A New Agenda for Academic Investigation
Before the revolutionary upheavals of the late 18th century, political leaders did not always look kindly upon innovation. It implied a break with tradition, the introduction of newness into political and religious affairs, and was thus often viewed with mistrust. Such times, of course, are long past. Today’s political leaders actively seek innovation—albeit a narrower form of newness in technological innovation—as the basis for fostering jobs, prosperity, and economic growth.
The study of innovation has often happened at two disconnected units of analysis. Economists, sociologists, and political scientists have generally seen innovation from a high altitude where it is removed from the small-scale processes that, for instance, move discoveries from the lab bench into the marketplace. These scholarly models hold that academic research has over time become more interdisciplinary, problem-oriented, and entrepreneurial. As John Ziman argued in his 2000 book Real Science, research after 1960 became a “wealth-creating technoscientific motor for the whole economy.”
Three Scholarly Models of Innovation
Triple helix: A model that considers the interactions between government, academia, and industry in explaining knowledge generation with an especial focus on the role of entrepreneurial academicians and the university as a source of innovation.
Mode 2: Problem-solving knowledge production that brings together interdisciplinary teams of experts to tackle real-world questions in a specific context. This is in contrast with “Mode 1” knowledge production that is investigator-initiated and confined to a specific research discipline.
Post-academic: A model of research in which activities are done in a collective and trans-disciplinary fashion; similar to “Mode 2,” it is also typified by a steady-state funding regime with a focus on utility and solving practicable problems which, in turn, requires especial attention to ethical questions.
But national R&D policy has always been heavily goal-oriented. New models (see sidebar at right) for knowledge-making better reflect the experiences of university-based scientists and engineers than those in the corporate world that employs most graduates. At the scholarly spectrum’s other end, historians who study innovation have produced detailed case studies that provide different perspectives than the broad models of innovation by looking at specific events, institutions, or individuals. Yet it is difficult to extrapolate a broader picture from these well-researched “trees” in order to understand how the whole “forest” works.
What is often lacking is a middle ground that makes extrapolation possible—the tools and analyses that can help connect specific empirical studies to more comprehensive models of innovation and technological change. Bridging this gap would complement recent innovation policies that aim to support regional technological innovation as a key link between specific locales and the “national system.” Understanding innovation is crucial as the U.S. government moves to renew its investment in the innovation infrastructure. This is especially important as Congressional wrangling last week delayed reauthorization of the America COMPETES Act, which would supply $86 billion for scientific research, innovation, and education.
Recently, Christopher J. Newfield, a researcher with the National Science Foundation-supported Center for Nanotechnology in Society organized a workshop in Lyon, France. Catalyzed by the tenth anniversary of the U.S. National Nanotechnology Initiative, the workshop brought together academics and policymakers from several countries to re-think how a decade’s worth of research on the social implications of nanotechnology might inform broader innovation policy and perhaps inform understanding of how innovation works. Attendees presented several new perspectives on innovation that spanned levels of analysis ranging from specific case studies to general theories of innovation and policy formulation.
The common message was that finding this middle ground is possible, but first we need to re-evaluate what we mean by innovation, how we understand it, and, perhaps, to consider some heretical thoughts about questioning it as a universal good and panacea. Let’s now consider each of these observations in turn.
The value of innovation
First, the heresy. Rarely does anyone question the value of innovation. But is it always beneficial? Good intentions aside, innovation as a historical force doesn’t always create jobs. It sometimes destroys them, as Amy Sue Bix argued in her book Inventing Ourselves Out of Jobs. Automation and innovation, from the 1920s through the 1950s, displaced tens of thousands of workers—think of the conflict between Spencer Tracy (a proponent of automation) and Katherine Hepburn (an anxious reference librarian) in the 1957 film Desk Set.
But what of broader societal benefits innovation brings? A recent book by Stanley Joel Reiser, Technological Medicine: The Changing World of Doctors and Patients, suggests that, at least in the world of healthcare, innovation is not always an unalloyed good. In his study of several medical innovations, Reiser concludes that it produces winners and losers—and the winners are not always the patients. Sometimes, instead, they are hospital administrators, physicians, or Big Pharma.
As Reiser argues in the case of some medical technologies, technology for its own sake can lead to unexpected outcomes and moral dilemmas. An especially compelling example he gives is the invention of the artificial respirator: while saving countless lives, this medical innovation also created ethical, legal, and policy debates over, literally, questions of life and death. Moreover, there is the broader ethical question of whether it is better to spend large amounts of money for medical technologies and treatments that will benefit future generations if this means less funding to address current medical needs.
At the CNS workshop in Lyon, economist Shyama Ramani raised similar issues with regard to how countries such as India were attempting to imitate U.S. nanotech policies. Her conclusion was that monies currently being spent for future nanotech innovation would be better spent on alleviating current environmental problems such as water remediation and agricultural productivity. The innovation needs of developing countries and emerging markets are not likely to map onto the priorities of countries such as the United States.
In other words, as Ramani argued, India’s proclivity to model its science, innovation, and intellectual property policies on those in countries like the United States—so as to compete in fields such as nanotechnology and biotechnology—may ultimately hinder India’s ability to serve the real needs of its people. Ramani also suggested that India not produce nanotech for the global market but rather for a global “technological commons,” which is more focused on the specific needs of emerging markets.
What is a “national innovation system”?
But these country-level priorities raise the question of a “national innovation system” making these sorts of decisions. Does such an entity exist—can it? Perhaps, as Berkeley economist David Mowery quipped, a “national innovation system” is a fiction like the Holy Roman Empire: not national, not about innovation, and not a system. This witticism is worth unpacking because it illuminates the components of innovation that we don’t fully understand.
First of all, are there really national innovation systems? Or is this a convenient way for academic and policymakers to parse something larger? Historians who have long studied the flow of technologies across borders and between nations would question that such a creature has rarely, if ever, existed. Andrew Jon Rotter makes this case, albeit with an extreme example, in Hiroshima: The World’s Bomb. Here we find that there are no national nuclear weapons programs—they have always been international in nature. The Manhattan Project, after all, was a multi-national undertaking by American scientists and engineers who were joined by their British and Canadian counterparts and dozens of high-profile refugee scientists from Germany, Italy, and Hungary. No nuclear weapons program then or since has been “home grown.”
The same could be said for “national” space programs, which also depend on much common engineering knowledge, and today’s “national” nanotech programs, which also build on shared engineering and scientific knowledge. The upshot: All innovation stems from a “transnational” network of knowledge circulation. A state that invests in R&D must, of course, have the capability to draw from this pool, but there is no guarantee that it will do that in ways that lead to economic growth and jobs. Simply put, too much focus on the “national” suggests a closed system that is ahistorical.
What happens if we de-center the nation from the narrative and think about innovation as a fully transnational phenomenon? This challenges the persistent inclination to frame innovation just a matter of national economic competitiveness. This would also entail reconsidering the metrics we use to evaluate success or failure in the innovation arena (patents, publications, numbers of engineers produced) by including ones that are more “purpose-driven.”
To use the case of nanotechnology, for example, the societal goals of investing in the NNI included more environmentally sustainable energy technologies and better healthcare technologies. How are we doing? The President’s Council of Advisors on Science and Technology recently completed its third review of the initiative. Beyond the traditional metrics cited above, PCAST concluded more attention was still needed to the “commercial deployment” of nanotech products and praised the idea of new “Signature Initiatives” to encourage application-specific R&D.
Innovation, however, means more than just bringing new products or market. If we are to think in terms of innovation systems, then this systemic view must be more wide-ranging. This means taking a view toward innovation that encompasses more than the traditional idea of introducing new “things” into the global marketplace. MIT economist Eric von Hippel notes that throughout history the use and re-use of existing technologies has been a powerful driver for innovation as well as the more traditional notion of supplier innovation. Von Hippel’s attention to the user complements British historian of science and technology David Edgerton’s argument that an over-commitment to “techno-nationalist” viewpoints obscures the reality of how innovation occurs.
Finally, in the United States, there is hardly an “innovation system” if one means a coherent set of policies, processes, and institutions working in concert. As historians know, metaphors and analogy have power to shape and frame debates and policy. Rather than thinking of an innovation system, with its flowcharts, performance metrics, and feedbacks, a more useful metaphor is that of an ecosystem. Complex and dynamic, ecosystems encompass the local, the regional, the national, and the global.
Such a metaphor also encourages us to think about the role played by niche and interstitial actors. For instance, in the 1980s and 1990s, futurists and visionaries played a powerful role in stimulating support for nanotechnology among the public and policymakers by generating ideas about what the field could be. In addition to the more familiar institutional actors, other components of the system that require additional consideration include visionary thinkers, long-term and sort-term goals, marketing, design, investors, entrepreneurs, popularizers, and skeptics.
Innovation in practice, scholarship, and policy
The power to shape the levers of innovation through such creative work is not new. Historically, artistic endeavor, broadly construed, has been a powerful driver of technological innovation. Advances in metalworking and ceramics traditionally originated in the workshops of artisans who produced objects valued more for their aesthetic quality than purely utilitarian ones. The feedback is powerful—in Renaissance Venice, improvements in glassmaking stimulated the production of more capable scientific instruments that played central roles in the Scientific Revolution.
At the CNS workshop, Roger Malina, a physicist and long-time editor of the art-and-technology journal Leonardo, proposed an idea for stimulating more of this creative “micro-innovation.” Similar in concept to micro-credit, a project would set aside small amounts of money to encourage innovation from unlikely quarters. Malina gave several examples of inexpensive products from the art-technology nexus that have produced interesting innovations such as smart textiles that change color in the presence of elevated CO2 levels. The idea of micro-innovation complements the use of prizes to foster larger-scale technological innovation, as White House science policy advisor Tom Kalil has written about.
Initiatives that would fund and cultivate new models like Malina’s “micro-innovation” are the province of policymakers, but they present a challenge to academics who study innovation: they must question the basic models of innovation. For decades, the predominant model was linear. Based on Science: The Endless Frontier, Vannevar Bush’s 1945 social contract for science, the linear model posited that investments in basic science research would produce new technologies and societal benefits—meaning innovation. Rhetorically powerful as well as easy to understand and explain to policymakers, deployment of the linear model ignores the historical contingency of Bush’s report, which has, for better or worse, been the touchstone for much U.S. R&D policy.
Bush, director of the Office of Scientific Research and Development during World War II, was an anti-New Dealer who sought to justify continued federal investment in science. Along with Harvard President James Conant, Bush was also eager to deflect criticism of the scientists who had produced weapons of mass destruction, namely the atomic bomb.
And since 1945, scientists and policymakers have pointed to a select group of basic science discoveries that led to specific innovations—solid state physics research led to the transistor and the laser, the discovery of giant magneto-resistance led to the iPod. But what if these are extreme examples that don’t reflect the everyday nature of innovation?
This might be just an academic question, but given the heavy investment in research as a tool for economic recovery, the validity of the model itself needs scrutiny. The linear model holds that investment equals societal benefits, but Bush’s actual report said little specific about jobs.
In 1925, the English mathematician and philosopher Alfred North Whitehead wrote that the “greatest invention of the nineteenth century was the invention of the method of invention.” Innovation today, as in the past, demands much more than just invention. What the 21st century needs is a better understanding not just of the method of innovation, but its goals, its transnational flows, its systemic nature, and the processes through which the “new” can become accepted, productive, responsive, and responsible.
W. Patrick McCray is a professor in the Department of History at the University of California, Santa Barbara and a researcher and former co-director of the Center for Nanotechnology in Society at UCSB. He is also a member of the Science Progress advisory board. This article is based upon research supported by the National Science Foundation under Grant No. SES 0531184. Any opinions, findings, and conclusions or recommendations are those of the author and do not necessarily reflect the views of the National Science Foundation.
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