 |
GetTextbooks.com
Compare Prices & Save up to 90% |
|
|
|
| Login | Sign up | My Wish List |
 | | The Design Inference: Eliminating Chance through Small Probabilities (Cambridge Studies in Probability, Induction and Decision Theory) by William A. Dembski ISBN-10: 9780521623872 ISBN-10: 0-521-62387-1 ISBN-13: 9780521623872 ISBN-13: 978-0-521-62387-2 Hardcover 1998-09-13 Cambridge University Press Find Lowest Price |
Editorials | ||
Product Description How can we identify events due to intelligent causes and distinguish them from events due to undirected natural causes? If we lack a causal theory how can we determine whether an intelligent cause acted? This book presents a reliable method for detecting intelligent causes: the design inference. The design inference uncovers intelligent causes by isolating the key trademark of intelligent causes: specified events of small probability. Design inferences can be found in a range of scientific pursuits from forensic science to research into the origins of life to the search for extraterrestrial intelligence. This challenging and provocative book will be read with particular interest by philosophers of science and religion, other philosophers concerned with epistemology and logic, probability and complexity theorists, and statisticians. | ||
Reviews | ||
Not as bad as I expected, but... The first impression of this book, especially if one is familiar with the author's more recent writing, is that it is not nearly as bad as I expected. It has no trace of the whining self-pitying style that is so prominent on his web site, and although the attempts at humour are weak, at least they are not as embarrassingly awful as the current ones. Rather surprisingly, Richard Dawkins in quoted is a positive way on p. 40. One might cynically expect this to be an example of the sort of quote-mining that characterizes so much of creationist attempts at academic discourse, but it appears to be a perfectly genuine quotation that does not distort Dawkins's view. Likewise on p. 61 the book presents Stuart Kauffman's ideas on the origin of organization in a way that accurately represents Kauffman's view. One can only suppose that 10 years ago the author was still expecting to be taken seriously by academic readers. However, when this is taken into account, what is left? Not much, unfortunately. As early as page 7, the author reveals his weak grasp of statistical principles when he claims that "standard statistical method for testing" is unable to show when the agreement between observation and expectation is too good to be true. Despite the fact that he mentions R. A. Fisher both immediately before and immediately after this nonsensical claim, and despite the fact that most of Chapter 1 is about exactly this subject, he appears not to have realized that Fisher developed the methods for doing what he says cannot be done. Nonetheless, the early chapters of the book do a reasonably good job of providing a popular account of how we recognize when things are too good to be true in human affairs, for example when the person responsible for choosing between two political parties in an unbiassed random way nonetheless managed to get a result favouring his own party 40 out of 41 successive times. Later on the book dissolves into mathematical detail. For example, pp. 122-135 read like something that has strayed in from a mathematics journal. Who is supposed to be impressed by this? It is hard to imagine any genuine mathematician wanting to read through it after all the populist material that leads up to it, but it is equally hard to imagine a non-mathematician struggling through nearly 14 solid pages of propositions like "For every phi as a member of RMS(S) and every nonnegative real number c, c.phi is a member of RMS(S)". (This is one of the simplest examples -- it is hardly possible to quote a more typical one without access to all the typographical possibilities offered by a mathematical journal). Who is supposed to be impressed by this? Not the real mathematicians, who are unlikely to read it, but it may help to give a veneer of solid argumentation to readers who have no idea what is actually being said in these pages. Much of the second half of the book is like that. It would be interesting to ask one of the book's supporters to summarize what they learned from these pages without having the book in front of them. The central problem with the book's principal thesis is very clearly explained by Sahotra Sarkar in Doubting Darwin: Creationist Designs on Evolution (Blackwell Public Philosophy Series): design is recognized by rejecting inevitability and chance; it is never tested for its own sake. In any case, the scientific objection to "intelligent design" is not the second word but the first. All biologists understand that the appearance of design is universal in the biological world, and Richard Dawkins has devoted a whole book The Blind Watchmaker: Why the Evidence of Evolution Reveals a Universe Without Design to an explanation of why the appearance of design is not a reason to accept William Paley's old argument that design implies a design. | ||
The Case that Natural Selection is Pseudo-Science and a Religion The beauty of this book is not just that it has been peer-reviewed under the scrutinizing eyes of Cambridge mathematicians, but that it uses math to show that Natural Selection is no more provable by science than religion itself. It is time the scientific community (and the public that has been under its voodoo spell) be awakened using their own language (mathematics). Much as the early Church used Latin to confuse their followers into believing lies, so the atheistic scientific community confuses Joe Public with the language of math. Now, in their own language, random probability seems far-fetched as an answer to the origins of life. Leave it to the individual to decide what is, since a scientist can no more tell us the truth in that area than a preacher. | ||
When Is The Design Inference Warranted? _The Design Inference: Eliminating Chance Through Small Probabilities_ in the Cambridge Studies in Probability, Induction, and Decision Theory series, by mathematician and philosopher William Dembski is a fascinating book which lays out the case for the design inference attempting to show when such an inference is warranted. Dembski is currently a Fellow at the Discovery Institute, and this book was his dissertation for his doctoral degree in philosophy. The central question motivating this book is stated as "How can we identify events due to intelligent causes and distinguish them from events due to undirected natural causes?" The manner in which Dembski proposes this is done is through the design inference, which relies on uncovering intelligent causes by isolating the key trademark of intelligent causes: specified events of small probability. As Dembski shows in this book the applications of the design inference are widespread. Among other examples, Dembski considers the role of the design inference in forensic science, cryptography, the origins of life, the search for extraterrestrial intelligence, and parapsychology. Perhaps the most controversial application of the design inference occurs in the role of design in the origin of life. From this controversy, has arisen the debate between the standard Darwinian account of the origin of life and the account of life's origins given by the Intelligent Design Movement. Unfortunately, there are profound philosophical implications underlying this debate and this has led to the politicization of the debate itself. This is an unfortunate state of affairs because rather than allowing for the subject to be debated in a rational manner, the debate has instead moved into a state where each side engages in hysterics and attempts to slander the other side. However, if one wishes to understand this debate from an objective standpoint, this book is essential. Modern Western mainstream science has long waged a war on "the design inference" (since the time of Darwin), seeing in it an appeal to the supernatural. This has led to various domains which may make use of this inference (such as parapsychology) to be stigmatized and labeled as pseudo-science. However, as this book effectively shows, it is necessary to take a new look at the role of the design inference, free from the dogmatic tendencies ensconced in scientific orthodoxy. It should also be pointed out though that this book is highly mathematical in nature, and relies on probability theory to make its case. Following the mathematics may prove at times difficult for some. In his introduction, Dembski considers the history of the idea of eliminating chance through small probabilities. One of the earliest instances of such an argument occurs in the writings of Cicero. But, later mathematicians and philosophers such as Laplace, Thomas Reid, and de Moivre appealed to this argument. From the history of science, a famous instance of the use of the design inference occurs when Ronald Fisher used it to show that Mendel's experimental results were falsified. Dembski also notes the role of this inference in the intelligent design debate. It should be pointed out that while noted Darwinists such as Richard Dawkins allow for the possibility of this argument, they maintain that in the case of the emergence of life the probabilities involved are not small enough. The mathematician Emile Borel was the first to state a version of the Law of Small Probabilities (what he called the "Single Law of Chance") as "Phenomenon with very small probabilities do not occur." However, there are difficulties with Borel's formulation, and a distinction must be made between patterns which are specified and patterns which are fabricated. As it turns out, the Law of Small Probabilities can be stated as "specified events of small probability do not occur by chance". What constitutes a "small probability" is another question, which was considered by Borel, and Dembski elaborates on such considerations. Another question for the design inference that occurs is what is meant by an "intelligent agent". Dembski then proceeds to give some examples of the design inference in the case of the legal system, forensic science, cryptography, and SETI. Following this, Dembski explains the design inference, proposing an explanatory filter which allows for one to determine whether an event occurs as a result of a regularity, chance, or design. Once the design inference has been written as an argument in symbolic form, the rest of this book will be devoted to showing that such an inference is valid and expounding upon the Law of Small Probability. In the case of the Creation-Evolution controversy, the design inference becomes a possibility. However, as Dembski shows the premise rejected by the evolutionist is either that "If Life is due to chance, then Life has small probability" or "Life is not due to regularity". To get around the first premise, evolutionists such as Dawkins may attempt to appeal to greater probabilistic resources, for example invoking the fact that one must consider the possibility that life can occur on any of all the planets in the universe or even the possibility of other universes and then invoking the Anthropic Principle (as Barrow and Tipler do). Some such as Kaufman have tried to get around the second premise by maintaining that life results from regularity and "crystallizes" at a phase transition. However, as Dembski successfully shows later in the book all of these approaches by evolutionists are problematic. Dembski then considers what is meant by intelligent agency. The next two chapters are highly technical and lay the groundwork for probability theory and complexity theory. Dembski explains Bayes' theorem, probability, background information, and likelihood. Following this, Dembski explains complexity, tractability, and randomness. In particular, applications occur in proof theory in a formal axiomatic system. Dembski also explains specification and detachability as well as prediction. Dembski then revisits the notion of randomness, showing how one can only know randomness from what it is not, and explaining the notion of Kolmogorov complexity. Following this, Dembski returns to the idea of small probability. Here, he explains what is meant by the idea of probabilistic resources. In particular, the evolutionist will attempt to invoke probabilistic resources (all the planets in the universe, the possibility of multiple universes, etc.) in his attempt to disallow the design inference. Dembski in particular regards attempts to appeal to multiple universes (or the "multiple worlds" of one interpretation of quantum mechanics or the "possible worlds" of philosophers) as being part of an "inflationary fallacy". Such notions defy common-sense and also an appeal to Occam's razor. Dembski ends by fully justifying the Law of Small Probability based on his foundational discussion in the past chapters. In the epilogue, Dembski argues against some of the criticisms that have been made of the design inference. In particular, it has been maintained that the design inference may amount to an appeal to the supernatural in certain cases (particularly as concerns the origin of life on earth and in certain instances in parapsychology). However, I believe this results more from a prejudice against the supernatural by scientists than any legitimate objection. Dembski also shows what is meant by coincidence (for example he considers the case of a coincidence which occurred to Carl Jung that he regarded as an instance of "synchronicity"). Finally, Dembski argues for the importance of information, maintaining along with Keith Devlin that "information should be regarded as . . . a basic property of the universe, alongside matter and energy (and being ultimately interconvertible with them)." This is perhaps one of the most important books written on the issue of the design inference. The implications of this book are far reaching. And, if one hopes to understand the current debate over the origins of life on earth, this is essential reading. | ||
A Pleasant Surprise: Readable, Reasonable, and Precise Some time after the publication of this book I felt I had to read it since it was making such a stir and I'm doing my PhD in Philosophy focusing on Probability Theory and Philosophy of Religion. I had tried to avoid the fray, but I couldn't put it off any longer. I was very happy to find the book immanently readable (some training in mathematical logic is very helpful indeed, but even the reader lacking in that will, I think, find much worthwhile even skipping over the symbols). Dembski's main concern is to define his terms with as much precision and rigor as possible. He does this admirably. In fact, I'd say the book is a model of method. He is clearly trying to be clear and largely succeeds. It is obvious that most people who talk about "Intelligent Design" (Dembski's 2002 *application* of the design inference from InterVarsity Press)--both pro and con--don't know much of *anything* about it. Thus, this is the perfect book since it's main goal is to communicate the understanding of the subject and illustrate its usefulness to a wide variety of disciplines. So if you really want to understand the cognitive architecture behind the Intelligent Design movement, read this book. | ||
The Design Inference One needs more than a college logic course to follow this one; however, it is a fascinating trip through probability theory, with interesting examples, and Dembski "probably" comes as close as anyone ever has to establishing valid bechmarks for deciding what are random, chance or coincidental events and what are not. | ||