Apollo's Arrow

by David Orrell

Book Overview

Hurricane Katrina, the internet stock bubble, disease outbreaks -- are these predictable, preventable events, or are we merely the playthings of chaos? A compelling, irreverent, elegantly written... This description may be from another edition of this product.

• Format: Paperback
• Language: English
• ISBN: 0002245701
• ISBN13: 9780002245708
• Release Date: January 2008
• Publisher: Harper Perennial
• Length: 464 Pages
• Weight: 0.70 lbs.
• Dimensions: 1.1" x 5.3" x 8.0"

Customer Reviews

Entertaining Science

This book makes exceptional reading for a young scientist-to-be, or for an adult with a broad range of interests. Orrell's writing is light and enjoyable while still presenting an accurate history of philosophy, mathematics, and science. For me, the book provoked a great deal of thought, leaving me feeling like I could have a much greater interest in science and math than I would have thought. Stories of philosophers, mathematicians and scientists make for great reading when combined with Orrell's off-hand remarks and fluid writing style. Some of his enjoyable off-sides will age quickly--relating his historical tales to current times with references to Microsoft and George W. Bush for example. [I predict that these will become dated sooner rather than later. ;)] However, these slight flaws do not hinder Orrell's achievement of a delightful and easy-to-read look at matters that normally would seem a daunting study. If you have enjoyed books like Metamagical Themas, you will love this book!

A watershed in more ways than one!

For years most of us have been hearing about "models" of just about everything from weather and hurricane predication to the stock market. Since the advent of the desktop computer, almost everyone seems to have a model of something or other. For those of us who are not modelers, it all sees so cut and dried. Orrell, however, definitely pops the bubble on the works. The author points out that many of the models, contrary to what most of us understand, are designed to "predict" the past. The presumed variables involved in a particular phenomenon are put into the form of an equation, numbers are estimated for each, and the equation fed to a computer. The problem is that both the variables chosen and the numbers selected to define them are arbitrary and subject to the estimates made by the modeler. I first ran into this when I was taking a structural geology course for my BS in geology. The text went into an elaborate description of a river's output and presented an equation that was said to help estimate the watershed that fed into the river. After looking over all the letters in the equation and what they represented, I realized that most if not all of the variable were almost impossible to measure directly in any accurate way! Orrell indicates that this is the case with nearly all models. Furthermore he notes that in order to test the results of the model, it is compared to the past to see how well it "predicts" what has occurred. Then the model is tweaked to make it come closer to what was actually seen in the past to "fix" it, on the assumption that the future will be the same as the past. Most of us would probably accept this as a plausible method of approach, but the author notes that, while events may seem similar, history is perforce not repeatable. He also notes that because life and the earth itself are complex systems in a state of dynamic equilibrium, they are inherently changeable. The estimates of the variables might be anything, and the outcome will change as the estimates do. Because of the complexity of systems in a constant state of change, the interactions of all the variables in the system are inherently beyond our calculation. Thus the more detailed the model, the more subject to error is becomes. When I first read the author's comments on the weather and other phenomena, I was certain that he was among the nay-sayers over global warming and waited for his objections to the current trends aimed at correcting human impact on the environment. Not so. The author states emphatically that global warming, while the specific outcome is not predictable, is obviously occurring. I suppose it's difficult to ignore a missing glacier. What he does note is that our romance with science and data manipulation has encouraged us to be over optimistic about our ability to control nature. We place too great a trust in models and what their designer's tell us they mean and take mistaken courses of action with respect to cl

The pros, cons and uncertainties of prediction science.

How can we predict the future, and can past discoveries help interpret tomorrow's events, from weather to finances? It's time for another probe of prediction science and THE FUTURE OF EVERYTHING: THE SCIENCE OF PREDICTION offers the latest research and methods, examining how past scientists predicted the future and how modern scientists forecast events. The author received his doctorate in mathematics from Oxford: his background provides a grounded, rational examination which considers the pros, cons and uncertainties of prediction science. Diane C. Donovan California Bookwatch

A Fascinating Analysis of Scientific Prediction

This book concentrates on three main, seemingly unrelated, subjects: the weather, human health and the economy. In particular, the focus is on the shortcomings of the computer models that are used to make predictions in each of these disciplines. The author's argument is that "model error", more than any other reason such as chaos theory, is to blame for the models' inability to accurately predict future (especially longer range) developments in these areas. The writing style is clear and friendly, as well as quite engaging. I did find a few passages a bit heavy going, requiring a couple of re-reads so that I could better grasp what the author was saying. This is a fascinating book from which I learned quite a bit about the ways in which forecasts are made and why they are so often wrong. This book should be of interest to everyone with inkling towards the above disciplines, but especially science buffs.

Crunching the number-crunchers

Physicists insist that time travel is impossible. For physical objects, the speed of light cannot be exceeded, and that velocity is too firmly tied to the passage of time to be violated. Another form of time travel exists, however, one that's mental instead of physical. Using various numerical tools, we can undertake "travel" into the future. By doing so we shift the foundations of how we undertake planning and make decisions. How we do this and how well we've succeeded and what that bodes for the future is the theme of this study. A clearly organised and well-written effort, this book should have significant impact. In Greek mythology, "Apollo's Arrow" [the book's original Canadian title] was a form of time machine. Those fortunate enough to seize the passing arrow could be conveyed over obstructions and help perceive events. Orrell uses this as a metaphor to examine the forecasting of three significant elements: weather, health and wealth. Although at first glance these seem wildly disparate, he explains how the methods applied to them are very similar. And with similar results. Orrell opens with a discussion of the ancient "forecasters" of Delphi where the prophecies of the Pythian Apollo were expressed. Although these prophecies were obscure and possibly misleading, people made decisions based on what they believed was said. From the beginning, some petitioners to the Oracle were favoured over others, allowing them to dictate conditions. The mathematician Pythagoras added a new dimension to the forecasts by applying the power of numbers to them - although the method by which this was accomplished remains unknown. Nevertheless, today's forecasting is based on numerical analytical methods. Are they a real improvement over Apollo's expressions? Orrell begins answering that question with everybody's favourite topic - the weather. Although the ancients made many attempts to understand the workings of weather, it wasn't until the Renaissance that real gains were achieved. The invention of the thermometer and barometer initiated measurements that could be recorded and analysed over time. Further technological leaps seem to bring better forecasts. Robert FitzRoy, "evolution's captain" initiated the first forecasting service across the British Isles. Although complex mathematical models have since ensued, Orrell argues that the systems under investigation are too vulnerable to small perturbations to allow truly reliable forecasts of weather systems. The same inhibition holds true for the other fields of Orrell's presentation, health and wealth. No matter how well refined and tested the model, little incidents or influences can skew the final pictures. Small, almost undetectable factors have the capacity to set in train a cascade of unforeseeable outcomes, rendering the most carefully conceived model ineffective. Trying to fit the model into the real world's events as they unfold results in the designers engaging in hand-