This article is an excerpt from the Shortform book guide to "Superforecasting" by Philip E. Tetlock. Shortform has the world's best summaries and analyses of books you should be reading.
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What is the butterfly effect theory? What are its implications for science?
In chaos theory, the butterfly effect is the idea that small changes in the initial state of a non-linear system can have drastic effects on its later state. The concept is usually illustrated with a butterfly flapping its wings in Brazil and thereby setting off a tornado in Texas.
Keep reading to understand the butterfly effect theory.
The Butterfly Effect Theory
The chaos theory was first proposed by a meteorologist who argued that tiny changes in nonlinear systems can escalate into enormous effects. You may have heard this referred to as “the butterfly effect,” a moniker that stems from the title of the original 1972 paper: “Predictability: Does the Flap of a Butterfly’s Wings in Brazil Set Off a Tornado in Texas?”
The butterfly effect theory is a massive departure from the previous scientific assumption that the universe is entirely predictable, if only we could discover all the laws that govern it. The idea was that, if you knew the precise details of the current state of the world and understood all the fundamental laws of science, you could accurately predict any future state.
Chaos theory threw a small but important wrench in this plan: Most of the time, atmospheric conditions would prevent a Brazilian butterfly from setting off a tornado in Texas—but if every other factor lined up just right, there is a tiny chance that it could happen. This possibility is so unlikely and requires such a specific arrangement of variables that it is almost entirely unpredictable, even with the knowledge of every law of the universe.
In late 2010, the world got a dramatic example of the power of chaos theory when the suicide of a poor Tunisian fruit vendor set off a chain of events that led to massive protests across six countries and the ousting of dictators in both Tunisia and Egypt. This chain of events was named “the Arab Spring.”
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- How to make predictions with greater accuracy
- The 7 traits of superforecasters
- How Black Swan events can challenge even the best forecasters
