(2012-01-31) Where Good Ideas Come Frombook By Johnson Summary
Michael on Where good ideas come from (book by Steven Johnson). This is a very interesting and easy-to-red book about creativity and innovation. The author identifies 7 patterns of innovation found in the human and natural world then illustrates the patterns with a variety of stories and explanations
few innovations are single great leaps but the accumulation of many small steps. In effect, each advance creates a new zone of possibility that can be exploited
Innovation occurs when ideas meet and merge, thus innovation inevitably has an environmental/cultural component
In a gas, the molecules move chaotically and reactions are rare. In a solid, the molecules barely move at all and reactions are rare. In a liquid, molecules move easily and reactions are plentiful
Similarly, organizations can be chaotic or rigid, and consequently not innovative
In this sense, large cities have some structure but a lot of fluidity of potential relationships. Innovative people with part of a big idea are more likely to encounter another person with a related part of the big idea – and be able to find a cheap place set up shop – and find customers – and financing – and media to advertise. These network effects support ideas colliding and then being brought to action. Naturally, there are rigid or chaotic big cities and fluid big cities – and these differ in their innovative output.
It’s not that the network itself is smart; it’s that the individuals get smarter because they’re connected to the network.
Much more recently, a study of scientists at work was conducted by placing cameras/voice recorders in their labs, offices and conference rooms. They transcribed all of their discussions and coded them for their purpose. Interviews with the scientists also recorded what they were thinking privately. The key learning was that the most important innovative “tool” in use was the conference room because this is where the scientists discussed their observations, critiqued analyses, solved problems together and refined their thinking. While the scientists had individual creative thoughts, the semi-structured interaction with others was what fueled the thinking leaps of each person.
Genuine insights are hard to come by….And so, most great ideas take shape in a partial, incomplete form. They have the seeds of something profound, but they lack a key element that can turn a hunch in to something truly powerful. And more often than not, that missing element is somewhere else, living as a hunch in someone else’s head.
One method of creating ideas is by forcing hunches to collide to see if they connect. These hunches are not quick insights, but hunches that develop over time as a person immerses themselves in a working domain. For example, Charles Darwin recorded in his notebooks
People in this time period couldn’t record things in their blogs or look in Wikipedia. The tool of choice in that day was a commonplace. A commonplace was a sort of journal where people copied passages, their own thoughts and doodles, drafted and revised essays and carried out many of the functions of a diary. Because these combined the authors own thoughts together with the thoughts of others, these mash-ups provided a way to keep memories alive and permit recombination. Darwin revisited these notebooks and kept renewing this information in his mind. These commonplaces mixed order and chaos.
Supported by reading a commonplace (where the randomness resembles liquidity) and by meeting and talking with others, creativity arises from multiple layers of liquid networks interacting. Though not mentioned in this book, Thomas Edison was famous for keeping notebooks with his ideas, theories and speculations. He dedicated 20 minutes a day to looking at old notebooks
Often the story of an innovation is told as a series of positive steps leading to the “aha” moment and success. This probably does happen, but the more likely case is that something that went wrong, and that made somebody look again, try again and re-think their approach.
In the section on liquid networks above the recording of scientists’ meetings were discussed. One interesting observation of the scientists at work was that when a scientist reported on an experiment gone wrong, their usual explanation was that they had made a mistake. But others, who were not part of the experiment, would interpret the results as a novel observation and suggest experiments to confirm the new observation.
Examination of other situations shows that more creative thinking occurs in environments with more “noise”, where disagreement is common, and data is not clean.
Exaption = external adaptation; where an idea or method from one domain is applied in another domain.
Analogy and metaphor are tools of Exaption.
Martin Ruef studied the social networks of Stanford Business School graduates. The most creative graduates (as measured by patents, product introduction, businesses started, etc.) generally had the most diverse networks that extended beyond their own organizations and included people with very different backgrounds. These people were able to connect a wide range of examples to their own situation, and exapt solutions
Apple offers an interesting counter-example. Apple barely interacts with other organizations, and its leaders were not networkers. However, Apple had a practice called concurrent development where all the disciplines work on the project interact right from the beginning. Though this causes projects to start with a lot of argument and confusion, this process prevents designs from being diluted over time and allows the methods of different disciplines to fertilize each other throughout the project. Early delays are overcome by later alignment and clarity.
Platforms represent the last big category of innovation types. A platform in this context is an innovation that spawns many more innovations. A beaver pond is a natural platform that provides an ecosystem suitable for numerous fish, amphibians, birds and plants. A technological platform example is GPS.
You can imagine two dimensions for an innovation. The first dimension relates to how networked the inventor(s) was: small team or highly networked. The second dimension is intended purpose (profit or knowledge sharing). Simplistically, these two dimensions form a 2x2 grid like the following.
four quadrants over time.
Early innovation was mostly individualistic and knowledge oriented, but over time networking came to dominate both the for profit and knowledge worlds. If 66% of innovation was individualist before 1600, 32% of modern innovation is non-networked. Profit motivation has also increased overtime, though not as much (24% to 34%).
The lower right quadrant is the most open of them all; characterized by open sharing through semi-formal networks, ideas and information flow allowing slow hunches to collide, solutions to be re-purposed, and platforms to be constructed.
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