- Shopping Bag ( 0 items )
Writing for the general reader and using examples from the environmental sciences, Orrin Pilkey and Linda Pilkey-Jarvis show how unquestioned faith in mathematical models can blind us to the hard data and sound judgment of experienced scientific fieldwork. They begin with the extinction of the North Atlantic cod on the Grand Banks of Canada, and then they discuss the limitations of many models across a broad array of crucial environmental subjects. Case studies depict how the seductiveness of quantitative models ...
Writing for the general reader and using examples from the environmental sciences, Orrin Pilkey and Linda Pilkey-Jarvis show how unquestioned faith in mathematical models can blind us to the hard data and sound judgment of experienced scientific fieldwork. They begin with the extinction of the North Atlantic cod on the Grand Banks of Canada, and then they discuss the limitations of many models across a broad array of crucial environmental subjects. Case studies depict 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, overoptimistic cost estimates of artificial beaches, and a host of other problems. The authors demonstrate how many modelers have been reckless, employing fudge factors to assure "correct" answers and caring little if their models actually worked.
— Carl Wunsch
— Fred Pearce
Useless Arithmetic dispels many myths and is a 'must read' packing in case studies and insights on faulty thinking.
[This] readily accessible book should be read by any activist who's ever had to face off against the opposition's engineers.
— Steven R. Carpenter
This book should be in every library... Essential.
— David Simberloff
This book is a welcome antidote to the blind use of supposedly quantitative models.
This is an easy and persuasive read.
A concise, powerful, and readable book.
Useless Arithmetic will surely excite any reader.
This book should be in every library... Essential.
The reliance on mathematical models has done tangible damage to our society in many ways. Bureaucrats that don't understand their limitations often use modeled predictions agencies that depend upon project approvals for their very survival (such as the U.S. Army Corps of Engineers) can and frequently do find ways to adjust models to come up with correct answers that will ensure project funding. Most damaging of all is the unquestioning acceptance of the models by the public because they are assured that the modeled predictions are the state-of-the-art way to go."-from Useless Arithmetic
one Mathematical Fishing 1
two Mathematical Models: Escaping from Reality 22
three Yucca Mountain: A Million Years of Certainty 45
four How Fast the Rising Sea? 66
five Following a Wayward Rule 92
six Beaches in an Expected Universe 114
seven Giant Cups of Poison 140
eight Invasive Plants: An Environmental Apocalypse 164
nine A Promise Unfulfilled 182
I stress that the problem was not mathematics per se but the place of idolatry we have given it. And it is idolatry. Like any priesthood, it has developed its own language, rituals and mystical signs to maintain its status and to keep a befuddled congregation subservient, convinced that criticism is blasphemy. . . . Most frightening of all, our complacent acceptance of this approach shows that mathematics has become a substitute for science. It has become a defense against an appropriate humility, and a barrier to the acquisition of knowledge and understanding of our ocean environments. . . . When used improperly, mathematics becomes a reason to accept absurdity.Linda has worked for both federal and state governments. Quantitative modelers, she independently observed, have an almost religiously fanatic outlook on the veracity of their models and brook little criticism. It is a characteristic we believe can be applied broadly to many natural-process modelers. The modeling modus operandi is shrouded in mystery, with necessary though poorly communicated assumptions made at each step along the way. In Linda’s view, those who rely on the models for making policy decisions rarely understand the limitations of the models, much less are prepared to communicate such information to the public.
Orrin H. Pilkey and Linda Pilkey-Jarvis: For more than twenty-five years we have monitored beach nourishment projects around the United States. In order to secure federal funding and justify the enormous costs of these projects, anyone undertaking one must make a prediction of how long the sand will last on the replenished beach. The predictions are based on mathematical models that are said to be sophisticated and state of the art, and yet are consistently, dramatically wrong—always in an optimistic direction. In the rare instances when communities questioned the models after the predictions of a long healthy replenished beach clearly failed, the answer typically was that an unusual and unexpected storm caused the error. Well, the occurrence of storms at any beach is neither unusual nor unexpected. Eventually we became interested in how models were used in other fields. When you start looking into it, you find that a lot of global and local decisions are made based on modeling the environment. There are some fascinating (and discouraging) stories of model misuse and misplaced trust in models in the book.
Q: What is the problem?
OHP and LP-J: The problem arises when we rely on quantitative models to find an accurate "when," "where," and "how much." We find that these types of applied models are frequently detached from reality—built on oversimplified and unrealistic assumptions about natural processes. Worse yet, we found that the modelers in many fields (global climate change being an exception) don't look back at the predictions to see if they were right. Instead they march forward, creating ever more sophisticated models. If your basic assumptions are wrong, it doesn't matter what the math does. By the way, the reader should not worry that this book is full of mathematical equations—it's not! This book is full of interesting stories and illustrates how the mathematically challenged can confront modeled predictions.
Q: You frequently use the term "fig leafs" throughout Useless Arithmetic. How does it apply to models?
OHP and LP-J: One example from our book is the "fig leaf" coverage provided by quantitative modeling in the Grand Banks fishery. The Canadian Grand Banks fishery has been described as the greatest in the world. It provided cod to the Western world for 500 years. In our lifetime, we watched the wild and senseless overfishing lead to the demise of an industry that employed as many as 40,000 people. The models, which many realized were questionable, provided a fig leaf behind which politicians could hide to avoid making the unthinkable decision to halt fishing.
Q: You also write about politics polluting mathematical models. How so?
OHP and LP-J: We tell the story of the selection of Yucca Mountain (Nevada) as the permanent repository for our nation's nuclear waste. Overconfidence in models caused the U.S. government and courts to set a ludicrously impossible standard of safety for the site. Now the federal government requires one million years of certainty that radioactive waste will not endanger the local communities. It should be obvious to all of us that there is no way to predict what will happen in the next million years—a time span longer than that of humans. During the next million years there will be several ice ages and vast changes in climate, and possibly earthquakes and volcanoes. The Yucca Mountain prediction is based on a precarious pyramid built by stacking hundreds of inaccurate models on top of each other.
Q. So what is the solution?
OHP and LP-J: The problem is not the math itself, but the blind acceptance and even idolatry we have applied to the quantitative models. These predictive models leave citizens befuddled and unable to defend or criticize model-based decisions. We argue that we should accept the fact that we live in a qualitative world when it comes to natural processes. We must rely on qualitative models that predict only direction, trends, or magnitudes of natural phenomena, and accept the possibility of being imprecise or wrong to some degree. We should demand that when models are used, the assumptions and model simplifications are clearly stated. A better method in many cases will be adaptive management, where a flexible approach is used, where we admit there are uncertainties down the road and we watch and adapt as nature rolls on.
Posted November 12, 2007
I highly recommend this book for engineers and modelers of natural systems who have dwelled too long in the world of fabricated realities and conflicted interests. You may not agree with everything the Pilkeys say - I didn't - but the book is sure to take off your rose-colored glasses and get your feet headed back towards the ground. This book encourages me, an ecologist who analyzes estuarine monitoring data, to keep questioning the assumptions and 'data' of fisheries and ecosystem models.Was this review helpful? Yes NoThank you for your feedback. Report this reviewThank you, this review has been flagged.
Posted October 24, 2008
No text was provided for this review.