The technical name for the butterfly effect is sensitive dependence on initial conditions. It was first proposed in meteorology but has an impressive array of implications in a variety of fields. Simply put, the butterfly effect occurs when a very small event has exceedingly large and far-reaching impact. The metaphor of the butterfly is used because a butterfly’s wings, fragile as they are, do not stir up much air as they flap, but even that minute movement may initiate a series of changes that grow such that they eventually cause a large storm thousands of miles away. In broad terms, then, the butterfly effect implies that large events may be tied to small, or even minuscule, occurrences.
The butterfly effect was used initially to explain why weather forecasts were frequently inaccurate. Initial conditions, sometimes quite subtle, tended to go unnoticed, so forecasters did not take them into account—yet those minute conditions eventually created hurricanes or similar sizeable changes in the weather. It is this insight concerning the large potential impact of minor occurrences that gives the butterfly effect broad appeal in many other fields, including psychology: It explains why predictions are often inaccurate. Recognizing the importance of initial conditions can dramatically improve the accuracy of scientific predictions.
The butterfly effect was discovered serendipitously and shows the benefits of interdisciplinary research efforts. The meteorologist Edward Lorenz, who first described the butterfly effect, saw meaningful patterns in what appeared to be random events in weather patterns. He studied them mathematically, and eventually caught the attention of other meteorologists. These ideas contributed significantly to the new science of chaos. To simplify, what appears to be chaotic may in fact reflect a nonlinear pattern in which seemingly negligible events have dramatic impact. This process is chaotic neither in the sense of being unpredictable, nor in the sense that the contributing factors cannot be determined. Instead, causes are related to effects in a nonlinear fashion, and although the results may appear to be chaotic, they are in fact deducible if nonlinear reasoning is applied.
Physicists, biologists, epidemiologists, ecologists, and psychologists now consider the butterfly effect, chaos, and nonlinear reasoning when making certain predictions. This has proven to be very useful in various social and behavioral sciences, as well as the physical and biological sciences. Data from a measles epidemic in New York City, for example, supported the new ideas of chaos and the butterfly effect, as did studies of the population variations of the Canadian lynx. Lightning and clouds showed the same trends and patterns, as did phenomena on much smaller scales, such as blood vessels and proteins, and on much larger scales, such as oceans, stars, and galaxies. This is one of the attractions of chaos theory: It applies regardless of scale.
The implications for the social sciences are suggested by the population patterns noted above, but implications for individuals are at least as clear. The butterfly effect in particular has been used to describe a variety of seemingly unpredictable behaviors and seemingly unpredictable thinking patterns. What may appear to be random or meaningless ideation, such as that of some psychotics, can, for example, be understood as a result of nonlinear reasoning. Along much the same lines, creative insights, which are by definition original, may be understood by taking initial perspective into account and allowing for nonlinear cognitive processes that may lead to a surprising insight or creative solution to a problem. Behavioral tendencies such as these were for many years difficult to understand, but the butterfly effect has improved our understanding of them in dramatic fashion.
SEE ALSO Chaos Theory; Differential Equations; Hurwicz, Leonid; Nonlinear Systems; Path Dependence; Phase Diagrams; Stability in Economics
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Mark A. Runco
Butterfly Effect is a term coined by the American metereologist Edward Lorenz (b. 1917) to describe a special effect in chaos theory. Because of the iterative character of chaos theory, the slightest change in the initial conditions of a chaotic system can accumulate in the long run into an enormous effect. Because of this sensitivity to initial conditions, the state of a chaotic system is practically unpredictable in the long run, even though such systems are deterministic. Lorenz came up with a fanciful image to illustrate this effect: The flapping of a butterfly's wing in the Amazon can result in a tornado in China. Thus, the sensitivity of chaotic systems to initial conditions came to be called the Butterfly Effect.
See also Chaos Theory; Unpredictability