Eric Lander’s argument for public funding of basic research

Eric Lander, who co-chairs the President’s Council of Advisors on Science and Technology (PCAST) for the White House, gave a great talk at the 2015 National Math Festival in Washington, DC on April 16th, called “The Miracle Machine.”  The full talk is available from this page, specifically as a Word document.  Eric’s abstract was:

Many governments are currently redirecting money for basic research into more applied areas. Tempting as this is, it risks losing the spectacular payoffs that basic research has provided in the past — and can provide in the future.

This blog post is intended to summarize this talk.

Eric began by saying that “we all have to be able to make the case for basic research.”  With the recent global economic problems, budgets are tights and governments are tending to scrutinize their spending, looking for “clear objectives, short-term outcomes, and avoidance of waste. No line item in the national budgets has escaped this scrutiny. And that includes research.”

Eric then gave examples of the changes in government policies that have gone into effect in Canada, Ireland, and the European Commission, and those that are being discussed in the US, and asked “so what can possibly be wrong with wanting to have a clear case for precisely how investments in basic research will pay off?”

Eric’s answer was “absolutely everything!”  He said this is because “the distribution of returns from basic research … doesn’t fall off like an exponential; it has very fat tails.”

Eric then described the Miracle Machine, a system that repeatedly turns a large amount of basic research into a small number of transformative ideas and discoveries. He then gave examples of basic research that was done without known practical application, that later turned out to have transformative impacts, such as, among others:

  • the study of prime numbers later impacting national security and communications, specifically public-key cryptography;
  • the invention of the laser, now used in manufacturing and medicine among other fields;
  • research in particle accelerators leading to x-ray crystallography, now used to study human proteins and central to drug development;
  • computer science research into “an integrated virtual library that will provide uniform access to the large number of emerging networked information sources and collections that will link everything to personal information collections to collections found today in conventional libraries to large data collection” that, after a lot of private investment, led to Google;
  • discovery of bacteria in hot springs, in particular the DNA polymerase enzyme found in these bacteria, that is crucial in the polymerase chain reaction DNA amplification; and
  • questioning why jellyfish glow, which led to the discovery of Green Fluorescent Protein (GFP) that now allows scientists to study the internal architecture of cells.

These demonstrate Eric’s Miracle Machine:  “an amazing partnership between a public good—publicly-funded, basic research, where we don’t know precisely what it will deliver, or on what time frame—and then private investment.”  He said, “when economists try to figure out the return on investment of basic research, the numbers vary because it’s hard to measure precisely,” with estimated ROI between 20 and 60 percent per year.

He then explained the two parts of the Miracle Machine. “The first component is public investment in basic research. It has to be public. Private investors won’t invest if they can’t own the fruits, but the public can invest because it gets its return in the form of benefits for society and in greater tax revenues from the economic activity. The second component is private investment that comes along to enable commercialization.”

Lander described basic research as being different than other types of investments, where elected officials think they should allocate funds to specific projects. For basic research, he said, funds should be allocated based on experts saying what they think are great questions to study.  And to see that this is working, we should monitor the payoff of past basic research, and use this to argue that we should continue to invest in basic research.

Again, I’ve tried to capture some of Lander’s ideas, but the best thing you should do is to read the full text of his talk yourself.


Some work by the author was supported by the National Science Foundation (NSF) while working at the Foundation; any opinion, finding, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the NSF.


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Assistant Director for Scientific Software and Applications at NCSA, Research Associate Professor in CS, ECE, and the iSchool at the University of Illinois Urbana-Champaign; works on systems and tools (aka cyberinfrastructure) and policy related to computational and data-enabled research, primarily in science and engineering

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