Inside Trump's Science Agenda: Anti-Science Claims, Fauci's Damage, DEI & China w/ Michael Kratsios

Is this administration anti-science? We want to essentially double the scientific output of the United States. Did we lose it, or did it lead to moments like Fauci? That's a great question. Are we in this populist moment in the West where science and technology are viewed as a tool of the elite, and therefore must be broken and destroyed? That's what's most tragic. That is a crazy fact. Has science stagnated in America? What the heck is going on?

Michael Kratsios, welcome to the All-In Interview. Thank you for having me. Excited to be here.

The Role of the Office of Science and Technology Policy

Michael Kratsios explains that the Office of Science and Technology Policy (OSTP) was created in the 1960s to coordinate science and technology policy across the administration. The setup is unique to the United States: there is no single agency for science and technology, but rather many agencies that each handle pieces of the enterprise — the National Science Foundation funds basic research, the Department of Energy runs the national labs, and the Department of War has extensive R&D programs such as DARPA. OSTP is the one office in the White House, and in the administration broadly, able to coordinate all of those efforts. Its job is to work with the president to set the national science and technology agenda and then implement it across all the agencies.

Asked whether he had held the role before, Kratsios notes that in the last administration he served as Chief Technology Officer of the United States. Since OSTP covers both science and tech, when Trump won he ran the tech portfolio for the president.

Is this administration anti-science?

It is not anti-science. One of the things I'm most proud of is the release a couple weeks ago of a new report called Science, a New Golden Age. Anyone who reads it will most likely see an administration that deeply cares about the American science and technology enterprise. We really want the US to be the home for the next great scientific discoveries, to empower young scientists, and to create an ecosystem that allows our greatest scientists to work on the hardest problems everywhere in the US. We're doing everything we can to align all of our agencies, as I just mentioned, to make that a reality.

But going back, there's a poll I want to give you from Nature, one of the scientific journals. They polled 2,000 of their readers, all scientists: 86% supported Kamala Harris in the election, and Donald Trump polled at 6%. Why is that? What is going on with the perception of the president and this administration as being anti-science?

To me, the scientific community has lost its way over the last few decades. America has been the place of some of the most amazing scientific transformations in history, and the government has played an important role in many of them — think of the Manhattan Project or Apollo, seismic events that only the US government could bring the ecosystem together to achieve. But over the last 15 or 20 years, science has been deeply politicized. We no longer ask the very hard and important questions: What is the scientific method? How should we approach it? Should we be questioning some of these conclusions? Instead, it's been dominated by dogma, and it really crescendoed and peaked in COVID, where suddenly there was a certain individual such that if you didn't agree with what he said, you were anti-science. To me, that is the most anti-science conclusion you could ever make. We have to return to the basics, and that's what we're trying to do in this administration.

At the basis of what you call the scientific method — for viewers who might not be familiar — is that you ask questions. The process of science is a process of asking questions and inquiry, and that inquiry leads to experiments, which collect data, and that data informs your view, and then you continue to ask questions. The idea that science is authority is almost antithetical to the basis of the scientific method, which is constant inquiry.

I could not agree more. What we as a government, for many decades, haven't taken the effort or the time to do is apply those same principles of the scientific method to the way we approach science policy and research and development. Right now, if you talk to your median lobbyists for the science community, the only thing they are fixated on, singularly, is the R&D budget. If the number doesn't go up, they haven't done their job and haven't "supported science." To me, that's a question. But the more important question every scientist should be asking is: is the way the US government spends $200 billion in S&T funding every year actually driving the best and biggest breakthroughs for the American people? Are there other ways to deploy that capital — to different organizations, different scientists, through different time horizons? There are so many questions we should be asking which we're not, and that's what Science, a New Golden Age tries to bring to the front.

I've heard this a lot from friends who are scientists and researchers, in academia, private industry, and elsewhere: there's a perception that this administration is cutting science funding. It sounds like what you're saying is that there's an allocation of resources, perhaps away from some things into other things.

Yeah. The most important thing to table-set initially is the distinction between a proposed budget and the dollars appropriated by Congress. Congress controls the purse strings — they're the ones who say how much science funding there will be, and they've consistently continued to fund science over the last decade-plus.

But the more interesting policy question, the way I view it, is that spending more money on the wrong types of things is not the right policy action.

What's an example of that?

Sorry, let me just say: in 2025 this administration disrupted, froze, or terminated $3 billion in unspent funds on active grants.

Yeah. So you terminated grants that scientists or labs had received approval for. Maybe you could give us an example—what was that $3 billion, and what are the other things your administration would say are not really the right place?

That's a good point. To me, the best example is the National Science Foundation. For some listeners, the NSF is essentially the premier funder of extramural basic research in the United States. It has about 8 to 9 billion a year, most of which is given to academics at universities who do research across all sorts of basic science domains.

Senator Ted Cruz and a Senate committee did an analysis of the grants given during the Biden administration and found that roughly one quarter—25%—of NSF grants during that period went toward DEI-related, quote unquote, science. If you think about that, that's an astronomical amount: roughly $2 billion a year times four years, so $8 billion of science funding went to these DEI-related initiatives. That isn't science, and it shouldn't be. It's a pure manifestation of the politicization of science, where the Biden administration stood up and said, "If you want to win a grant, you have to make sure you talk about some DEI-related factor in your application—that's the only way we're going to give you money." That obviously is not the way we should be doing it, and it is not gold standard science.

There were also cuts to climate science.

The conversation turned to cuts in climate research funding, which media and broad parts of the scientific community—journals, associations, and similar bodies—have sharply criticized. The interviewer asked the administration's view: how settled is anthropogenic climate change—the idea that the climate is changing because of human action releasing carbon into the atmosphere—how critical is it, is it a climate emergency, what do we know and not know, and why are dollars being redirected away from that research?

The guest replied that Secretary Wright has been very vocal on this and serves as the focal point for these issues within the administration. What Wright has advocated for publicly, and said many times, is that yes, the climate is changing, and yes, humans have burned fossil fuels over the last hundred years, and that has contributed CO2 to the environment. What is not true, and what the data does not support, is that it is a climate emergency.

One of the best examples is what happened with RCP 8.5. These are scenarios climate scientists use to estimate the impact of climate change on the world. This was the most extreme scenario, present in numerous national climate assessments and run by the IPCC as well. A few months ago, its developers determined that they could not, with any scientific integrity, substantiate continuing to keep this scenario, so they had to pull it down.

The interviewer noted that a lot of media coverage, re-reporting, and funding had been based on this simulation of the future that did not come to bear. The guest agreed: it was a crazy narrative. The extreme scenario—which most people believed would never happen—was this year proven never to happen, since it was even removed from all their predictions. Yet every media report of every climate assessment over the last 20 years has focused on that extreme example; that is what the media fixates on and what captures people's attention. The guest called that a real disservice to science.

Asked whether this explains why, over the last 10 to 15 years, funding flowed into climate research and why terminating grants and reducing budgets is a rollback, the guest framed it differently: the administration wants to invest in technologies and science that will ultimately create abundant energy for Americans. That includes winning the fusion race, with a target set for 2035, and it has been one of the most forward-leaning administrations in the country's history on nuclear energy, trying to get that up to speed and supplying energy as soon as humanly possible. Technology, in its view, is what will have the biggest impact for everyday Americans.

The interviewer offered two arguments: China's carbon output eclipses the rest of the world, so a plus or minus 50% change in the US doesn't really move the needle. And then there's the question of whether it's worth the economic cost, particularly because it mostly impacts poorer communities—wealthy communities can afford alternatives, but poorer communities that lose access to certain energy sources have to pay the most.

The guest agreed, citing numbers roughly to the effect that two billion people around the world use very dirty fuels for cooking in their homes—wood, dung, or charcoal—which, according to UN reports, leads to roughly 3 million deaths every year. These are the people for whom clean fossil fuel could make a huge difference in quality of life. If we can accelerate the transition to alternative energy sources—and arguably that doesn't need the government to make it happen—some cases require technical breakthroughs like fusion, but for solar and battery backup the economic incentive is so strong, being cheaper, easier, and deployable, that the market is solving that problem on its own.

You can believe that carbon going into the atmosphere causes climate change, and that the world is getting warmer, but still argue that the best way to solve the problem isn't to go backwards by 30 or 40 years, but to go forward with new technology that replaces carbon—rather than forcing change by making things more expensive, which makes it very hard for people to adapt.

Absolutely. I keep going back to your point about China: any of these extreme policy reactions to this perceived problem would inevitably hurt Americans the most, without actually solving the problem—whether or not you believe it's happening.

So let's talk about the NIH and the stagnation of scientific progress in the United States. It's easy to look around and say we've got AI, gene editing, an understanding of the genome, flying cars—all of it came from the United States—so it would be easy to argue we're making great progress as a nation. And we have made great progress. But if you look at

NIH funding went from $14 billion in 1998 to $27 billion in 2003 and $47 billion in 2024. The budget has more than tripled since 1998, but there has not been a proportional rise in breakthrough treatments coming out of that funding. Arguably, people call it Eroom's Law — Moore's Law in reverse: outcomes per dollar spent have fallen roughly eightyfold since 1950, halving every nine years. Every nine years we get half as efficient a return on the investment we're making. So has science stagnated in America? What the heck is going on?

I think, generally, our argument is it has, and that's one example. The one that a lot of Americans see and feel and notice quite obviously is the speed of flight: in the 1990s you could fly on a Concorde, and now you can't. We're flying slower than we were 10 or 20 years ago, and I think we can do much better.

The question we always ask is why this is happening in the context of government funding. You could say the easy problems have all been solved — the low-hanging fruit has been picked, so it's harder to solve the next thing. Sure. But broadly, the issue is we have not been innovative in any way in how we actually conduct the science. Whether it's at NIH or NSF or any of our other science agencies, the answer has always been: keep doing the same thing but add more money and hope we get proportionally more outcomes, rather than asking harder questions — are there other ways we could be conducting the science, other types of scientists who could be getting the funding, other institutions that could be getting the money? Those are some of the questions we raise in New Golden Age: we should really be looking in the mirror and asking ourselves whether we're spending money in the smartest and best ways.

Why weren't we doing that along the way? And as you pour more money in, where does it go that makes the overall outcome less efficient?

There's no incentive to do that. The incentive on the Hill is often just to keep increasing budgets that ultimately flow down to particular districts or particular states. On the government side, there's no incentive to check your homework and reveal that what you're doing is not actually working very well. It's always easy to take a headline that you're increasing funding in some domain, and the work of evaluating it is actually quite hard — it's not easy to go through $47 billion worth of funding and figure out what's working and what isn't.

That's what we try to introduce. There's a concept of metascience in the report: setting up metascience units at both NSF and NIH where we actually start running experiments on different ways of doing funding, analyze them, course correct, and direct money toward places where innovation is actually occurring.

So you're going to start doing your own experiments on how you're allocating money to see what has the highest return. How do you measure that?

You start by figuring out what experiments you want to run. Take the National Science Foundation: almost all grants follow a standard format. A set of peer reviewers—maybe three or four people from a particular field—review all the applications and, as a group, select the ones they believe are most meritorious. It is merit-based, but it also often incentivizes scientists not to propose crazy, bold, out-of-the-box ideas; they tend to propose ones in the strike zone that the whole board will support.

One experiment we're going to test at NSF is a concept called golden tickets, where each evaluator is given one, two, or three golden tickets. This was initially tested in Denmark and some other places. The theory is that a reviewer can unilaterally, without the rest of the committee agreeing, select a particular grant—so you incentivize more interesting grants. Another cool aspect is that it incentivizes better people to participate on the boards, because having a golden ticket makes them more likely to want to take part. We want to run that experiment and see what kinds of applications get approved and what kind of science gets done.

It creates an incentive for scientists to propose wild ideas, because the way scientists typically get a research grant—which they need to do, since it's their living, paying their salary and their lab's—is to submit an application that looks like the kind of thing that will get approved. That's typically low risk, because if something is likely to succeed, the review board can say, "Great, we're giving that grant because we're confident the money is well spent." But the reality, as in venture capital, is that one out of ten things works. It's a power law—that one thing is worth 100x—and you want to have nine out of ten failures, because that means you're taking a lot of risk. That's really how you push the envelope, discover new things, and make big breakthroughs: you have to take risk, which means failure.

Exactly right. Another example: most NSF grants are roughly 18 months, which has become a natural equilibrium given academic calendars. But not all research ideas need 18 months—some need 3 or 6 months, some need 5 years. So another thing we're testing, which we proposed in New Golden Age, is different grant durations: fast-track grants for ideas that can be done in six months, with the option to apply for a longer grant if they work, as well as longer-dated ideas needing three, four, or even five years. At its core, almost everything Golden Age tries to do is meet scientists where they are—some ideas require 18 months, others 6—and make sure there are opportunities to at least propose their ideas for evaluation.

"Well, besides funding ideas, an alternative model is to fund individuals."

Funding People vs. Funding Projects

Funding individuals rather than ideas has been strongly advocated for, as we both know, in the venture capital world: you find great entrepreneurs, and they may have a crappy idea, but because they are who they are, they eventually make something amazing work. I was just reading again about Stewart Butterfield, who started Slack. He was working on a totally different business and had three million dollars left. He told the investors, "Should I give the money back? But by the way, we built a communication tool that we use in our engineering team." They said, "No, go ahead, pivot—make that the business." It turned into Slack, and they sold it for $30 billion.

The idea in science may be the same: you find great people, give them significant funding, and let them decide how to spend the money, rather than having some overlord scrutinize every dollar they're spending and every action they're taking. You get out of their way and say, "I trust that you're going to get somewhere. Here's a whole bunch of money—a lot more than you're asking for—and a whole lot of time. See you in 10 years. You'll figure something amazing out."

One manifestation of that is how we think about some early-career fellowships. The GRFPs are the flagship fellowship at the National Science Foundation. We give roughly 2,600 of these to the smartest and best aspiring PhDs in the country. The idea is that we give you this money to pursue your PhD, but it's totally portable, so you can take it anywhere you want. You can have universities compete for you, and ultimately you'll end up in a place where you're comfortable and can do your best research. That's rewarding the scientist as an individual and giving them the opportunity to pursue their studies.

The alternative is to go after big projects: the Human Genome Project, the Manhattan Project, the Apollo moon mission. China seems to be exceptionally good at this—in a central planning context, they set big objectives they want to achieve, then organize resources and allocate significant capital to reach that goal.

The interviewer asked whether China's centralized approach to big projects suggests an alternative funding model — and how the US, with its small labs, grant competition, and private industry, can organize and execute projects that require significant capital, time, and long-term commitment.

The short answer is yes, we have that capacity — but as argued in Science: The New Golden Age, we have lost our way on doing it. Most Americans look back favorably on the Apollo mission: it brought the country together around a discrete goal, and only the federal government could marshal the resources to accomplish it. The argument is that we have to return to that — not as the only thing we do, but as one thing we do alongside everything else.

Four flagship bets

The first is space. The president boldly declared in the first Trump administration that we would go back to the moon, and we're almost there: American boots back on the moon in 2028, a nuclear reactor in space by 2028, and the first elements of a moon base by 2030. These are big, bold bets that take a decade to accomplish, and we're going to do it.

The second is quantum computing. The president signed an executive order just last month launching a new national quantum initiative, with a key goal of creating a scientifically relevant quantum computer by 2028. This was a directive to the Department of Energy, and we'll be working very hard to hit that pretty crazy timeline. Your camp wants fusion by 2035, and we're trying very hard to get resources allocated at DOE, combined with private sector investment, to get there.

The last one is the administration's flagship project, the Genesis Mission: essentially doubling the scientific output of the United States by applying AI to our hardest scientific challenges. We fundamentally believe AI will be the biggest unlock to scientific discovery in the history of the world. Whether you're in materials science, chemistry, math, or physics, applying AI to your discipline will fundamentally change how you do science and accelerate it. We launched the initiative late last year, and now pretty much all of government is working toward that effort.

Why government funding, when private capital is flowing into AI?

The interviewer pushed back: hundreds of billions of dollars of private capital are flowing into AI, and there's a natural market incentive to use it. Does government really need to fund quantum computing and AI, versus funding things private capital markets won't touch — deep space research, the origins of the universe, pure physics, the fundamental breakthroughs everyone waves off? History shows those fundamental understandings eventually yield unanticipated applications. How are those selections made?

That's a great point. We've advocated aggressively that government-funded research should return its primary focus to basic, early-stage, pre-competitive R&D — discovery science that the private sector isn't incentivized to pursue and that only government can do. At the same time, big bold ideas that only government can undertake are also very important. With the urgency of a scientifically relevant quantum computer by 2028: there's lots of quantum activity in the private sector, but for them it's about commercial applications.

We want to create an instrument that can be used for scientific discovery and will pay huge dividends across the whole ecosystem. On AI for science, the nuance is that we're not funding the AI research the private sector is already doing. There is more compute and more money going into AI today than you could ever imagine, and the government isn't trying to compete in that space. What it's saying is: if you're doing basic research on all the important areas you mentioned, you should be considering how AI will impact or accelerate your work, and we want to help you along that journey.

I always felt like so much of the challenge with government is the complication—it's like entropy over time. You have all these different agencies and groups competing for budget, and everything balloons.

Is there a rationale for consolidating so many of our agencies into a single science and technology agency, better organized and prioritized, allocating capital to the most important things?

It's a perennial debate, and having reflected on it for many years, I honestly think it's a feature, not a bug. The alternative extreme is roughly what China is doing: a top-down, single-agency entity that sets priorities and tries to execute. They have been trying to figure out EUV lithography essentially since we put export controls in place in 2019, and no breakthrough has happened. There is nothing more important to their economy than solving that scientific problem, and they haven't been able to do it. To me, one of the most special features of our system is that we have people competing. This free-market approach to innovation is a huge feature of our ecosystem and an important reason we have all these breakthroughs.

— So that's fundamentally critical for our success.

I think so. The fact that the DARPA people and those working on national security–related R&D sit at the DOD and not at some science agency makes their work much better and more relevant to their mission.

Before we get to China and the great race underway across every domain—I don't talk to anyone in industry, government, or elsewhere who isn't acutely experiencing this competitiveness with China right now—I want to talk about how we allocate capital. NIH, NSF, so much of the money flows either to a government agency or to a university. It seems to me there are probably four channels, though you may have your own rubric:

1. A government agency takes the money and does the research itself.
2. A university takes the money; the lab is at the university, administered by the university, all done on campus—and we should talk about the challenges with that, which are really important to highlight.
3. Industry companies with an economic incentive do research, achieve breakthroughs, and get government money to help them.
4. Independent organizations like the Howard Hughes Medical Institute, the Mayo Clinic, and in Europe the Max Planck institutes—entities that are neither government nor private industry, sort of nonprofits.

How should we think about allocating capital among those four channels—why each is good, why it's not, and how the balance needs to shift over time so we get better ROI on our science dollars?

What you're bringing up here is one of the big reasons we even wrote the Golden Age report.

If you rewind history to 1945, World War II was ending. Vannevar Bush, who was the science adviser in my role for FDR, received a letter from the president asking what to do with the science enterprise after the war. Bush's response became Science, the Endless Frontier, the seminal work on how the US government should interface with the science community, and it has served as the north star for science funding for the last 70 years.

What Bush proposed was essentially the system we have today: the government funds basic research, primarily at universities. Researchers sprang up and did great basic research in the postwar era, and in parallel the national labs that helped build nuclear weapons during World War II did the intramural work. So there were two pieces: government and academia.

Why that mattered in that era is that at the time the vast majority of science funding came from the federal government—roughly 70% of R&D was paid for by the US government, about 30% by the private sector. Over the last 70 years there's been a dramatic shift: now roughly 70% of R&D is done by the private sector and 30% is funded by the federal government. As you correctly mentioned, new institutions have sprung up—philanthropies that fund focused research organizations, Howard Hughes, Max Planck Institutes, and so on.

The question now is whether the model Bush pushed forward—which led to the great discoveries of the last 50 years—is still as relevant today. Our answer is that it's not, and we need a refresh. That's why we wrote the New Golden Age report.

For us, the first basic question is always: is the government spending on something the private sector or others in the community, like philanthropy, are not incentivized to do? That should be your first cut at all points. Then ask what the most important priorities for the United States are.

That sometimes creates tension with the science community. Many people believe all discovery science is good and you should have no opinion about what's important. We disagree. The government is a set of elected individuals; Congress has a very strong opinion about where we should spend money and directs science funding all the time through its appropriations, and the executive branch should have some thesis about what's important for the country. We have to win on things like AI, quantum, nuclear, and bio, and there can be an overlay of the biggest priorities for the US government, making sure the government steps in where the private sector and philanthropy can't fill the need.

What is going on with university funding? There's this administrative charge universities have—you changed that. And what is this administration's view on universities taking capital allocated for scientific research, taking an administrative fee, and using that money in ways this administration views as counterproductive? Some people have made the case that the administration is being political with these changes because it doesn't like the politics or social views of university administrators.

My view as science adviser is that we should meet the best scientists wherever they are. If they're at a university, we should fund them. If they're at a focused research organization, we should fund them. If they're on their own in their garage doing incredible work and can pass a merit-based review panel, we should fund them in their garage. The idea that we're open to funding scientists outside universities has been twisted by the academic community into a belief that we're somehow anti-academic scientists. We are pro-scientists and we don't care where they are. That's a core tenet of the Golden Age that we're going to be pushing for the next few years.

Let's talk about the great race with China. In 2000, China was spending $33 billion a year; by 2021, $670 billion — a 19x increase. Over the same period, US spending grew roughly 3x. I'll quote a statistic that's hard to verify, but my estimate is that about a decade ago the US published roughly twice as many papers in scientific journals as Chinese labs and academics. Today, China publishes roughly 50% more in nearly every domain, with the exception of some life sciences — China has kind of raced ahead.

Why the scientific race matters

Why should people care? Isn't science for the benefit of humanity — doesn't everyone benefit from breakthroughs? I think the Chinese realized a few years ago that technological and scientific leadership is the most important foundational block for economic and national security. Everything we do as a country is, in my opinion, rooted in scientific and technological discovery. We see it with semiconductors today; the breakthroughs in transformers and other technology led to today's large language models. Literally everything powering our economy at its core came from some scientific discovery.

What I keep trying to push is this idea that centralizing science has historically not led to the breakthroughs you may want. The free-market approach — an extraordinarily vibrant venture ecosystem, paired with government science funding, paired with what industry is incentivized to do — ultimately leads to these great discoveries. I'm also very assured because we continue to be the place where everyone wants to come work, live, and study; everyone wants to build a business here and learn at our universities. That's what makes our ecosystem so special and unique, and that's why we have to nurture it and keep succeeding.

You could argue that some of our biggest breakthroughs were centrally planned, managed, and funded — the Human Genome Project, the Manhattan Project, Apollo, and so on. But generally, competitiveness in the market — the market-based system — yields greater risk-taking, greater pushing of the envelope, and ultimately greater outcomes. That's why the portfolio approach we talked about is so important: we set bold bets in quantum, space, and fusion, while at the same time opening the aperture for discovery science and a free-market approach to commercialization.

What China gets right

When we look at China, what do we see as being incredibly well done with respect to their policy? The playbook they've used for a long time is essentially copying our IP, creating cheaper alternatives of that technology, dumping them in the United States, getting our businesses to go out of business, and then squeezing us. You've seen that with a wide variety of technologies over the years, and it's something we need to be very cognizant of. The second area where they've taken — or threatened — action is around some of our critical minerals, which we realize are a very important piece of our larger tech and science supply chain. Those are things we have to constantly think about and prepare ourselves to be independent on.

But given the number of papers they're publishing — arguably credible, peer-reviewed — let's just say they're making breakthroughs and getting ahead of us in many cases. What's helping them there? The IP theft and market dumping are industrial trade policy, but on the core basis of discovery, are they not getting ahead? Are they just funding more? By some estimates they're spending roughly on par with us, but by some estimates they get 2x for every dollar they put in — by some estimates 4x, by some estimates 10x — because their labor costs are lower.

They have far more automation and lower supply chain costs, and their standards for how things operate are obviously different. So on a dollar-for-dollar basis, they are way overspending relative to us in terms of generating output, and it's showing up in the papers they're publishing. Is it just a function of spending more, or are there other things we could be doing differently?

Look, I think what we could be doing a lot more of is encouraging more Americans to enter the STEM fields. This is something that has been on my mind for many years, and a statistic I've tracked for a long time is the percentage of US-born PhD recipients in computer science. If you rewind the clock 30 years, I think it was 70% American and 30% foreign. Now it's inverted. To us as a country, I believe that having a STEM-literate workforce is one of the most important superpowers we could have, and we're doing everything we can to find ways to encourage our younger students to continue to pursue these degrees.

Another thing we have to take a lot more seriously is what I've observed in our science ecosystem: our young scientists, the ones just finishing their PhD and starting their academic careers, have one of the toughest jobs you can imagine. You're paid almost nothing, you're in a university, toiling away trying to do research. These are the most underpaid people you could imagine for what they're doing for our country. We have to return our scientific enterprise to rewarding them, giving them opportunities to work on their best ideas and allowing them to excel. That's what we're focused on.

So we train a lot of foreign students, we bring them in, they get PhDs here. Why don't we let them stay more? What immigration policy would bolster the points you made earlier about getting the right people into scientific research? We've got a lot of Chinese students that come here, get a degree, get a PhD, and then we don't have a program for actively retaining that talent. They go back and work in Chinese labs or Chinese industry, or in other countries. And China is now starting to attract scientists from India and from Europe. Why aren't we doing that, given that we don't have the homegrown talent pool in science? Shouldn't we be more active in recruiting that talent?

I think you've got to do two things. One, make sure we're encouraging young Americans to go into these STEM fields. And two, for those who do want to stay, allow them to pursue legal pathways to stay here.

So is that policy being heard by the administration? Is it accepted, or is it in conflict with a more America-first policy that's looking out for Americans first, making sure jobs are for Americans before anyone else?

Well, I don't think it's in conflict with the policy. Before we even start thinking about anyone else, we have to get our house in order about how we can get more Americans to pursue this. Again, these numbers around computer science should be very alarming for people. The idea that seven out of ten STEM-related PhD candidates in the United States are not American—anyone can look at that and say that just doesn't look right, given the way we've been educating Americans for so many decades. And I think we have a huge opportunity through a lot of these science programs to bring folks back in.

One thing I discovered in writing this book and this report: we used to have programs at the National Science Foundation that would actually support and encourage gifted and talented students in American high schools and middle schools. Those were stopped for some reason. Encouraging high-performing young students to pursue STEM in America was something an actual decision was made by the government to no longer fund. I think those are discouraging actions that we want to turn around.

Why is that? It seems silly.

It feels like it's part of this larger DEI effort. You can imagine—and you probably know well, being in California—there were all these initiatives out in San Francisco where they stopped teaching advanced algebra to students in high school.

And there's this battle right now at the University of California over SAT scores.

The battle over SAT scores at the University of California continues: professors are saying that kids are coming in unable to do math, and they have to run remedial math just to teach students basic mathematics at UC Berkeley — a school where, back when the SAT was still scored out of 1600, you needed roughly a 1500 just to get in. Berkeley stopped taking SAT scores, and now the damage shows up in the performance of the kids who arrive. The professors who initially wanted to drop the SAT are now saying no, no, no, we need it back.

These policies are fundamentally harming the progression of talented STEM kids in America and undermining the pipeline that produces the country's next generation of scientists. We should be rewarding the greatest and most talented Americans, giving them the opportunity to pursue their science and tech dreams and endeavors. What's most tragic is having kids with the potential to pursue this work while we actively run programs that discourage them from doing it — and that has to stop. The rest of the world is doing it, and talented people are getting paid a lot, given nice homes, and moving to China now.

This is why I keep harping on it: the core tenet of New Golden Age is thinking about how we can elevate the scientist again. The way we fund our programs, the types of programs we do fund, and how we structure our grants and fellowships should all be centered around the scientist himself. It's not about what institution you work at, or where you came from, or where you grew up. It's about you yourself — can you pursue gold-standard scientific work? And if so, we'll support you.

In the 20th century, particularly after World War II, scientists were celebrities — rock stars featured in magazines, newspapers, and television shows, rewarded economically with fame and notoriety. Did we lose that, or did it lead to moments like Fauci?

That's a great question. I do feel there are a few names today that meet that moment — someone like Demis at Google, for example, who has won a Nobel Prize.

Though 90% of people hate AI.

That's true. Maybe he can turn the tide on that one, I'm not sure.

He's probably the best qualified, but I think it's an uphill battle at this point. There's a deep anti-science, anti-technology sentiment, not just in the US but across the West. Do you think it's bred locally because people feel left behind? Historically, through great cycles, scientists and technologists are often scapegoats — viewed as elitists because they know things others don't. There's knowledge, access, control, power. When you have a new technology or understanding, you have something others don't. Are we in this populist moment in the West where science and technology are viewed as a tool of the elite, and therefore must be broken and destroyed?

I don't know about that, but what I often think about is what happened during COVID and what Fauci represented. I think he did more disservice to science than anyone in modern history. When he advocated for positions like masking students in schools, while pediatric societies were putting out letters saying it was okay for people to go out and collectively protest but not allowed to visit their dying grandmother in a hospital — no regular median American can listen to that and still take science seriously. There's a lot of healing that needs to be done. That's why our approach of going back to the roots of gold standard science is so important. We have to let people understand and trust what science is about, and see that it's an inspiring, good thing that can change our way of life — not some dogma, rule, or edict from on high, but a process we're all part of, all experimenting and learning about the world and universe we live in. I try to be more optimistic, but we really hit a low point during COVID, and it's going to take quite a while to dig ourselves out.

My observation during that era: I always assumed that if everyone thinks something, it's probably wrong. But if some percent of people argue viciously against it and some argue for it, there's some objective truth to be found in that. If everyone aligns behind something in a uniform way, something is really off.

What was scary to me was how so many people abandoned empiricism. The fundamental basis of science is that you gather empirical data — you ask questions, you inquire, you gather data, and you use that data to inform your conclusions. There wasn't a lot of empirical data being used to make conclusions, yet everyone lined up behind these conclusions and assumptions and was told to "trust the science." As a result, it not only destroyed trust in science, but raises questions: what happened to the scientists? Why did they all line up like that? Why did everyone feel it was okay to put down people who asked questions, when the basis of science is to ask questions? It's fine if people ask dumb or wrong questions — but there was this breakdown in scientists being able to ask questions without being shunned.

I could not agree more. Anyone who asked questions was criticized by the scientific community as being anti-science.

It's crazy.

Anti-vaxer, anti-this, anti-that, anti-science. You ask one question, you're anti-science. If you question some of the conclusions in the IPCC reports on climate change — you can agree with some things and disagree with others — but if you don't agree with it all, you're anti-science.

Well, no—but the idea that you would push back on RCP 8.5: if I had pushed back on that publicly three or four years ago, I would have been criticized dramatically by everyone as being anti-Trump, anti-science, a MAGA guy. The IPCC says we can't even talk about that anymore. I think if you stay the course and stick to gold-standard science ideals—being inquisitive, asking questions, following the scientific method—you'll ultimately be proven right.

I think one of your points in the report about the aging of scientists is worth highlighting. Maybe you could talk about where we are, because the scientific community we're working with today, the loss of STEM graduates, the loss of the pipeline may be hurting our progress with China.

No, we have to continue to back and support young scientists. One of the most alarming statistics—which Jay Bhattacharya, the director of NIH, shared with me—is that the median age of an intramural researcher at NIH is 71 years old.

71?

71.

That's the median age?

The median age. These are researchers who work at an NIH institution.

Wow. Isn't the retirement age—don't you get a pension before that?

I've got to dig into that statistic more, but I think so. I think there's a huge opportunity to bring young scientists back into the fold, so stay tuned—I think there's a lot of interesting stuff going to happen at NIH.

How do you get pure science research—physics, mathematics, astronomy—funded and get the attention it needs in an era where everyone is consumed with AI, which is an applied technology? AI can be leveraged in some of this other work, but how do you think about competing on AI? Every meeting I go into—it's AI this, AI that, chips, progress with China, open models. That's dominating the conversation in DC and the world, and I feel like we're leaving behind some really important advances we need to be making in fundamental research.

After A New Golden Age was released—actually on the same day—Russ Vought, the OMB director, and I wrote our annual R&D priorities memo. It lists the administration's priorities and how individual agencies should write their budgets to map to those research priorities. First and foremost, on the very first page, we talk about the importance of basic fundamental research—the things you mentioned. That memo serves as the policy of the United States for how agencies like NSF should be prioritizing those things. I'm excited to see us go in that direction and, as you say, keep reminding the world: there's an insane amount of capital going into R&D—really into AI—in the private sector. We should be thinking about the stuff only the US government can fund, and that is basic research.

After the publication of A New Golden Age, are there executive orders coming from the president to follow? Are there going to be asks of Congress? What actions do you need in the administration and with Congress to carry forward the ideals you lay out?

Totally. The first implementation document is this R&D priorities memo. It goes out to the White House and to the agencies and essentially tells them: these are the budget priority areas and practices you need to implement going forward. The top five research agencies—those with over $3 billion in R&D—have a report due back to us 90 days after publication on how they're going to implement it. You've already started seeing announcements from agencies on implementation: an XLabs announcement out of the National Science Foundation to fund focused research organizations, and NSF also put out an announcement around four-year PhDs done in partnership with industry, so people can graduate from the PhD program and go into industry much more quickly. I think these are the kinds of programs we'll be seeing across our agencies. The second piece is working with Congress on the appropriations to make sure they're aligned with the direction of A New Golden Age.

But I would just stay tuned. We have a lot in the pipeline, and the first big step is the White House saying that budgets must prioritize these things — you're going to start seeing that manifested over the next year.

One thing that makes me pull my hair out when I come to Washington — fortunately not as often as you have to deal with it — is that when you go meet with members of the House and Senate, all they want is funding for their people. They want money to flow to their district or their state. How do you balance that demand from Congress against what really matters — the science, how it has to get done, where the people and institutions are? It's not about spreading money to states; it's about achieving a clearly defined mission. The mission is what matters, not a money grab for everyone.

I think there are a couple of answers. First, and I'm very optimistic about this, most of the recommendations in the Golden Age report are nonpartisan or bipartisan. Rethinking how we deploy science capital, funding different institutions, and promoting individual scientists are all things that will be broadly accepted or welcomed on the Hill. The other thing that could work in our favor is that many of these tenets touch lots of different states. If you go out and say, look, there is really great work being done at a few select institutions in the Northeast, but there's lots of research done all over the country and we want to make sure the best scientists, no matter where they are, are funded — that can also gain a lot of support. So I'm optimistic, but as you know, the Hill will always be a slog.

And if 2028 happens and, let's say, a DSA person becomes president, will everything quickly flip back to the way it was? What institutional memory gets created by your administration and this return to a gold standard in science, versus things being driven by politics?

I'm optimistic, first, that we'll win in '28. But I also think these ideas I mentioned are pretty nonpartisan. If you're just someone looking at the science ecosystem and wanting it to succeed, these are generalizable ideas you can get behind. Our hope is that we can run really hard through the tape over the next two years and prove they're actually working — because then turning things around would be costly from a political capital standpoint, since they'll be working.

Michael Kratsios, director of the Office of Science and Technology Policy here at the White House — thank you for being with me today.

Thank you. This was so fun.