
Research is complex and easily misunderstood. Scientific advance doesn't always precede, it often follows, engineering advance. Answering questions isn't always the goal, finding questions often is. We don't always seek to strengthen conventional wisdom, sometimes we seek to surprise it. What if we could rethink research so that its nurturing, through policy and management, harmonizes with its nature?
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.
Science and technology are distinct repositories of knowledge with distinct characteristics. The science repository of knowledge consists of facts and their explanations, and the technology repository of knowledge consists of human-desired functions and the forms that fulfill those functions. Of most interest to us is not the static nature of these bodies of knowledge, though, but their dynamic nature — how new science and new technology are created and evolve. That creation and evolution are mediated by mechanisms that comprise what we call the technoscientific method, the interacting combination of parallel and complementary engineering and scientific methods.
Human technoscientific knowledge is organized into loose hierarchically modular networks of question-and-answer pairs, and these questions and answers evolve in an intricate dance to create new question-and-answer pairs. Importantly, answers of a scientific nature can lead to questions of an engineering nature. Just as importantly, answers of an engineering nature can lead to questions of a scientific nature: a technological form that fulfills a human-desired function, as it performs that function, can reveal unusual phenomena that become scientific facts ripe for explanation — scientific questions ripe for scientific answers. New questions or answers are not equally easy to find. They are harder to find the further they are from existing answers and questions — from what might be called the "possible."
Sometimes conventional wisdom "disbelieves" that potential new knowledge will be useful — but, after further playing out, the knowledge is found indeed to be useful. This is classic creativity, whereby revolutionary ideas that run counter to conventional wisdom are ultimately proved useful. Flying machines heavier than air, evolution by natural selection, quantum mechanical action at a distance, wave-particle duality, the theory of continental drift, efficient blue LEDs fabricated from highly defective semiconductors — all these ideas were initially disbelieved but later proved correct and useful and hence changed the way we think and do. When surprise wins, previous conventional wisdom thought to be true must be deleted or unlearned — reminiscent of the saying sometimes attributed to Mark Twain: "What gets us into trouble isn't what we don't know; it's what we know for sure that just ain't so."
An essential role of research leadership, at all levels but particularly at the lowest levels, is that of gardener: even as researchers extend their interests, which naturally leads to the blooming of hundreds of flowers, research leaders must weed out distractions so the research organization maintains its critical mass, focus, and strategic advantage relative to other competing research organizations. It is better to forgo a line of research than to enter into it without the resources needed to develop critical mass. Research leadership must fertilize the plants and judiciously kill the weeds — otherwise the flowers will die before they go to seed.
Our hope is that such principles enable a new generation of “Research Labs 2.0” that go beyond our current generation of “Research Labs 1.0.” This new generation of “Research Labs 2.0” could come in very different shapes and sizes. They could have different organizational governance structures, funding models, technoscientific knowledge domain foci, and scales—some at the large scale of CERN, some at the medium scale of a research organization embedded in a larger corporation, and some at the small-scale of a philanthropically supported research institute. But they would all be aware of the timeless and overarching principles associated with nurturing research.
This new generation of labs would be aware that nurturing research must be aligned with what is being nurtured. It must be aligned with the nature of research and all its feedback loops and amplifications – not just the reductionism of physics, though that is important, but also the complexity sciences and the fusion of disciplines with a holistic “more is different” attitude (American Academy of Arts & Sciences, 2013; National Research Council, 2014). If the symbiosis between science and technology is not understood, then the full technoscientific cycle and its collective power will not be embraced. If the symbiosis between question-finding and answer-finding is not understood, question-finding especially is fragile and will go unsupported. If the importance of surprise and the overturning of conventional wisdom is not understood, then informed contrarians who are always questioning, always pushing past conventional wisdom’s comfort zone, will be weeded out.
This new generation of labs would also be aware that nurturing research requires an appreciation of research as a deeply human, collaborative, and social endeavor. Like all social endeavors, it requires active social construction: organization, funding, and governance that is aligned with research; a human culture that supports holistic technoscientific exploration; and the nurturing of people with care and accountability. Like all collaborative endeavors, it benefits from the full diversity and inclusiveness of the society in which it is embedded and to which it will contribute. Like all human endeavors, particularly those that require extraordinary performance, it requires nurturing the whole human being and spirit. We have borrowed his insights many times throughout this book but cannot help but borrow once more. To paraphrase the words of Ralph Bown, vice president of research at Bell Labs from 1951 to 1955 (Narayanamurti & Odumosu, 2016, p. 76), "[R]esearch environments reflect human relationships and group spirit. In short, successful research institutions should never forget that they are human institutions and they should place people above structure."
Our hope is also that in the more distant future, an increasingly effective generation of research laboratories, Research Labs 3.0, will emerge. This new generation would be based on improved principles that go beyond, and perhaps even overturn or displace, the ones articulated in this book. To reach beyond where we find ourselves today, we must continue to “learn how to learn” (Odumosu, Tsao, & Narayanamurti, 2015). We recognize two sources of learning: First, real experiments. As we become more deliberate in designing research organizations and watching them operate, we must use these same organizations as experiments from which to learn more about the nature and nurturing of research. The nurturing of research is a body-contact sport that requires direct human experience. Second, artificial experiments. As artificial intelligence advances and begins to learn how to learn, we look forward to mapping the nature of artificial learning onto the nature of human learning.
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