President Donald Trump announced the formation of the Department of Government Efficiency, or DOGE, days after his re-election. Tasked with eliminating wasteful spending and streamlining federal operations, DOGE’s ostensible mission is to ensure every taxpayer dollar produces measurable results.

In the weeks following the announcement, the MAGA memeplex took specific aim at seemingly obscure government-funded research. And since the Elon Musk-led U.S. DOGE Service assumed its legally ambiguous power in January, both the National Science Foundation and National Institutes of Health have found their funding frozen, then unfrozen, and as of this writing, still in limbo. While the ultimate impacts of DOGE and Trump’s “efficiency” campaign remain unclear, early indications suggest that federally funded research will face steep cuts.

This would be a mistake. Projects that seem odd or impractical — on animal behavior, obscure molecules, or fundamental physics — may be easy targets for ridicule, but such studies have repeatedly yielded transformative breakthroughs. While it makes sense to pursue efficiency in government spending, the returns on federal science funding are, on average, extremely high.

In 1979, a Duke University team led by neuroscientist Saul Schanberg, began studying the effects of separating rat pups from their mothers. Their work — funded by the NIH — found that isolated pups experienced impaired development. Yet, strikingly, stroking the pups with a soft brush to simulate a mother rat’s grooming prevented these developmental issues from occurring. 

Several years later, developmental psychologist Tiffany Field saw an opportunity to apply these findings to human preterm infants. Approximately 10% of births in the US are preterm, and those infants face higher rates of both developmental complications and mortality due to poor growth, weakened immune systems, and extended hospital stays. Field — also partially supported by the NIH — conducted clinical trials in neonatal intensive care units to test whether a similar form of tactile stimulation could improve the infants’ trajectories. Babies who received massages for 15 minutes, three times a day gained 47% more weight than those who did not. Massaged infants had shorter hospital stays, reducing costs for families and health care systems.

By the mid-1990s, massage therapy for preterm infants had become widespread in U.S. NICUs. One study estimates that the practice may reduce hospital stays by an average of 3 to 6 days and save approximately $10,000 in medical costs per infant. ¹ If applied across the roughly 400,000 preterm infants born each year in the U.S., this could amount to $4 billion in savings. ²

This case exemplifies a broader pattern: Government spending on scientific research tends to result in returns that far exceed the initial investment. According to the Dallas Fed, science spending writ-large generates enough social benefit to pay for itself 1.5 times over and is responsible for roughly 25% of productivity growth since World War II — and that estimate is conservative. Other papers suggest that every dollar spent on science generates anywhere between $14 to $70 in social benefits. Some economists believe that all growth in living standards comes from scientific research and development. 

It's easy to defend research like the preterm infant studies. The practical application is clear, and the benefits appeared early and conclusively. Few people believe that the federal government should have no role in research funding. But when agencies fund research to, for example, levitate frogs, ³ skeptics reasonably ask: Shouldn't we focus instead on creating useful technologies or medicines?

But this perspective misunderstands how scientific progress happens. Scientific research broadly falls into two categories. Basic research seeks to understand fundamental principles about how our world works. Applied research develops specific technologies or treatments using that existing knowledge. Basic research often appears strange to outside observers precisely because it isn't tied to immediate applications.

And so there are scientists who study frog skin or become experts in the sex lives of flies. But that frog skin led to a new theory of rehydration, and ultimately the invention of oral rehydration therapy, which has saved over 70 million lives — most of them children. The sex lives of flies? Well, understanding how flies reproduce led to the development of a sterilized screwworm fly and the elimination of a common livestock pest, saving some $200 million a year.

The applications of basic science are often unexpected because new technologies can be broadly applied. NASA was certainly not trying to develop better vacuums when they invested in research on batteries — yet the result was the Dustbuster. NASA-funded research is also responsible for the fundamental developments behind LASIK eye surgery (laser research), TempurPedic mattresses (materials research), and even Astroglide (initially developed as a substance to improve heat transfer). These important (or, at the very least, useful) technologies all relied on doing basic science first.

Of course, none of this happens overnight. It often takes decades for something to go from “science” to “a new technology.” But basic research is necessary to get to a stage where funding the development of a piece of useful technology, or the clinical trial of a new drug, is even possible.

Consider CRISPR, the gene-editing technology with the potential to cure diseases caused by genetic mutations. In 1987, scientists in Japan investigating E. coli DNA discovered unusual repetitive sequences. It took another 18 years before a team of Spanish researchers recognized these sequences as part of bacterial immune systems, and another seven years to figure out how to use them to target and edit at a specific point in the genome. Though it took more than two decades, these fundamental insights, which might have seemed esoteric at the time, eventually enabled the development of CRISPR, one of the most important biotechnology breakthroughs of the century. 

This is not a one-off. Basic research is, on average, estimated to give even higher returns on investment than the average research endeavor. If all science returns 150% of investment, basic science returns even more. A study of hundreds of major manufacturing firms in the 1970s found that increasing basic research spending had three to five times more impact on productivity growth than other research and development investments.

However, these impacts are often impossible to articulate before the research has been done. The lack of a clear path to application means this research may seem pointless from the outside view. This makes it a prime target for efficiency-based cuts. We didn’t know that studying Gila monster venom would lead to the invention of GLP-1 agonists like Ozempic, or that horseshoe crab blood would prove crucial to vaccine development, or that studying bacteria in geysers would lead to the development of PCR, the technology which allows scientists to detect DNA in small samples, and on which much of modern molecular biology — from genetic testing and COVID diagnostics — rests. Basic research is often high risk — projects sometimes go nowhere or fail to provide meaningful results.  But some discoveries revolutionize entire fields.

If basic scientific research produces such high returns, why isn't the private sector eager to fund it? Several structural barriers make it particularly challenging for private companies to support such endeavors, even when the aggregate returns are compelling.

The first is time. Basic research typically takes about 20 years to go from "science" to "technology," and often longer. Few companies can justify waiting this long for a return, regardless of its magnitude. Shareholders and investors expect profits on much shorter timelines, typically quarterly or annual returns. Even the most patient venture capital rarely extends beyond a 10 year horizon. Governments, with their ability to think in terms of decades rather than quarters — and their focus on societal rather than financial returns — can more readily make these long-term investments.

Even if a company could wait out these timelines, they face a more fundamental challenge: Basic research is a public good, meaning private actors cannot capture the full value their investment creates. The knowledge generated through basic research is non-rivalrous (everyone can use it without diminishing others' access) and largely non-excludable (no one can be prevented from benefiting). This means many companies will benefit from the research, not just the one that funded it.

Take CRISPR. While companies like Editas and Intellia have begun to commercialize gene-editing technologies, they built on decades of foundational research funded primarily by government grants. The researchers who discovered these unusual DNA sequences in bacteria — and the institutions that funded them — won't capture the financial benefits from CRISPR applications, even though their work was essential to creating that value. Nor is CRISPR unusual: One study which looked at new drugs introduced between 2010 and 2016 found that every single one relied on federally funded basic research.

This value-capture problem is compounded by spillover effects, unexpected applications that emerge far beyond the original field of research. These spillovers often form the majority of the value from basic research, but are impossible to predict or monetize. When the Department of Defense funded ARPANET in the 1960s to help researchers communicate, few predicted it would evolve into the internet and transform almost every aspect of modern life. The original funders had no way to capture the massive value created across different sectors.

Finally, basic research requires a portfolio approach that private companies struggle to sustain. While the aggregate returns are high, individual projects are inherently high-risk and speculative. Many will fail to produce valuable results, while a few will generate extraordinary breakthroughs. This uncertainty makes it difficult for any single company to justify investments. Success requires scale — the ability to take many shots on goal and withstand individual failures while still coming out ahead. Governments can better absorb these risks while benefiting long-term from the hits.

The government’s unique structure and position allows it to play a distinct role from the private sector. Treating government funding like corporate investment is a false equivalence. Focusing on near-term returns will not make public investments more efficient in the long run. It merely eliminates the government’s unique advantages to advance scientific research for the public benefit.

The government may be in a better position to fund this work, but critics often question whether they can identify the right work to fund. A common objection to government-funded research is that — even if basic scientific research broadly offers high returns — the government is poorly placed to recognize good investments because they lack market signals to guide their decision-making. Or, more pointedly, the government simply has skewed political incentives.

While profit motives provide a natural guiding star for the private sector, federal agencies have developed their own methods for finding high-return opportunities. Agencies like the NIH and the NSF rely on peer review to evaluate grant applications, which use the expertise of scientists and researchers to identify the most promising projects. These processes are not perfect, but they represent a form of internal competition that mirrors market forces. Applicants must compete not only against others within their field but also against the broader pool of submissions, ensuring that only the strongest proposals receive funding. Typically, less than 30% of NIH or NSF grant applicants are funded. Every seemingly silly-sounding study has to outcompete many others.

Another potential argument against continued federal research funding is that research productivity has been steadily declining across multiple sectors, including agriculture, semiconductors, and pharmaceuticals. It is much harder to find new drugs today than it in the past. Pharmaceutical companies now spend 15 times more to bring a single drug to market than they did in the 1970s.

One theory behind this trend is that early discoveries were “low-hanging fruit." Now that these are exhausted, new ideas are harder to uncover and require significantly more effort. Another explanation, the “burden of knowledge” argument, proposes that as the body of scientific knowledge grows, researchers must spend more time mastering existing work before they can contribute something new.

If this is true, that might suggest that funding research is becoming less valuable over time. Perhaps science is just more expensive now, and each new discovery will be smaller. But it’s also possible that the decline in research productivity points to institutional hurdles rather than inherent challenges in discovery. Academic science has faced growing bureaucracy and siloed disciplines. The emphasis on near-term research outputs has stifled interdisciplinary collaboration and discouraged bold, exploratory research. These systemic barriers may artificially amplify the perception that ideas are harder to find.

Innovation getting more difficult and more expensive over time does not make research funding a bad investment. But, if these theories of what is driving this are true, this would suggest there is room to improve its returns.

Of course, it’s possible that both things are true — that new ideas are both hard to find, and that we have made them harder to find. The current peer review process, though rigorous and better than many alternatives, can present exactly this kind of issue. Scientists spend significant time on grant proposals at the cost of actually doing research. These proposals typically require preliminary data, which can further discourage high-risk, high-reward projects. Most grants also last only a few years, pressuring researchers to prioritize short-term results over long-term breakthroughs.

To better support curiosity-driven science, funding mechanisms need reform. Simplifying grant applications and reducing administrative overhead would allow scientists to focus on discovery. Extending grant cycles for exploratory research would provide stability for transformative work without the constant need to reapply for funding.

Shifting from a consensus-driven peer review process to one that allows for more reviewer discretion could also improve outcomes. For example, the Howard Hughes Medical Institute adopts a risk-tolerant approach, granting researchers greater freedom to pursue unconventional ideas rather than holding them precisely to their proposals. This model produces high-impact research papers at nearly double the rate of traditional NIH-funded projects. Incorporating elements of reviewer discretion, like discretionary funding overrides, into existing systems could unlock similar benefits.

Even with our current system, seemingly odd experiments in pursuit of basic science frequently yield transformative discoveries that improve lives and drive economic growth. This is true not only for headline-grabbing breakthroughs but also for projects that hover just below traditional funding thresholds.

Consider a 2019 paper that analyzed how universities allocate the windfalls generated by their football teams better-than-expected seasons. ⁴ Departments often use these surprise funds to support previously unfunded, “on-the-bubble” research proposals. These marginal projects produced valuable publications and patents, showing that even more research funding would continue to deliver returns.

Unfortunately, it appears likely that the Trump administration will fund less science, not more. It remains to be seen whether the administration's scientific cuts will make it through courts or Congress. But we can be confident that, on average, we will be worse off if they do.

It's not always possible to predict which projects will succeed, or how their benefits will manifest. But history shows that even seemingly inefficient investments in basic science often yield transformative returns over time. By funding the speculative, the strange, and the bold, we’re not just taking risks — we’re making some of the best bets for our collective future.