Excerpt from Introduction

Science and technology have been key to the success and well-being of humanity, and will almost certainly continue to be so. In just this past century and a half alone, our daily lives have been revolutionized by scientific advances such as the theory of special relativity and the transistor effect, and by technological advances such as the light bulb, the transistor, the laser, the blue LED, and the iPhone. One can only imagine what advances in the coming century might prove likewise revolutionary—ultrapowerful quantum information systems, general artificial intelligence, productive and human-centered global socioeconomic systems, sustainable life on earth and in space—not to mention advances that we cannot even imagine but will likely prove even more profound. As eloquently articulated by US president Jimmy Carter (American Academy of Arts & Sciences, 2014, p. 27; Carter, 1981):

"Science and technology contribute immeasurably to the lives of all Americans. Our high standard of living is largely the product of the technology that surrounds us in the home or factory. Our good health is due in large part to our ever-increasing scientific understanding. Our national security is assured by the application of technology. And our environment is protected by the use of science and technology. Indeed, our vision of the future is often largely defined by the bounty that we anticipate science and technology will bring."

Because science and technology are central to modern life, public support for advancing them—in the formal process society knows as research and development (R&D)—is substantial. But substantial support of R&D means little unless the R&D that is supported is effective. We are particularly concerned about research, the precious front end of R&D and the genesis of technoscientific revolutions that change the way we think and do. While development and research are both vital, research is far more fragile. Research is a deeply human endeavor and must be nurtured to achieve its full potential. As with tending a garden, care must be taken to organize, plant, feed, and weed—and the manner in which this nurturing is done must be aligned with the nature of what is being nurtured.

From our vantage point as practitioners of research, however, we have witnessed the emergence of three widespread yet mistaken beliefs about the nature of research —beliefs that are misaligned with its effective nurturing (Narayanamurti & Tsao, 2018). 

The first widespread yet mistaken belief is that technology is subservient to and follows from science and thus that the advance of science (so-called basic research) is the pacesetter of the advance of technology (so-called applied research). This belief, stemming in part from Vannevar Bush’s seminal report “Science, the Endless Frontier” (Bush, 1945), is limiting because it conflates research with science, hence narrowly confines research to the creation of new science and explicitly not to the creation of new technology. In fact, scientific and engineering research feed off each other to advance both in cycles of invention and discovery (Narayanamurti & Odumosu, 2016)—exemplified by the deeply interactive and virtually simultaneous engineering invention of the transistor and scientific discovery of the transistor effect at the iconic Bell Labs in 1947 (refer to the case study in Chapter 1). To emphasize the importance of the symbiotic union between science and technology, we will in this book call that union technoscience.

The second widespread yet mistaken belief is that the goal of research is to answer questions. This belief is limiting because it misses the complementary and equally important finding of new questions. In Albert Einstein’s words (Einstein & Infeld, 1971, p. 92):

The formulation of a problem is often more essential than its solution, which may be merely a matter of mathematical or experimental skill. To raise new questions, new possibilities, to regard old questions from a new angle, requires creative imagination and marks real advance in science. 

Finding a new hypothesis (a new question) is just as important as testing that hypothesis (answering that question), but is far less supported in today’s research environments. If Albert Einstein, were now to propose research into the relationships between space, time, mass, and gravity, he would have difficulty getting funded, but Arthur Eddington, who tested Einstein’s theory of general relativity, wouldn’t; Charles Darwin, who came up with the theory of evolution by natural selection, would have difficulty today getting his research funded, but a test of Darwin’s theory wouldn’t. In fact, both question-finding and answer-finding are vital to research and bolster each other in a symbiotic union.

The third widespread but mistaken belief stems from the “Wall Street” perspective that gained strength in the latter half of the twentieth century: the primacy of short-term and private return on invested capital. This belief when applied to research is limiting because it blinds us to the value of long-term and public return on invested capital. Truly path-breaking research seeks surprise. It overturns previous ways of doing and thinking in ways that cannot be anticipated—both in terms of when they will occur and whom they will benefit. Much of the benefit of research is long-term and public (extending beyond the organization that performed the research) rather than short-term and private (confined to the organization that performed the research). This has been true even for private industrial research laboratories, including the iconic ones active in the twentieth century, such as Bell Labs, IBM, Xerox PARC, Dupont, and GE. These laboratories shared common traits such as research cultures that emphasized learning and surprise, and an irreverence for boundaries of all kinds—between disciplines, between science and technology, and between finding questions and finding answers. As a consequence, their contributions had enormous long-term public benefit. Examples of their scientific contributions include information theory, the 2.7K cosmic microwave background, electron diffraction, scanning tunneling microscopy, high-temperature superconductivity, laser-atom cooling, and fractional quantization of electronic charge. Examples of their technological contributions include the transistor, the semiconductor laser, solar cells, charge-coupled devices, the UNIX operating system and C programming, the ethernet, the computer mouse, polymer chemistry, and synthetic rubber. When, instead, short-term private benefit crowds out long-term public benefit, R&D becomes weighted away from research, whose outcomes are less certain, toward development, whose outcomes are more certain. Ultimately, such a shift in the 1980s and 1990s caused the demise of research at the great industrial research laboratories.

In this book, we present a modern rethinking of the nature and nurturing of research, with the aim of significantly improving the effectiveness of research. By considering the nature and nurturing of research as an integrated whole, we focus on those aspects of the nature of research most germane to its effective nurturing, and likewise we focus on those aspects of the nurturing of research necessary for alignment with its nature. Going forward, our hope is that the nature and nurturing of research become a powerful positive feedback loop, as illustrated in Figure 0-1, in which society continues to better understand the nature of research so as to improve its nurturing, all the while experimenting with its nurturing so as to inform and improve an understanding of its nature (Odumosu et al., 2015). To that end, our hope is also that the audience for this book will be broad and include both those interested in the nature and “understanding” of research and those interested in the nurturing and “doing” of research.

Our rethinking of the nature of research, illustrated at the top of Figure 0-1, is organized around correcting the three widespread yet mistaken beliefs discussed above. Borrowing a phrase from the social sciences, we refer to the three corrected versions as “stylized facts” because they are empirical observations about the nature of research that we believe are true, general, and important. First, science and technology coevolve interactively to create new science and technology in what might be called a larger technoscientific method. Second, technoscientific knowledge is organized into seamless webs of question-and-answer pairs, and finding new questions and answers are both essential parts of an intricate dance that creates new question-and-answer pairs. Third, technoscientific knowledge evolves by the extension and consolidation of conventional wisdom, punctuated occasionally by surprise—and such surprise and the eventual impact of that surprise cannot be predicted or anticipated within conventional wisdom.

Importantly, our rethinking of the nature of research is both reductionist and integrative. On the one hand, our rethinking breaks technoscience and its advance into fundamental categories and mechanisms: science and technology, questions and answers, and surprise (which we identify with and research) and consolidation (which we identify with development). On the other hand, our rethinking emphasizes powerful feedbacks between the categories and mechanisms, with technoscience and its overarching advance a unified whole much greater than the sum of its parts. Moreover, although our rethinking of the nature of research was in large part motivated by a desire to better understand how to nurture research, we are cautiously optimistic that it will also be of value beyond that immediate motivation.

Our rethinking of the nurturing of research, illustrated at the bottom of Figure 0-1, is organized around three guiding principles that center on, respectively, aligning organization, funding, and governance for research; embracing a culture of holistic technoscientific exploration; and nurturing people with care and accountability. In developing these guiding principles, we drew lessons from two sources. First, we drew from our own and others’ experiences on what it means to “do” research. Our own experiences in research practice and the experiences of research leaders who nurtured spectacularly effective research organizations, including the iconic Bell Laboratories, comprise our “data.” Second, we drew from our rethinking of the nature of research: how best to align the nurturing of research so that the various mechanisms of associated with the nature of research are healthy and the feedback loops and internal amplifications between them are not short-circuited.

Throughout, we benefitted from the perspectives of distinguished scholars of research: Thomas Kuhn and Brian Arthur from the history and philosophy of science and technology; Stephen Jay Gould, Herbert Simon, Philip Anderson, Stuart Kauffman, and Joseph Schumpeter from the evolutionary biological, complexity, physical, and economic sciences; and Ralph Bown, Vannevar Bush, and Donald Stokes from the world of research leadership and policy. But, drawing on our experiences within technoscientific research practice, we reframe those perspectives in language that can be followed not only by scholars, but also by practitioners, of research.

This book is not a casual read, but we hope it will be a rewarding one. It contains a significant rethinking of the nature and nurturing of research—with new ideas as well as old ideas integrated in new ways.