Where Good Ideas Come From | Steven Johnson
We now call this phenomenon Darwin’s Paradox: so many different life forms, occupying such a vast array of ecological niches, inhabiting waters that are otherwise remarkably nutrient-poor. Coral reefs make up about one-tenth of one percent of the earth’s surface, and yet roughly a quarter of the known species of marine life make their homes there.
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.”
But there was on fundamental difference: the quarter-power law governing innovation was positive, not negative. A city that was ten times larger than its neighbor wasn’t ten times more innovative; it was seventeen times more innovative. A metropolis fifty times bigger than a town was 130 times more innovative.
West’s power laws suggested something far more provocative: that despite all the noise and crowding and distraction, the average resident of a metropolis with a population of five million people was almost three times more creative than the average resident of a town of a hundred thousand.
In fact, if you look at the entirety of the twentieth century, the most important developments in mass, one-to-many communications clock in at the same social innovation rate with an eerie regularity. Call it the 10/10 rule: a decade to build the new platform, and a decade for it to find a mass audience. The technology standard of amplitude-modulated radio — what we now call AM radio — evolved in the first decade of the twentieth century. The first commercial AM station began broadcasting in 1920, but it wasn’t until the late 1920s that radios became a fixture in American households.
But even with all those extra layers of innovation, YouTube went from idea to mass adoption in less than two years. Something about the Web environment had enabled Hurley, Chen, and Karim to unleash a good idea on the world with astonishing speed. They took the 10/10 rule and made it 1/1.
The pattern of “competition” is an excellent case in point. Every economics textbook will tell you that competition between rival firms leads to innovation in their products and services. But when you look at innovation from the long-zoom perspective, competition turns out to be less central to the history of good ideas than we generally think.
The scientist Stuart Kauffman has a suggestive name for the set of all those first-order combinations: “the adjacent possible.” The phrase captures both the limits and the creative potential of change and innovation.
The strange and beautiful truth about the adjacent possible is that its boundaries grow as you explore those boundaries. Each new combination ushers new combinations into the adjacent possible. Think of it as a house that magically expands with each door you open. You begin in a room with four doors, each leading to a new room that you haven’t visited yet. Those four rooms are the adjacent possible. But once you open one of those doors and stroll into that room, three new doors appear, each leading to a brand-new room that you couldn’t have reached from your original starting point. Keep opening new doors and eventually you’ll have built a palace.
The creating brain behaves differently from the brain that is performing a repetitive task. The neurons communicate in different ways. The networks take on distinct shapes.
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.
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 descriptions of commonplacing’s virtues: maintaining the books enabled one to “lay up a fund of knowledge, from which we may at all times select what is useful in the several pursuits of life.”
If it takes you two weeks to finish a book, by the time you get to the next book, you’ve forgotten much of what was so interesting or provocative about the original one. You can immerse yourself in a single author’s perspective, but then it’s harder to create serendipitous collisions between the ideas of multiple authors. One way around this limitation is to carve out dedicated periods where you read a large and varied collection of books and essays in a condensed amount of time. Bill Gates (and his successor at Microsoft, Ray Ozzie) are famous for taking annual reading vacations. During the year they deliberately cultivate a stack of reading material — much of it unrelated to their day-to-day focus at Microsoft — and then they take off for a week or two and do a deep dive into the words they’ve stockpiled.
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. Modern indexing software like DEVONthink’s learns associations between individual words by tracking the frequency with which words appear near each other. This can create almost lyrical connections between ideas.
I use DEVONthink as an improvisational tool as well. I write a paragraph about something — let’s say it’s about the human brain’s remarkable facility for interpreting facial expressions. I then plug that paragraph into the software, and ask DEVONthink to find other passages in my archive that are similar. Instantly, a list of quotes appears on my screen: some delving into the neural architecture that triggers facial expressions, others exploring the evolutionary history of the smile, others dealing with the expressiveness of our near-relatives, the chimpanzees. Invariably, one or two of these triggers a new association in my head — perhaps I’ve forgotten about the chimpanzee connection — and so I select that quote, and ask the software to find a new batch of passages similar to it. Before long, a larger ideas takes shape in my head, built upon the trail of associations the machine has assembled for me.
In early 2010, Nike announced a new Web-based marketplace it called the GreenXchange, where it publicly released more than 400 of its patents that involve environmentally friendly materials or technologies. The marketplace was a kind of hybrid of commercial self-interest and civic good. By making its good ideas public, Nike made it possible for outside firms to improve on those innovations, creating new value that Nike itself might ultimately be able to put to use in its own products.
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 errors of the great mind exceed in number those of the less vigorous one.” This is not merely statistics. It is not that the pioneering thinkers are simply more productive than less “vigorous” ones, generating more ideas overall, both good and bad. Some historical studies of patent records have in fact shown that overall productivity correlates with radical breakthroughs in science and technology, that sheer quantity ultimately leads to quality.
Apple’s approach, by contract, is messier and more chaotic at the beginning, but it avoids these chronic problem of good ideas being hollowed out as they progress through the development chain. Apple calls it concurrent or parallel production. All the groups — design, manufacturing, engineering, sales — meet continuously through the product-development cycle, brainstorming, trading ideas and solutions, strategizing over the most pressing issues, and generally keeping the conversation open to a diverse group of perspectives. The process is noisy and involves far more open-ended and contentious meetings than traditional production cycles — and far more dialogue between people versed in different disciplines, with all the translation difficulties that creates. But the results speak for themselves.
As for really new ideas of any kind — no matter how ultimately profitable or otherwise successful some of them might prove to be — there is no leeway for such chancy trial, error and experimentation in the high-overhead economy of new construction. Old ideas can sometimes use new buildings. New ideas must use old buildings.
Economists define “efficient markets” as markets where information is evenly distributed among all the buyers and sellers in the space. Efficiency is generally held to be a universal goal for any economy — unless the economy happens to traffic in ideas. 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.
Does this mean we have to do away with intellectual property law? Of course not. The innovation track record of the fourth quadrant doesn’t mean that patents should be abolished and all forms of information allowed to run free. But it should definitely put the lie to the reigning orthodoxy that without the artificial scarcity of intellectual property, innovation would grind to a halt. There are plenty of understandable reasons why the law should make it easier for innovative people or organizations to profit from their creations. 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.