Where Good Ideas Come From

by Steven Johnson

April 4, 1836. Over the eastern expanse of the Indian Ocean, the reliable northeast winds of monsoon season have begun to give way to the serene days of summer. On the Keeling Islands, two small atolls composed of twenty-seven coral islands six hundred miles west of Sumatra, the emerald waters are invitingly placid and warm, their hue enhanced

What lingers in the back of Darwin’s mind, in the days and weeks to come, is not the beauty of the submarine grotto but rather the “infinite numbers” of organic

“The island has no domestic quadruped excepting the pig,” Darwin notes with disdain.

You might find a dozen fish if you were lucky. On the reef, you would be guaranteed a thousand. In Darwin’s own words, stumbling across the ecosystem of a coral reef in the middle of an ocean was like encountering a swarming oasis in the middle of a desert.

The next day, Darwin ventures to the windward side of the atoll with the Beagle’s captain, Vice Admiral James FitzRoy, and there they watch massive waves crash against the coral’s white barrier. An ordinary European spectator,

The ocean throwing its waters over the broad reef appears an invincible, all-powerful enemy; yet we see it resisted, and even conquered, by means which at first seem most weak and inefficient. It is not that the ocean spares the rock of coral; the great fragments scattered over the reef, and heaped on the beach, whence the tall cocoa-nut springs,

Darwin is drawn to those minuscule architects because he believes they are the key to solving the mystery that has brought the Beagle to the Keeling Islands.

Charles Lyell, had recently proposed that atolls are created by undersea volcanoes

Darwin’s mind had been profoundly shaped by Lyell’s understanding of the deep time of geological transformation, but standing on the beach, watching the breakers crash against the coral, he knows that his mentor is wrong about the origin of the atolls.

larger, more encompassing theory that might account for the vast scope of life’s innovations.

Presaging a line he would publish thirty years later in the most famous passage from On the Origin of Species, Darwin writes, “I can hardly explain the reason, but there is to my mind much grandeur in the view of the outer shores of these lagoon-islands.” In time, the reason would come to him.

Swiss scientist Max Kleiber had a knack for testing the edges of convention.

During his tenure in the Swiss army, he discovered that his superiors had been trading information with the Germans, despite the official Swiss position of neutrality in World War I. Appalled, he simply failed to appear at his next call-up, and was ultimately jailed for several months. By the time he had settled on a career in agricultural science, he had had enough of the restrictions of Zurich society.

Estimating metabolic rates had great practical value for the cattle industry, because it enabled farmers to predict with reasonable accuracy both how much food their livestock would require, and how much meat they would ultimately produce after slaughter. Shortly

The hearts of birds and small mammals pump blood much faster than those of giraffes and blue whales. But the relationship between size and speed didn’t seem to be a linear one. A horse might be five hundred times heavier than a rabbit,

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 more we embrace these patterns—in our private work habits and hobbies, in our office environments, in the design of new software tools—the better we will be at tapping our extraordinary capacity for innovative thinking.3

explosion of new software tools on the Web,

When we look at the history of innovation from the vantage point of the long zoom, what we find is that unusually generative environments display similar patterns of creativity at multiple scales simultaneously.

The long-zoom approach lets us see that openness and connectivity may, in the end, be more valuable to innovation than purely competitive mechanisms.

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. Like the free market itself, the case for restricting the flow of innovation has long been buttressed by appeals to the “natural” order of things. But the truth is, when one looks at innovation in nature and in culture, environments that build walls around good ideas tend to be less innovative in the long run than more open-ended environments. Good ideas may not want to be free, but they do want to connect, fuse, recombine. They want to reinvent themselves by crossing conceptual borders. They want to complete each other as much as they want to compete.

Good ideas are like the NeoNurture device. They are, inevitably, constrained by the parts and skills that surround them. We have a natural tendency to romanticize breakthrough innovations, imagining momentous ideas transcending their surroundings, a gifted mind somehow seeing over the detritus of old ideas and ossified tradition. But ideas are works of bricolage; they’re built out of that detritus. We take the ideas we’ve inherited or that we’ve stumbled across, and we jigger them together into some new shape.

Good 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.

made that experiment thinkable.

We have a phrase for those ideas: we call them “ahead of their time.”

Unlocking a new door can lead to a world-changing scientific breakthrough, but it can also lead to a more effective strategy for teaching second-graders, or a novel marketing idea for the vacuum cleaner your company’s about to release. The trick is to figure out ways to explore the edges of possibility that surround you. This can be as simple as changing the physical environment you work in, or cultivating a specific kind of social network, or maintaining certain habits in the way you seek out and store information.

What kind of environment creates good ideas? The simplest way to answer it is this: innovative environments are better at helping their inhabitants explore the adjacent possible, because they expose a wide and diverse sample of spare parts—mechanical or conceptual—and they encourage novel ways of recombining those parts. Environments that block or limit those new combinations—by punishing experimentation, by obscuring certain branches of possibility, by making the current state so satisfying that no one bothers to explore the edges—will, on average, generate and circulate fewer innovations than environments that encourage exploration. The infinite variety of life that so impressed Darwin, standing in the calm waters of the Keeling Islands, exists because the coral reef is supremely gifted at recycling and reinventing the spare parts of its ecosystem.

The canisters and nozzles are like the ammonia and methane molecules of the early earth, or Babbage’s mechanical gears, or those Toyota parts heating an incubator: they are the building blocks that create—and limit—the space of possibility for a specific problem.

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.

There are a dozen different metaphors we use colloquially to describe good ideas: we call them sparks, flashes, lightbulb moments; we have brainstorms and breakthroughs, eureka moments and epiphanies. Something about the concept pushes our language into rhetorical overdrive, our verbiage straining to reproduce the innovation it describes.

A good idea is a network.

If we’re going to try to explain the mystery of where ideas come from, we’ll have to start by shaking ourselves free of this common misconception: an idea is not a single thing. It is more like a swarm.

First, the sheer size of the network: you can’t have an epiphany with only three neurons firing. The network needs to be densely populated. Your brain has roughly 100 billion neurons, an impressive enough number, but all those neurons would be useless for creating ideas (as well as all the other achievements of the human brain) if they weren’t capable of making such elaborate connections with each other.

The second precondition is that the network be plastic, capable of adopting new configurations.

The answer, as it happens, is delightfully fractal: to make your mind more innovative, you have to place it inside environments that share that same network signature: networks of ideas or people that mimic the neural networks of a mind exploring the boundaries of the adjacent possible.

Carbon atoms measure only 0.03 percent of the overall composition of the earth’s crust, and yet they make up nearly 20 percent of our body mass. That abundance highlights the unique property of the carbon atom: its combinatorial power. Carbon is a connector.

The computer scientist Christopher Langton observed several decades ago that innovative systems have a tendency to gravitate toward the “edge of chaos”: the fertile zone between too much order and too much anarchy.

In a gas, chaos rules; new configurations are possible, but they are constantly being disrupted and torn apart by the volatile nature of the environment. In a solid, the opposite happens: the patterns have stability, but they are incapable of change. But a liquid network creates a more promising environment for the system to explore the adjacent possible. New configurations can emerge through random connections formed between molecules, but the system isn’t so wildly unstable that it instantly destroys its new creations.

Economists have a telling phrase for the kind of sharing that happens in these densely populated environments: “information spillover.” When you share a common civic culture with thousands of other people, good ideas have a tendency to flow from mind to mind, even when their creators try to keep them secret. “Spillover” is the right word; it captures the essential liquidity of information in dense settlements. As species go, Homo sapiens had been on a fairly good run in the million years that led up to the birth of agriculture: its members had invented spoken language, art, sophisticated tools for hunting, and cooking. But until they settled in cities, they had not figured out a way to live inside a high-density liquid network.

It is not a coincidence that Northern Italy was the most urbanized region in all of Europe during the fourteenth and fifteenth centuries. But, in a crucial sense, the pattern of Renaissance innovation differs from that of the first cities: Michelangelo, Brunelleschi, and da Vinci were emerging from a medieval culture that suffered from too much order. If dispersed tribes of hunter-gatherers are the cultural equivalent of a chaotic, gaseous state, a culture where the information is largely passed down by monastic scribes stands at the opposite extreme.

In thinking about networked innovation this way, I am specifically not talking about a “global brain,” or a “hive mind.” There are indeed some problems that are wonderfully solved by collective thinking: the formation of neighborhoods in cities, the variable signals of market pricing, the elaborate engineering feats of the social insects. But as many critics have pointed out—most recently, the computer scientist and musician Jaron Lanier—large collectives are rarely capable of true creativity or innovation. (We have the term “herd mentality” for a reason.) When the first market towns emerged in Italy, they didn’t magically create some higher-level group consciousness. They simply widened the pool of minds that could come up with and share good ideas. This is not the wisdom of the crowd, but the wisdom of someone in the crowd. It’s not that the network itself is smart; it’s that the individuals get smarter because they’re connected to the network.

The most striking discovery in Dunbar’s study turned out to be the physical location where most of the important breakthroughs occurred. With a science like molecular biology, we inevitably have an image in our heads of the scientist alone in the lab, hunched over a microscope, and stumbling across a major new finding. But Dunbar’s study showed that those isolated eureka moments were rarities. Instead, most important ideas emerged during regular lab meetings, where a dozen or so researchers would gather and informally present and discuss their latest work. If you looked at the map of idea formation that Dunbar created, the ground zero of innovation was not the microscope. It was the conference table.

The magic of Building 20, powerfully eulogized in Stewart Brand’s How Buildings Learn, lay in the balance the environment struck between order and chaos. There were walls and doors and offices, as in most academic buildings. But the structure’s temporary origins—it was originally built with the expectation that it would be torn down after five years—meant that those structures could be reconfigured with little bureaucratic fuss, as new ideas created new purposes for the space.

For almost a century, the Malthusian epiphany was the canonical story of Darwinism’s roots. But in the early 1970s, a psychologist and intellectual historian named Howard Gruber decided to revisit Darwin’s copious notebooks from the period, reconstructing the elaborate dance of speculation, fact-marshaling, and internal debate that led to Darwin’s breakthrough in the fall of 1838. What Gruber found in the notebooks was a story very different from the account relayed in Darwin’s Autobiography. All the core elements of Darwin’s theory are present in the notebooks well before the Malthusian epiphany, which the notebooks explicitly date at September 28, 1838. Darwin understands the importance of variation; the connection between natural and artificial selection; the competition among different species for survival; the clear physiological connections among species; the epic scale of evolutionary time. All these key concepts are discussed at great length in the notebooks from 1837 on.

Exactly a year before his Malthus reading, he asks, in shorthand English: “Whether every animal produces in course of ages ten thousand varieties (influenced itself perhaps by circumstances) and those alone preserved which are well adapted?” All it takes to cement a working theory of natural selection is to modify the formula ever so slightly, and clarify that the preservation of “well adapted” forms comes from their reproductive success. And yet somehow Darwin fails to understand that he has the solution at his fingertips, and continues his enquiry for another year before “getting a theory by which to work.”

In the months before the Malthus reading, we could probably say that Darwin had the idea of natural selection in his head, but at the same time was incapable of fully thinking it. This is how slow hunches often mature: by stealth, in small steps. They fade into view.

Keeping a slow hunch alive poses challenges on multiple scales. For starters, you have to preserve the hunch in your own memory, in the dense network of your neurons. Most slow hunches never last long enough to turn into something useful, because they pass in and out of our memory too quickly, precisely because they possess a certain murkiness. You get a feeling that there’s an interesting avenue to explore, a problem that might someday lead you to a solution, but then you get distracted by more pressing matters and the hunch disappears. So part of the secret of hunch cultivation is simple: write everything down.

We can track the evolution of Darwin’s ideas with such precision because he adhered to a rigorous practice of maintaining notebooks where he quoted other sources, improvised new ideas, interrogated and dismissed false leads, drew diagrams, and generally let his mind roam on the page. We can see Darwin’s ideas evolve because on some basic level the notebook platform creates a cultivating space for his hunches; it is not that the notebook is a mere transcription of the ideas, which are happening offstage somewhere in Darwin’s mind. Darwin was constantly rereading his notes, discovering new implications. His ideas emerge as a kind of duet between the present-tense thinking brain and all those past observations recorded on paper. Somewhere in the middle of the Indian Ocean, a train of association compels him to revisit his notes on the fauna of the Galápagos archipelago from five months before. As he reads through his observations, a new thought begins to take shape in his mind, which provokes a whole new set of notes that will only make complete sense to Darwin two years later, after the Malthus episode.

Darwin’s notebooks lie at the tail end of a long and fruitful tradition that peaked in Enlightenment-era Europe, particularly in England: the practice of maintaining a “commonplace” book. Scholars, amateur scientists, aspiring men of letters—just about anyone with intellectual ambition in the seventeenth and eighteenth centuries was likely to keep a commonplace book. The great minds of the period—Milton, Bacon, Locke—were zealous believers in the memory-enhancing powers of the commonplace book. In its most customary form, “commonplacing,” as it was called, involved transcribing interesting or inspirational passages from one’s reading, assembling a personalized encyclopedia of quotations. There is a distinct self-help quality to the early d...

John Locke first began maintaining a commonplace book in 1652, during his first year at Oxford. Over the next decade he developed and refined an elaborate system for indexing the book’s content. Locke thought his method important enough that he appended it to a printing of his canonical work, An Essay Concerning Human Understanding. Locke’s approach seems almost comical in its intricacy, but it was a response to a specific set of design constraints: creating a functional index in only two pages that could be expanded as the commonplace book accumulated more quotes and observations: When I meet with any thing, that I think fit to put into my common-place-book, I first find a proper head. Suppose for example that the head be EPISTOLA, I look unto the index for the first letter and the following vowel which in this instance are E. i. if in the space marked E. ...

Locke’s method proved so popular that a century later, an enterprising publisher named John Bell printed a notebook entitled “Bell’s Common-Place Book, Formed generally upon the Principles Recommended and Practised by Mr Locke.” The book included eight pages of instructions on Locke’s indexing method, a system which not only made it easier to find passages, but also served the higher purpose of “facilitat[ing] reflexive thought.” Bell’s volume would be the basis for one of the most famous commonplace books of the late eighteenth century, maintained from 1776 to 1787 by Erasmus Darwin, Charles’s grandfather. At the very end of his life, while working on a biography of his grandfather, Charles obtained what he called “the great book” from his cousin Reginald. In the biography, the younger Darwin captures the book’s marvelous diversity: “There are schemes and sketches for an improved lamp, like our present moderators; candlesticks with telescope stands so as to be raised at pleasure to...