Kevin Kelly Quotes

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The way to build a complex system that works is to build it from very simple systems that work.

A brain is a society of very small, simple modules that cannot be said to be thinking, that are not smart in themselves. But when you have a network of them together, out of that arises a kind of smartness.

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An organization's intelligence is distributed to the point of being ubiquitous.

It's generally much easier to kill an organization than to change it substantially.

Organisms by their design are not made to adapt too far.

Managers tend to treat organizations as if they are infinitely plastic. They hire and fire, merge, downsize, terminate programs, add capacities. But there are limits to the shifts that organizations can absorb.

Species go extinct because there are historical contraints built into a given body or a given design.

But when you are embodied in a location, in a physical plant, in a set of people, and in a common history, that constrains your evolution and your ability to evolve in certain directions.

Organizations get invested into a particular product. And sometimes the best thing is to stop making that product, even though it's profitable, because it has optimized at a local peak.

Technological advances could allow us to see more clearly into our own lives.

The great advance of personal computers was not the computing power per se but the fact that it brought it right to your face, that you had control over it, that were confronted with it and could steer it.

Complexity that works is built up out of modules that work perfectly, layered one over the other.

Changing things from the top down works when things are stable.

But in a turbulent environment the change is so widespread that it just routes around any kind of central authority. So it is best to manage the bottom-up change rather than try to institute it from the top down.

Managing bottom-up change is its own art.

The nature of an innovation is that it will arise at a fringe where it can afford to become prevalent enough to establish its usefulness without being overwhelmed by the inertia of the orthodox system.

The system continually has to make this choice: it can either continue to exploit a known process and make it more productive, or it can explore a new process at the cost of being less efficient.

Much of outcomes research is a systematic attempt to exploit what is known and make it better.

Everything that we are making, we are making more and more complex.

It's more along the lines of raising a child: we train the system to a certain range of behaviors that we find most useful. But then we let it go, because we don't want to have to be babysitting it...

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