Writing for the general, nonmathematician reader, the authors begin with a riveting account of the extinction of the North Atlantic cod on the Grand Banks of Canada.
The book offers fascinating case studies depicting how the seductiveness of quantitative models has led to unmanageable nuclear waste-disposal practices, poisoned mining sites, unjustifiable faith in predicted sea level rise rates, bad predictions of future shoreline erosion rates, over-optimistic cost estimates of artificial beaches, and a host of other thorny problems.
©2007 Columbia University Press; (P)2008 Audible, Inc.
"This is an easy and persuasive read." (New Scientist)
"This book is a welcome antidote to the blind use of supposedly quantitative models." (American Scientist)
This book is fascinating for someone interested in the Philosophy of "knowing". Scientist are regularly trying to capture magnificently complex systems in mathematical models that are, at best, applicable within a small range of parameters. No big deal...scientists do that. What is a big deal is that politicians and regulators then use those mathematical models to make decisions in the real world. Some of those decisions have had tragic results. If that interests you (as it did me), please read this book. If not you'll be bored to death.
A much needed expose on the inadequacies of quantitative modeling for environmental systems. A lot of the subject matter seemed to have a narrow focus; i.e. hours of information on beach erosion was not what I expected. Disappointingly, less time was spent discussing climate models. When referencing figures, the robotic phrase "Please reference downloadable pdf from product page where purchased" occurs frequently.
It's about useless arithmetic, but I think it is a pretty useless book too... I personally found it very boring and repetitive.
The concept in a nutshell is: don't trust mathematical models for complex systems, they can be twisted and bent to produce pretty much any result you want them to produce. Politics often gets in the way. In itself, not a bad topic altogether, but the examples it provides are dealt with ineffectively, with the same concepts repeated on and on and a lot of irrlevant material making things worse.
The authors also claim that less sophisticated models, which provide "qualitative" rather than "quantitative" predictions are better than complex ones and more useful. I have a hard time agreeing with this statement. Being an engineer, I've seen plenty of oversimplified models which simply could not capture the essence of certain phenomena and in the end completely failed to reproduce reality, even at the "qualitative" level.
Even though some interesting information is present in this book, it is buried within a lot of redundant and often irrelevant material and in the end there is no really useful recommendation that comes out of this book, except for a generic caveat againts making important decision based on mathematical "models" that can be wrong or misleading for a number of reasons.
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