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Science and soothsayers in same boat
By Jeanne Wu |
February 28, 2009, Saturday
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PEOPLE today often take modern forecasting for granted. They expect accurate weather forecasting, precise economic predictions as well as correct diagnoses of most ailments, if not all.
However, the disappointing truth is that despite ever-developing complex mathematical models and technologies, "social forecasting, scientific and otherwise, is about as accurate as random guessing,'' David Orrell observes in "The Future of Everything''.
By looking back into the history of telling the future and giving a detailed description of the current state of forecasting, especially its unmanageable limitations, Orrell makes a convincing case that forecasting with precision is a mission impossible, even in the future.
The history of telling the future is closely related to subjective predictions from mystical sources, or superstition, as well as numerical predictions.
It was not until in the 16th century that the concept of the universe as an ordered, structured place came into prominence - a view that still has a profound influence on how modern thinkers view forecasting.
Based on this concept, it appeared that it would only be a matter of time until experts could predict the future of the earth or the universe precisely after having collected enough information and data.
Most people believe strongly in this "gospel'' today, being convinced that with advanced science and technology, numerous new discoveries about the universe and complex forecasting models, we should not be far from predicting the future precisely.
Yet a closer examination of the state of forecasting in the real world would show that the science of prediction has turned out to be conditional, varied and extremely complicated, argues Orrell.
On the one hand, predictive models are based on sets of equations that are simplified from complex underlying systems.
The systems tend to be sensitive to all kinds of changes, which may put the accuracy of the equations in question.
On the other hand, all kinds of forecasting are based on past experiences.
But it is not reasonable for people to expect to figure out when (or if) something would happen again just because it happened in the past.
That's why "the models often get better at fitting what has happened in the past, but they don't get much better at making predictions.''
Take the prediction of earthquakes.
While experts can predict where they're likely, given where tectonic plates strain against each other, they cannot determine when a quake will occur because the release of tension between plates is not gradual, but abrupt, says Orrell.
That explains why the China Earthquake Administration failed to predict the devastating earthquake last May in Sichuan Province.
Even Japan, a country so experienced with dealing with earthquakes, could only give warning seconds before an earthquake. Sometimes it cannot give warnings at all.
A sudden earthquake is comparable to economic plunges that happen because of "a sudden shift in balance between buyers and sellers,'' writes Orrell.
The same is true on the health front.
While scientists have mapped the human genome and medical researchers have discovered what triggers certain conditions, it is completely beyond them to tell whether a particular set of conditions will cause certain diseases and whether specific treatments will work.
Perhaps the biggest complexity of all, as Orrell points out, lies in the interrelationship and the interaction between various systems.
Hence Orrell's conclusion: "The realization that the earth system is inherently unpredictable - coupled with a deeper understanding of ... complex systems - may turn out to be highly liberating.''
However, the disappointing truth is that despite ever-developing complex mathematical models and technologies, "social forecasting, scientific and otherwise, is about as accurate as random guessing,'' David Orrell observes in "The Future of Everything''.
By looking back into the history of telling the future and giving a detailed description of the current state of forecasting, especially its unmanageable limitations, Orrell makes a convincing case that forecasting with precision is a mission impossible, even in the future.
The history of telling the future is closely related to subjective predictions from mystical sources, or superstition, as well as numerical predictions.
It was not until in the 16th century that the concept of the universe as an ordered, structured place came into prominence - a view that still has a profound influence on how modern thinkers view forecasting.
Based on this concept, it appeared that it would only be a matter of time until experts could predict the future of the earth or the universe precisely after having collected enough information and data.
Most people believe strongly in this "gospel'' today, being convinced that with advanced science and technology, numerous new discoveries about the universe and complex forecasting models, we should not be far from predicting the future precisely.
Yet a closer examination of the state of forecasting in the real world would show that the science of prediction has turned out to be conditional, varied and extremely complicated, argues Orrell.
On the one hand, predictive models are based on sets of equations that are simplified from complex underlying systems.
The systems tend to be sensitive to all kinds of changes, which may put the accuracy of the equations in question.
On the other hand, all kinds of forecasting are based on past experiences.
But it is not reasonable for people to expect to figure out when (or if) something would happen again just because it happened in the past.
That's why "the models often get better at fitting what has happened in the past, but they don't get much better at making predictions.''
Take the prediction of earthquakes.
While experts can predict where they're likely, given where tectonic plates strain against each other, they cannot determine when a quake will occur because the release of tension between plates is not gradual, but abrupt, says Orrell.
That explains why the China Earthquake Administration failed to predict the devastating earthquake last May in Sichuan Province.
Even Japan, a country so experienced with dealing with earthquakes, could only give warning seconds before an earthquake. Sometimes it cannot give warnings at all.
A sudden earthquake is comparable to economic plunges that happen because of "a sudden shift in balance between buyers and sellers,'' writes Orrell.
The same is true on the health front.
While scientists have mapped the human genome and medical researchers have discovered what triggers certain conditions, it is completely beyond them to tell whether a particular set of conditions will cause certain diseases and whether specific treatments will work.
Perhaps the biggest complexity of all, as Orrell points out, lies in the interrelationship and the interaction between various systems.
Hence Orrell's conclusion: "The realization that the earth system is inherently unpredictable - coupled with a deeper understanding of ... complex systems - may turn out to be highly liberating.''
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