Proving Darwin: Making Biology Mathematical Kindle Edition

3.3 out of 5 stars 21 customer reviews
ISBN-13: 978-0375423147
ISBN-10: 0375423141
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Editorial Reviews


“One of the great ideas men of mathematics and computer science.” —New Scientist

“Strange and marvelous. . . Disarmingly funny, but also thrillingly clear.” —The Guardian

“[Chaitin’s] enjoyment of the topics of his own research is infectious.” —The Times Higher Education Supplement
“Call him Omega Man. . . . In the rarefied world of pure mathematics, Gregory Chaitin is indeed something of a venerated superhero.” —Waterloo Region Record

“[Chaitin is] enthusiastic and extremely readable. . . . Amazing. No wonder [he] chose mathematics over physics.” —New Scientist

“The musings of a great mind on a subject beyond most of us.” —Ottawa Citizen

“Provocative. . . . Stimulating. . . . Credit the author for a lively style, lots of useful historical references and an appendix that includes von Neumann’s prescient essay on self-reproducing automata.” —Kirkus Reviews

"Gregory Chaitin has devoted his life to the study of mathematics. . . . A great mind.” —The Victoria Times Colonist

“[Chaitin] is a creative genius.” —Tucson Citizen

About the Author

Gregory Chaitin is widely known for his work on metamathematics and for his discovery of the celebrated Omega number, which proved the fundamental unknowability of math. He is the author of many books on mathematics, including Meta Math! The Quest for Omega. This is his first book on biology. Chaitin was for many years at the IBM Watson Research Center in New York. The research described in this book was carried out at the Federal University of Rio de Janeiro in Brazil, where Chaitin is now a professor. An Argentine-American, he is an honorary professor at the University of Buenos Aires and has an honorary doctorate from the National University of Cordoba, the oldest university in Argentina.

Product Details

  • File Size: 6105 KB
  • Print Length: 144 pages
  • Publisher: Vintage; 1 edition (May 8, 2012)
  • Publication Date: May 8, 2012
  • Sold by: Random House LLC
  • Language: English
  • ASIN: B006E512HU
  • Text-to-Speech: Enabled
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  • Word Wise: Enabled
  • Lending: Not Enabled
  • Enhanced Typesetting: Enabled
  • Amazon Best Sellers Rank: #324,628 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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Customer Reviews

Top Customer Reviews

By J. Andrew Howe on May 30, 2012
Format: Kindle Edition Verified Purchase
This book promised so much, and yet delivered so little. To be sure, the author has some very interesting ideas that are worth being exposed to but that does not save this book. The first problem is in delivery - almost the entire book seems to be taken verbatim from class lectures. Certain content is duplicated often enough, that the book could have been cut in half with no loss. The second issue lies in the content itself. The author claims to have developed a working toy model of Darwinian evolution. But there's one fundamental problem here - his model relies on algorithmic mutation to introduce diversity, whereas real organisms generally undergo bitwise mutation. Hence, his model allows for a much more sophisticated search of the genotype space than is allowed in nature. In the same vein, by his own admission, the model can not actually be simulated, because it relies on a fitness function that can not be guaranteed to produce a result.

Not as important, but still misleading, is that his result claims to model Darwinian evolution. This is not true, as Darwinism posits that all existing life forms came into being from nothing (or from a primordial soup, if you wish) solely through natural selection acting on genetic crossover & mutation. What his model actually demonstrates (or would, if it could be simulated) is non-Darwinian adaptation & evolution. His evolution is only capable of tiny incremental changes that can not possibly create entirely new structures - they can only rearrange existing structures.

In summary, the fundamental ideas relating biology-mathematics-creativity are very interesting, as is the goal of developing a mathematical model for evolution. However, all this is worth a 30-60 minute lecture; not this book.
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Format: Hardcover
Mathematician Gregory Chaitin attempts to provide a mathematical model of evolution in this short book based on a university course given in the Spring of 2011 at the Federal University of Rio de Janeiro, where the author is a professor. It also adapts material given at one of his lectures at the Santa Fe Institute. It is a quick read and an outline at best of his work, but it does give the reader a general idea of the concepts behind what the author calls "metabiology", an attempt to model evolutionary adaptation through computer software rather than natural software, otherwise known as DNA.

The central premise of this book is that by utilizing algorithmic information theory and the flexible and creative nature of postmodern mathematics, one can construct a working mathematical toy model of evolution, creating a piece of randomly mutating software that selects for a fitness trait. The main idea here is that DNA is a naturally occurring piece of software, our internal programming language as it were. This is not an original concept, but it is one that Chaitin expands upon greatly in the text.

I'll admit that it's an absolutely compelling idea. Evolution, after all, is the backbone of modern biology, but its main concepts are often misunderstood or outright rejected by a significant portion of the population. If one can really take a mathematical model and "prove" that the basic mechanisms of evolution (random mutations and natural selection) work as advertised, then it could go a long way towards advancing scientific literacy.

Keep in mind that the author's model is simplistic at best, selecting for only one trait and having none of the environmental pressures that truly drive adaptation.
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Format: Paperback Verified Purchase
This is a book in which Gregory Chaitin explores the fascinating topic of artificial life. Most scientists venturing outside their normal realm take pains to show that they have studied the new area - with name-dropping and citations. Chaitin doesn't bother with that. Indeed, he shows no sign of being aware of other workers in the field. He refers to the field as "metabiology" - and acts as though this is a new subject area which he has invented. While reading the book I kept wondering if he was going to cite the work of Chris Langton, John Holland, John Koza, Tom Ray, Moshe Sipper - or any of the other artificial life pioneers. John von Neumann did get referenced - but that was about it.

Does Chaitin say much of interest - despite apparently not having read any of the literature in the field? Unfortunately, not knowing the literature seems to lead to a distorted idea about what the open problems in the field are. Instead, Chaitin says he was inspired by David Berlinski's critique of Darwinism. Hang on, though. David Berlinski is a senior fellow of the Discovery Institute. He clearly doesn't have a clue what he is talking about. A scientist should not choose their research program based on what David Berlinski says. Chaitin just decreases his own credibility by taking Berlinski seriously.

Overall, this book won't be worth reading for most readers. If you want to learn about artificial life, I recommend looking to sources which have more thoroughly researched the topic.
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Format: Paperback
I feel compelled to weigh in here, if only to help balance the negative reviews. It's true that one who is not familiar with Gregory Chaitin's broader research program will probably not fully comprehend important points of his lecture series on which *Proving Darwin* is based. As one who has listened to Dr. Chaitin hold forth to an enchanted audience for a 20 minute stretch without benefit of notes or visual aids, however, I expect that if you give him a chance to influence your thinking on how life and mathematics intersect and evolve together -- you'll be enchanted, too. More, you might be motivated to look into the rich tapestry of results that Chaitin has woven from his Algorithmic Information Theory and Omega Number.

It's well worth the effort.

~ T.H. Ray
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