trends continue, African countries are poised to reshape the global supply chain for minerals and their role within it, moving from exporters of raw materials to integral partners in the emerging green economy. This change would come at the expense of China’s long-standing dominance in the African mining sector.”

Bhattacharya neglected to mention that competing with China to secure African raw materials for Indian industries, with the goal of ending Chinese dominance of African mining, is Indian policy. And that policy is not solely motivated by a wish to help African nations achieve greater “agency” and economic sovereignty. Nurturing the economic sovereignty of Ghana or the Democratic Republic of Congo is not in itself a leading goal for Indian policy. Nonetheless, the language is important because it marks the enduring significance of anti-imperial politics when negotiating contracts with African states — and because it shows two former very large colonized nations competing to show which is less imperial in its motivations than the other. They would not be bothering to do that if it didn’t promise to improve business.

A century and a half ago, empires themselves competed in roughly this way, each claiming to be more liberal than its competitors — or, in the case of the Japanese empire circa 1910, claiming to be the champion of other non-white peoples, or at least Asian peoples, in rallying “the yellow races against the white as a common enemy,” as a Japanese professor put it in 1918. China and India in Africa today are marketing themselves in ways that stretch back to the late 19th century.

Of course, from an economic-nationalism perspective, on the ground in Lagos or Kinshasa, the key point is not to find more comrades for a united anti-imperialist front but to secure investment that can bring local production out of the raw-materials trap and advance it up the value chain. Just as Americans on both continents in 1800 did not want London, Lisbon or Madrid to keep them forever digging in the mines, felling the forests or laboring on export-oriented farms, the inhabitants of less-developed countries today do not want only to produce petroleum or cocoa or strategic minerals for refinement elsewhere. But actual transfers of intellectual capital, such as production methods, are not simple or easy. They often require a great deal of “agency” from local actors. Such actors will not always be loyal followers of mainstream economic theory.

A remarkable recent example is the deal struck at the end of August between Dangote Group, of Nigeria, and the government of Ethiopia. The story of Aliko Dangote, sometimes called the richest black man in the world, is well known, but in brief: Born in 1957 to a wealthy business family, Dangote was educated in a madrasa and public schools, then at Cairo’s celebrated Al-Azhar University. He began importing cement to Nigeria in the 1970s but his biggest business was in sugar refining. He formed the idea that he would lead in freeing Nigeria, and perhaps Africa, from dependence on imported refined materials — the classic post-imperial goal. When a friend became president of Nigeria, Dangote seized the moment. He acquired formerly state-owned cement plants and established a highly successful cement business, expanding to production elsewhere in Africa. His efforts were self-consciously mocking, in a gentle way, the Smithian economic doctrine that there was no point in Nigeria developing its own cement industry because it could import cement from countries that already excelled at cement production. Such “import substitution,” popular in the 1960s, had become deeply out of international favor. Dangote did it anyway and was hugely successful. By 2024 Nigeria was a net exporter of cement.

Petroleum is the biggest industry in Nigeria, but it has long been mainly a matter of exporting raw materials for refinement elsewhere. Dangote became a major player in oil refining, such that in 2024 Nigeria was a net exporter of petroleum products for the first time in decades. His other major sector has been fertilizer, which uses natural gas as its main input. Nigeria has immense natural-gas deposits. The $2.5 billion deal with Ethiopia last month involves Dangote (with a 60% share) developing Ethiopia’s fertilizer capacity using Ethiopian natural gas.

On X, Ethiopia’s prime minister, Abiy Ahmed, framed the deal as one ensuring “food sovereignty” and “food security.” Ethiopia currently enjoys neither, and the Trump administration’s cuts in food aid — Ethiopia had been the single largest recipient — made matters worse.

“Food sovereignty” has been a recurring issue in both US and, especially, Chinese economic nationalism. Now that their rivalry has so disrupted international markets, the reliability of food imports has gone down for everyone. The same is true of strategic-minerals imports, now such an important focus of Indian Africa policy. Indeed, one could say that US-China economic nationalism has created a world of economic nationalisms. The repudiated “import substitution” of yesteryear has returned, not from preference (or ideology) but from a necessity created principally, if unintentionally, by the policy decisions of the world’s two largest economies. One nearly certain result will be increased production outside of the US and China that will provide new competition to those dominant countries.

The next post in this series will look at how economic nationalism came to dominate the international scene.

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.