Where Good Ideas Come From
Steven Johnson book, ISBN:978-1-59448-771-2. This 2010 book adduces seven conditions (patterns) that enable discoveries and inventions (Huge Invention, Breakthrough, Generative), each of which gets its own chapter.
- 1) The Adjacent Possible (Stuart Kauffman): The inventor must use the components that exist in his environment. Gutenberg used a wine press for his printing press. Engineers used analog vacuum tubes to make digital computers.
- 2) Liquid networks: Large cities (Urban), and now the Internet, make it possible for loose, informal networks to form, and these enable discoveries. (scenius)
- 3) The Slow Hunch: It can take years for a hunch to blossom into a full-blown invention.
- 4) Serendipity: Some examples are mentioned: LSD, Teflon, Viagra, etc. Johnson argues that serendipity is not really under threat from Google, etc.
- 5) Error (Failure): This can also be a creative force. Lee de Forest's development of the audion diode and the triode was the result of erroneous thinking, and de Forest never understood how they worked. But the inventions changed the world.
- 6) Exaptation: Birds developed feathers to keep warm and regulate their body temperature and later used them for flight. Vacuum tubes were developed for long-distance telephone networks and radio transmission and were later used for electronic computers. This story was repeated with transistors.
- 7) Platforms: Platforms are the complex constructions which bring other increasingly complex Innovation-s within the realm of the adjacent possible. This is similar to Daniel Dennett's conception of 'cranes' He gives the example of the development of the Transit satellite, a precursor of GPS, by the Applied Physics Laboratory. http://en.wikipedia.org/wiki/Steven_Johnson_(author)#Where_Good_Ideas_Come_From
John Battelle reviews it. Includes screenshot mapping past inventions to quadrant based on individual-vs-Networked and Market-vs-Non-Market - the biggest bunch is in Networked/Non-Market (Network Economy) - This doesn’t mean those ideas don’t become the basis for commerce – quite the opposite in fact. But this is a book about how good ideas are created, not how they might be exploited.
Introduction: REEF, CITY, WEB
This is a book about the space of innovation. Some environments squelch new ideas; some environments seem to breed them effortlessly. The city and the Web have been such engines of innovation because, for complicated historical reasons, they are both environments that are powerfully suited for the creation, diffusion, and adoption of good ideas.
The argument of this book is that a series of shared properties and patterns recur again and again in unusually fertile environments. I have distilled them down into seven patterns, each one occupying a separate chapter
The academic literature on innovation and creativity is rich with subtle distinctions between innovations and inventions, between different modes of creativity: artistic, scientific, technological. I have deliberately chosen the broadest possible phrasing—good ideas—to suggest the cross-disciplinary vantage point I am trying to occupy
If there is a single maxim that runs through this book’s arguments, it is that we are often better served by connecting ideas than we are by protecting them
I. - THE ADJACENT POSSIBLE
Challenging problems don’t usually define their adjacent possible in such a clear, tangible way. Part of coming up with a good idea is discovering what those spare parts are, and ensuring that you’re not just recycling the same old ingredients. This, then, is where the next six patterns of innovation will take us, because they all involve, in one way or another, tactics for assembling a more eclectic collection of building block ideas, spare parts that can be reassembled into useful new configurations. The trick to having good ideas is not to sit around in glorious isolation and try to think big thoughts. The trick is to get more parts on the table
II. - LIQUID NETWORKS
A good idea is a network (associative)
an idea is not a single thing. It is more like a swarm.
III. - THE SLOW HUNCH
The failed spark of the Phoenix memo suggests an answer to the mystery of superlinear scaling in cities and on the Web. A metropolis shares one key characteristic with the Web: both environments are dense, liquid networks where information easily flows along multiple unpredictable paths. Those interconnections nurture great ideas, because most great ideas come into the world half-baked, more hunch than revelation. Genuine insights are hard to come by; it’s challenging to imagine a terrorist plot to fly passenger planes into buildings, or to invent a programmable computer. And so, most great ideas first take shape in a partial, incomplete form. They have the seeds of something profound, but they lack a key element that can turn the hunch into something truly powerful. And more often than not, that missing element is somewhere else, living as another hunch in another person’s head. Liquid networks create an environment where those partial ideas can connect. (associative, collective intelligence)
IV. - SERENDIPITY
the canon of scientific breakthroughs contains many revolutionary ideas that originated in dreams
the dream is not somehow unveiling a repressed truth. Instead, it is exploring, trying to find new truths by experimenting with novel combinations of neurons
V. - ERROR
triode... at almost every step of the way, de Forest was flat-out wrong about what he was inventing
A shockingly large number of transformative ideas in the annals of science can be attributed to contaminated laboratory environments. Alexander Fleming famously discovered the medical virtues of penicillin when the mold accidentally infiltrated a culture of Staphylococcus he had left by an open window in his lab. In the 1830s, Louis Daguerre spent years trying to coax images out of iodized silver plates. One night, after another futile attempt, he stored the plates in a cabinet packed with chemicals; to his wonder the next morning, the fumes from a spilled jar of mercury produced a perfect image on the plate—and the daguerreotype, forerunner of modern photography, was born.
Error often creates a path that leads you out of your comfortable assumptions
Thomas Kuhn makes a comparable argument for the role of error in The Structure of Scientific Revolutions. Paradigm shifts, in Kuhn’s argument, begin with anomalies in the data, when scientists find that their predictions keep turning out to be wrong
The trouble with error is that we have a natural tendency to dismiss it
noise makes the rest of us smarter, more innovative, precisely because we’re forced to rethink our biases, to contemplate an alternate model
VI. - EXAPTATION
Sometime around the year 1440, a young Rhineland entrepreneur began tinkering with the design of the wine press
Johannes Gutenberg was not interested in wine. He was interested in words.
Gutenberg’s printing press was a classic combinatorial innovation, more bricolage than breakthrough
Evolutionary biologists have a word for this kind of borrowing, first proposed in an influential 1971 essay by Stephen Jay Gould and Elisabeth Vrba: exaptation. An organism develops a trait optimized for a specific use, but then the trait gets hijacked for a completely different function. The classic example, featured prominently in Gould and Vrba’s essay, is bird feathers, which we believe initially evolved for temperature regulation, helping nonflying dinosaurs from the Cretaceous period insulate themselves against cold weather. But when some of their descendants, including a creature we now call Archaeopteryx, began experimenting with flight, feathers turned out to be useful for controlling the airflow over the surface of the wing, allowing those first birds to glide.
A feather adapted for warmth is now exapted for flight.
VII. - PLATFORMS
the real benefit of stacked platforms lies in the knowledge you no longer need to have
Conclusion: THE FOURTH QUADRANT (see image above)
All of which leads to the inevitable question: Is Willis Carrier an anomaly or not? The question has real political and social stakes, because the doxa of market capitalism as an unparalleled innovation engine has long leaned on stories like Willis Carrier’s miraculous cooling device as a cornerstone of its faith.6 In many respects, these beliefs made sense, because the implicit alternatives were the planned economies of socialism and communism. State-run economies were fundamentally hierarchies, not networks. They consolidated decision-making power in a top-down command system, which meant that new ideas had to be approved by the authorities before they could begin to spread through the society. Markets, by contrast, allowed good ideas to erupt anywhere in the system. In modern tech-speak, markets allowed innovation to flourish at the edges of the network.
There are three main approaches for settling a question as complicated as this
You can dive deeply into a single story and try to persuade your audience that it is representative of a larger societal truth. (This is the strategy I adopted in telling the stories of John Snow and Joseph Priestley
The second approach, which I have taken in the preceding chapters of this book, is to build an argument around dozens of anecdotes, drawn from different contexts and historical periods. The anecdotal approach sacrifices detail for breadth. Yet it, too, runs the risk of being accused of cherry-picking.
To see around the potential distortions of the case-study and anecdotal approaches, you need to see the entire field of innovation through a single lens. You can’t tell whether Willis Carrier is an anomaly by studying the fine points of his biography. You need a wider view. So let us perform an experiment on the data available on the history of innovation. Take roughly two hundred of the most important innovations and scientific breakthroughs from the past six hundred years
Plot each breakthrough somewhere in one of the four quadrants of this diagram
Classify innovations that involved a small, coordinated team within an organization—or, even better, a single inventor—as “individual.” Classify as “networked” all the innovations that evolved through collective, distributed processes, with a large number of groups working on the same problem
Inventors who planned to capitalize directly from the sale or licensing of their invention should be classified as “market”; those who wished their ideas to flow freely into the infosphere belong to the “non-market” side
It is in the nature of good ideas to stand on the shoulders of the giants who came before them, which means that by some measure, every important innovation is fundamentally a network affair. But, for the sake of clarity, let’s not blur the line between “individual” and “network” by admitting to the discussion the prior innovations that inspired or supported the new generation of ideas
In taking this approach, I am exapting a technique that the literary historian Franco Moretti calls “distant reading.” In a series of influential books and essays published over the past decade, Moretti has broken from the traditional English Department approach of “close reading,” in which individual literary texts are analyzed in exhaustive detail
Distant reading takes the satellite view of the literary landscape, looking for larger patterns in the history of the stories we tell each other. In one typically inventive analysis, Moretti tracked the evolution of subgenres in popular British novels from 1740 to 1915, an immense taxonomy of narrative forms—spy novels, picaresques, gothic novels, nautical tales, mysteries, and dozens of other distinct forms. He plotted the life span of each sub-genre as a dominant species in the British literary ecosystem
the diversity of forms is strikingly balanced by their uncannily similar life spans, which Moretti attributes to underlying generational turnover. Every twenty-five to thirty years a new batch of genres becomes dominant, as a new generation of readers seeks out new literary conventions
the four quadrants display distinct shapes at different historical periods. Start with this view of the breakthrough ideas from 1400 to 1600, beginning with Gutenberg’s printing press and continuing on to the dawn of the Enlightenment (see page 227).
This is the shape that Renaissance innovation takes, seen from a great (conceptual) distance. Most innovation clusters in the third quadrant: non-market individuals
1600-1800: Scanning the next two centuries, we see that the pattern changes dramatically (see page 229).
Solo, amateur innovation (quadrant three) surrenders much of its lead to the rising power of networks and commerce (quadrant four). The most dramatic change lies along the horizontal axis, in a mass migration from individual breakthroughs (on the left) to the creative insights of the group (on the right).
A vertical movement toward market incentives is noticeable, nonetheless. As industrial capitalism arises in England in the eighteenth century, new economic structures raise the stakes for commercial ventures: tantalizing rewards lure innovators into private enterprise, and the codification of English patent laws in the early 1700s gives some reassurance that good ideas will not be stolen with impunity. Despite this new protection, most commercial innovation during this period takes a collaborative form, with many individuals and firms contributing crucial tweaks and refinements to the product.
the final two centuries of the millennium
I think most of us would expect to see a dramatic consolidation of innovative activity in the first quadrant, as capitalism enters its mature period, spanning the ages of mass production and the consumer society
Against all odds, the first quadrant turns out to be the least populated on the grid
Why have so many good ideas flourished in the fourth quadrant, despite the lack of economic incentives? One answer is that economic incentives have a much more complicated relationship to the development and adoption of good ideas than we usually imagine
If ideas were fully liberated, then entrepreneurs wouldn’t be able to profit from their innovations, because their competitors would immediately adopt them. And so where innovation is concerned, we have deliberately built inefficient markets: environments that protect copyrights and patents
That deliberate inefficiency doesn’t exist in the fourth quadrant
All of the patterns of innovation we have observed in the previous chapters—liquid networks, slow hunches, serendipity, noise, exaptation, emergent platforms—do best in open environments where ideas flow in unregulated channels
Like any complex social reality, creating innovation environments is a matter of trade-offs
When you introduce financial rewards into a system, barricades and secrecy emerge, making it harder for the open patterns of innovation to work their magic. So the question is: What is the right balance?
The test is not how the market fares against command economies. The real test is how it fares against the fourth quadrant. As the private corporation evolved over the past two centuries, a mirror image of it grew in parallel in the public sector: the modern research university.
Universities have a reputation for ivory-tower isolation from the real world, but it is an undeniable fact that most of the paradigmatic ideas in science and technology that arose during the past century have roots in academic research
The next decade will likely see a wave of pharmaceutical products enabled by genomic science, but that underlying scientific platform—most critically, the ability to sequence and map DNA—was almost entirely developed by a decentralized group of academic scientists working outside the private sector in the 1960s and seventies
Fourth-quadrant innovation has been assisted by another crucial development: the increased flow of information
the Internet has effectively reduced the transmission costs of sharing good ideas to zero
We do not have a ready-made political vocabulary for the fourth quadrant, particularly the noninstitutional forms of collaboration that have developed around the open-source community
A few months after Darwin published On the Origin of Species in 1859, Karl Marx wrote Friedrich Engels a letter that included a few lines endorsing Darwin’s biological radicalism. “Although it is developed in the crude English style, this is the book which contains the basis in natural history for our view.”
they couldn’t have been more wrong in their predictions about the way the theory would play out in the politico-economic arena. They anticipated, correctly, that analogies would be drawn between Darwin’s “survival of the fittest” and the competitive selection of capitalist free-market economies. Marx and Engels just assumed those analogies would be launched as critiques of capitalism.
As it turned out, the exact opposite happened. Darwin’s theories were invoked countless times in the twentieth century as a defense of the free-market system. Aligning them with the animal world didn’t discredit markets, as Engels had predicted. It made markets look natural.
Yet the true story of nature is not one of exclusively ruthless competition between selfish agents, as Darwin himself realized
Darwin’s words here oscillate between two structuring metaphors that govern all his work: the complex interdependencies of the tangled bank, and the war of nature; the symbiotic connections of an ecosystem and the survival of the fittest
so many of the insights his theory made possible have revealed the collaborative and connective forces at work in the natural world.
We have been living with a comparable caricature in our assumptions about cultural innovation. Look at the past five centuries from the long view, and one fact confronts the eye immediately: market-based competition has no monopoly on innovation
Ideas, Thomas Jefferson argues, have an almost gravitational attraction toward the fourth quadrant. The natural state of ideas is flow and spillover and connection. It is society that keeps them in chains
To my mind, the great question for our time is whether large organizations—public and private, governments and corporations alike—can better harness the innovation turbine of fourth-quadrant systems
governments and other non-market institutions have long suffered from the innovation malaise of top-heavy bureaucracies
Generative platforms require all the patterns of innovation we have seen over the preceding pages; they need to create a space where hunches and serendipitous collisions and exaptations and recycling can thrive. It is possible to create such a space in a walled garden. But you are far better off situating your platform in a commons
perhaps “commons” is the wrong word for the environment we’re trying to imagine
I prefer another metaphor drawn from nature: the coral reef.
What makes the reef so inventive is not the struggle between the organisms but the way they have learned to collaborate—the coral and the zooxanthellae and the parrotfish borrowing and reinventing each other’s work
The reef helps us understand the other riddles we began with: the runaway innovation of cities, and of the Web. They, too, are environments that compulsively connect and remix that most valuable of resources: information.
You may not be able to turn your government into a coral reef, but you can create comparable environments on the scale of everyday life: in the workplaces you inhabit; in the way you consume media; in the way you augment your memory. The patterns are simple, but followed together, they make for a whole that is wiser than the sum of its parts. Go for a walk; cultivate hunches; write everything down, but keep your folders messy; embrace serendipity; make generative mistakes; take on multiple hobbies; frequent coffeehouses and other liquid networks; follow the links; let others build on your ideas; borrow, recycle, reinvent. Build a tangled bank.