Here is a short article I wrote for New Scientist that appeared in the September 17, 2005 issue. It is one of 10 articles on 10 big ideas in science. -JY

 

Scientists were probably the last people to find out about chaos. Everyone knows our lives are all chaotic and unpredictable in the long run. The mother of a friend of mine once took a taxi, met the driver, and wound up marrying him. If she had taken a different taxi, my friend would never have existed. I often say that the most successful people are those who are good at plan B. Our predictions must be flexible. Franklin wrote the famous lines “For the want of a nail, the shoe was lost; for the want of a shoe the horse was lost; and for the want of a horse the rider was lost, being overtaken and slain by the enemy, all for the want of care about a horseshoe nail." Others carried this story further so that losing the rider and his message lead to the loss of a battle, then a war, and finally a kingdom, all for the want of a horseshoe’s nail. There is common science fiction theme of time travelers making small pivotal perturbations in the past that result in crucial changes in the present. In Ray Bradbury’s 1952 short story, “A Sound of Thunder”, a time traveler goes back millions of years and accidentally steps on a butterfly, significantly changing the present day world.

 

Chaos is an area of science and mathematics that describes situations in which small changes can cascade into larger and larger long-term effects. Few recognized until the last 30 years that scientific environments in which precise rules govern change can be quite unpredictable in the long run. It is not the complexity of our lives that cause chaos as much as the instability of our lives. Meteorologist Edward Lorenz, one of the founders of chaos theory, suggested in 1960 that the flap of a butterfly wing in Brazil might set off a tornado in Texas, implying that we can never know all the factors that determine our weather. At best we can only predict the details of the weather a few days ahead. Scientists have found that many situations are equally unstable. Computer models have greatly helped us understand how pervasive chaos is throughout science. Our group at the University of Maryland has aimed at telling scientists how to look for varieties of chaos, for specific phenomena common to many situations. But I continue to wonder, if nearly all scientists missed this pervasive phenomenon, what else might we all be missing now?

 

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