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The Drunkard's Walk: How Randomness Rules Our Lives Paperback – Illustrated, May 5, 2009
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“Mlodinow writes in a breezy style, interspersing probabilistic mind-benders with portraits of theorists.... The result is a readable crash course in randomness.” —The New York Times Book Review
With the born storyteller's command of narrative and imaginative approach, Leonard Mlodinow vividly demonstrates how our lives are profoundly informed by chance and randomness and how everything from wine ratings and corporate success to school grades and political polls are less reliable than we believe.
By showing us the true nature of chance and revealing the psychological illusions that cause us to misjudge the world around us, Mlodinow gives us the tools we need to make more informed decisions. From the classroom to the courtroom and from financial markets to supermarkets, Mlodinow's intriguing and illuminating look at how randomness, chance, and probability affect our daily lives will intrigue, awe, and inspire.
- Print length252 pages
- LanguageEnglish
- PublisherVintage
- Publication dateMay 5, 2009
- Dimensions5.2 x 0.82 x 8 inches
- ISBN-100307275175
- ISBN-13978-0307275172
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Review
“Mlodinow writes in a breezy style, interspersing probabilistic mind-benders with portraits of theorists.... The result is a readable crash course in randomness.” —The New York Times Book Review
“A wonderfully readable guide to how the mathematical laws of randomness affect our lives.” —Stephen Hawking, author of A Brief History of Time
"[Mlodinow] thinks in equations but explains in anecdote, simile, and occasional bursts of neon. . . . The results are mind-bending." —Fortune
"Even if you begin The Drunkard's Walk as a skeptic, by the time you reach the final pages, you will gain an understanding-if not acceptance-of the intuitively improbable ways that probability biases the outcomes of life's uncertainties." —Barron's
“Delightfully entertaining.” —Scientific American
“A magnificent exploration of the role that chance plays in our lives. The probability is high that you will be entertained and enlightened by this intelligent charmer.” —Daniel Gilbert, author of Stumbling on Happiness
“Mlodinow is the perfect guy to reveal the ways unrelated elements can relate and connect.” —The Miami Herald
“A primer on the science of probability.” —The Washington Post Book World
“Challenges our intuitions about probability and explores how, by understanding randomness, we can better grasp our world.” —Seed Magazine
“Mlodinow has an intimate perspective on randomness.” —The Austin Chronicle
About the Author
Excerpt. © Reprinted by permission. All rights reserved.
I remember, as a teenager, watching the yellow flame of the Sabbath candles dancing randomly above the white paraffin cylinders that fueled them. I was too young to think candlelight romantic, but still I found it magical-because of the flickering images created by the fire. They shifted and morphed, grew and waned, all without apparent cause or plan. Surely, I believed, there must be rhyme and reason underlying the flame, some pattern that scientists could predict and explain with their mathematical equations. "Life isn't like that," my father told me. "Sometimes things happen that cannot be foreseen." He told me of the time when, in Buchenwald, the Nazi concentration camp in which he was imprisoned and starving, he stole a loaf of bread from the bakery. The baker had the Gestapo gather everyone who might have committed the crime and line the suspects up. "Who stole the bread?" the baker asked. When no one answered, he told the guards to shoot the suspects one by one until either they were all dead or someone confessed. My father stepped forward to spare the others. He did not try to paint himself in a heroic light but told me that he did it because he expected to be shot either way. Instead of having him killed, though, the baker gave my father a plum job, as his assistant. "A chance event," my father said. "It had nothing to do with you, but had it happened differently, you would never have been born." It struck me then that I have Hitler to thank for my existence, for the Germans had killed my father's wife and two young children, erasing his prior life. And so were it not for the war, my father would never have emigrated to New York, never have met my mother, also a refugee, and never have produced me and my two brothers.
My father rarely spoke of the war. I didn't realize it then, but years later it dawned on me that whenever he shared his ordeals, it was not so much because he wanted me to know of his experiences but rather because he wanted to impart a larger lesson about life. War is an extreme circumstance, but the role of chance in our lives is not predicated on extremes. The outline of our lives, like the candle's flame, is continuously coaxed in new directions by a variety of random events that, along with our responses to them, determine our fate. As a result, life is both hard to predict and hard to interpret. Just as, looking at a Rorschach blot, you might see Madonna and I, a duck-billed platypus, the data we encounter in business, law, medicine, sports, the media, or your child's third-grade report card can be read in many ways. Yet interpreting the role of chance in an event is not like intepreting a Rorschach blot; there are right ways and wrong ways to do it.
We often employ intuitive processes when we make assessments and choices in uncertain situations. Those processes no doubt carried an evolutionary advantage when we had to decide whether a saber-toothed tiger was smiling because it was fat and happy or because it was famished and saw us as its next meal. But the modern world has a different balance, and today those intuitive processes come with drawbacks. When we use our habitual ways of thinking to deal with today's tigers, we can be led to decisions that are less than optimal or even incongruous. That conclusion comes as no surprise to those who study how the brain processes uncertainty: many studies point to a close connection between the parts of our brain that make assessments of chance situations and those that handle the human characteristic that is often considered our prime source of irrationality-our emotions. Functional magnetic resonance imaging, for example, shows that risk and reward are assessed by parts of the dopaminergic system, a brain-reward circuit important for motivational and emotional processes. The images show, too, that the amygdala, which is also linked to our emotional state, especially fear, is activated when we make decisions couched in uncertainty.
The mechanisms by which people analyze situations involving chance are an intricate product of evolutionary factors, brain structure, personal experience, knowledge, and emotion. In fact, the human response to uncertainty is so complex that sometimes different structures within the brain come to different conclusions and apparently fight it out to determine which one will dominate. For example, if your face swells to five times its normal size three out of every four times you eat shrimp, the "logical" left hemisphere of your brain will attempt to find a pattern. The "intuitive" right hemisphere of your brain, on the other hand, will simply say "avoid shrimp." At least that's what researchers found in less painful experimental setups. The game is called probability guessing. In lieu of toying with shrimp and histamine, subjects are shown a series of cards or lights, which can have two colors, say green and red. Things are arranged so that the colors will appear with different probabilities but otherwise without a pattern. For example, red might appear twice as often as green in a sequence like red-red-green-red-green-red-red-green-green-red-red-red, and so on. The task of the subject, after watching for a while, is to predict whether each new member of the sequence will be red or green.
The game has two basic strategies. One is to always guess the color that you notice occurs more frequently. That is the route favored by rats and other nonhuman animals. If you employ this strategy, you are guaranteed a certain degree of success but you are also conceding that you will do no better. For instance, if green shows up 75 percent of the time and you decide to always guess green, you will be correct 75 percent of the time. The other strategy is to "match" your proportion of green and red guesses to the proportion of green and red you observed in the past. If the greens and reds appear in a pattern and you can figure out the pattern, this strategy enables you to guess right every time. But if the colors appear at random, you would be better off sticking with the first strategy. In the case where green randomly appears 75 percent of the time, the second strategy will lead to the correct guess only about 6 times in 10.
Humans usually try to guess the pattern, and in the process we allow ourselves to be outperformed by a rat. But there are people with certain types of post-surgical brain impairment-called a split brain-that precludes the right and left hemispheres of the brain from communicating with each other. If the probability experiment is performed on these patients such that they see the colored light or card with only their left eye and employ only their left hand to signal their predictions, it amounts to an experiment on the right side of the brain. But if the experiment is performed so as to involve only their right eye and right hand, it is an experiment on the left brain. When researchers performed those experiments, they found that-in the same patients-the right hemisphere always chose to guess the more frequent color and the left hemisphere always tried to guess the pattern.
Making wise assessments and choices in the face of uncertainty is a rare skill. But like any skill, it can be improved with experience. In the pages that follow, I will examine the role of chance in the world around us, the ideas that have been developed over the centuries to help us understand that role, and the factors that often lead us astray. The British philosopher and mathematician Bertrand Russell wrote,
We all start from "naive realism," i.e., the doctrine that things are what they seem. We think that grass is green, that stones are hard, and that snow is cold. But physics assures us that the greenness of grass, the hardness of stones, and the coldness of snow are not the greenness of grass, the hardness of stones, and the coldness of snow that we know in our own experience, but something very different. In what follows we will peer at life through the eyepiece of randomness and see that many of the events of our lives, too, are not quite what they seem but rather something very different.
In 2002 the Nobel committee awarded the Nobel Prize in Economics to a scientist named Daniel Kahneman. Economists do all sorts of things these days-they explain why teachers are paid so little, why football teams are worth so much, and why bodily functions help set a limit on the size of hog farms (a hog excretes three to five times as much as a human, so a farm with thousands of hogs on it often produces more waste than the neighboring cities). Despite all the great research generated by economists, the 2002 Nobel Prize was notable because Kahneman is not an economist. He is a psychologist, and for decades, with the late Amos Tversky, Kahneman studied and clarified the kinds of misperceptions of randomness that fuel many of the common fallacies I will talk about in this book.
The greatest challenge in understanding the role of randomness in life is that although the basic principles of randomness arise from everyday logic, many of the consequences that follow from those principles prove counterintuitive. Kahneman and Tversky's studies were themselves spurred by a random event. In the mid-1960s, Kahneman, then a junior psychology professor at Hebrew University, agreed to perform a rather unexciting chore: lecturing to a group of Israeli air force flight instructors on the conventional wisdom of behavior modification and its application to the psychology of flight training. Kahneman drove home the point that rewarding positive behavior works but punishing mistakes does not. One of his students interrupted, voicing an opinion that would lead Kahneman to an epiphany and guide his research for decades.
"I've often praised people warmly for beautifully executed maneuvers, and the next time they always do worse," the flight instructor said. "And I've screamed at people for badly executed maneuvers, and by and large the next time they improve. Don't tell me that reward works and punishment doesn't work. My experience contradicts it." The other flight instructors agreed. To Kahneman the flight instructors' experiences rang true. On the other hand, Kahneman believed in the animal experiments that demonstrated that reward works better than punishment. He ruminated on this apparent paradox. And then it struck him: the screaming preceded the improvement, but contrary to appearances it did not cause it.
How can that be? The answer lies in a phenomenon called regression toward the mean. That is, in any series of random events an extraordinary event is most likely to be followed, due purely to chance, by a more ordinary one. Here is how it works: The student pilots all had a certain personal ability to fly fighter planes. Raising their skill level involved many factors and required extensive practice, so although their skill was slowly improving through flight training, the change wouldn't be noticeable from one maneuver to the next. Any especially good or especially poor performance was thus mostly a matter of luck. So if a pilot made an exceptionally good landing-one far above his normal level of performance-then the odds would be good that he would perform closer to his norm-that is, worse-the next day. And if his instructor had praised him, it would appear that the praise had done no good. But if a pilot made an exceptionally bad landing-running the plane off the end of the runway and into the vat of corn chowder in the base cafeteria-then the odds would be good that the next day he would perform closer to his norm-that is, better. And if his instructor had a habit of screaming "you clumsy ape" when a student performed poorly, it would appear that his criticism did some good. In this way an apparent pattern would emerge: student performs well, praise does no good; student performs poorly, instructor compares student to lower primate at high volume, student improves. The instructors in Kahneman's class had concluded from such experiences that their screaming was a powerful educational tool. In reality it made no difference at all.
This error in intuition spurred Kahneman's thinking. He wondered, are such misconceptions universal? Do we, like the flight instructors, believe that harsh criticism improves our children's behavior or our employees' performance? Do we make other misjudgments when faced with uncertainty? Kahneman knew that human beings, by necessity, employ certain strategies to reduce the complexity of tasks of judgment and that intuition about probabilities plays an important part in that process. Will you feel sick after eating that luscious-looking seviche tostada from the street vendor? You don't consciously recall all the comparable food stands you've patronized, count the number of times you've spent the following night guzzling Pepto-Bismol, and come up with a numerical estimate. You let your intuition do the work. But research in the 1950s and early '60s indicated that people's intuition about randomness fails them in such situations. How widespread, Kahneman wondered, was this misunderstanding of uncertainty? And what are its implications for human decision making? A few years passed, and Kahneman invited a fellow junior professor, Amos Tversky, to give a guest lecture at one of his seminars. Later, at lunch, Kahneman mentioned his developing ideas to Tversky. Over the next thirty years, Tversky and Kahneman found that even among sophisticated subjects, when it came to random processes-whether in military or sports situations, business quandaries, or medical questions-people's beliefs and intuition very often let them down.
Suppose four publishers have rejected the manuscript for your thriller about love, war, and global warming. Your intuition and the bad feeling in the pit of your stomach might say that the rejections by all those publishing experts mean your manuscript is no good. But is your intuition correct? Is your novel unsellable? We all know from experience that if several tosses of a coin come up heads, it doesn't mean we are tossing a two-headed coin. Could it be that publishing success is so unpredictable that even if our novel is destined for the best-seller list, numerous publishers could miss the point and send those letters that say thanks but no thanks? One book in the 1950s was rejected by publishers, who responded with such comments as "very dull," "a dreary record of typical family bickering, petty annoyances and adolescent emotions," and "even if the work had come to light five years ago, when the subject [World War II] was timely, I don't see that there would have been a chance for it." That book, The Diary of a Young Girl by Anne Frank, has sold 30 million copies, making it one of the best-selling books in history. Rejection letters were also sent to Sylvia Plath because "there certainly isn't enough genuine talent for us to take notice," to George Orwell for Animal Farm because "it is impossible to sell animal stories in the U.S.," and to Isaac Bashevis Singer because "it's Poland and the rich Jews again." Before he hit it big, Tony Hillerman's agent dumped him, advising that he should "get rid of all that Indian stuff."
Product details
- Publisher : Vintage; Reprint edition (May 5, 2009)
- Language : English
- Paperback : 252 pages
- ISBN-10 : 0307275175
- ISBN-13 : 978-0307275172
- Item Weight : 2.31 pounds
- Dimensions : 5.2 x 0.82 x 8 inches
- Best Sellers Rank: #45,138 in Books (See Top 100 in Books)
- #5 in Chaos Theory
- #44 in Probability & Statistics (Books)
- #99 in Pure Mathematics (Books)
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About the author
Leonard Mlodinow was born in Chicago, Illinois, received his PhD in theoretical physics from the University of California at Berkeley, and is the author of five best-sellers. His book The Drunkard's Walk: How Randomness Rules our Lives was a New York Times Bestseller, Editor's Choice, and Notable Book of the Year, and was short-listed for the Royal Society book award. His book Subliminal won the PEN/Wilson award for literary science writing. His other books include two co-authored with physicist Stephen Hawking -- A Briefer History of Time, and The Grand Design. In addition to his books and research articles, he has taught at Caltech, written for the Wall Street Journal, the New York Times, and Forbes magazine, among other publications, and for television series such as McGyver and Star Trek: the Next Generation. www.leonardmlodinow.com
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The stories and anecdotes, Dr. Mlodinow (who has collaborated twice with Hawking!) relates are wonderful and well-told. The progression is thoughtful and coherent and interesting. Yet, the text stops well short of the math of "decision analysis,"which makes the chit-chat on poor human thinking beneath many other authors from both breezy and mathematical perspectives.
The modern editorial decision to exclude even one mathematical expression from a book on mathematics or even an illustration limits the work. While the book might read well on a Kindle(tm), books on this topic should be on an iPad/web with hyperlinks. The irony of an exceptionally intelligent author writing about the limits of human action, using weak tools that he emasculates even further, doesn't bring a smile to my face.
While this review sounds negative, it should be noted that The Drunkard's Walk is better than the average pop science/math book. Learning about Cardano's development of outcomes in a sample space was inspiring and the restatement of the importance of Bayes, without putting him down, was uplifting. This helped counter the exasperation of reading about Bernoulli's golden theorem four times without being told what it was. De Moivre was mentioned and more could have been said of Polya's role in fully proving De Moivre's Central Limit Theorem, but 20th century math doesn't exist in the book!
In summary, Mlodinow's book joins other pop books in providing one very important value: it is a quick read that provides scaffolding for a reader, not to go further intentionally, but to allow advanced work a home in the brain later. For example, decades ago, if I had known of Riemann's great contribution to geometry, I would have realized in the years ahead why I was being taught particular items and they would have stuck better.
But what an explanation of statistics it is! I've read a lot of introductory statistics material over the years (which of course says a good bit about my ability to understand statistics -- or lack thereof). I have NEVER read a book that explains the concepts so well. He explains the "normal curve," and then uses it to explain the underlying intuition behind Bayesian reasoning, the chi-squared test, and significance testing, just to name three. If that was so easy to do, then someone would have done it already. They haven't. Note that what I am talking about is the intuitive notion behind the tests. Lots of books (mostly textbooks) will explain the tests; what they won't do is give you a good intuitive sense of what these tests are doing, and how they work.
Mlodinow also communicates with exceptional clarity about the nature of statistical fallacies. For example, Alan Dershowitz argued that admitting evidence of OJ Simpson's abuse of his wife was irrelevant because only a minuscule number of women who are abused are also murdered by their husband. Using the Bayesian test, Mlodinow shows that the true question is: what percentage of women who were abused by their husband and were murdered were actually murdered by someone else?
Mlodinow also effectively sets forth the issues of how human beings see order in randomness and randomness where there is order. Of these, by far the more interesting heuristically is the former, and skillfully uses examples (such as random number series) to show how it happens. I agree that he does not as effective a job as others do in surveying all of the heuristics and biases. I think that Predictable Irrational (Dan Ariely), Nudge (Sunstein and Thaler), and Sway (Ori Branfman) are somewhat better than that. But all of these books are short and well-written: quite literally, you can read them all (or listen to them unabridged, as I did), and it will help the concepts stick in your head.
But one book that this is clearly superior to is The Black Swan, by Nassim Taleb. Taleb sticks with the "people see order when it's random" problem, but more than anything else, The Black Swan focuses on TALEB, not the problem. Taleb does discuss the problem of not knowing when you have a Gaussian distribution, but his account of the alternative "Mandelbrotian" way of thinking is just opaque (perhaps an occupational hazard, but then he shouldn't do it). I recommend Black Swan as well, but if you have to choose, Drunkard's Walk is better.
If you are a specialist in the field, then this book isn't for you. But if you really are a specialist, then the popular books aren't generally for you, either. Read this book if you want to get a good intuitive understanding of what is going on. You can't do better.
Top reviews from other countries
The content is very well written and easy to follow, while having little funny bits added by the autor that make this book one of the best I have ever read.
This is worth reading from anyone that have a need to better understanding chance/randomness and how this affect our life and way to see the world. As a data analyst I find this very useful.
This description of the impacts of chance and probability on anyone’s life is fascinating and convincing.
That is exactly what this book describes. We know even evolution had chance element at its heart. The author is truly brilliant as probability, randomness and statistics are not very well received or learnt subjects even today but reading these topics from this book was a breeze. However truth be told, two-three examples I found were little dense in the book or its possible I have not been able to follow but abstractions had helped in understanding those as well. I will go back to the book sometime later anyway.
There are stories picked up to narrate why determinism is not what is everywhere...but it is what we seek and how things that seem absolute are in reality only the probability distributions (like how we know from uncertainty principle & schroedinger's observation theory as well anyway..although these are my conjecture). But we, because of our developed biases try to make it definitive.
So many stories are mentioned of tremendous success, so few you could believe had to do with measuring talent by results after reading the book.
It is like strings of events/non-events going on & on & on endlessly, mindlessly, randomly, hopelessly, meaninglessly and we just have happened to be somewhere along, around, under, over, hanging, running on those strings trying to make our way by thinking that probabilities & patterns are absolute or deterministic.
The examples of 1) mathematical expectation, 2) infinite sequence of zeroes and ones could produce what seem to be definitive patterns, 3) the probabilities of success explained through the story of a successful market analyst and 4) finding theft, fraud, anomaly through pascal's triangle or bell curve were like the light switch!!