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54 of 62 people found the following review helpful
5.0 out of 5 stars Refreshing
This is a review intended for the experienced popular science reader. As someone who is fairly widely read in the popular science literature, I found this book to be refreshing. Let me explain. A problem I've had with many popular science books is that they tend to all repeat the tired "greatest hits" of science and math stories, even if they're only ever so slightly...
Published on October 11, 2012 by Johan U.

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49 of 57 people found the following review helpful
3.0 out of 5 stars Expected a bit better
This is a book on a very interesting subject that mostly irritated me in the end.

I think the biggest issue I had with it was the very myopic view applied to the topics. And the fact that I think that Mr Arbesman really makes too much of the methods he relies on to tell a story. Basically the book relies on the idea that you can graph anything that you can put...
Published on November 10, 2012 by Marsapalto


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54 of 62 people found the following review helpful
5.0 out of 5 stars Refreshing, October 11, 2012
This review is from: The Half-life of Facts: Why Everything We Know Has an Expiration Date (Hardcover)
This is a review intended for the experienced popular science reader. As someone who is fairly widely read in the popular science literature, I found this book to be refreshing. Let me explain. A problem I've had with many popular science books is that they tend to all repeat the tired "greatest hits" of science and math stories, even if they're only ever so slightly related, in a manner that makes them tired. For example, when Graph Theory 1736-1936 brings up the 'Seven Bridges of Königsberg', this is relevant; when Fermat's Enigma brings it up, Singh is stretching the connection simply because it's a good story. But for frequent readers of popular science writing, it feels more like a disservice. For the well read fan of popular science, the seven bridges, the Monty Hall problem, and the birthday paradox are well known.

And so, I was delighted to find Arbesman's book genuinely refreshing. He omits any discussion of Königsberg and the birthday paradox, which would have been off topic, and instead contributes a genuine thesis about the 'science of science' that is delightfully fresh. Many of his vignettes were entirely new to me: the coPub approach to discovering links between disparate domains of science, his review of Galton's more esoteric studies (apparently Galton was an early Scientometrician, the book discusses several great studies I'd never heard of), and the 'Bone Wars' that have shaped the public knowledge of dinosaurs.

So, I guess what I'm trying to say is that I'm a sucker for vignettes, and where many books fail to deliver me fresh ones, Arbesman's tour of scientometrics offered wonderful portions of fresh meat. Yes, there was Pluto, and a somewhat slow discussion of exponential growth, but I'll forgive that. This was a worthy read.

Note: I "read" this book as an audiobook while on a long drive. When I've recommended a book that I've audiobook'ed in the past, it has on occasion happened that people have found it slow in book form when I had no such opinion of the audiobook. This seems to be because it's easier to space out during a chapter while driving then to wade through a slow chapter of reading. I don't think that's the case here, but just a brief warning.
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49 of 57 people found the following review helpful
3.0 out of 5 stars Expected a bit better, November 10, 2012
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This is a book on a very interesting subject that mostly irritated me in the end.

I think the biggest issue I had with it was the very myopic view applied to the topics. And the fact that I think that Mr Arbesman really makes too much of the methods he relies on to tell a story. Basically the book relies on the idea that you can graph anything that you can put a number on, and then using math that is complicated compared to, say what you learn in high school, you can fit a line to any graph and a lot of times that line is a particular family of curves. He makes it sound very magical but its not really - sometimes the fit is great and you can learn a lot from it but you can do this, like I said for anything. It doesn't per se, mean anything major. It isn't really even uncovering any secrets of how things are organized in nature or the world - we're fitting the lines after all.

Plus, when he talks about science he seems to ignore lots of factors that would make his "story" messier or just different. He talks a lot about citations of research papers but without seemingly understanding how people actually function in science. Finally, at the end, he has a chapter that promises to discuss the "human" aspects of knowledge generation but he doesn't really do that there either. What I mean is, he attributes the fact that few references in papers appear to have been actually read by the authors to laziness and doesn't talk at all about how social networks among scientists influence choice of citations (i.e. I cite what my boss cites, or even better, what he wrote) despite have a whole chapter on the social movement of information just earlier in the book! Lame, I say!
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17 of 18 people found the following review helpful
5.0 out of 5 stars The Half-Life of Facts, October 24, 2012
This review is from: The Half-life of Facts: Why Everything We Know Has an Expiration Date (Hardcover)
After I saw Samuel Arbesman speak at Tedx Kansas City a few weeks ago, I knew I had to read his book. The premise of his talk and his book is that facts are not really information set in stone, the way we usually think about them. The world is constantly changing and nothing is for certain forever. I was floored by the notion that what my kids are learning in school may contradict what I learned in school. For some reason, that notion had never occurred to me!

The Half-Life of Facts is easily understood by a lay person. I found it very readable and I don't have a head for science at all. Each chapter outlines a different reason why facts may either change or be found to be untrue. Arbesman uses examples throughout, all of which I found fascinating. I would love to read even more stories about which facts have changed over time and why.

I was surprised by some of the facts that are no longer true. For instance, did you know that there really isn't a dinosaur called a Brontosaurus? I had no idea and both of my boys have been through dinosaur obsessions within the past few years. The Brontosaurus was found to be a type of Apatosaurus over a hundred years ago. However, once something is out in the ether, it's really hard to circulate information modifying or correcting the original assertion.

I appreciated that not only does Arbesman discuss the various ways in which untruths persist and facts change over time, he also offers suggestions of how to keep current without getting information overload.

I love that in keeping with the spirit of The Half-Life of Facts, Arbesman's website has a Errata and Updates section for the book. There is already one case listed in which Arbesman unknowingly perpetuated a myth about how spinach became known to have a high iron content.

It's very rare that I read a non-fiction book that I have a hard time putting down. The Half-Life of Facts is one of those rare riveting works of non-fiction. I highly recommend it to all.
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17 of 20 people found the following review helpful
2.0 out of 5 stars Aggravatingly bad, March 1, 2013
This review is from: The Half-life of Facts: Why Everything We Know Has an Expiration Date (Hardcover)
The author put me on edge almost immediately with how much hype he crammed into his introduction. It was as if he wrote three different introductions, and just included them all instead of editing them down. But I figured I would wait to see the actual substance before passing judgment. Unfortunately, that also failed to deliver. After 30 pages of buildup, his first example (and as it turns out, his ONLY example) illustrating the title of the book and his main thesis, makes me certain that he failed high school math. This is rather distressing, as his bio starts off by saying he is an applied mathematician.

Arbesman cites a study where nearly 500 medical articles from the past 50 years were vetted by current experts, and a graph is shown which displays the time since publication on the x-axis and the percentage that stand up to scrutiny on the y-axis. The graph is ambiguous, showing a stair-step curve so that you can't tell where the actual data points are, but this is not the main problem. The graph clearly shows a curve which is accelerating downward; it is concave down. Arbesman infers from this that "they got a clear measurement for the half-life of facts in these fields by looking at where the curve crosses 50 percent on this chart: forty-five years." He goes on to say that this graph displays exponential decay. This is blatantly and hilariously wrong. An exponential decay curve has exactly the opposite shape, its rate of decay slows down, it is concave up. If the half-life were 45 years, then it would cross the 25 percent mark at 90 years. However, the graph shows it dropping to 25 percent at about 50 years. Even worse, this graph does not track a group of papers published at about the same time, displaying their time to be disproven or rendered obsolete. It takes papers published at different times and tested at one time, so there is no real valid comparison between them. An exponential decay curve will drop to half of its value in a certain amount of time, FOR EACH POINT ON THE CURVE, meaning, you need to measure this 45 years at multiple times and make sure it is consistent. Arbesman tries to infer such a curve from only one data point, and because of the problem with how the papers were selected, it's not even a true data point.

This tendency to draw grand conclusions from insufficient data pervades the text. On page 18 he states that Nobel laureates tend to give first authorship of their papers to their younger colleagues more frequently that other scientists. His immediate conclusion is that nicer people are more likely to win Nobel prizes. This is a fundamental error, similar to how false positives can be relatively frequent in drug tests compared to true positives, despite a high testing accuracy. The population of Nobel laureates is much smaller than the population of nice people who also happen to be scientists. The conclusion does not follow.

Another example: On page 53, he states that the average American lifespan is increasing, and that this rate of increase is itself increasing. Without blinking, he says: "If this acceleration continues, something curious will happen at a certain point. When we begin adding more than one year to the expected life span ... per year, we can effectively live forever." This of course does not follow. It is entirely conceivable that lifespan increases will tend to be heavily weighted towards younger people, i.e. medical technology may help a baby live to be 150, but not an 80-year-old man who didn't have that technology 80 years ago. Whether or not this is the case is irrelevant; Arbesman does not provide enough information to show it.

There are much simpler examples as well. On page 46, he says that the movement abilities of robots "have gone through about thirteen doublings in twenty-six years. That means that we have had a doubling about every two years: right on schedule and similar to Moore's Law." No, it doesn't. He has not given any indication that these doublings have been equally spaced.

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His apparent lack of understanding of math, and inability to explain it clearly, also shows up throughout the book. On page 42, when describing Moore's Law of exponential increase, he says, "Processing power grows every year at a constant *rate* rather than by a constant amount." These are the same thing. A constant rate means growing by a constant amount. Of course he means that the rate itself is growing, proportional to the processing power (not at a constant rate, that would be quadratic growth instead of exponential), but his explanation is obfuscated.

A few pages later, he is describing how multiple logistic curves (curves that start out looking exponential but eventually approach a maximum, as in population growth) can be overlayed to produce an exponential looking curve. The point of this is to illustrate how successive technologies can contribute to a continued exponential growth in processing power or whatever. But the graph he includes shows three of these "S-curves" combining to form a linear trend, a straight line. He certainly does not state that the scale is logarithmic, in fact the axes are not even labelled. I really doubt that he understands the difference between constant, polynomial, and exponential growth.

On page 59, we have this gem: "A population's growth rate will increase in size proportionally to the current number of people. To be clear: This is much faster than exponential growth, the fastest growth rate we've considered so far. Exponential growth is a constant rate, and here the rate is growing, and growing along the speed at which the population increases." Now, this completely confused me until I figured out that he was actually talking about technological growth, not the actual growth of the population. But even so, the statement is absurd. Exponential growth is NOT a constant rate. (It's a constant proportion, making the rate grow, well, exponentially.) At this point I'm pretty sure that he's never taken an intro level calculus class.

I'm not just cherry-picking the worst examples. This stuff is on virtually every page. I started skimming heavily at around page 40, and still managed to find all these examples. The funniest one is on page 149: "By fitting the curve of Pluto's diminishing size to a bizarre mathematical function using the irrational number pi, they argued that Pluto would vanish in 1984." Bahaha, that must be a bizarre mathematical function indeed, to be using irrational numbers like pi. That kind of thing NEVER happens in math.

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The book is also sloppy in many non-technical ways. Arbesman constantly touches on topics without ever finishing his thoughts, or refers back to something that he didn't actually talk about before. Around page 80, he is telling a story about a nasty rivalry between paleontologists Edward Cope and Othniel Marsh. He talks about Marsh discovering the brontosaurus and the apatosaurus, and then a bit later says, "Despite their vitriol and animosity, they actually didn't fight any more about the brontosaurus." But I don't know what he's talking about here, because he never mentioned them fighting about the brontosaurus to begin with.

On page 161: "Regarding a kerfuffle about the possibility of bacteria that can incorporate arsenic into their DNA backbone ... Carl Zimmer explains: 'But none of those critics had actually tried to replicate the initial results.'" He goes on to make points about replication and publishing negative results, etc. But what about the damn arsenic bacteria? What ever happened with them? I remember reading an article when that was discovered, and now I'm curious.

The most maddening case of this is on page 134: "Some famous problems go decades before being solved, and some, those that exist far out in the tail of the distribution, remain outstanding for hundreds of years. There was even a famous conjecture in the data set that took more than fifteen hundred years before it was eventually proven." WHAT WAS IT?!! The longest ones I can find, proven or not, are Fermat's Last Theorem, the Goldbach Conjecture, and Kepler's Conjecture. Seriously, if anybody knows the answer to this, comment with it please.

-

Probably the best parts of the book are when Arbesman is quoting or summarizing somebody else. There is actually quite a lot of this, and it's why it just barely gets 2 stars. But it's a shame that it's covered in crap, and I'll never see most of it. This book was a birthday gift, along with Nate Silver's The Signal and the Noise: Why So Many Predictions Fail -- but Some Don't. I let a friend borrow that while I was reading this one, and he said it was pretty good, so maybe go read that instead.
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7 of 8 people found the following review helpful
4.0 out of 5 stars The Half Life of Facts (or more appropriately "the current consensus"), January 16, 2013
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J. Humphrey "lostmountainman" (Sequim, Washington United States) - See all my reviews
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This review is from: The Half-life of Facts: Why Everything We Know Has an Expiration Date (Hardcover)
A very interesting discussion with some details, but also limited in that the term "Fact" is not precisely defined.
Almost nothing in Science is "Fact"! 99.99999999% of Scientific data supports a theory or theories through the support of evidence produced in various studies that may or may not have been designed properly to support the theory being tested. For example lack of precision in the use of the term "Fact" has led to the statement paraphrased as 'Global Warming and Climate Change Due to Rising CO2 Levels is Settled Science'(blatantly false as to the "settled science" conclusion). The whole thing is a theory that has been modeled and tested to some degree but certainly not to the degree of predictive certainty.
The problem in that situation is that the ability to precisely measure temperature and the necessary complete record keeping from the past allowing one to compare current temperatures to those 100-200 years ago or longer is just not available. Therefore those who study this area use proxies such as tree rings, etc. There are many variables affecting what produces our weather and climate that we know about, and likely thousands if not millions of ones we know nothing about. That makes any realistic projections based on atmospheric CO2 content simple extrapolations and calling it settled science is ludicrous.
That area of study is not the primary subject of this book, but the author uses the word "fact" when the more appropriate word/words would be "consensus belief", "knowledge" or "current theories" in the title and discussion would be more appropriate. The problem with using the word "Fact" is that the general public and some scientists associate "Fact" with "Truth" which is a major mistake. There are only a few absolute truths such as the value of Pi and a few other constants and very basic theorems.
The political class and politically motivated scientists use the word "fact" in such a sloppy way that it's meaning has been perverted. More alarmingly they are using such statements to force major laws and policies on the entire human population worldwide using "theories" stated as "facts".
The late Stephen J. Gould, PhD wrote many books and essays dealing with this subject as it applies to evolution and natural science. His writings document vividly how the "Facts" of the day were used for political purposes to the detriment of whole races of people, and in fact, set the stage for racial problems present in our country and worldwide among many other examples. The author may cite some of Dr. Gould's writings but in reading half the book I have yet to see any mention of his work.
Using the word "fact" with such a loose definition is very dangerous and increasingly so because of the internet and how easy it is for people to read selectively to support beliefs and not consider the many aspects of an area of study leading to an absolute belief when it is clearly not justified.
While I think this book is a good discussion of the evolution of knowledge and how "current theories" or "current consensus belief" evolves in a predictable pattern, I wish the word "Fact" was not used. The very subject of the evolution of "current consensus belief" to an entirely different place over time and the definition of a "half-life" for such things is proof that what is being discussed is not "Fact" but current theory at best.
I would recommend reading this book for the theory and discussion but would always stay conscious of the false use of the word "Fact" and the need to translate it's meaning to another less definitive word or phrase.
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27 of 38 people found the following review helpful
2.0 out of 5 stars An Epistomological Rabbit-Hole, October 3, 2012
This review is from: The Half-life of Facts: Why Everything We Know Has an Expiration Date (Hardcover)
Author Arbesman is an expert on the topic, and I picked up the book expecting to read a credible summary of how fast knowledge is increasing and changing. Instead, some generalities (eg. smoking has gone from doctor recommended to deadly, we used to think the Earth was the center of the universe), followed by data on the pace of new information in a few areas that seems suspect to me. Specifically, that major contributions to medicine and hygiene double in 87 years - that doesn't seem right considering the fact that medical experts assert that one-third of medical treatment is given w/o evidence of efficacy, the anticipated contributions of DNA research, automated drug research, and the promise of government-sponsorship under ObamaCare to greatly expand clinical research. As for chemistry, the author reports a much shorter doubling time - 35 years, and 32 years for genetics. Arbesman then expounds a bit on Moore's Law, adding comparative data on the progress in digital cameras, Internet speed, etc.

Overall - too many of the 'knowledge changes' Arbesman referred to are obvious and of little import. Examples would include new population figures, counts of new planets discovered, etc. Basically - academic trivia.
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14 of 19 people found the following review helpful
5.0 out of 5 stars Google first else publish and be half-lifed, October 13, 2012
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This review is from: The Half-life of Facts: Why Everything We Know Has an Expiration Date (Hardcover)
I first learned of this book when Sam Arbesman sent me an email to let me know his book supported a myth that he had only learned about after going into print. The myth is the one that Steven Strogatz mentions as though it is veracious in the promotional blurbs on the dust jacket and you'll find it wrongly disseminated again at pages 83 and 84 of this excellent book. The myth is the widely believed spinach Popeye iron decimal error myth (SPIDES).

Sam blogged on his Wired blog to set the record straight and added the mythbusting he had missed in the Errata and updates web page for this book. His own immediate admission of his human error in fact proves the central thesis of this excellent book. To my mind anyone who responds that diligently to what must have been a cringe-worthy "Oh doh!" moment is a scientist whose work is worth following. I'd like to thank Sam for the virtual handshake - he's a much bigger man and better scholar than the little English professor of criminology who in trying to silence me went into ballistic bullying and threatening mode when I recently busted the myth he created in my own field of criminology.

The question that remains outside of the realms of how knowledge expands at exponential rates is why is the SPIDES myth so widely believed and spread by skeptical scholars? Perhaps we need to study the whole life of myths, particularly those believed by credulous skeptics who weirdly fail to check the underlying premises and facts for widely believed claims?

Sam Arbesman (pp. 67-68) tells us: `The creation of facts, as well as their decay, is governed by mathematical rules. But individually, we don't hear of new facts, or their debunking, instantly. Our own personal facts are subject to the information we receive. Understanding how and why information and misinformation spread or don't spread are [sic] just as important when it comes to figuring out how well we know what we know. Knowledge doesn't always reach us all simultaneously, whether we're talking about big new theories or simple incorrect facts - it filters through the population in fits and starts. But there are rules for how facts spread, reach individuals, and change what each of us knows."

In his clear and elegantly riveting prose, a writing style that never wavers throughout the book, Arbesman neatly explains how knowledge gained from social network analysis reveals that it is medium strength social bonds that are the most important conduits of the dissemination of facts and errors of fact because they are not so strong as those characterized by in-bred knowledge in the strongest social groups yet are strong enough to penetrate such groups. Perhaps this neat explanation accounts for Arbesman's own unintended dissemination of the Spinach Myth as though it is veracious knowledge? Could it be that the social network link between himself (a scientist of science) and the natural science bio-chemistry and medical community (and their prestigious journals and books)from whence the myth arose and was most prolifically spread is a medium strength one, which is stronger than his weak social links to peer-to-peer generalist sites such as BestThinkng where the myth was finally bust in December 2010 or the social science Internet Journal of Criminology where it was part-bust earlier in the same year by a criminologist? That seems very likley to me. Moreover, his accounts of examples of undiscovered public knowledge and the reasons why also fits why he never learened that the Spinach, Popeye, Iron Decimal Error Story (SPIDES)is actually a myth. In fact, Arbesman's own error in spreading the Spinach Myth provides confirmatory evidence for his own explanations for how and why such errors persist in our thinking and are spread in our published work. What more could a skeptical reader wish for than that? Arbesman's Error is confirmatory evidence for his own explanations for the persistence of errors.

Arbesman spreads the Semmelweis Supermyth as well. What's going on?

Not only does Arbesman spread the busted spinach myth but he also credulously spreads a myth that was bust 91 years ago. Namely, the Semmelweis Myth. It is, of course, remotely possible that Arbesman is some kind of sceptically mischievous experimenting genius who has deliberately peppered his book on the half-life of facts with myths in order to see whether they are spotted by others and pointed out by them as I have done so here in this Amazon review of his book. But, unless he has written down or made a pre-publication dated video recording of such an aim - along with a list of the myths he has deliberately re-told as though they are veracious knowledge - and left it in a sealed container with his lawyer or publisher we should remain highly skeptical of such a possibility. In reality, Arbesman's Errata and Updates page for The Half-Life of Facts is already pointing the way to a much needed second edition if he is to avoid prolonging the half-life of myths beyond what they would have been had he not written the book in the first place. Most surely that was not his aim.

The big question I have now after reading The Half Life of Facts is: How long exactly then before busted myths and other wrong 'facts' supersede the continuation of the publication of debunked myths in books about bad science and in a unique one such as The Half-Life of Fact's, which is essentially about how facts and myths are spread? Would Googling first to check that the "facts" they claim are "facts" and the myths they claim are myths help authors of such books to avoid disseminating supermyths, such as the Spinach Myth, before going into print? I was surprised, since in Chapter 9 Sam suggests we use search engines to keep our own biased and out of date memories veracious and up-to-date. Weirdly, he did not himself take his own advice before going to print. Had Arbesman Googled all of the apocryphal examples that he provides to support his arguments he would have surprised himself. Had he, for example, Googled "spinach myth" he would not have added to the problem of myth perpetuation in his own book on the problem of the perpetuation of myths and fallacies in such books. Likewise, had he Googled "Semmelweis Myth" he would have avoided the additional embarrassment of perpetuating the life of another pernicious supermyth. Hoisted by his own petard would be one criticism of Arbesman, but that would be only the poorer half of the story. Because while he appears to have ignored his own good advice, his advice is 100 per cent sound and bang-up-to-date for this Information Age.

In the Information Age, therefore, Arbesman's advice in Chapter 9 is essentially that we should all Google first or else publish and be half-lifed.

Perhaps Google might help us to transcend the medium strength social-bond influence upon myth spreading that Arbesman writes about? After all Google's current algorithm seems to rely heavily upon the most recent viewings of popular web pages rather than those which have been around the longest or in the most prestigious sources.

While Arbesman's expert book provides the non-expert reader with an excellent understanding of his field and its usefulness, and I've learned an enormous amount of useful information from it; I do have some concerns that authors such as Arbesman who do such a perfect job of meeting the requirements of the popular science genre to avoid formal referencing to their sources - apart from the very occasional naming of some notable individuals - run a high risk of spreading new Supermyths and perpetuating old ones. It is for this reason that in academia we insist that our students fully cite the sources of all their statements of fact. The same is usually required in peer-reviewed academic journals.

Arbesman has admirably set up an Errata and Updates web page for his book. This is an excellent development facilitated by the communications revolution. Perhaps popular science books should have a similar facility that provides full Harvard style references for every one of the un-cited sources upon which their work is based? If that were done then readers would be able to fact check for themselves the veracity of claims made and the half-life of myths might be shorter.

Finally, buy this book because its an extremely useful addition to your skeptical toolkit.
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4 of 5 people found the following review helpful
2.0 out of 5 stars The fact is, it's really trite, May 11, 2013
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A mildly interesting book for a very short while, the content of which would better be presented in a magainze article.

Ever since I read Toeffler's "Future Shock" I have realized that there are some ideas so simple that they can be completely expressed in a sentence or two, but so grand that it takes a book-length treatment to make the impression they are entitled to. That book's central theme is the essence of simplicity--our world is changing so rapidly today that it is outpacing our ability to adapt. But putting the idea in a sentence denigrates it. It truly was worth a book. At least to me.

The idea of this book is equally simple; the things we take as facts may later be proven not to be true. And the author offers plenty of examples of how our understanding of things changes. How what seemed to be facts can be overturned. To me, at least, this is pretty obvious stuff. We are constantly bombarded with :"facts" which turn out not to be correct, and anyone who goes through life believing everything he hears is going to be in a lot of trouble.

But the problem is not that "facts" change--it is that we are too often offered theories of why things are or happen, and these theories are too often presented as "facts." The pre-Copernican view of the solar system they knew was never a fact--it was an effort to jam all of the known facts into a theory attempting to rationalize all of the facts about the universe that were known at the time.

And today is not that much better than 1500. The people who are supposed to know these things have announced that the entire universe originated with a "Big Bang" some billions of years ago. Perhaps. But that surely is not a fact. It is a theory; a conjecture. One which, incidentally, remqarkably like the conjectures of the Ancient Greek Atomists. Over time, the theory will be constantly tested as new facts are learned. Perhaps it will survive. The history of ideas suggests that it will not.

There are more productive ways to spend one's time than plowing through this book. That's not a fact--it's a theory.

.
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9 of 12 people found the following review helpful
5.0 out of 5 stars The Patterns of Science Charted, October 3, 2012
By 
Joel Nishimura (Bellevue, Washington USA) - See all my reviews
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This review is from: The Half-life of Facts: Why Everything We Know Has an Expiration Date (Hardcover)
I really liked this book. In my experience people talking about the history of science tend to string together a bunch of anecdotes, leaving the impression that all of science is due to five dead guys. But that approach can't see the forest for the trees. This book has finally given me a framework in which to think of scientific progress. It also reads delightfully, somewhere between a TED talk and a fascinating conversation in a faculty lounge.
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4 of 5 people found the following review helpful
2.0 out of 5 stars Incorrect premise for book, February 10, 2013
By 
Kent Price (Palo Alto, CA USA) - See all my reviews
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The title of this book, "the half-life of facts" says that everything we know has an expiration date. However, this is misleading and what is really happening is improved accuracy of measurement for many of the author's "gotcha" examples. For example, the elevation of Mount Everest changes over time due to improved measurement accuracy (use of GPS vs. terrestrial surveying) and the recognition that plate tectonics is causing the mountain to rise with time. Other "facts" discussed such as whether "red wine is good for you" are really not basic facts but opinions, and depend on other unmentioned factors such as quantity consumed and heredity.

I found the book too much a hodgepodge of information.
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The Half-life of Facts: Why Everything We Know Has an Expiration Date
The Half-life of Facts: Why Everything We Know Has an Expiration Date by Samuel Arbesman (Hardcover - September 27, 2012)
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