Where Good Ideas Come From

by Steven Johnson

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. Neither environment is perfect, by any means. (Think of crime rates in big cities, or the explosion of spam online.) But both the city and the Web possess an undeniable track record at generating innovation.

Link to Blinkist summary on Medium.com: https://medium.com/key-lessons-from-books/the-key-lessons-from-where-good-ideas-come-from-by-steven-johnson-1798e11becdb

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.

The main message of the book in two sentences: Both evolution and innovation thrive in collaborative networks where opportunities for serendipitous connections exist. Great discoveries often evolve as slow hunches, maturing and connecting to other ideas over time.

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.

Designing an incubator for a developing country wasn’t just a matter of creating something that worked; it was also a matter of designing something that would break in a non-catastrophic way. You couldn’t guarantee a steady supply of spare parts, or trained repair technicians. So instead, Prestero and his team decided to build an incubator out of parts that were already abundant in the developing world.

Building the NeoNurture out of car parts was doubly efficient, because it tapped both the local supply of parts themselves and the local knowledge of automobile repair. These were both abundant resources in the developing world context,

Good ideas are like the NeoNurture device. They are, inevitably, constrained by the parts and skills that surround them.

We take the ideas we’ve inherited or that we’ve stumbled across, and we jigger them together into some new shape. We like to think of our ideas as $40,000 incubators,

Ecologists use the term keystone species to describe organisms which are disproportionately important to the welfare of the ecosystem. The Global Positioning System (GPS) is a good example of such a platform. Originally developed for military use, it has now spurned countless innovations from GPS trackers to location-based services and advertising. Platforms often stack on top of each other, meaning that one platform provides the foundation for even more platforms, which again produce countless new innovations.

Evolution advances by taking available resources and cobbling them together to create new uses.

The lifeless earth was dominated by a handful of basic molecules: ammonia, methane, water, carbon dioxide, a smattering of amino acids, and other simple organic compounds.

Four billion years ago, carbon atoms mulled around the primordial soup. But as life began, those atoms did not spontaneously arrange themselves into complex life forms like sunflowers or squirrels. First, they had to form simpler structures like molecules, polymers, proteins, cells, primitive organisms and so forth. Each step along the way opened up possibilities for new combinations, expanding the realm of what was possible, until finally a carbon atom could reside in a sunflower.

Think of all those initial molecules, and then imagine all the potential new combinations that they could form spontaneously, simply by colliding with each other (or perhaps prodded along by the extra energy of a propitious lightning strike).

The atomic elements that make up a sunflower are the very same ones available on earth before the emergence of life, but you can’t spontaneously create a sunflower in that environment, because it relies on a whole series of subsequent innovations that wouldn’t evolve on earth for billions of years:

The scientist Stuart Kauffman has a suggestive name for the set of all those first-order combinations: “the adjacent possible.”

Both evolution and innovation tend to happen within the bounds of the adjacent possible, in other words the realm of possibilities available at any given moment.

the adjacent possible defines all those molecular reactions that were directly achievable in the primordial soup. Sunflowers and mosquitoes and brains exist outside that circle of possibility.

The adjacent possible is a kind of shadow future, hovering on the edges of the present state of things, a map of all the ways in which the present can reinvent itself.

What the adjacent possible tells us is that at any moment the world is capable of extraordinary change, but only certain changes can happen.

Great leaps beyond the adjacent possible are rare and doomed to be short-term failures. The environment is simply not ready for them yet. Had YouTube been launched in the 1990s, it would have flopped, since neither the fast internet connections nor the software required to view videos was available then.

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.

Although in retrospect great discoveries may seem like single, definable eureka-moments, in reality they tend to fade into view slowly. They are like gradually maturing slow hunches, which demand time and cultivation to bloom.

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.

On an organizational level, the key to innovation and inspiration is a network which allows hunches to mature, scatter and combine with others openly. The greatest such network in existence is, of course, the World Wide Web, where a wealth of ideas is not only available, but hyper-linked for easy connections between several disciplines.

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.

Random connections drive serendipitous discoveries. Dreams for example are the primordial soup of innovation, where ideas connect seemingly at random. In fact, neuroscientists have confirmed that “sleeping on a problem” greatly helps solve it.

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.

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.

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 average neuron connects to a thousand other neurons scattered across the brain, which means that the adult human brain contains 100 trillion distinct neuronal connections,

On an individual level, facilitating such serendipitous connections is simply a matter of simultaneously introducing ideas from different disciplines into your consciousness. Innovators like Benjamin Franklin and Charles Darwin favored working on multiple projects simultaneously, in a kind of slow multitasking mode. One project would take center stage for days at a time, but linger at the back of the mind afterwards too, so connections between projects could be drawn.

The connections are the key to wisdom, which is why the whole notion of losing neurons after we hit adult-hood is a red herring. What matters in your mind is not just the number of neurons, but the myriad connections that have formed between them.

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.

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. Certain environments enhance the brain’s natural capacity to make new links of association.

Without the generative links of carbon, the earth would have likely remained a lifeless soup of elements, a planet of dead chemistry.

The basis of all life on earth (and likely any extraterrestrial life out there) is carbon, because it is fundamentally good at connecting with other atoms, and can thus construct complex chains of molecules. These connections allow new structures like proteins to emerge. Without carbon, the earth would have likely remained a dead soup of chemicals.

Langton sometimes uses the metaphor of different phases of matter—gas, liquid, solid—to describe these network states. Think of the behavior of molecules in each of these three conditions. 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.

This mix of turbulence and stability is why liquid networks are optimal both for the evolution of life and for creativity. Innovative networks too must teeter on the brink of chaos, in the fruitful realm between order and anarchy, just like water.

somewhere within a thousand years of the first cities emerging, human beings invented a whole new way of inventing. A strong correlation exists between those dense settlements and the dramatic surge in the societal innovation rate.

In a low-density, chaotic network, ideas come and go. In the dense networks of the first cities, good ideas have a natural propensity to get into circulation. They spill over, and through that spilling they are preserved for future generations.

Connections also facilitate ideas. When humans first began to organize themselves into settlements, towns and cities, they became members of networks, which exposed them to new ideas and allowed them to spread their own discoveries. Before this happened, a novel idea by one person could well die with her, since she had no network to spread it to. Great ideas rise in crowds.

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.

Cities facilitate such large networks which allow ideas to be diffused and combined in novel ways. This is one of the reasons why cities are disproportionately more creative than smaller towns. Today though the greatest such creative network is not a city at all, but the World Wide Web, creating, connecting and diffusing ideas more effectively than any network before it.

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 a sense, Nike was widening the network of minds who were actively thinking about how to make its ideas more useful, without putting anyone else on its payroll.

Certainly market-spurred innovation has been far more effective than innovation achieved in command economies like the Soviet Union, but that still does not mean it is the optimal way forward. Yes, inventors may well deserve to be rewarded, but the real question should be how to increase innovation in general.

Nike is a big corporation, with many products in many categories, but there are limits to its reach. Some of its innovations might well turn out to be advantageous to industries or markets where it has no competitive involvement whatsoever. By keeping its eco-friendly ideas behind a veil of secrecy, Nike was holding back—without any real commercial justification—ideas that might, in another context, contribute to a sustainable future.

Open networks of connections among innovations can be just as generative as vigorous competition. Free markets have greatly spurred innovation, but so has the collaborative, open way of sharing knowledge in networks.

The invention of the Audion sounds like a classic story of ingenuity and persistence: a maverick inventor holed up in his bedroom lab notices a striking pattern and tinkers with it for years as a slow hunch, until he hits upon a contraption that changes the world. But telling the story that way misses one crucial fact: that at almost every step of the way, de Forest was flat-out wrong about what he was inventing. The Audion was not so much an invention as it was the steady, persistent accumulation of error.

Error is present in both the evolution of life and the innovation of great ideas, and it is not always a bad thing. Consider natural reproduction: genes are passed on from parent to offspring, providing “building instructions” for how the offspring should develop. Without occasional mutations, meaning random errors in those instructions, evolution would have long ago come to a virtual standstill. The elephant’s tusks or peacock’s feathers would have never emerged if only perfect copies of existing genes would have propagated. Mutations endow creatures with new traits. While most of them fail fantastically, these errors also produce a few winners, thus driving evolution.

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.

Feathers, for example originally evolved as a method for temperature regulation, but today their airfoil-shape helps birds fly. Ideas are often similarly repurposed along the way. Tim Berners-Lee created the World Wide Web as a tool for scholars, but in the course of time it became a network for shopping, social networking and pornography, among other things.