Alex Tabarrok warns of the Trump administration’s “nationalization of American science.” A slice:
OMB, joined by some forty grantmaking agencies—NSF, HHS, DOE, NASA, DOD among them—has proposed a sweeping rewrite of the rules governing all federal grants, the Regulation for Federal Financial Assistance.
American science has long been state funded but not state directed. Since Vannevar Bush, money has flowed through many agencies to independent universities, allocated largely by peer review. The system has flaws—conformity, gerontocracy, waste—but it had one great virtue, the system was decentralized and not under state control. This rule proposes to bring science funding under top-down, state control.
Program goals must now be “aligned with administration policies and priorities” (§ 200.202). Merit review is subordinated to politics: “senior appointees must conduct these reviews,” ensuring “that discretionary awards advance the President’s policy priorities,” while “peer review remains advisory and does not replace agency discretion” (§ 200.205). And every grant becomes terminable at will, whenever it “no longer effectuates program goals, Federal agency priorities, or the national interest *as they exist at the time of the termination*” (§ 200.340, emphasis added). Universities must even ensure their subrecipients don’t “significantly damage the reputation of… the Federal Government” (§ 200.332)—a loyalty clause for scientists.
All this is sold as cutting “burdensome conditions,” a goal I would support, but sadly that is bullshit. The proposed rules add more paperwork and many more layers of bureaucratic review. Payment requests must include written justifications. Every disbursement gets screened through Treasury’s “Do Not Pay” system. Every recipient must run E-Verify. Applicants must disclose any employee who worked at the awarding agency within two years. And on top of the existing review machinery sits a new pre-issuance review committee of “senior appointees” second-guessing the experts. Fixed amount awards—pay for outputs, not inputs—an innovative reward mechanism are *eliminated*, so every award now gets routine cost monitoring and financial reporting.
Political review of every award, peer review demoted, agency review promoted, termination whenever “priorities” change. Chilling. It’s a nightmare of petty low-trust review of the kind that is already drowning science. I must deal with this kind of nonsense all the time. More is not better.
The Editorial Board of the Wall Street Journal identifies one reason for Zohran Mamdani’s electoral success: economically successful people are moving out of Gotham and thus leaving disproportionately more political power with the young and economically ignorant. A slice:
While out-migration has slowed in the last couple of years, high earners and married people continue to leave in large numbers. The data show that 13,662 taxpayers—roughly 1 in 1,000 resident taxpayers—on net left the state in 2024.
“The greatest net loss of taxpayers was among married filers with incomes between $100,000 and $500,000—a net loss of 8,200, or more than half of the total net out-migration, in 2024,” the comptroller’s office says. The highest out-migration rate was for households making $500,000 or more—about one in 100 of whom moved out that year.
The data underscore how the state’s high taxes and cost of living drive out top earners as well as middle and upper middle class families. Other flight propellants include New York City’s poor public schools and disorderly streets. Enrollment in New York City public schools has fallen 117,800 since 2019.
But here’s the political irony, which the comptroller’s office calls “one positive post-pandemic trend”: An influx to the state of single tax filers. These include the young urban progressives who form New York City Mayor Zohran Mamdani’s base and propelled his socialist comrades to victory in Democratic primaries last month.
Progressive policies in New York City and other big cities are driving out the moderate and conservative voters who have historically been an electoral check on bad governance. The New York voters who made George Pataki Governor in 1994 and Rudy Giuliani mayor in 1993 now live elsewhere.
These are the taxpayers who pay the bills for the welfare state and public unions. Good luck funding universal child care and socialist housing with the taxes from graduate students and community organizers.
Lethal ignorance of economics and history is certainly having a day in the United States, as reported by the Washington Post. A slice:
Democrats want to regulate and reform capitalism to curb its excesses and make the results fairer to everyone. The DSA, by contrast, seeks in the long term to replace capitalism, which the group sees as “a system designed by the owning class to exploit the rest of us.” They want workers to “run both the economy and society democratically to meet human needs, not to make profits for a few.”
And as National Review‘s John Puri notes, lethal ignorance of economics and history also now runs rampant among many Republicans. A slice:
One month later, Trump blew his first equity deal out of the water. He eyed an ownership stake in the struggling chip giant Intel, which was bleeding money and jobs despite billions of dollars in federal subsidies under the Biden-era CHIPS Act. Trump noticed that $5.7 billion in grants had previously been awarded to Intel but had not yet been paid. In exchange for releasing the promised funds, the administration asked for 10 percent of the company. Intel was happy to accede, winning the most powerful ally in the world.
Before 2025, economic analyst Scott Lincicome notes, the federal government had not made an indefinite, noncrisis investment in a healthy private company since at least the 1950s. The Trump administration has now taken more than 20 such stakes, targeting a range of industries from minerals and semiconductors to nuclear energy and quantum computing. There is no limiting principle at work; the government is taking equity in any company it can, on any terms, in any amount. It’s a scheme that progressives can fall in love with: Bernie Sanders is now clamoring to take government stakes in artificial intelligence companies.
This endeavor is enabled by a mix of old and new legislative appropriations written with few constraints on their deployment for stretchable ends: bolstering the defense-industrial base, accelerating innovation, etc. Congress clearly did not anticipate the current president’s cleverness.
Trump is reaping the benefits of the industrial policy pushed by his predecessor. The CHIPS Act and Biden’s green-energy law, the Inflation Reduction Act, gave the executive tens of billions of dollars that he could dangle. Last year’s reconciliation bill gave the Defense Department billions more to dole out, and the administration’s recent budget request would supercharge the military’s investment accounts.
Trump related his extralegal investment philosophy in an interview last December: “We should take stakes in companies when people need something. I think we should take stakes in companies. Now, some people would say that doesn’t sound very American. Actually, I think it is very American.” To call this approach transactional may sound trite — every equity deal is a transaction, of course. But conservatives have long insisted that government be the neutral arbiter of the marketplace, not an active participant. And, under law, the executive branch was never meant to trade special favors and taxpayer money for profit.
Eric Boehm reports this sorry but unsurprising fact: “More than $1 of every $10 in SNAP benefits went to people who didn’t qualify in 2025.”
Writing about fears of AI, Victor Menaldo explains that the predicted apocalypse isn’t coming. A slice:
But a job is not a to-do list of separable chores. Firms employ people for bundles of work held together by judgment, coordination, client trust and accountability. When a job’s tasks complement one another, automating the pieces does not reduce the job’s scope. It raises the value of the human work that remains.
When power looms automated much of weaving in the 19th century, they devastated many handloom weavers. But in the mechanized mills, the workers who learned to tend the new looms grew more valuable, not less. They still had to tie the weaver’s knot, swap a spent shuttle in seconds, adjust the warp tension so the threads wouldn’t snap and mind several looms at once. The workers who mastered these skills earned more even as the looms multiplied and cloth grew cheap.
For all its fluency, AI is not an all-knowing mind that does your job for you or better than you. It is a prediction engine that has digested a vast share of human writing.
That gives this machine astonishing reach — and several crippling gaps. It cannot tell you how biased its sources are, cannot show its work in a way you can audit, and can sound just as confident when it invents a citation as when it reports a fact. It is, in this sense, the near opposite of its closest ancestor, statistics, the tool that shows how much to trust a prediction. Statistics implies error bars; AI offers none.
Because AI cannot flag its own margins of error, an organization that deploys it widely can find itself operating in a fog of uncertainty — and that is where the true economic bottleneck emerges. When plausible-sounding output becomes cheap and instant, the premium shifts to the judgment required to tell whether a flawlessly formatted answer to a chatbot query is a breakthrough, a dead end or a hallucination.
Ryan Yonk and Ravi Roy remember Art Denzau.