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.