An exploration of what “creates” innovation. Even though the book wasn’t long, it still felt longer than necessary.
Main Takeaways
- 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.
- 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.
- Most great ideas first take shape in a partial, incomplete form. They have the seeds of something profound, but they lack a key element that can turn the hunch into something truly powerful. And more often than not, that missing element is somewhere else, living as another hunch in another person’s head.
- Error often creates a path that leads you out of your comfortable assumptions.
Notes
The adjacent possible
- 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. Yet it is not an infinite space, or a totally open playing field.
- The number of potential first-order reactions is vast, but it is a finite number, and it excludes most of the forms that now populate the biosphere. What the adjacent possible tells us is that at any moment the world is capable of extraordinary change, but only certain changes can happen.
- You can see the fingerprints of the adjacent possible in one of the most remarkable patterns in all of intellectual history, what scholars now call “the multiple”: A brilliant idea occurs to a scientist or inventor somewhere in the world, and he goes public with his remarkable finding, only to discover that three other minds had independently come up with the same idea in the past year.
- 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. Some of those parts are conceptual: ways of solving problems, or new definitions of what constitutes a problem in the first place. Some of them are, literally, mechanical parts.
- In human culture, we like to think of breakthrough ideas as sudden accelerations on the timeline, where a genius jumps ahead fifty years and invents something that normal minds, trapped in the present moment, couldn’t possibly have come up with. But the truth is that technological (and scientific) advances rarely break out of the adjacent possible; the history of cultural progress is, almost without exception, a story of one door leading to another door, exploring the palace one room at a time.
- 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.
Liquid networks
- 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.
- And so, when we look back to the original innovation engine on earth, we find two essential properties. First, a capacity to make new connections with as many other elements as possible. And, second, a “randomizing” environment that encourages collisions between all the elements in the system.
The slow hunch
- Most great ideas first take shape in a partial, incomplete form. They have the seeds of something profound, but they lack a key element that can turn the hunch into something truly powerful. And more often than not, that missing element is somewhere else, living as another hunch in another person’s head.
- Liquid networks create an environment where those partial ideas can connect; they provide a kind of dating service for promising hunches. They make it easier to disseminate good ideas, of course, but they also do something more sublime: they help complete ideas.
Serendipity
- The truth is, your mind contains a near-infinite number of ideas and memories that at any given moment are lurking outside your consciousness. Some tiny fraction of those thoughts are like Kekulé’s serpent: surprising connections that might help you unlock a door in the adjacent possible. But how do you get those particular clusters of neurons to fire at the right time?
- One way is to go for a walk. The history of innovation is replete with stories of good ideas that occurred to people while they were out on a stroll.
Error
- Error often creates a path that leads you out of your comfortable assumptions.
- Being right keeps you in place. Being wrong forces you to explore.
- Nemeth’s research suggests a paradoxical truth about innovation: good ideas are more likely to emerge in environments that contain a certain amount of noise and error.
- Without noise, evolution would stagnate, an endless series of perfect copies, incapable of change. But because DNA is susceptible to error—whether mutations in the code itself or transcription mistakes during replication—natural selection has a constant source of new possibilities to test. Most of the time, these errors lead to disastrous outcomes, or have no effect whatsoever. But every now and then, a mutation opens up a new wing of the adjacent possible. From an evolutionary perspective, it’s not enough to say “to err is human.” Error is what made humans possible in the first place.
Exaptation
- 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.
- The classic example, featured prominently in Gould and Vrba’s essay, is bird feathers, which we believe initially evolved for temperature regulation, helping nonflying dinosaurs from the Cretaceous period insulate themselves against cold weather. But when some of their descendants, including a creature we now call Archaeopteryx, began experimenting with flight, feathers turned out to be useful for controlling the airflow over the surface of the wing, allowing those first birds to glide.