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Useless Arithmetic: Why Environmental Scientists Can't Predict the Future Hardcover – January 9, 2007
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This book is a welcome antidote to the blind use of supposedly quantitative models.(Carl Wunsch American Scientist)
This is an easy and persuasive read.(Fred Pearce New Scientist)
Useless Arithmetic dispels many myths and is a 'must read' packing in case studies and insights on faulty thinking.(The Midwest Book Review)
[This] readily accessible book should be read by any activist who's ever had to face off against the opposition's engineers.(Earth Island Journal)
A concise, powerful, and readable book.(Steven R. Carpenter Issues in Science and Technology)
This book should be in every library... Essential.(Choice)
Useless Arithmetic will surely excite any reader.(David Simberloff BioScience)
Using concrete examples, the authors of Useless Arithmetic cut through the scientific jargon to show how and why many aspects of the environment are under threat because of the slavish adherence to misleading mathematical models by their technical and political advocates.(Victor R. Baker, University of Arizona)
In a complex, imperfect world quantitative models feed the delusion that society can predict its way out of its environmental dilemmas. The corrosive result is that politics and science have become inextricably interwoven to the considerable detriment of both. This engaging, wise, and far-reaching book diagnoses the causes and costs of our quantitative hubris, and in so doing points the difficult way toward a more productive relationship among science, democracy, and the vexing challenges of environmental stewardship.(Daniel Sarewitz, director, Consortium for Science, Policy, and Outcomes, Arizona State University)
Useless Arithmetic is an important book for those of us who believe that environmental science and policy should be self-correcting on the basis of experience. Written for lay persons, it draws attention to a broad range of sobering experiences typically ignored in the over-promotion of quantitative models for predictive purposes.(Ron Brunner, Center for Public Policy Research, University of Colorado, Boulder)
Orrin H. Pilkey and Linda Pilkey-Jarvis argue that many models are worse than useless, providing a false sense of security and an unwarranted confidence in our scientific expertise. Regardless of how one responds to their views, they can't be ignored. A must-read for anyone seriously interested in the role of models in contemporary science and policy.(Naomi Oreskes, professor, Department of History, University of California, San Diego)
Top Customer Reviews
Quantitative models are decried throughout the book, and the suggestion is made that what is reasonable is "qualitative" modelling. The distinction isn't really developed until the last chapter where some good examples are to be found. Still, the distinction isn't as crisp as I'd like - perhaps it is a qualitative difference and not a quantitative one! Another positive suggestion is that incrementalism is a generally better approach to interacting with the complexities of nature than the brittle approaches that arise from an overly numerate engineering mentality. In other words, instead of using quantitative models to plan enormous, long-term projects, try something on a small scale, observe the results, and go from there.
I came away with considerably more knowledge of the topics discussed.Read more ›
Not one of these groups has had any success, but it is arguable that the environmental scientists have done the most damage to other people by being wrong.
Orrin Pilkey, a well-known if not always well-liked specialist on coastal processes at Duke, began a seminar to examine why the predictions of coastal engineers seemed so often to lead to projects that didn't work. (I have known the North Carolina beaches where Pilkey does much of his work for more than 50 years. The Outer Bankers hate what Pilkey says about their beaches, but he's right.)
The investigation led to a wider examination of numerical models of all sorts of natural processes. Among those examined -- all failures -- were managing the Grand Banks fishery, predicting the lifetime of nourished beaches, predicting toxicity of lakes in abandoned pit mines and predicting how fast sea level will rise. Predictably, more attention is paid to coastal processes than anything else, but other topics get fair treatment, even one as far from the coast as the Yucca Mountain atomic waste dump.
What the Pilkeys found was no surprise to me as a newspaper reporter, and will be even less a surprise to scientists. People forget, but reporters keep clipping files. Mine contain many reminders about predictions made but unfulfilled. The Pilkeys conclude that it is impossible to write quantitative numerical models of any complex process on the surface of the earth.Read more ›
The Good: The authors advance the idea that mathematical (computer) modeling of complex systems is often misused. A combination of not understanding all of the important physical processes, making inappropriate assumptions about initial conditions and improper handling of chaotic events make the predictions inaccurate. The process is further corrupted by politics, money, bias and hubris. This is all too true.
The subject material is presented virtually without mathematics and can be understood by just about anyone. It will also arm the lay person to ask questions that are likely to be embarrassing to most models. Those questions range from "what were the assumptions?" to "has the model successfully predicted events or does it need to be constantly fudged to match the real world?". Multiple examples are given of assumptions and processes that violated basic common sense.
I was particularly interested in the chapter on modeling the nuclear waste repository at Yucca Mountain. I made some of the permeability measurements of basalt and granite that were used in the models. I shared office and lab space with people that generated a lot of the measurements on salt that went into the modeling effort. I can't offer independent confirmation of every statement the author's made.Read more ›
Most Recent Customer Reviews
Excellent work. I have now read the text from cover to cover. I have a bachelor's and masters degree in geology, and an MBA and a PhD in organizational behavior and theory. Read morePublished 7 days ago by Amazon Customer
As many reviewers have said, this book gives an excellent account of some deeply flawed modeling practice. Read morePublished on November 26, 2010 by Aaron C. Brown
The key points regarding this book have been well summarized by previous reviewers. The star ratings are somewhat deceptive. Read morePublished on October 10, 2009 by Bookworm
The authors of this book do not provide useful criticisms of environmental modeling and only highlight their own ignorance. Read morePublished on April 22, 2009 by C. Merow
I am a modeler. I was happy to hear one of mentors, Charlie Hall, mentioned in another review here. Read morePublished on March 6, 2009 by Seth J. Myers
"Usless Arithmetic" was, both, good and bad. The authors seem to know the subjects upon which they are writing. Read morePublished on January 9, 2009 by Norman Strojny
The Pilkey's have given a thoughtful and thorough review of how mathematical models can be used improperly. Read morePublished on November 30, 2008 by J. Cunning
I share an office with a fisheries modeller who I tease constantly about fudge factors etc. My experience with models has been exactly what is so well put together in this book. Read morePublished on October 31, 2008 by Wendy Barron
A repetitive and droning treatment on the topic of the over-reliance of the scientific community on computational models. Read morePublished on March 27, 2008 by A. Neal