Scott E. Page, University of Michigan and Santa Fe Institute
Guest contributor
This entry is part of the CFHSS’s VP Equity Issues series on diversity, creativity and innovation / diversité, innovation et créativité.
Scientific inquiry proceeds most fruitfully when sufficient funding is spread across a complexity of disciplines to a diversity of researchers.
Whether put forth by Vannevar Bush, one of the godfathers of the military-industrial complex, or Richard C. Atkinson, the long-serving head of the U.S. National Science Foundation, the case for the funding of basic science remains largely the same even after 50 years – investment in basic research produces the knowledge that drives innovation and, in turn, human progress.
This faith in government funding of basic research rests (first of all) on the proven gap in profit-driven science. The demands of the marketplace obviously create incentives to explore many scientific pursuits, most often practical problems such as how to build faster computer chips, safer allergy medications, and more fuel-efficient cars. But businesses won’t set out to make the world a better place unless they can make money at it.
That leaves many fundamental questions related to the causes of disease, the workings of society, and the maintenance of the earth’s ecosystems in need of funding from governments. Finding solutions to existing problems is reason enough to support science research, yet government investment in basic science also encourages unguided exploration, which can result in solutions in search of problems, such as the laser. As odd as this sounds science often finds answers to problems we didn’t even know we had.
So why would I argue that the current science funding model is clearly inadequate to the needs of scientific inquiry? Why is this model antiquated? Because the sources and causes of innovation remain mysterious (and will always be so), which in turn requires new thinking about how best to finance innovation.
Innovation, in economic terms, resides inside the heads of people. What we find inside the pumpkins is that people possess ways of seeing problems and solutions – oftentimes different perspectives depending on the kinds of people viewing particular problems and solutions. People’s perspectives are accompanied by ways of searching for solutions to problems, something scientists call heuristics. When confronted with a problem, people encode their (often quite different) perspectives and then apply their particular heuristics to locate new, possibly better, solutions.
Individuals who perform best obviously possess good perspectives and heuristics (think Thomas Edison and his multiplicity of inventions), yet 30 Edisons each may have 20 useful heuristics while collectively possessing a mere 25. In contrast, a diverse team of individual innovators may on average only know 15 heuristics apiece but collectively know 40. When a diverse team applies those diverse heuristics, the effects can be superadditive. Watson plus Crick were far more impressive than either in isolation.
On a far larger scale, Silicon Valley’s breadth of bright engineers from different academic disciplines and from almost every corner of the globe out-innovates other technology hotspots with equal brainpower but less diversity.
Government funding of science must take this diversity calculation into account. Government spending on science today is in effect a giant hedge fund. Lots of money gets tossed around. Some investments yield little, while others produce enormous dividends. This “portfolio” metaphor for scientific funding leads to an intuition that diversity has value – that basic scientific research should be allocated to diverse research projects.
That intuition is correct – diversity does provide portfolio insurance – yet the value of diversity goes far beyond mere portfolio effects. Diversity can produce superadditive effects.
A breakthrough in one domain can be combined with a breakthrough in another to produce even deeper knowledge. Research on disease transmission by epidemiologists helps us understand the spread of disease. Research by computational social scientists on how to construct large-scale simulations of societies helps us understand how markets work and how economies collapse. When we combine just these two breakthroughs, we’re able to construct a third, in the form of high fidelity computational models of disease spread that enable us to learn when and how to intervene.
In short, the mathematics of innovation shows that one plus one equals three. Government can encourage scientific diversity in four ways:
First, they can encourage interdisciplinary research through programs such as the National Science Foundation’s Integrative Graduate Education Research Traineeship initiative, or IGERT, which funds Ph.D. students in novel, interdisciplinary programs. The diversity of study in the IGERT program breaks through the current incentive structures of the modern academy, which reward progress within disciplines. Well-placed (and sufficiently large) IGERT carrots can provide incentives for scholars to step out of the comfort of their home departments to work with interdisciplinary teams.
Second, the government can continue to support underrepresented scholars. In the U.S. fewer than two in 100 Ph.D.’s in physics are African American and fewer than two in 10 are women. The situation is similar for women and Aboriginal scholars in Canada. Yet, we know from biology, psychology, and economics that the inclusion of women and minorities not only changes the questions being asked within a discipline but also changes how those questions are answered.
Third, funding must loosen up, and not just the purse strings. Government grants, be they from the National Science Foundation or the National Institutes of Health, often require perfect scores from multiple referees. This tends to bias awards in favor of safer, more conservative grants. Fear of failure, which is unavoidable given that future prospects depend on past successes, exacerbates the tendency toward more mainstream research. Innovation won’t be produced by people producing safe ideas.
In its golden era of innovation, Bell Labs used to demand a certain failure rate. They believed too much success signified a lack of experimentation. Given that most breakthroughs in science come from someone seeing a problem in a new way, government needs to fund the space, resources, and opportunity for scientists to step outside of their usual boxes.
Fourth, the government can make commitments to big problems – finding a clean source of energy, exploring Mars, curing cancer, eradicating poverty and disease. Big problems create diversity by shifting attention away from techniques and toward solutions. Thus, they spawn multiple approaches. Big problems almost always unpack into lots of smaller problems, each of which requires diverse ways of thinking. And big problems make science focal and fun, encouraging more people, and more diverse people, to choose science as a career.
Many of the problems we face today are complex. They consist of diverse, dynamically interconnected parts. Certainly climate change, epidemics, terrorism, and poverty fit into that category.
Other problems are just plain difficult; finding a workable form of fusion, understanding protein folding, and curing diseases. We won’t solve these problems, the difficult or the complex ones, with current modest levels of funding for well-established routes of inquiry. We need more funding and more diverse ways of thinking.
The aim of governmental scientific funding is the production of innovation that improves the lives of everyone, and the seeds of innovation lie in seeing problems in new ways. The funding of science should reflect what powers innovation by rewarding diverse thinkers, funding interdisciplinary research, broadening the pool of scholars, and focusing attention on big problems.
Scott E. Page is the author of The Difference: How the Power of Diversity Creates Better Groups, Teams, Schools, and Societies, and the Leonid Hurwicz Collegiate Professor of Complex Systems, Political Science, and Economics at The University of Michigan, Ann Arbor.