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Download The Future of Everything eBook

by David Orrell

Download The Future of Everything eBook
ISBN:
1568583699
Author:
David Orrell
Category:
Physics
Language:
English
Publisher:
Basic Books (February 26, 2008)
Pages:
458 pages
EPUB book:
1373 kb
FB2 book:
1142 kb
DJVU:
1157 kb
Other formats
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Rating:
4.3
Votes:
598


The Future of Everything book. David Orrell looks back to show us how past scientists (and some charlatans) predicted the future, and where we are on the path to truly understanding what comes next

The Future of Everything book. David Orrell looks back to show us how past scientists (and some charlatans) predicted the future, and where we are on the path to truly understanding what comes next. He asks how today's scientists can claim to predict future climate events when even three-day forecasts prove a serious challenge. Can we predict and control epidemics?

The Future of Everything:. has been added to your Cart. received his doctorate in mathematics from the University of Oxford

The Future of Everything:. received his doctorate in mathematics from the University of Oxford. His work in the prediction of complex systems has been featured in New Scientist and the Financial Times, and on BBC Radio, ABC Radio, and NPR. He lives in Vancouver, British Columbia.

David Orrell’s The Future of Everything is a wonderful guide and companion to that land; its history, its valuable .

David Orrell’s The Future of Everything is a wonderful guide and companion to that land; its history, its valuable resources and its fault lines. And it still manages to be a good read. Orrell’s writing is top-notch, but he’s at his finest when writing about the old days, somehow finding exactly the right mix of anecdote, broad brush, and humor. Mathematician David Orrell explains why the mathematical models scientists use to predict the weather, the climate, and the economy are not getting any better, just more refined in their uncertainty. Dr. Orrell is no climate-change denier. He calls himself green.

New York Times Bestselling Author. Creepers & Scavenger Series. Thomas De Quincy Series. Join David's Newsletter.

Summary of The Future of Everything. Whatever we select for our library has to excel in one or the other of these two core criteria: Enlightening – You’ll learn things that will inform and improve your decisions.

David Orrell looks back to show us how past scientists (and some charlatans) predicted the future, and where we are on the path to truly understanding what comes next. 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 history of our future that addresses the most important issues of our time, "Apollo's Arrow" examines such questions as: How well can we predict the future?

For centuries, scientists have strived to predict the future. But to what extent have they succeeded?

For centuries, scientists have strived to predict the future.

449 pages : 24 cm. Canadian scientist David Orrell examines the methods, past and present, used to predict future events and asks the question of whether modern science is any more accurate at predicting the future than the prognosticators and astrol. Canadian scientist David Orrell examines the methods, past and present, used to predict future events and asks the question of whether modern science is any more accurate at predicting the future than the prognosticators and astrologers of the past. Includes bibliographical references (pages 410-432) and index.

In The Future of Everything, David Orrell looks back at the history of forecasting, from the time of the oracle at Delphi to the rise of astrology to the advent of the TV weather report, showing us how scientists.

In The Future of Everything, David Orrell looks back at the history of forecasting, from the time of the oracle at Delphi to the rise of astrology to the advent of the TV weather report, showing us how scientists (and some charlatans) predicted the future. How can today's scientists claim to anticipate future weather events when even thee-day forecasts prove a serious challenge?

For centuries, scientists have strived to predict the future. But to what extent have they succeeded? Can past events-Hurricane Katrina, the Internet stock bubble, the SARS outbreak-help us understand what will happen next? Will scientists ever really be able to forecast catastrophes, or will we always be at the mercy of Mother Nature, waiting for the next storm, epidemic, or economic crash to thunder through our lives? In The Future of Everything, David Orrell looks back at the history of forecasting, from the time of the oracle at Delphi to the rise of astrology to the advent of the TV weather report, showing us how scientists (and some charlatans) predicted the future. How can today's scientists claim to anticipate future weather events when even thee-day forecasts prove a serious challenge? How can we predict and control epidemics? Can we accurately foresee our financial future? Or will we only find out about tomorrow when tomorrow arrives?
  • ChallengeMine
The book in general is easy to read, but some sections require some basic knowledge in math, economics and biology, though you may skip the excessively technical paragraphs, jump to the end of argument and still understand the general idea. The first three chapters present a very good summary of the history, philosophy and development of science, starting with the Greeks. A real crash course for those not familiar with these subjects and a necessary background to better understand the main topics being discussed in the book: The science of prediction in the fields of climate, health, and economics, and what I consider a very objective critic of simulation models and other techniques used for predictions on these fields. The book includes technical appendices, notes, a glossary and a full bibliography, so you can do follow-up or check the facts by yourself.

The explanation on Chapter 3 on the subject of complex systems is short but outstanding, allowing the layman to understand the basics without the confusion of the math involved. This explanation is fundamental for understanding the limitations of the science of prediction in non-linear systems, such as climate and economics, particularly because it makes clear that these models are not based simple on mathematical relationships reflecting cause-and-effect explanations, like Newton's laws. In astronomy you can calculate where the moon is going to be tomorrow at 5 am, this book makes crystal clear that complex systems are not like that, they are incomputable. And even if existing models can be twisted to fit past data, they cannot predict the future, as it is the case with many models in Economics and the climate simulation models supporting the consensus theory of Global Warming. It is well known that economists have developed models that can explain past external shocks, recessions, commodity booms, Dutch Disease, etc, so they understand conceptually what happened then, but they not predict the future, because neither the economy nor the climate are constrained to follow past behavior. The conditions of the initial variables are not the same, history does not repeat. Technically speaking, positive and negative feedbacks, and multiple feedbacks between the variable result in the inherent unpredictability of complex systems. For example, all 18 models used by the UN's IPCC 2007 Report cannot account for the clouds feedbacks, which may result in much lower temperatures than predicted or much higher (look for in the web for Chapter 8 of the UN's Climate Report, to check by yourself this and other important simulation limitations). As Mr. Orrell explained after showing how badly the OECD predicted GDP growth for the G7 countries from 1986 to 1998, "...Consensus between an ensemble of different models is no guarantor of accuracy: economic models agree with one another far more often than they do with the real economy" (pp 243). This statement is valid for climate models too.

Particularly Chapter 6, on economic predictions, is very interesting, but I will only comment on climate predictions, because so much is being discussed in the media and echoed by famous politicians and even Nobel laureates, with total disregard of basic scientific principles, and an absolute absence of scientific criticism or critical rationalism, as Karl Popper called it. Chapter 4, on climate forecast or prediction, begins with a brief but comprehensive summary of the history of meteorology and climate forecasting, which is important to understand the limitations of modern long-term predictions. As remembered to us by Mr. Orrell, Copernicus and Darwin hold publication of their works because they were afraid of the consequences, since their theories were against the scientific consensus of their times. Unfortunately, most of the environmental movement is blocking any serious discussion of the science behind the theory explaining the causes of Global Warming (the incomplete science has to do with the cause and effect relationship, not with the indisputable fact that most of the world is getting warm), which is based mainly on climate simulation models and assumptions about the state of affairs of the world for the next 100 years. And if you dare to contradict them, you become a heretic, since most environmentalists are acting as if defending a dogma. Not to mention that science must be politically neutral, as quite rightly cited by Mr. Orrell (pp. 107).

Since I do not want to spoil the contents of the book, let me just say that this book is a welcomed light of hope in the middle of the media and political frenzy regarding the real causes of Global Warming. We should be doing real science instead of politicizing science, and as Mr. Orrell recommends at the end of the book, "Apollo's arrow cannot fly to the future or protect us from plague, but it may serve as a compass, point out dangers, and help us navigate an unpredictable world", of course this is possible, if climate scientist stop playing politics and doing the science as they should, objectively and apolitically. Finally, someone has the courage to clearly explain what's wrong with the science behind the consensus theory explaining the Global Warming, as well as in other scientific and social fields.

The final chapter, "Consulting the Cristal Ball" is a must reading. Mr. Orrell presents quite a collection of ideas, scenarios, predictions, and concerns regarding how things will look in the year 2100, together with a box with some great predictions from the past. Just try to image how anyone would have made a reliable prediction of today in the year 1900 (such as cars, airplanes, television, CDs, iPods, computers, atomic bombs, you name it).

If you are serious about understanding the science behind Global Warming, this book is a must. Read it and as previously mentioned, it is worthwhile to search the web for the IPCC 2007 Report, Chapter 8, which presents the evaluation of the simulation models used by the U.N. and their present limitations. You will see that Mr. Orrell is right on the money, there are plenty of positive and negative feedbacks that these models can not replicate and other "anomalies" pending sound explanation. A highly recommended reading for follow-up is Marcel Leroux's "Global Warming - Myth or Reality?: The Erring Ways of Climatology" (too bad this is an expensive book!). We are in need of good old objective science.

Finally, after reading this book it becomes clear that climate simulation models lack any real explanatory power and are incapable to make any reliable predictions, so it seems appropriate to close with a quotation from the best known (Nobel Prize) advocate of the manmade GW based on climate simulation models:

"I have learned that, beyond death and taxes, there is at least one absolutely indisputable fact. Not only does human-caused global warming exist, but it is also growing more and more dangerous, and at a pace that has now made it a planetary emergency". Al Gore, "An Inconvenient Truth: The Planetary Emergency of Global Warming and What We Can Do About It", 2006.
  • Kirinaya
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 climate change, epidemic diseases, and the economy. The entire book is intended to alert and caution the general public about grand claims.

A superb book.
  • Rigiot
A book that everyone should read. The paperback is finally out; so if cost is a factor you can still read it. There may be more math than most would like but there is an attempt to keep it to the minimum with notes for those who want the details. If your are worried about global warming, do investing, or wonder about your DNA, then this book will be interesting.
  • Buzatus
Underwhelming. This is a book from someone in dynamical systems discussing chaos in settings to which dynamical systems theory may or may not apply. It is also a typical modern book where 50 pages of material is written and then expanded to 500 pages by adding (possibly through internet searches) background material in great detail on every proper noun in the book. The main point of the author is that model error is also important and he mentions work he has done suggesting it is very important. He does not mention contrary work that has given data suggesting errors in initial conditions contribute 80+% to total uncertainty in weather forecasting. The topics are such that (in my opinion) some precision is required to make sense while the book avoids it studiously.