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Free Download , by Gordon Rugg Joseph D'Agnese

Free Download , by Gordon Rugg Joseph D'Agnese

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, by Gordon Rugg Joseph D'Agnese

, by Gordon Rugg Joseph D'Agnese


, by Gordon Rugg Joseph D'Agnese


Free Download , by Gordon Rugg Joseph D'Agnese

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, by Gordon Rugg Joseph D'Agnese

Product details

File Size: 9563 KB

Print Length: 317 pages

Publisher: HarperOne (April 30, 2013)

Publication Date: April 30, 2013

Sold by: HarperCollins Publishers

Language: English

ASIN: B007HBHA6W

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Amazon Best Sellers Rank:

#47,829 Paid in Kindle Store (See Top 100 Paid in Kindle Store)

I've reviewed dozens of books on decision theory and human error, from the simply ridiculous ("follow your gut" in 500+ pages) to the profoundly complex but unhelpful (dynamic systems differential equations about hidden utility functions running in the background of our cortex) to ugly advice about reinventing our to do lists. After reading 30 "management" books on thinking outside the box, and putting most of them down while dozing off by page 20, Blind Spot, to bend a pun/ metaphor, is both an eye opener AND a page turner!I've wondered why nobody who knows search engine design, big data algorithms, and "mistakes" made by computers in machine learning hadn't applied that knowledge to human problem solving-- and here it is! This book is a smorgasbord of high tech algorithmic prioritization methods, good old deductive reasoning, just plain fascinating story telling, and a sprinkling of "aha" moments, not on how the brain confuses the figure for the ground, but how simply failing to apply the tools we have at the right time in the right way can continually keep us making the same mistakes.The amazing thing is that the author is really presenting the brain like a complex software program (AutoCad, Maya, various SDKs come to mind), which today are filled with multiple tools, tool trays, pull downs, hover overs, and other sophisticated GUIs. The interfaces themselves are like a genius with unlimited tools, with the genius not being the tools, but knowing which one to select when! "Experts" are supposedly those who know the tools, but... hmmm, what if they were applying them wrong? The image that comes to mind is a physicist pulling out a really astonishing looking metric tool, then using it to pry open his briefcase. Given the sophistication of the author's arguments, my first reaction would be: DRY! Not so! This isn't yet another "how to" management advice column, but a series of spellbinding "Holmes" like stories about how supposedly sound reasoning can go awry, even in the hands of "renowned experts." The interesting thing is the odd feeling you get when you're done with this ride-- about who you can trust and who you can't, and why! It puts a spotlight on trust in a way I've never seen before.Here's the thing: Sure, information is better than ever, with Wiki and all that floating all around us. But how do we filter the gems from the fool's gold? Old methods aren't cutting it! In some ways this author is a true maverick-- suggesting, of all things, we think for ourselves and actually BELIEVE that we can figure things out ALL the experts are getting wrong! The tools he uses are at once high tech and yet simple-- occam's razor at it's best, reminding us not to rule out what's staring us in the face just because it is TOO obvious. If you're from a "show me" State, you'll love this. Someone said that as we get older the path between naievete and skepticism gets perilously thin. This book is a must read in navigating that razor's edge, in an age where "assumptions" abound, "signed off" by someone we all trust! Highly recommended, and way fun. Can be life changing, a deep yet easy read -- that kind of flavor.Library Picks reviews only for the benefit of Amazon shoppers and has nothing to do with Amazon, the authors, manufacturers or publishers of the items we review. We always buy the items we review for the sake of objectivity, and although we search for gems, are not shy about trashing an item if it's a waste of time or money for Amazon shoppers. If the reviewer identifies herself, her job or her field, it is only as a point of reference to help you gauge the background and any biases.

I didn't enjoy this book as much as LibrayPicks. "Blind Spot" is a very good book, amazingly written, and full of information. As you read it you know that you're in the presence of a genius - no sarcasm here. Dr. Rugg is brilliant, so much so that the book often went over my head. Dr. Rugg often falls into the trap he warns about, namely that experts use language and make assumptions that novices won't grasp. Dr. Rugg talks about so many tools, studies, techniques, and advanced research methodologies that the reader, at least me, went along breathlessly trying to cope with the intellectual overload."Blind Spot" has sparkling prose and is as interesting and fun to read as any famous novel. Dr. Rugg weaves his thesis throughout his story of debunking the Voynich Manuscript. Dr. Rugg's story of the Voynich manuscript reads like "The Da Vinci Code" by Dan Brown. The story is chock full of medieval mystery that intrepid investigators using modern science try to unravel. This story alone makes "Blind Spot" a valuable read. Dr. Rugg uses a vast amount of historical and scientific references, from Roman battles to torpedo design. Just getting a glimpse into the kind of mind Dr. Rugg must have makes reading "Blind Spot" worthwhile.At the end however I'm not sure if Dr. Rugg's Verifier method (principle idea of the book) is about solving human error or about identifying error in academic publications. While Dr. Rugg gave us a working outline (the steps) of the Verifier method there isn't a practical application to solving daily human errors or errors outside of those extensively documented with peer reviewed and published articles. The Verifier process is:1. Decide if a problem really exists.2. Try to determine if the problem has already been solved by experts in a different discipline.3. Determine if there are any expertise gaps.4. Identify the key themes and chains of evidence that people are using.5. Carefully study the concepts and representations used by experts in the field.6. Deliberately avoid writing anything down or using formal diagrams too early.7. Deliberately avoid actively looking for errors in the material you're reading; concentrate on getting a feel for the big picture.8. Now home in on the things that feel wrong.9. Choose tools that will let you check whether you really have found an error.We desperately need to rethink how we think. Dr. Rudd's book is very useful for making us aware of that need.

I read this book because Dr. Rugg has used his methodology to conclude that the Voynich Manuscript is a hoax. I totally disagree with this conclusion, but admire his clear thinking and rigorous logic. I recommend this book highly.

Blind Spot shares Gordon Rugg's ideas about information theory as well as his stories about developing those ideas. As you might infer from the range of reviews, some people wanted only one or the other of those, so it might be best to come to this book knowing you are in for both.Blind Spot does a nice job of capturing Rugg's notions of the ways to elicit and structure information (Chapters 1-5) and to examine that information for strengths and weaknesses (mostly in Chapter 10), although it would be nice to have his methodology summarized and mapped out here as a clearer working hypothesis. Sandwiched between those two parts is a recounting of his work on the Voynich manuscript (which some will find interesting in its own right and others perhaps a tad long for a case study) and Jo Hyde's work on different medical diagnoses (more useful as case studies here, if a bit less colorful than the Voynich story).Overall, Blind Spot takes a novel approach to sharing some interesting ideas in the growing field of information theory.

BoringA total waste of time. Little info to help in real world business situationsThe author is a little to proud of himself

Old regurgitated mantra elongated in way too many pages, seek older books for true wizdom om this kind of subject .

It told lots about problems, generically about solutions, but little you could walk away with and implement. I was expecting more.

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