The Future of Everything: The Science of Prediction
David Orrell
Language: English
Pages: 464
ISBN: 1568583699
Format: PDF / Kindle (mobi) / ePub
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the future or have an accurate model. THE BUTTERFLY EFFECT This is not to say that it is impossible to make any kind of sense out of the global climate system, or to make any predictions. To take an example from a different context, suppose that a dietician monitors a child who has taken to eating a number of candy bars a day. It would be impossible to compute or predict the exact effect: in some children the candy will speed their metabolism so they burn off the energy (negative feedback),
we prove whether avian flu is the revenge of chickens on the human race? As Garrett says, “The bottom line for policymakers: Science does not know the answer.”91 It is hard to get the balance right, and even our own immune system overreacts sometimes. All we can do is watch for coming storms. WE DON’T KNOW It might seem in this chapter that we have fallen into the trap of assuming that the future will resemble the past: just because we cannot predict atmospheric, biological, or economic systems
information. . . . Therefore we put into World3 the kinds of information one uses to understand the generic behaviour modes of thrown balls, not the kinds of information one would need to describe the exact trajectory of one particular throw of one specific ball.”45 But the world is not an inert ball, and there is no generic response. Perhaps that is why, like Cassandra, such models so often fail to convince or to move. Lack of predictability is a deep property of life. Any organism that is too
a dynamic balance between these forces: subjective greed or panic versus “objective” calculations of value. The behaviour gets interesting when the market participants are allowed to influence one another: if a majority thinks that the market is going to tank, then this mood eventually deflates the most optimistic chart-follower. Predictions therefore affect the future in a self-reinforcing, positive feedback loop. Tastes and preferences are treated as dynamic rather than fixed. The result is an
them sensitive to even small errors in parameterization. As a result, the models are highly flexible and can be made to match past data, but accurate predictions of the future remain elusive. The models are often most useful as tools for understanding the present function of the underlying systems. The three areas of scientific forecasting—weather, health, and wealth—are like siblings. They have the same origins, grew up together, and hung out with some of the same people. Each has its own