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Useless Arithmetic: Why Environmental Scientists Can't Predict the Future Hardcover – January 9, 2007

2.9 out of 5 stars 22 customer reviews

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Editorial Reviews

Review

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)

Review

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)
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Product Details

  • Hardcover: 248 pages
  • Publisher: Columbia University Press (January 9, 2007)
  • Language: English
  • ISBN-10: 0231132123
  • ISBN-13: 978-0231132121
  • Product Dimensions: 6.3 x 0.8 x 9.3 inches
  • Shipping Weight: 15.2 ounces (View shipping rates and policies)
  • Average Customer Review: 2.9 out of 5 stars  See all reviews (22 customer reviews)
  • Amazon Best Sellers Rank: #1,981,821 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

By Curtis Abbott on July 25, 2007
Format: Hardcover
The first author is a retired professor of geology and a particular expert on beaches. He's a scientist's scientist, and clearly an opinionated and occasionally irascible guy. This book is a bit of a tirade in places but it's full of real examples, good data, and thought provoking stories. I enjoyed it a lot. The main theme is that the natural world is too complicated a place for quantitative models to work well, and that when politics is involved they can lead to really bad decisions. The majority of examples are drawn from cases where earth sciences meet human activities - sea level rise, beach erosion and "nourishment", hydrology of abandoned pit mines, storage of nuclear waste. Closely related are discussions of fishery management and invasive species. For the most part the book is well researched. The writing is clear - the book is an easy read and never boring.
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.
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Format: Hardcover
At first glance, it is odd to single out environmental scientists for being unable to predict the future. However, like stock pickers, some preachers and electoral pollsters, environmental scientists do make a business of predicting the future.

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.
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Format: Hardcover Verified Purchase
I wanted to give this book three ratings: Five stars for the basic tenets, three stars for supporting their tenets and one star for violating every valid point they make when the discussion turns to man made global warming. The book is relatively short, but should probably be condensed to a chapter. Bottom line: I didn't find much in the book that wasn't already in one of the reviews.

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.
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