On Wednesday, President Trump issued three executive orders, delivered a speech, and released an motion plan, all on the subject of continuous American leadership in AI.
The plan accommodates dozens of proposed actions, grouped into three “pillars”: accelerating innovation, constructing infrastructure, and leading international diplomacy and security. A few of its recommendations are thoughtful even when incremental, some clearly serve ideological ends, and plenty of enrich big tech corporations, however the plan is only a set of really helpful actions.
The three executive orders, alternatively, actually operationalize one subset of actions from each pillar:
- One goals to stop “woke AI” by mandating that the federal government procure only large language models deemed “truth-seeking” and “ideologically neutral” somewhat than ones allegedly favoring DEI. This motion purportedly accelerates AI innovation.
- A second goals to speed up construction of AI data centers. A far more industry-friendly version of an order issued under President Biden, it makes available somewhat extreme policy levers, like effectively waiving a broad swath of environmental protections, providing government grants to the wealthiest corporations on the planet, and even offering federal land for personal data centers.
- A third promotes and funds the export of US AI technologies and infrastructure, aiming to secure American diplomatic leadership and reduce international dependence on AI systems from adversarial countries.
This flurry of actions made for glitzy press moments, including an hour-long speech from the president and onstage signings. But while the tech industry cheered these announcements (which is able to swell their coffers), they obscured the undeniable fact that the administration is currently decimating the very policies that enabled America to develop into the world leader in AI in the primary place.
To keep up America’s leadership in AI, you’ve to grasp what produced it. Listed below are 4 specific long-standing public policies that helped the US achieve this leadership—benefits that the administration is undermining.
Investing federal funding in R&D
Generative AI products released recently by American corporations, like ChatGPT, were developed with industry-funded research and development. However the R&D that allows today’s AI was actually funded largely by federal government agencies—just like the Defense Department, the National Science Foundation, NASA, and the National Institutes of Health—starting within the Fifties. This includes the primary successful AI program in 1956, the primary chatbot in 1961, and the primary expert systems for doctors within the Nineteen Seventies, together with breakthroughs in machine learning, neural networks, backpropagation, computer vision, and natural-language processing.
American tax dollars also funded advances in hardware, communications networks, and other technologies underlying AI systems. Public research funding undergirded the event of lithium-ion batteries, micro hard drives, LCD screens, GPS, radio-frequency signal compression, and more in today’s smartphones, together with the chips utilized in AI data centers, and even the web itself.
As a substitute of constructing on this world-class research history, the Trump administration is slashing R&D funding, firing federal scientists, and squeezing leading research universities. This week’s motion plan recommends investing in R&D, however the administration’s actual budget proposes cutting nondefense R&D by 36%. It also proposed actions to higher coordinate and guide federal R&D, but coordination won’t yield more funding.
Some say that corporations’ R&D investments will make up the difference. Nonetheless, corporations conduct research that advantages their bottom line, not necessarily the national interest. Public investment allows broad scientific inquiry, including basic research that lacks immediate business applications but sometimes finally ends up opening massive markets years or a long time later. That’s what happened with today’s AI industry.
Supporting immigration and immigrants
Beyond public R&D investment, America has long attracted the world’s best researchers and innovators.
Today’s generative AI is predicated on the transformer model (the T in ChatGPT), first described by a team at Google in 2017. Six of the eight researchers on that team were born outside the US, and the opposite two are children of immigrants.
This isn’t an exception. Immigrants have been central to American leadership in AI. Of the 42 American corporations included within the 2025 rating of the 50 top AI startups, 60% have not less than one immigrant cofounder, in accordance with an evaluation by the Institute for Progress. Immigrants also cofounded or head the businesses at the middle of the AI ecosystem: OpenAI, Anthropic, Google, Microsoft, Nvidia, Intel, and AMD.
“Brain drain” is a term that was first coined to explain scientists’ leaving other countries for the US after World War II—to the Americans’ profit. Sadly, the trend has begun reversing this 12 months. Recent studies suggest that the US is already losing its AI talent edge through the administration’s anti-immigration actions (including actions taken against AI researchers) and cuts to R&D funding.
Banning noncompetes
Attracting talented minds is just half the equation; giving them freedom to innovate is just as crucial.
Silicon Valley got its name due to mid-Twentieth–century corporations that made semiconductors from silicon, starting with the founding of Shockley Semiconductor in 1955. Two years later, a gaggle of employees, the “Traitorous Eight,” quit to launch a competitor, Fairchild Semiconductor. By the top of the Sixties, successive groups of former Fairchild employees had left to start out Intel, AMD, and others collectively dubbed the “Fairchildren.”
Software and web corporations eventually followed, again founded by individuals who had worked for his or her predecessors. Within the Nineties, former Yahoo employees founded WhatsApp, Slack, and Cloudera; the “PayPal Mafia” created LinkedIn, YouTube, and fintech firms like Affirm. Former Google employees have launched greater than 1,200 corporations, including Instagram and Foursquare.
AI isn’t any different. OpenAI has founders that worked at other tech corporations and alumni who’ve gone on to launch over a dozen AI startups, including notable ones like Anthropic and Perplexity.
This labor fluidity and the innovation it has created were possible largely, in accordance with many historians, because California’s 1872 structure has been interpreted to ban noncompete agreements in employment contracts—a statewide protection the state originally shared only with North Dakota and Oklahoma. These agreements bind one in five American staff.
Last 12 months, the Federal Trade Commission under President Biden moved to ban noncompetes nationwide, but a Trump-appointed federal judge has halted the motion. The present FTC has signaled limited support for the ban and should be comfortable dropping it. If noncompetes persist, American AI innovation, especially outside California, might be limited.
Pursuing antitrust actions
One among this week’s announcements requires the review of FTC investigations and settlements that “burden AI innovation.” Through the last administration the agency was reportedly investigating Microsoft’s AI actions, and a number of other big tech corporations have settlements that their lawyers surely see as burdensome, meaning this one motion could thwart recent progress in antitrust policy. That’s a difficulty because, along with the labor fluidity achieved by banning noncompetes, antitrust policy has also acted as a key lubricant to the gears of Silicon Valley innovation.
Major antitrust cases within the second half of the 1900s, against AT&T, IBM, and Microsoft, allowed innovation and a flourishing marketplace for semiconductors, software, and web corporations, because the antitrust scholar Giovanna Massarotto has described.
William Shockley was capable of start the primary semiconductor company in Silicon Valley only because AT&T had been forced to license its patent on the transistor as a part of a consent decree resolving a DOJ antitrust lawsuit against the corporate within the Fifties.
The early software market then took off because within the late Sixties, IBM unbundled its software and hardware offerings as a response to antitrust pressure from the federal government. As Massarotto explains, the Fifties AT&T consent decree also aided the flourishing of open-source software, which plays a significant role in today’s technology ecosystem, including the operating systems for mobile phones and cloud computing servers.
Meanwhile, many attribute the success of early 2000s web corporations like Google to the competitive respiration room created by the federal government’s antitrust lawsuit against Microsoft within the Nineties.
Time and again, antitrust actions targeting the dominant actors of 1 era enabled the formation of the subsequent. And today, big tech is stifling the AI market. While antitrust advocates were rightly optimistic about this administration’s posture given key appointments early on, this week’s announcements should dampen that excitement.
I don’t wish to lose give attention to where things are: We should always need a future through which lives are improved by the positive uses of AI.
But when America desires to proceed leading the world on this technology, we must put money into what made us leaders in the primary place: daring public research, open doors for global talent, and fair competition.
Prioritizing short-term industry profits over these bedrock principles won’t just put our technological future in danger—it is going to jeopardize America’s role because the world’s innovation superpower.
