The Genesis of Technoscientific Revolutions: Rethinking the Nature and Nurture of Research QUOTES

1 " Evaluation must be done in hindsight, after the work has been done, not for proposals for work to be done. That said, secondary factors must carry some weigh, because research results depend too much on historical contingency and luck. As articulated by Ralph Bown, vice president of research at Bell Labs from 1951 to 1955:
'A conviction on the part of employees that meritorious performance will be honestly appraised and adequately rewarded is a necessary ingredient of their loyalty. This appraisal, to be fair and convincing, must be based on the individual's performance and capabilities rather than wholly on the direct value of his results. A system which rewards only those lucky enough to strike an idea which pays off handsomely will not have the cooperative teamwork needed for vitality of the enterprise as a whole. "

― , The Genesis of Technoscientific Revolutions: Rethinking the Nature and Nurture of Research

2 " Great research labs are like big families, a lot of sibling rivalry, a very successful big family. There's a certain bonding that occurs that is really rather special ... I think it comes from that notion of it like being in a big family. There's some sibling rivalry, but everybody is doing fantastically well. "

― , The Genesis of Technoscientific Revolutions: Rethinking the Nature and Nurture of Research

3 " So long as module improvement respects the protocols by which the module connects to other modules, module improvement can proceed independently of those other modules.
An extreme case of this is when the protocols are between different levels of the modular hierarchy and when there is richness on both sides of the protocol. When the upper side of the protocol is rich, the knowledge base on the lower side of the protocol is often referred to as a 'platform' on which knowledge modules above it can be based. In science, Newton's laws were a platform on which both celestial and terrestrial mechanics could be based. In technology, the personal computer software operating system is a platform on which a rich set of software application can be based. Moreover, when the lower side of the protocol is also rich, the shape of the knowledge network becomes hourglass-like. In the case of technological knowledge, the waist of the hourglass is a distinguished layer or protocol, with technologies underneath implementing the protocol and technologies above building on the protocol - with both sides 'screened' from each other by the protocol itself. As a result, the number of applications explodes independent of implementation details; similarly, the number of implementations explodes independent of application details. The number of software applications built on the Windows operating system is enormous; the number of hardware and software implementations of the Windows operating system is also enormous.
In other words, imagine two complex adaptive systems, one organized modularly and one not. At one moment, both might be able to exploit their environments equally and thus be equally 'adapted' to their environment. But they will evolve at vastly different rates, with the one organized modularly quickly outstripping the one not so organized. Modularity appears to be an evolved property in biology, one that is mimicked in the organization of human knowledge. "

― , The Genesis of Technoscientific Revolutions: Rethinking the Nature and Nurture of Research

4 " Researchers and research organizations who aim to 'change the way people think or do' must have the freedom, not only to be contrarian, bot also the be wrong. Contrariness sometimes leads to failure, but from failure comes learning, and from learning very often comes implausible utility, the useful and surprising.
Contrariness is not the only thing required of researchers to achieve implausible utility, however. The second thing that is required is informedness. Conventional wisdom and existing paradigms 'work' - that is why we adopt them in the first place and that is why we resist so strongly their overthrow. If a researcher is going to take seriously observations and ideas that go against conventional wisdom, the researcher had better have good reasons for doing so - and the discipline to develop those good reasons. These reasons we call informedness - 'inside' knowledge or capabilities the researcher possess that the researcher's peers don't yet have. This inside knowledge makes the researcher think the researcher is right and conventional wisdom is wrong. The researcher is an 'informed contrarian,' going against conventional wisdom but in an informed way to reduce the tremendous risk associated with going against that very wisdom.
Like a financial arbitrageur who uses greater informedness about the true value of an asset to buy those assets currently undervalued by conventional wisdom, informed contrarian researchers are research arbitrageurs who use their greater informedness about the value of a research observation or idea to take seriously those ideas currently undervalued by conventional wisdom. "

― , The Genesis of Technoscientific Revolutions: Rethinking the Nature and Nurture of Research

5 " Why are surprise and consolidation both important to knowledge evolution? Because exploration and exploitation are both important as we create new, and make use of existing, knowledge to interact with the world around us. Surprise emphasizes exploration, the creation of new paradigms; consolidation emphasizes exploitation, the use and extension of existing paradigms. While both are important, the balance between exploration and exploitation, surprise versus consolidation, is not governed by a hard-and-fast rule. In an approximate way, the balance depends on the kind of world in which the evolving knowledge system is embedded and the speed with which evolution for survival must occur. The more complex and changing the world, the more reason to emphasize and incur the cost of exploration; the simpler and more static the world, the more reason to emphasize exploitation and avoid the cost of exploration.
In biological evolution, when organism variants are generated, those variants are tested in and by their world. Those that survive go on to reproduce, inheriting the original variation but also adding yet new variations. As formalized in Fisher's fundamental theorem of natural selection, the greater the variance in properties across organisms within each generation, the faster the rate at which the organismal population evolves, becoming fitter generation to generation. Variation, however, is costly, as most variants are less fit and die before reproducing, so the degree of variance is itself an optimizable and evolvable trait. The more complex and changing the world, the more reason to incur the cost of variance; the simpler and more static the world, the less reason to incur the cost of variance. The optimal rate of evolution or 'evolvability' depends on the kind of world in which the organismal population is embedded.
In knowledge evolution, analogously, potential paradigms are generated, and those paradigm variants are tested by being played out in the real world. The measure of variance here is the degree to which the paradigm differs from or contradicts conventional wisdom, hence the degree to which one anticipates surprise. Thus, the paradigm generation process can be skewed either toward anticipated surprise or anticipated consolidation. Skewing toward surprise, however, is costly, as most potential paradigms that disagree with conventional wisdom are wrong and will have low utility. Thus, the optimal degree of variance depends on the kind of world in which the cognitive entity is embedded. At one extreme, if the world is complex or changing rapidly, then the optimal variance might weigh anticipated surprise more heavily. Indeed, at this extreme, it might be optimal to explore new paradigms simply for their novelty and potential for surprise. At the other extreme, if the world is simple or changing slowly, then the optimal variance might weigh anticipated consolidation more heavily. Why not make use of conventional wisdom rather than make a risky attempt to overturn it?
Thus, there is a balance between paradigm creation and extension, but the precise balance is situational. Human societies and organizations might adopt the balance appropriate for world to which they had to adapt during the long-term course of human evolution. An engineered or augmented human cognition might adopt a balance more appropriate to the current world, and a purely artificial cognition might adopt whatever balance is appropriate to the world into which humans have embedded it. Most importantly, a human society with sufficient self-understanding might adopt a balance that is optimal for its environment and them might implement that balance in its public polocy that determines relative investment in the two - relative investment in research versus development. "

― , The Genesis of Technoscientific Revolutions: Rethinking the Nature and Nurture of Research

6 " Outstanding research leaders are rare and their jobs, while different, are just as demanding as those of researchers themselves. Successful research leaders must have all the characteristics of outstanding researchers, particularly technical depth and breadth, otherwise their technical vision and judgment will not be sound. But they also need to be grounded in a second, orthogonal way: the human dimension that delights in and nurtures people's overall well-being and success. "

― , The Genesis of Technoscientific Revolutions: Rethinking the Nature and Nurture of Research

7 " Engineering research is both extremely powerful and often underappreciated. Existing science can be a conservative force that denies the possibility of new technologies if they are inconsistent with current scientific understanding. But counter-to-current-science new technologies thrive and serve notice that nature, richer than we can imagine, is a fertile source of both new technology and new science.
We must go beyond Bush and realize that engineering research grounds scientific research in the real world and in real problems; it is a key conduit through which nature surprises us and forces us to be creative; and it is a key cross-check on science. "

― , The Genesis of Technoscientific Revolutions: Rethinking the Nature and Nurture of Research