The knowledge required to ride a bicycle can’t be fully captured in words and conveyed to others. We need “tacit knowledge,” the sort we only get from bruising experience.

Statisticians call that the base rate—how common something is within a broader class. Daniel Kahneman has a much more evocative visual term for it. He calls it the “outside view”—in contrast to the “inside view,” which is the specifics of the particular case.

That is a very smart move. Researchers have found that merely asking people to assume their initial judgment is wrong, to seriously consider why that might be, and then make another judgment, produces a second estimate which, when combined with the first, improves accuracy almost as much as getting a second estimate from another person. The same effect was produced simply by letting several weeks pass before asking people to make a second estimate. This approach, built on the “wisdom of the crowd” concept, has been called “the crowd within.”

There is nothing mystical about an accurate intuition like the fire commander’s. It’s pattern recognition. With training or experience, people can encode patterns deep in their memories in vast number and intricate detail—such as the estimated fifty thousand to one hundred thousand chess positions that top players have in their repertoire.

The knowledge required to ride a bicycle can’t be fully captured in words and conveyed to others. We need “tacit knowledge,” the sort we only get from bruising experience. To learn to ride a bicycle, we must try to ride one.

Keynes operated on a higher plane than most of us, but that process—try, fail, analyze, adjust, try again—is fundamental to how all of us learn, almost from the moment we are born. ... The mother could skip the drama by putting her baby on her back, or in a chair, but she knows that when her baby flops she learns that she shouldn’t tilt her head that far and the next time she sits up she will be a little steadier. The baby will still have to practice this new skill to make it reliable, then habitual, but the initial flop delivers the conceptual breakthrough.

What Fermi understood is that by breaking down the question, we can better separate the knowable and the unknowable. ... But we have brought our guessing process out into the light of day where we can inspect it. And the net result tends to be a more accurate estimate than whatever number happened to pop out of the black box when we first read the question.

There is nothing mystical about an accurate intuition like the fire commander’s. It’s pattern recognition. ... Whether intuition generates delusion or insight depends on whether you work in a world full of valid cues you can unconsciously register for future use.

In 1972 the American meteorologist Edward Lorenz wrote a paper with an arresting title: “Predictability: Does the Flap of a Butterfly’s Wings in Brazil Set Off a Tornado in Texas?” A decade earlier, Lorenz had discovered by accident that tiny data entry variations in computer simulations of weather patterns—like replacing 0.506127 with 0.506—could produce dramatically different long-term forecasts. It was an insight that would inspire “chaos theory”: in nonlinear systems like the atmosphere, even small changes in initial conditions can mushroom to enormous proportions.