Kevin Kelly Quotes

We know from chaos theory that even if you had a perfect model of the world, you'd need infinite precision in order to predict future events. With sociopolitical or economic phenomena, we don't have anything like that.

Whenever you have dynamic interactions between 300 million people and the American economy acting in really complex ways, that introduces a degree of almost chaos theory to the system, in a literal sense.

The thing that got me started on the science that I've been building now for about 20 years or so was the question of okay, if mathematical equations can't make progress in understanding complex phenomena in the natural world, how might we make progress?

When the number of factors coming into play in a phenomenological complex is too large scientific method in most cases fails. One need only think of the weather, in which case the prediction even for a few days ahead is impossible.

A forecasting game is a kind of simulation, a kind of scenario, a kind of teleconference, a kind of artifact from the future - and more - that enlists the participants as 'first-person forecasters.'

The current understanding was that it was impossible to predict how something would evolve because it was a very turbulent environment full of things interacting with each other.

The way that organizations and organisms anticipate the future is by taking signals from the past, most the time.

As we get more transparent with data sets about infrastructure and systems management, I have a feeling we'll see big changes in how we think about complexity and our relationship to our actions.

I'm interested in complexity, in the mathematical sense, as well as the idiomatic sense. The idea of emergence - that it's possible for complex patterns to arise out of many simple interactions - is fascinating.

If you look at any leaf on any tree branch, it's similar to but not exactly a repetition of the previous branch. So the new science of complexity or showing how an architecture can be produced just as quickly, cheaply and efficiently by using computer production methods to get the slight variation, the self-similarity.

I have been doing technology foresight for a number of years now on the level of scenario design, primarily. I want to become more rigorous with research methodology and statistical methods. I want to shift from creating clever SF scenarios to being a professional forecaster able to make rigorous predictions.

Occurrences in this domain are beyond the reach of exact prediction because of the variety of factors in operation, not because of any lack of order in nature.

Basins of attraction, of self organization, show up as well in our complex social environment, in human organizations. Here again, while we cannot predict the result of any given input, we can say that it will likely fall within one of several areas.

We have a picture for how complexity arises, because if the universe is computationally capable, maybe we shouldn't be so surprised that things are so entirely out of control.

We have to pay close attention to what we see, and be ready to work with the unexpected according to the basic principles of systems biology and medicine.

Nature doesn't feel compelled to stick to a mathematically precise algorithm; in fact, nature probably can't stick to an algorithm.

When systems come to be far from points of equilibrium, they reach bifurcation points, wherein multiple, as opposed to unique, solutions, to instability become possible.

Chaos is hard to create, even on the Internet.

It turns out that an eerie type of chaos can lurk just behind a facade of order - and yet, deep inside the chaos lurks an even eerier type of order.

Information is just simply bootstrapping itself to higher and higher levels of self-reflection and self-coordination using whatever means are necessary.

I think one of the things we learned from the physicists and also the theoretical biologists is the idea that when you're dealing with very complex systems you're going to get a large variety of behavior which can be interpreted as hill climbing, but hill climbing with a lot of modifications, hill climbing with big jumps occasionally.

I think the next [21st] century will be the century of complexity. We have already discovered the basic laws that govern matter and understand all the normal situations. We don't know how the laws fit together, and what happens under extreme conditions. But I expect we will find a complete unified theory sometime this century. The is no limit to the complexity that we can build using those basic laws.

Science has explored the microcosmos and the macrocosmos; we have a good sense of the lay of the land. The great unexplored frontier is complexity.

Life is chaotic and unpredictable. If a butterfly flaps its wings in one part of the world, it could cause people at the opposite end of the globe to watch a Discovery Channel special on butterflies

At the edge of chaos, unexpected outcomes occur. The risk to survival is severe.