The central premise of Steven Johnson’s “Where Do Ideas Come From: The Natural History of Innovation” is that, similarly to the principle of evolution in the theory of natural selection, hunches or ideas emerge within the realm of possibilities at any given stage and innovation gradually develops over time. In other words, ideas and innovations do not come from random lightbulbs moments, flashes, epiphanies, and so on, but from proper timing and when nurtured further in proper environments.

Johnson explains:

A good idea is a network. A specific constellation of neurons–thousands of them–fire in sync with each other for the first time in your brain, and an idea pops into your consciousness. A new idea is a network of cells exploring the adjacent possible of connections that they can make in your mind….an idea is not a single thing. Is is more like a swarm.” (p.45-46)

Everything that happens in our brain is technically a network but

“the creative brain behave differently from the brain that is performing a repetitive task. The neurons communicate in different ways… the question is how to push your brain toward these more creative networks” (p.47)

The answer is to place your mind in environments that enhance the innate brain’s capacity to make new links and associations.

“When you think about ideas in their native state of neural networks, two key preconditions become clear. 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…but all those neurons would be useless for creating ideas …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. A dense network incapable of forming new patterns is, by definition, incapable of change” (p.38-39)

The Edge of Chaos

Innovative systems have the tendency to gravitate toward the “edge of chaos”, that is an area between “too much order and too much anarchy”.

The computer scientist Christopher Langton sometimes uses the metaphor of different phases of matter—gas, liquid, solid—to describe these network states. Molecules in each of these three states behave differently.

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.”

The 100 billion neurons in your brain form another kind of liquid network: densely interconnected, constantly exploring new patterns, but also capable of preserving useful structures for long periods of time.

Cities as Liquid Networks

According to Steven Johnson, when people started living together in cities the possibilities of innovating increased exponentially, because cities created “liquid networks”.

For example, it is not a coincidence that Northern Italy was the most urbanized region in all of Europe during the fourteenth and fifteenth centuries when it experienced an explosion of commercial and artistic innovation and became the birthplace of the European Renaissance. The rise of urban networks triggered a dramatic increase in the flow of good ideas.


“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. A cloister is a solid. By breaking up those information bonds and allowing ideas to circulate more freely through a wider, connected population, the great Italian innovators brought new life to the European mind.” (p. 44)

Capitalism and Double-Entry Accounting

Capitalism was one of the important elements that promoted the growth of the Italian cities, by creating extra wealth that was later used by the rich and powerful to support artists and architects.

“But markets should not be exclusively defined in terms of the profit motive. Consider the invention of one of capitalism’s key conceptual tools: double-entry accounting, which Goethe called one of the “finest inventions of the human mind.” (p. 45)

While it was codified by the Franciscan friar and mathematician Luca Pacioli in 1494, we do not really know if the the double-entry method originated in the mind of a single person, or whether the idea emerged simultaneously in the minds of multiple people, or whether it was passed on by Islamic entrepreneurs.

The technique first became commonplace in the merchant capitals of Italy—Genoa, Venice, and Florence—but what makes the history of double-entry so fascinating is the fact that no one seems to have claimed ownership of the technique, despite its enormous value. In other words,

“One of the essential instruments in the creation of modern capitalism appears to have been developed collectively, circulating through the liquid networks of Italy’s cities…Double-entry accounting illustrates a key principle in the emergence of markets… A society organized around marketplaces, instead of castles or cloisters, distributes decision-making authority across a much larger network of individual minds…Cities and markets recruit more minds into the collective project of exploring the adjacent possible. As long as there is spillover between those minds, useful innovations will be more likely to appear and spread through the population at large.” (p.46)

But networked innovation is not a “global brain,” or a “hive mind” because large collectives are rarely capable of true creativity or innovation. It’s not some “higher-level group consciousness”, but those cities

“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.” (p.47)

The Importance of Physical Locations

In the early 1990s, a psychologist named Kevin Dunbar decided to study idea formation in “the wild”, by actually watching scientists as they worked in their laboratories. He also conducted interviews in which the researchers described the latest developments in their experiments almost in real time.

These techniques allowed Dunbar to overcome one of the major problems of traditional studies that rely on retrospective interviews, where people tend to condense the origin stories of their best ideas into tidy narratives, forgetting the messy, complicated paths to inspiration that they actually followed.

“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.” (p.48)

“The lab meeting creates an environment where new combinations can occur, where information can spill over from one project to another….The social flow of the group conversation turns that private solid state into a liquid network.” (p.48)


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