ideas are not conjured out of thin air; they are built out of a collection of existing parts, the composition of which expands (and, occasionally, contracts) over time.
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
But serendipity is not just about embracing random encounters for the sheer exhilaration of it. Serendipity is built out of happy
accidents, to be sure, but what makes them happy is the fact that the discovery you’ve made is meaningful to you. It completes a hunch, or opens up a door in the adjacent possible that you had overlooked.
DEVONthink features a clever algorithm that detects subtle semantic connections between distinct passages of text. These tools are smart enough to get around the classic search-engine failing of excessive specificity: searching for “dog” and missing all the articles that only have the word “canine” in them.
The problem with these closed environments is that they inhibit serendipity and reduce the overall network of minds that can potentially engage with a problem. This is why a growing number of large organizations—businesses, nonprofits, schools, government agencies—have begun experimenting with work environments that encourage the architecture of serendipity. Traditionally, organizations that have a strong demand for innovation have created a kind of closed playpen for hunches: the research-and-development lab.
In collaboration with Creative Commons, Nike released its patents under a modified license permitting use in “non-competitive” fields. (They also created a standardized, pre-negotiated contract for the patents, thereby reducing the transaction costs of haggling over each patent license individually.)
The secret to organizational inspiration is to build information networks that allow hunches to persist and disperse
Instead of cloistering your hunches in brainstorm sessions or R&D labs, create an environment where brainstorming is something that is constantly running in the background, throughout the organization, a collective version of the 20-percent-time concept that proved so successful for Google and 3M. One way to do this is to create an open database of hunches, the Web 2.0 version of the traditional suggestion box.
In other words, when subjects were exposed to inaccurate descriptions of the slides, they became more creative. Associations that traditionally lay on the fringes of the probability table suddenly became mainstream. Nemeth had deliberately introduced noise into the decision-making process, and what she found ran directly counter to our intuitive assumptions about truth and error. The groups that had been deliberately contaminated with erroneous information ended up making more original connections than the groups that had only been given pure information.
The best innovation labs are always a little contaminated.
Innovative environments thrive on useful mistakes, and suffer when the demands of quality control overwhelm them.
An important part of Gutenberg’s genius, then, lay not in conceiving an entirely new technology from scratch, but instead from borrowing a mature technology from an entirely different field, and putting it to work to solve an unrelated problem.
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.
Birds that fly at unusually high velocities, like hawks, have more extreme asymmetries than slower birds. Yet down feathers that simply provide insulation are perfectly symmetrical.
match you light to illuminate a darkened room turns out to have a completely different use when you open a doorway and discover a room with a pile of logs and a fireplace in it. A tool that helps you see in one context ends up helping you keep warm in another. That’s the essence of exaptation. It’s tempting to assume
In The Act of Creation, Arthur Koestler argued that “all decisive events in the history of scientific thought can be described in terms of mental cross-fertilization between different disciplines.” Concepts from one domain migrate to another as a kind of structuring metaphor, thereby unlocking some secret door that had long been hidden from view.
Those shared environments often take the form of a real-world public space, what the sociologist Ray Oldenburg famously called the “third place,” a connective environment distinct from the more insular world of home or office. The eighteenth-century English coffeehouse fertilized countless Enlightenment-era innovations; everything from the science of electricity, to the insurance industry, to democracy itself. Freud maintained a celebrated salon Wednesday nights at 19 Berggasse in Vienna, where physicians, philosophers, and scientists gathered to help shape the emerging field of psychoanalysis. Think, too, of the Paris cafés where so much of modernism was born; or the legendary Homebrew Computer Club in the 1970s, where a ragtag assemblage of amateur hobbyists, teenagers, digital entrepreneurs, and academic scientists managed to spark the personal computer revolution. Participants flock to these spaces partly for the camaraderie of others who share their passions, and no doubt that support network increases the engagement
But encouragement does not necessarily lead to creativity. Collisions do—the collisions that happen when different fields of expertise converge in some shared physical or intellectual space. That’s where the true sparks fly. The modernism of the 1920s exhibited so much cultural innovation in such a short period of time because the writers, poets, artists, and architects were all rubbing shoulders at the same cafés.
Eno had been exploring the possibilities of using tape loops as a musical instrument. (“The tape recorder was always the instrument I felt most comfortable with,” he once said in an interview. “Keyboards after that, with bass as a distant third.”)
Ruef interviewed 766 graduates of the school who had gone on to have entrepreneurial careers. He created an elaborate system for scoring innovation based on a combination of factors: the introduction of new products, say, or the filing of trademarks and patents. And then he tracked each graduate’s social network—not just the number of acquaintances but the kind of acquaintances they had. Some graduates had large social networks that were clustered within their organization; others had small insular groups dominated by friends and family. Some had wide-ranging connections with acquaintances outside their inner circle of friends and colleagues. What Ruef discovered was a ringing endorsement of the coffeehouse model of social networking: the most creative individuals in Ruef’s survey consistently had broad social networks that extended outside their organization and involved people from diverse fields of expertise.
Diverse, horizontal social networks, in Ruef’s analysis, were three times more innovative than uniform, vertical networks. In groups united by shared values and long-term familiarity, conformity and convention tended to dampen any potential creative sparks.
A similar study, conducted by a University of Chicago business school professor named Ronald Burt, looked at the origin of good ideas inside the organizational network of the Raytheon Corporation. Burt found that innovative thinking was much more
likely to emerge from individuals who bridged “structural holes” between tightly knit clusters.
From the perspective of innovation, it’s even more important that the information arriving from one of those weak ties is coming from a different context, what the innovation scholar Richard Ogle calls an “idea-space”: a complex of tools, beliefs, metaphors, and objects of study.
new technology developed in one idea-space can migrate over to another idea-space through these long-distance connections; in that new environment, the technology may turn out to have unanticipated properties, or may trigger a connection that leads to a new breakthrough.
Gutenberg was trained as a metallurgist, but he had weak ties to the vintners of Rhineland Germany.
The current project can exapt ideas from the projects at the margins, make new connections. It is not so much a question of thinking outside the box, as it is allowing the mind to move through multiple boxes.
Chance favors the connected mind.
For forty years, ecologists have used the term “keystone species” to designate an organism that has a disproportionate impact on its ecosystem—a carnivore, for instance, who is the only predator of another species that would otherwise overwhelm the habitat with unchecked population growth. Remove the keystone predator and the habitat falls apart. But about twenty years ago, a scientist named Clive Jones at the Cary Institute of Ecosystem Studies decided that ecology needed another term to describe a very specific kind of keystone species: the kind that actually creates the habitat itself. Jones called these organisms “ecosystem engineers.” Beavers are the classic example of ecosystem engineers.
Platform building is, by definition, a kind of exercise in emergent behavior. The tiny Scleractinia polyp isn’t actively trying to create an underwater Las Vegas, but nonetheless out of its steady labor—imbibing algae and erecting those aragonite skeletons—a higher-level system emerges. What had been a largely desolate stretch of nutrient-poor seawater is transformed into a glittering hub of activity. The beaver builds a dam to better protect itself against its predators, but that engineering has the emergent effect of creating a space where kingfishers and dragonflies and beetles can make a life for themselves. The platform builders and ecosystem engineers do not just open a door in the adjacent possible. They build an entire new floor.
When Guier and Weiffenbach were asked to explain how they had hit upon their Sputnik revelation, they credited the intellectual habitat of the Applied Physics Lab more than their own particular talents: APL was a superb environment for inquisitive young kids, and particularly so in the Research Center. It was an environment that encouraged people to think broadly and generally about task problems, and one in which inquisitive kids felt free to follow their curiosity. Equally important, it was an environment wherein kids, with an initial success, could turn to colleagues who were broadly expert in relevant fields, and particularly because of the genius of the Laboratory Directorship, colleagues who were also knowledgeable about hardware, weapons, and weapons needs. In its own small way, the APL was a platform that encouraged and amplified hunches, that allowed those hunches to be connected with other minds that had relevant expertise.
hotbeds of innovation have similar physical spaces associated with them: the Homebrew Computing Club in Silicon Valley; Freud’s Wednesday salon at 19 Berggasse; the eighteenth-century English coffeehouse. All these spaces were, in their own smaller-scale fashion, emergent platforms. Coffeehouse proprietors like Edward Lloyd or William Unwin were not trying to invent the modern publishing industry or the insurance business; they weren’t at all interested in fostering scientific advancement or political turmoil. They were just businessmen, trying to make enough sterling to feed their families, just like those beavers constructing lodges to keep their offspring safe. But the spaces Lloyd and Unwin built turned out to have these unusual properties: they made people think differently, because they created an environment where different kinds of thoughts could productively collide and recombine.
Conventionally, a developer will create a piece of software, and once it’s finished, expose a small part of its functionality to outside developers via the API. The Twitter team took the exact opposite approach. They built the API first, and exposed all the data that was crucial to the service, and then they built Twitter.com on top of the API.
What Apps for Democracy suggests is a more open-ended idea: some of the best ideas for government are likely to come from outside the government.
Part of that magic is economic: emergent platforms can dramatically reduce the costs of creation. Those forty-seven apps generated in a month by the original Apps for Democracy contest had a total cost to the D.C. government of $50,000. Kundra estimated that, had the city government contracted out for those applications using its traditional methods, the cost to the city would have been more than $2,000,000.
The promise of an immense payday encourages people to come up with useful innovations, but at the same time it forces people to protect those innovations.
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 and trade secrets and a thousand other barricades we’ve erected to keep promising ideas out of the minds of others.
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.
Most academic research today is fourth-quadrant in its approach: new ideas are published with the deliberate goal of allowing other participants to refine and build upon them, with no restrictions on their circulation beyond proper acknowledgment of their origin.
Fourth-quadrant innovation has been assisted by another crucial development: the increased flow of information.
The connectedness of modern life means that we face the opposite problem: it is much harder to stop information from spilling over than it is to get it into circulation. The consequence of this is that private-sector firms who are intent on protecting their intellectual assets have to invest time and money in building barricades of artificial scarcity. Participants in the fourth quadrant don’t have those costs: they can concentrate on coming up with new ideas, not building fortresses around the old ones.
That ideas should freely spread from one to another over the globe, for the moral and mutual instruction of man, and improvement of his condition, seems to have been peculiarly and benevolently designed by nature, when she made them, like fire, expansible over all space, without lessening their density in any point, and like the air in which we breathe, move, and have our physical being, incapable of confinement or exclusive appropriation. Inventions then cannot, in nature, be a subject of property. Ideas, 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.
We may very well decide as a society that people simply deserve to profit from their good ideas, and so we have to introduce a little artificial scarcity to ensure those rewards. As someone who creates intellectual property for a living, I am more than sympathetic toward that argument. But it is another matter altogether to argue that those restrictions will themselves promote innovation in the long run.
On the private-sector side, the success of companies like Google and Twitter and Amazon—all of whom have, in different ways, contributed to and benefited from fourth-quadrant innovation—has made it clear that, in the software world, at least, a little openness goes a long way. I suspect those lessons will grow increasingly inescapable in the decades to come.
But it is the public sector that I find more interesting, because governments and other non-market institutions have long suffered from the innovation malaise of
top-heavy bureaucracies. Today, these institutions have an opportunity to fundamentally alter the way they cultivate and promote good ideas. The more the government thinks of itself as an open platform instead of a centralized bureaucracy, the better it will be for all of us, citizens and activists and entrepreneurs alike.
Note: Zuck
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.
Note: Is 4.0 a commons or a platform? Ok it is a 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.
Ideas collide, emerge, recombine; new enterprises find homes in the shells abandoned by earlier hosts; informal hubs allow different disciplines to borrow from one another. These are the spaces that have long supported innovation, from those first Mesopotamian settlements eight thousand years ago to the invisible layers of software that support today’s Web.
Ideas rise in crowds, as Poincaré said. They rise in liquid networks where connection is valued more than protection.
Note: Why We want more people in the community...
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.