Tons of words have been written about the Trump Administrations war on Science in Universities. But few people have asked what, exactly, is science? How does it work? Who are the scientists? What do they do? And more importantly, why should anyone (outside of universities) care?
(Unfortunately, you won’t see answers to these questions in the general press – it’s not clickbait enough. Nor will you read about it in the science journals– it’s not technical enough. You won’t hear a succinct description from any of the universities under fire, either – they’ve long lost the ability to connect the value of their work to the day-to-day life of the general public.)
In this post I’m going to describe how science works, how science and engineering have worked together to build innovative startups and companies in the U.S.—and why you should care.
(In a previous post I described how the U.S. built a science and technology ecosystem and why investment in science is directly correlated with a country’s national power. I suggest you read it first.)
How Science Works
I was older than I care to admit when I finally understood the difference between a scientist, an engineer, an entrepreneur and a venture capitalist; and the role that each played in the creation of advancements that made our economy thrive, our defense strong and America great.
Scientists
Scientists (sometimes called researchers) are the people who ask lots of questions about why and how things work. They don’t know the answers. Scientists are driven by curiosity, willing to make educated guesses (the fancy word is hypotheses) and run experiments to test their guesses. Most of the time their hypotheses are wrong. But every time they’re right they move the human race forward. We get new medicines, cures for diseases, new consumer goods, better and cheaper foods, etc.
Scientists tend to specialize in one area – biology, medical research, physics, agriculture, computer science, materials, math, etc. — although a few move between areas. The U.S. government has supported scientific research at scale (read billions of $s) since 1940.
Scientists tend to fall into two categories: Theorists and Experimentalists.
Theorists
Theorists develop mathematical models, abstract frameworks, and hypotheses for how the universe works. They don’t run experiments themselves—instead, they propose new ideas or principles, explain existing experimental results, predict phenomena that haven’t been observed yet. Theorists help define what reality might be.
Theorists can be found in different fields of science. For example:
Physics Quantum field theory, string theory, quantum mechanics
Biology Neuroscience and cognition, Systems Biology, gene regulation
Chemistry Molecular dynamics, Quantum chemistry
Computer Science Design algorithms, prove limits of computation
Economics Build models of markets or decision-making
Mathematics Causal inference, Bayesian networks, Deep Learning
The best-known 20th-century theorist was Albert Einstein. His tools were a chalkboard and his brain. in 1905 he wrote an equation E=MC2 which told the world that a small amount of mass can be converted into a tremendous amount of energy. 
When he wrote it down, it was just theory. Other theorists in the 1930s and ’40s took Einstein’s theory and provided the impetus for building the atomic bomb. (Leo Szilard conceived neutron chain reaction idea, Hans Bethe led the Theoretical Division at Los Alamos, Edward Teller developed hydrogen bomb theory.) Einstein’s theory was demonstrably proved correct over Hiroshima and Nagasaki.
Experimentalists
In addition to theorists, other scientists – called experimentalists – design and run experiments in a lab. The pictures you see of scientists in lab coats in front of microscopes, test tubes, particle accelerators or NASA spacecraft are likely experimentalists. They test hypotheses by developing and performing experiments. An example of this would be NASA’s James Webb telescope or the LIGO Gravitational-Wave Observatory experiment. (As we’ll see later, often it’s engineers who build the devices the experimentalists use.)
Some of these experimentalists focus on Basic Science, working to get knowledge for its own sake and understand fundamental principles of nature with no immediate practical use in mind.
Other experimentalists work in Applied Science, which uses the findings and theories derived from Basic Science to design, innovate, and improve products and processes.
Applied scientists solve practical problems oriented toward real-world applications. (Scientists at Los Alamos weretrying to understand the critical mass of U-235 (the minimum amount that would explode.) Basic science lays the groundwork for breakthroughs in applied science. For instance: Quantum mechanics (basic science) led to semiconductors which led to computers (applied science). Germ theory (basic science) led to antibiotics and vaccines (applied science). In the 20th century Applied scientists did not start the companies that make end products. Engineers and entrepreneurs did this. (In the 21st century more Applied Scientists, particularly in life sciences, have also spun out companies from their labs.)
Scientists
Where is Science in the U.S. Done?
America’s unique insight that has allowed it to dominate Science and invention, is that after WWII we gave Research and Development money to universities, rather than only funding government laboratories. No other country did this at scale.
Corporate Research Centers
In the 20th century, U.S. companies put their excess profits into corporate research labs. Basic research in the U.S. was done in at Dupont, Bell Labs, IBM, AT&T, Xerox, Kodak, GE, et al.
This changed in 1982, when the Securities and Exchange Commission ruled that it was legal for companies to buy their own stock (reducing the number of shares available to the public and inflating their stock price.) Very quickly Basic Science in corporate research all but disappeared. Companies focused on Applied Research to maximize shareholder value. In its place, Theory and Basic research is now done in research universities.
Research Universities
From the outside (or if you’re an undergraduate) universities look like a place where students take classes and get a degree. However, in a research university there is something equally important going on. Science faculty in these schools not only teach, but they are expected to produce new knowledge—through experiments, publications, patents, or creative work. Professors get grants and contracts from federal agencies (e.g., NSF, NIH, DoD), foundations, and industry. And the university builds Labs, centers, libraries, and advanced computing facilities that support these activities.
In the U.S. there are 542 research universities, ranked by the Carnegie Classification into three categories.
R1: 187 Universities – Very High Research Activity
Conduct extensive research and award many doctoral degrees.
Examples: Stanford, UC Berkeley, Harvard, MIT, Michigan, Texas A&M …
R2: 139 Universities – High Research Activity
Substantial but smaller research scale.
Examples: James Madison, Wake Forest, Hunter College, …
R3: 216 Research Colleges/Universities
Limited research focus; more teaching-oriented doctoral programs.
Smaller state universities
Why Universities Matter to Science
U.S. universities perform about 50% of all basic science research (physics, chemistry, biology, social sciences, etc.) because they are training grounds for graduate students and postdocs. Universities spend ~$109 billion a year on research. ~$60 billion of that $109 billion comes from the National Institutes for Health (NIH) for biomedical research, National Science Foundation (NSF) for basic science, Department of War (DoW), Department of Energy (DOE), for energy/physics/nuclear, DARPA, NASA. (Companies tend to invest in applied research and development, that leads directly to saleable products.)
Professors (especially in Science, Technology, Engineering and Math) run labs that function like mini startups. They ask research questions, then hire grad students, postdocs, and staff and write grant proposals to fund their work, often spending 30–50% of their time writing and managing grants. When they get a grant the lead researcher (typically a faculty member/head of the lab) is called the Principal Investigator (PI).
The Labs are both workplaces and classrooms. Graduate students and Postdocs do the day-to-day science work as part of their training (often for a Ph.D.). Postdocs are full-time researchers gaining further specialization. Undergraduates may also assist in research, especially at top-tier schools.
(Up until 2025, U.S. science was deeply international with ~40–50% of U.S. basic research done by foreign-born researchers (graduate students, postdocs, and faculty). Immigration and student visas were a critical part of American research capacity.)
The results of this research are shared with the agencies that funded it, published in journals, presented at conferences and often patented or spun off into startups via technology transfer offices. A lot of commercial tech—from Google search to CRISPR—started in university labs.
Universities support their science researchers with basic administrative staff (for compliance, purchasing, and safety) but uniquely in the U.S., by providing the best research facilities (labs, cleanrooms, telescopes), and core scientific services: DNA sequencing centers, electron microscopes, access to cloud, data analysis hubs, etc. These were the best in the world – until the sweeping cuts in 2025.
Engineers Build on the Work of Scientists
Engineers design and build things on top of the discoveries of scientists. For example, seven years after scientists split the atom, it took 10s of thousands of engineers to build an atomic bomb. From the outset, the engineers knew what they wanted to build because of the basic and applied scientific research that came before them.
Scientists Versus Engineers
Engineers create plans, use software to test their designs, then… cut sheet metal, build rocket engines, construct buildings and bridges, design chips, build equipment for experimentalists, design cars, etc.
As an example, at Nvidia their GPU chips are built in a chip factory (TSMC) using the Applied science done by companies like Applied Materials which in turn is based on Basic science of semiconductor researchers. And the massive data centers OpenAI, Microsoft, Google, et al that use Nvidia chips are being built by mechanical and other types of engineers. 
My favorite example is that the reusable SpaceX rocket landings are made possible by the Applied Science research on Convex Optimization frameworks and algorithms by Steven Boyd of Stanford. And Boyd’s work was based on the Basic science mathematical field of convex analysis (SpaceX, NASA, JPL, Blue Origin, Rocket Lab all use variations of Convex Optimization for guidance, control, and landing.)
Startup Entrepreneurs Build Iteratively and Incrementally
Entrepreneurs build companies to bring new products to market. They hire engineers to build, test and refine products.
Engineers and entrepreneurs operate with very different mindsets, goals, and tolerances for risk and failure. (Many great entrepreneurs start as engineers e.g., Musk, Gates, Page/Brin). An engineer’s goal is to design and deliver a solution to a known problem with a given set of specifications.
In contrast, entrepreneurs start with a series of unknowns about who are the customers, what are the wanted product features, pricing, etc. They retire each of these risks by building an iterative series of minimum viable products to find product/market fit and customer adoption. They pivot their solution as needed when they discover their initial assumptions are incorrect. (Treating each business unknown as a hypothesis is the entrepreneurs’ version of the Scientific Method.)
Venture Capitalists Fund Entrepreneurs
Venture capitalists (VCs) are the people who fund entrepreneurs who work with engineers who build things that applied scientists have proven from basic researchers.
Unlike banks which will give out loans for projects that have known specifications and outcomes, VCs invest in a portfolio of much riskier investments. While banks make money on the interest they charge on each loan, VCs take part ownership (equity) in the companies they invest in. While most VC investments fail, the ones that succeed make up for that.
Most VCs are not scientists. Few are engineers, some have been entrepreneurs. The best VCs understand technical trends and their investments help shape the future. VCs do not invest in science/researchers. VCs want to minimize the risk of their investment, so they mostly want to take engineering and manufacturing risk, but less so on applied science risk and rarely on basic research risk. Hence the role of government and Universities.
VCs invest in projects that can take advantage of science and deliver products within the time horizon of their funds (3–7 years). Science often needs decades before a killer app is visible.
As the flow of science-based technologies dries up, the opportunities for U.S. venture capital based on deep tech will decline, with its future in countries that are investing in science – China or Europe.
Why Have Scientists? Why Not Just a Country of Engineers, Entrepreneurs and VCs (or AI)?
If you’ve read so far, you might be scratching your head and asking, “Why do we have scientists at all? Why pay for people to sit around and think? Why spend money on people who run experiments when most of those experiments fail? Can’t we replace them with AI?”
The output of this university-industry-government science partnership became the foundation of Silicon Valley, the aerospace sector, the biotechnology industry, Quantum and AI. These investments gave us rockets, cures for cancer, medical devices, the Internet, Chat GPT, AI and more.
Investment in science is directly correlated with national power. Weaken science, you weaken the long-term growth of the economy, and national defense.
Tech firms’ investments of $100s of billions in AI data centers is greater than the federal government’s R&D expenditures. But these investments are in engineering not in science. The goal of making scientists redundant using artificial general intelligence misses the point that AI will (and is) making scientists more productive – not replacing them.
Countries that neglect science become dependent on those that don’t. U.S. post-WWII dominance came from basic science investments (OSRD, NSF, NIH, DOE labs). After WWII ended, the UK slashed science investment which allowed the U.S. to commercialize the British inventions made during the war.
The Soviet Union’s collapse partly reflected failure to convert science into sustained innovation, during the same time that U.S. universities, startups and venture capital created Silicon Valley. Long-term military and economic advantage (nuclear weapons, GPS, AI) trace back to scientific research ecosystems.
Lessons Learned
- Scientists come in two categories
- Theorists and experimentalists
- Two types of experimentalists; Basic science (learn new things) or applied science (practical applications of the science)
- Scientists train talent, create patentable inventions and solutions for national defense
- Engineers design and build things on top of the discoveries of scientists
- Entrepreneurs test and push the boundaries of what products could be built
- Venture Capital provides the money to startups
- Scientists, engineers, entrepreneurs – these roles are complementary
- Remove one and the system degrades
- Science won’t stop
- Cut U.S. funding, then science will happen in other countries that understand its relationship to making a nation great – like China.
- National power is derived from investments in Science
- Reducing investment in basic and applied science makes America weak
Appendix – How Does Science Work? – The Scientific Method
Whether you were a theorist or experimentalist, for the last 500 years the way to test science was by using the scientific method. This method starts by a scientist wondering and asking, “Here’s how I think this should work, let’s test the idea.”
The goal of the scientific method is to turn a guess (in science called a hypothesis) into actual evidence. Scientists do this by first designing an experiment to test their guess/hypothesis. They then run the experiment and collect and analyze the result and ask, “Did the result validate, invalidate the hypothesis? Or did it give us completely new ideas?” Scientists build instruments and run experiments not because of what they know, but because of what they don’t know.
These experiments can be simple ones costing thousands of dollars that can be run in a university biology lab while others may require billions of dollars to build a satellite, particle accelerator or telescope. (The U.S. took the lead in Science after WWII when the government realized that funding scientists was good for the American economy and defense.)
Good science is reproducible. Scientists just don’t publish their results, but they also publish the details of how they ran their experiment. That allows other scientists to run the same experiment and see if they get the same result for themselves. That makes the scientific method self-correcting (you or others can see mistakes).
One other benefit of the scientific method is that scientists (and the people who fund them) expect most of the experiments to fail, but the failures are part of learning and discovery. They teach us what works and what doesn’t. Failure in science testing unknowns means learning and discovery.
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Filed under: National Security, NIH (National Institutes of Health), NSF (National Science Foundation) |
It would make sense for those who aspire to do science in the US of today, to make a living as plumbers, septic installers, electricians . . . and submit their theories to the Germans and the Chinese to let them get on with the grunt work of the funding and the experiments.
The thing is, you have to have vision to understand this, and regrettably, it seems, few (in power) do. Or perhaps they simply don’t care any more. Sad days.
Excellent write up, as usual. I might not be apprised of the situation, but has Trump’s administration slashed or stopped investments in the theoretical and early experimental aspects that do not directly lead to products?
Steve, I hope your write up helps to understand that current policy of defunding universities research programs is wrong
Today’s economics Nobel is literally about how scientific research was instrumental to the industrial revolution https://x.com/NobelPrize/status/1977673139019538490
Nothing about science requires this institutionalized structure.
Conservation of institutions is conservatism.
End the institutions which are clearly manipulated by their administrators and science will again become essential and fundamental as the pressures of physics on human biology are felt again and cannot be insulated against by illusory, fiat wealth investment
An additional layer in this continuum is the field of “economic development.” Economic development professionals operate at the intersection of university-based science and the technology commercialization activity it fosters (via start-ups and licensing). They facilitate and promote the transfer of invention from lab to business enterprise … “bench to bedside.” They do this in part to “capture” some of the benefits of science and technology—and its attendant job and wealth creation—for the community where they work. Their tools include building or operating research parks and incubator facilities, usually with local tax or philanthropic support and often with additional university (non-federal) investments. Often these “bricks and mortar” initiatives include companion programs such as funding to support “proof of concept” and very early-stage commercialization, before VC funding is available. In these facilities start-ups and established companies may work side-by-side, creating a dynamic climate that helps build a community’s entrepreneurial ecosystem. These locally generated resources—including building lab facilities for start-ups who otherwise could not afford them—come on top of the federal funding cited by Steve above. While adding “at the margins,” on a collective basis they represent a significant addition to the nation’s technology commercialization capabilities, particularly in communities beyond the top tier university and venture capital-driven technology centers.
The damage already done to US science will take decades to repair if it’s that even possible. Most of the graduate degrees in science, technology engineering and math awarded in the last 50+ years have been awarded to foreign students, many of whom stayed on in the US and contributed to the US economy. Now they are looking elsewhere (see recent figures for web site traffic on PhD programs in the US — down significantly — and other countries — up significantly). All the US needs now is to start losing US scientists to countries more willing to fund their work.
I studied in the US and enjoyed it a lot, considered staying on and applying for a green card. Wild horses wouldn’t persuade me to go now.
In essentially every promising field of research in science and/or math, the US has plenty of bright, dedicated, hard working, sacrificing, well educated workers. Commonly they are very poorly paid — e.g., when go to buy a car or house or pay tuition for private education for children K-12 and college get laughs — so that in trying to support a family they are financially irresponsible unless they have another source of money, e.g., family money.
Result: Young person, don’t have a good net worth? Okay, imagine, start, own, run a successful BUSINESS. If also can make good use of something got in good versions of K-Ph.D. and own technical ideas, so much the better, but Gates, Jobs, Page, Brin, Zuck, Bezos had what from their own K-Ph.D. or own technical ideas? They did build on a lot from high end optics, ASML, TSMC, Intel, AMD, and the US military as customers. Only rarely is even a prestigious Ph.D. a qualification for a job with a salary that will support a family.
Great article – minor correction – UCSC is a R1!
(https://carnegieclassifications.acenet.edu/institution/university-of-california-santa-cruz/)
Thanks for making the effort to explain the basic differences between scientists, engineers, entrepreneurs and Investors. It might have been a necessary introduction to your hypothesis that „National power is derived from investments in Science.“ If you were right, the process which leads from heavy investments in science to wealthy and therefore powerful nation states should be repeatable. China seems to prove this hypothesis right. But would this simple mechanic also be repeatable for countries such as say Gambia, Honduras or the Philipines? I‘d doubt that! Having great science is definitely a good thing. It can make nation states wealthy. But natural resouces can do do that too (see Russia or the Arab countries). I assume you would reply that innovation is a renewable resouce while natural resouces are finite so that – in the long run – power via science would be the more sustainable option. But I‘m sure you will admit that it needs more than great science and the related ecosystem to make a nation state powerful. Geopolitics has its part, history and culture, too. Last but not least, I ask myself what power you are talking about. Is it the power to force or the power to influence and inspire? As a 56 year old German native, Amercan power to me meant much more inspiration and influence than force for most of my lifetime. Other people in other countries and regions on this planet might have a different view. But today the USA are in decline, the inspiration is long gone, the influence is fading. More investment in science won‘t stop that, I‘m afraid. It might not even maintain the power to force.
Thank you for a great summary. We need to return to funding science consistently at a very high level asap.
Steve. I have nothing but admiration for you and your contributions to society. But you are dead wrong about this and while I believe that the Trump Administration is probably using a shotgun instead of a snipers, but it’s definitely a target rich environment
There are too many to list but I’ll leave you with the following:
– Most funding doesn’t actually go to scientists. Until recently, universities had a concept called overhead, where they take upwards of 65% of research dollars earmarked by congress for research through an accounting norm (skipping details for brevity).
– Theorist vs Scientist – Is not a valid distinction. Most successful scientists do both. The people measuring reality are best placed to theorize about it. This is why Physical Review (a,b,c,d,e….) are filled with theories that no one has read, let alone tested or proven. You can most subsciences and this will be the case. We spend too much time writing papers, and not enough time running experiments. Biologists, Computer scientists, neurologists all do experiments (in a lab or not). Economists test their theories in the markets.
– No penalty for noise (& low risk for lies) – Science is a painful exercise. So people cheat. There is no downside to publishing noise. There is a little bit of reputational risk to publishing lies. I’ll leave to look into the Alzheimers scandal. (see https://www.science.org/content/article/potential-fabrication-research-images-threatens-key-theory-alzheimers-disease)
– Incrementalism (swinging for a foul ball)
– So much politics and power games
…
I could go on. But honestly funding is the only way of putting some accountability into the system.
‘– Most funding doesn’t actually go to scientists. Until recently, universities had a concept called overhead, where they take upwards of 65% of research dollars earmarked by congress for research through an accounting norm (skipping details for brevity).”
The skipped details are important. Besides the hated, bloated administrators, the overhead also pays for campus facilities, electricity and a/c, plumbers to fix the stopped up drains, security, shared research equipment, etc. It’s like the overhead for programmers in private companies: the programmer gets $100 k/year, but the company also pays for the other stuff that the programmer needs, like computers. Also, the overhead rate is more like 50% of the direct costs, so the scientist gets 2/3 of the total grant dollars, and the university gets 1/3.
Firstly, all of the equipment that goes to the lab (computers, etc) gets taken out of the scientists grant funding. (Luckily indirects are not applied to these dollars only the remaining funding). Most of the shared equipment I’ve delt with is usually through informally managed.
The large buildings and labs are generally paid through other funding initiatives (usually state funded)
Do you reasonably believe that 0.35 cents of every research dollar needs to go to these administrative functions? Is it really an egregious thing to simply lower indirect rate to 25%? Most private corporate grants contractually mandate an indirect rate of 0%
If we look at the top of the top universities, they have student bodies between 10K and 20K students. Making a simplifying assumption that anything over 10K is free. each of these schools brings in north ~$500M / year.
I recently went to a conference in VIenna. 51% of publications there were from China, rank 1, Japan occupied the second spot. The US and the UK lost the top ranks.
Universities became a place of conflict and hate. Main target is the Jewish minority, but not only. It’s hard to focus on science in such environments.
My brain reads “No science, no startups” — alarm bells. This kind of mono-causal oversimplification can only be anti-Trump clickbait — I ignore the post.
A few seconds later, guilt kicks in — “Don’t be so ignorant!” — I click the link. Literally the ninth word is Trump. My brain: “Alright, that says it all.”
I scroll a bit — should I really read this? My brain: “No, let ChatGPT analyze it critically.”
Conclusion:
The same kind of simplistic linear causality is presented without substance — no sources, no data, no valid projections — uncritically carried through. Typical NPC-scripted “science,” representative of much of today’s “NPC academia.” It’s just a patchwork of general knowledge and some combinatorial creativity, pretending to be expertise, seriousness, and understanding — enumerated to suggest strange, subjective, unscientific, and mostly personal goals.
This exact kind of NPC-scripted “science” needs to be exposed and discredited as pseudo. If this is the so-called “defense” of science, then it deserves to be opposed. Simple as that.
Thanks for writing this up, Steve. I really appreciated the framing here. One nit I’d offer: when you say, “But every time they’re right they move the human race forward,” I’d expand that to: even when scientists are wrong, their experiments still push us forward. Every failed hypothesis teaches us boundaries — what doesn’t work, what assumptions were wrong, what paths not to take. Embracing that “failure as progress” mindset is crucial if we want more people to pursue creative, risky, bold experiments.
This is a just-so story. Science has failed to produce anything of economic worth since around the end of Bell Labs. Feel free to list counterexamples. There aren’t any other than Fracking, which was primarily privately funded.
Thanks for putting your thoughts together- makes for interesting reading albeit simplistic. One major area that you seem to have forgotten is the area of regulatory science. As a member of that community it is appalling that you failed to include that just like all the producers in the country who fancy they have picked themselves up with their bootstraps and contributed to the country not paying any heed to the infrastructure of roads and postal system that gets their goods to other parts of the country or world.
The FDA, the EPA (federal and state) and CDC has been asking the basic questions and tried to keep drug/food and other related industries honest.
Is there bloat ? Most certainly there is but this break the dish and find out mentality is not suitable to the human condition, so accountability is needed but not by amateurish or more correctly novices who are claiming it is for the greater good when it is obvious just to make an extra few bucks during the ensuing chaos.
So clearly you seem to miss that and now all those who read the article and fell into the pro or con camp also are blissfully unaware. You need an addendum !
Good article by Steve, well supported by 2008 post based on my experience at the old Bell Labs:
https://archive.nytimes.com/dotearth.blogs.nytimes.com/2008/12/12/r2-d2-and-other-lessons-from-bell-labs/
The situation is even worse in Europe, particularly in Southern Europe. We face minimal investment in science and a weak startup ecosystem compared to the US. As one of the major consequences of this underfunding, our best talent emigrates to more developed European countries or to the United States, creating a vicious cycle where we lose the very people who could help build our innovation capacity. This brain drain compounds the problem – we not only lack the infrastructure and funding, but we’re also losing the human capital needed to change this reality.