By Steven Johnson April 29, 2019 ⋅ 6 min read ⋅ Books
Introduction: REEF, CITY, WEB
The reef is a story of how Charles Darwin observed a coral reef.
The number of heartbeats per lifetime tends to be stable from species to species. Bigger animals just take longer to use their quota so they live longer.
Kleiber’s law: as life gets bigger, it also gets slower.
This isn’t true for cities as they get bigger, they get more innovative.
10/10 Rule: ten years to develop an idea, ten years to find mass market.
To understand where good ideas come from, we first have to understand the context that gives rise to them.
There are shared patterns that recur again and again to create these innovative ideas.
Each pattern is its own chapter.
We lack a unified theory that describes innovation systems.
We are often better served by connecting ideas rather than protecting them.
Good ideas want to complete each other as much as they want to compete.
Chapter 1: THE ADJACENT POSSIBLE
Good ideas are constrained by the parts and skills that surround them.
Good ideas don’t come cleanly from a factory, they’re cobbled together from spare parts in a garage.
Evolution does the same thing when innovating.
E.g. The kludge of the brain.
Adjacent possible: the area of possible innovations given the current area. The realm of available possibilities.
E.g. Going from electricity to the telegram, not the Internet.
You can’t explore outside of that area and if you do, you’re called ahead of your time.
The adjacent possible boundaries grow as we explore those boundaries.
New innovations open up more new innovations.
Think of it like a circle that keeps expanding.
Good ideas aren’t conjured out of thin air, they’re built out of what we already know.
E.g. The paper “Are Inventions Inevitable?“.
The story of innovation is linear, with one door opening another.
Ideas that jump pass the closed doors are often short-term failures. Right idea, wrong environment.
E.g. Babbage’s Analytical Engine.
What kind of environment creates good ideas?
Ones that help people explore their adjacent possible.
Encouraging novel ways of using what we have.
To push the adjacent possible. To advance. To explore.
The dominance of multiples in innovation highlights how the adjacent possible is constrained by existing parts and knowledge.
Multiples: when several people independently make the same discovery almost simultaneously.
What tactics can we use to better explore the adjacent possible?
One tactic, the next pattern, is to have the adjacent possible expand itself.
E.g. Recursive self-improvement.
We must improve our ability to improve.
Chapter 2: LIQUID NETWORKS
There’s a misconception that an idea is a single thing. It isn’t, its a network.
Its a literal network in your brain, a new connection that’s never been formed before.
The network has two preconditions
The sheer size of the network
The network must be plastic and changeable
To push the brain towards more creative networks, you have to place it into an environment that shares the same network signature.
Networks of ideas or people that mimic the neural networks of the mind exploring the boundaries of the adjacent possible.
The network in the brain is similar to a liquid: flexible enough to adapt but rigid enough to preserve.
One of the benefits of the agriculture revolution was that it brought people together to share ideas.
High-density liquid networks make it easier for innovation to happen, but they also store those innovations.
A network let’s good ideas thrive while killing off bad ideas. The natural selection of ideas.
However, these networks aren’t the same as a hive mind or global brain.
Large collectives aren’t capable of true innovation due to herd mentality.
Networks simply widen the pool of minds that could come up with and share good ideas.
It isn’t the wisdom of the crowd, it’s the wisdom of someone in the crowd.
People tend to condense the origin stories of their ideas into tidy narratives but that isn’t the case.
Innovation is often messy, convoluted, and full of failures.
The most productive tool for generating good ideas is discussion with others.
There needs to be a balance between order and chaos, between solid and gas.
The mental state of flow is a good analogy for fluid ideas. It’s being carried in a clear direction but still being tossed in surprising ways from eddies and whirls.
Chapter 3: THE SLOW HUNCH
A pattern that recurs throughout the history of world changing ideas: a hunch that collides with another hunch.
Most great ideas first take shape in partial, incomplete form.
E.g. The theory of evolution was nearly complete in Darwin’s notebooks.
Liquid networks help those ideas become complete by merging it with other hunches.
Sustaining the slow hunch is less a matter of perspiration than of cultivation.
Slow hunches mature slowly, in stealth and then fading into view.
Secrets of hunch cultivation
Write it down because it won’t last in memory.
A system to capture the hunches, not categorize them.
A space for slow hunches to grow.
Chapter 4: SERENDIPITY
Dreams seem to explore new truths by trying new neuron firing combinations.
Sexual reproduction is slow and complicated, but is repaid in its rate of innovation and creativity.
When nature finds itself in need of new ideas, it strives to connect, not protect.
Serendipity needs unlikely collisions and discoveries, but it also needs something to anchor those discoveries.
Potential combinations of ideas are limited by what you remember.
If the commonplace book tells us that the best way to nurture hunches is to write everything done, then the web tells us to look everything up.
Protecting ideas from copycats and competitors also protects them from improvements and innovations.
The secret to organizational inspiration is to build information networks that allow hunches to persist, disperse, and recombine.
Chapter 5: ERROR
A lot of spectacularly right ideas have a shadow history of spectacular failures.
The same lesson about quantity over quality.
The errors of the great mind exceed in number those of the less vigorous one.
Being right keeps you in place, being wrong forces you to explore.
Error is needed to set off the truth, much as a dark background is required for exhibiting the brightness of a picture.
Being wrong doesn’t unlock new doors in the adjacent possible, but it does force us to look for them.
They assumed the results of the experiment was noise, not signal.
A paradoxical truth about innovative ideas: good ideas are more likely to emerge in environments that contain a certain amount of noise and error.
Interesting, evolution has struck a balance between too much mutation and too much stability.
The explore-and-exploit tradeoff. The risk and reward tradeoff.
When the going gets tough, life tends to gravitate towards more innovative reproductive strategies.
Sex keeps the door to the adjacent possible open by just a crack, so that we can adapt to the changing pressures or opportunities of our environment.
The complicated relationship between accuracy and error, between signal and noise.
Perhaps the history of the errors of mankind, all things considered, is more valuable and interesting than that of their discoveries. Truth is uniform and narrow; it constantly exists, and does not require so much an active energy, as a passive aptitude of soul to encounter it. But error is endlessly diversified.
Chapter 6: EXAPTATION
Exaptation: an organism develops a trait optimized for a single use but then the trait gets hijacked for a completely different function.
E.g. A feature adapted for warmth, such as feathers, is now exapted for flight.
It’s using what you have in a new environment or way.
Collisions of different fields of expertise leads to creativity.
The value of “weak tie” networks isn’t just that information is communicated across distant fields, it’s that it allows for exaptation to occur.
Chance favors the connected mind.
Chapter 7: PLATFORMS
The platform builders and ecosystem engineers don’t just open a door in the adjacent possible. They build an entire new floor.
Playing inside the rules versus playing with the rules.
The real benefit of stacked platforms is that they abstract away the details.
Conclusion: THE FOURTH QUADRANT
When you view things at a distance, what you lose in detail you gain in perspective.
We can organize innovations into four quadrants: individual vs network and market vs non-market.
Because innovations are cumulative, the quadrants display distinct shapes at different historical periods.
The pattern of growth seems to be network non-market as profit creates barriers.
The pattern we see again and again in the modern era: network non-market innovations create a new platform for businesses to profit by refining the original idea or by building upon it.
The reef has unlocked so many doors of the adjacent possible because of the way it shares.