7 of 7 people found the following review helpful:
4.0 out of 5 stars
Rethinking the process of thinking, January 1, 2004
The astonishing thing about human communication is not that it sometimes fails but that failure is so rare. Given the complexities of context, facial expressions, tone, body movements, and grammar, all going in at least two directions, it is truly incredible that it works so well. As the author points out by example, he can write a sentence that no one else has ever created before, and yet there is no difficulty in determining what he means. Understanding human language is a situation where our obviously finite brains are capable of resolving an infinite number of scenarios. The examples given in this book make you appreciate just how much "computing" power there is in the human brain.
Many of the theories regarding the instinctive understanding of human language, independent of word order, are considered and often questioned. The gross shortcomings of Artificial Intelligence (AI) are also raised and used to demonstrate that there is now no effective model for how humans process data and make "rational" decisions. Despite all the original promise and hype, AI has been used to solve few problems and even some of the reported successes are clearly very weak when thoroughly examined. Therefore, the argument throughout the book is that there needs to be a new approach to the problems of cognition
The arguments are presented in a thoughtful, detailed, and understandable manner. There are times when the arguments do get technical, but they are few and can be skipped without disrupting the flow of the material. At the end, Devlin also argues for a radical rethinking of the last three thousand years of traditional reasoning that dates back to the Greek origins of logic. He uses the phrase "soft mathematics" to describe what he believes the answer to be. Unfortunately, or perhaps necessarily, he is quite vague as to what it is. Devlin only points out that it will be something quite different from the current rigorous reasoning.
Raising some profound and fascinating questions regarding fundamental shortcomings in understanding the most human of activities, Devlin is at his best. Whatever your field of interest or background, if you are interested in thinking about thinking, then you must decipher the squiggles that appear on these ages.
Published in Journal of Recreational Mathematics, reprinted with permission.
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9 of 10 people found the following review helpful:
5.0 out of 5 stars
Monty Hall reasoning correct, July 29, 1997
By A Customer
The previous reader makes the same error with the monty Hall Problem as do many. New Scientist has been running a web discussion on this problem in its "biteback" section (http:www.newscientist.com),
after a strongly positive review of "Goodbye Descartes" brought a small deluge of letters from readers who, like the previous reader, had misunderstood not only the correct Monty Hall solution given in the book, but along with it most of the book's argument.
Wise readers will decide for themselves who is "right" on this issue.
--Keith Devlin
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6 of 6 people found the following review helpful:
3.0 out of 5 stars
argues effectively for a new approach to the human mind., September 6, 2004
This review is from: Goodbye, Descartes: The End of Logic and the Search for a New Cosmology of the Mind (Paperback)
For more than 2000 years, philosophers and scientists have attempted to use symbolic logic to investigate the structure of language and, by extension, the human mind. Our speech and thought processes, they believe, operate according to underlying rules that are rigorously mathematical. Devlin argues that this approach is a dead end and that we should pursue new avenues of research.
Much of the book is a critique of symbolic logic. Invented by Aristotle, it was merged with algebra and became a branch of mathematics and its most recent applications have been in artificial intelligence (AI) as well as the liguistic of Chomsky. What these disciplines have in common - what is "cartesian" about them - is their attempt to "captur[e] patterns of reasoning...in a pure fashion, isolated from context" and even meaning. In this view, computers are the perfect logic machines, processing info by manipulating symbols without understanding what they are doing.
The failure of AI to meet its original goals demonstrates, in Devlin's view, what is wrong with this approach. AI (or an "expert system") lacks common sense, whatever its daignostic capabilities, and cannot make judgments when unforseen or ambiguous situations arise. Consequently, AI cannot operate outside extraordinarily narriow confines and hence are unreliable in many applications. Computers have also failed to produce a human-like language. This is proof, Devlin says, that the human mind is more than a logic machine ("Smart meat" as the WIred crowd might argue) that acts according to rigid subsystems of logical rules: context and meaning matter. These arguments are convincing and cogently argued.
Unfortunately, Devlin's arguments of where to go from there are far weaker than his analyses of past failures. The last third of the book is a loose jumble of idaes and speculation. He wants to create a "soft math" to incorporate context, meaning, and the qualitative into the study of the human mins, but does not get beyond saying we need it. THis is a research agenda, but too vague to be of much use in my opinion. Of course, maybe I am expecting too much and his next book will cover that!
Unfortunately, his writing style is repetitive and gets bogged down in elaborate proofs and thought experiments - just the type of arcane stuff that keeps (or bars) many of us from reading more by academics.
So this is a mixed bag. The ideas on the human mind are well worth the effort, but getting through it is not fun, at least for me.
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