Read Volume 100 : 25th October 2015
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Read Volume 100 : 25th October 2015
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Page 3: Gamblers, Scientists and the Mysterious Hot Hand By George Johnsonoct
Page 8: Daniel Kahneman on Intuition and the Outside View By Elliot Turner
Page 13: Metaphors Are Us: War, murder, music, art. We would have none without metaphor By Robert Sapolsky
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Read Volume 100 : 25th October 2015
Gamblers, Scientists and the Mysterious Hot Hand
By George Johnsonoct 17 October 2015 IN the opening act of Tom Stoppard’s play “Rosencrantz and Guildenstern Are Dead,” the two characters are passing the time by betting on the outcome of a coin toss. Guildenstern retrieves a gold piece from his bag and flips it in the air. “Heads,” Rosencrantz announces as he adds the coin to his growing collection.
Guil, as he’s called for short, flips another coin. Heads. And another. Heads again. Seventy-seven heads later, as his satchel becomes emptier and emptier, he wonders: Has there been a breakdown in the laws of probability? Are supernatural forces intervening? Have he and his friend become stuck in time, reliving the same random coin flip again and again?
Eighty-five heads, 89… Surely his losing streak is about to end. Psychologists who study how the human mind responds to randomness call this the gambler’s fallacy — the belief that on some cosmic plane a run of bad luck creates an imbalance that must ultimately be corrected, a pressure that must be relieved. After several bad rolls, surely the dice are primed to land in a more advantageous way.
The opposite of that is the hot-hand fallacy — the belief that winning streaks, whether in basketball or coin tossing, have a tendency to continue, as if propelled by their own momentum. Both misconceptions are reflections of the brain’s wired-in rejection of the power that randomness holds over our lives. Look deep enough, we instinctively believe, and we may uncover a hidden order.
Recent studies show how anyone, including scientists, can be fooled by these cognitive biases. A working paper published this summer has caused a stir by proposing that a classic body of research disproving the existence of the hot hand in basketball is flawed by a subtle
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misperception about randomness. If the analysis is correct, the possibility remains that the hot hand is real.
I was thinking about Guil and the psychologists last week as I walked into the Camel Rock Casino, operated by the pueblo of Tesuque, a few miles north of Santa Fe. With five full-scale gambling operations in a stretch of 30 miles, the highway there has become a kind of elongated Las Vegas Strip.
Continue reading the main story Gamblers, with their systems and superstitions, sat nearly immobile at video slots, trying to outguess the algorithmic heart beating inside. They were immersed in what the anthropologist Natasha Dow Schüll calls “the machine zone.”
In her book “Addiction by Design,” she describes how modern slot machines are engineered to maximize “gaming productivity” — the velocity with which dollars fly from the players’ pockets. Mechanical levers have been replaced by faster, more efficient electronic buttons, while the simulated reels of cherries, bars and other symbols are programmed to give the illusion that you missed a jackpot by just a hair — fuel for the gambler’s fallacy.
I’d first come to Camel Rock more than 20 years ago while I was writing a book about the human drive to find order in the world — and impose it when it is not really there. In those days there was only a makeshift bingo hall, and all eyes were on a large machine in which the lettered and numbered balls jumped around like popcorn — an analog equivalent of the random-number-generating chips driving today’s slots. I thought of how an omniscient intelligence, like the one imagined by the philosopher Pierre-Simon Laplace, could precisely track the trajectories of the balls, the elasticity of their impacts, the buoyancy of the air — a vast amount of data — and predict the outcome of the game.
We mortals can benefit, at least in theory, from islands of predictability — a barely perceptible tilt of a roulette table that makes the ball slightly more likely to land on one side of the wheel than the other. The same is true for the random walk of the stock market. Becoming aware of information before it has propagated worldwide can give a speculator a tiny, temporary edge. Some traders pay a premium to locate their
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computer servers as close as possible to Lower Manhattan, gaining advantages measured in microseconds.
But often the patterns we see are illusions. Some research has suggested that more excitable people are likelier to embrace the magic of the hot hand (go, go, go!) while those with “higher cognitive skills,” as the studies put it, are prone to the gambler’s fallacy — the belief that a run of heads will probably be followed by tails. Their swaggering brains think they have psyched out the system, discovering an underlying regularity.
Or maybe they are misapplying a real phenomenon called regression toward the mean. In the long run the number of heads and tails will even out, but that says nothing about how the next flip will fall. A paper this summer in a German economics journal found that in clearly random situations, the tables are turned: People with lower cognitive abilities are likelier than more rational types to be led astray by the gambler’s fallacy.
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In a study that appeared this summer, Joshua B. Miller and Adam Sanjurjo suggest why the gambler’s fallacy remains so deeply ingrained. Take a fair coin — one as likely to land on heads as tails — and flip it four times. How often was heads followed by another head? In the sequence HHHT, for example, that happened two out of three times — a score of about 67 percent. For HHTH or HHTT, the score is 50 percent.
Altogether there are 16 different ways the coins can fall. I know it sounds crazy but when you average the scores together the answer is not 50-50, as most people would expect, but about 40-60 in favor of tails.
There is not, as Guildenstern might imagine, a tear in the fabric of space-time. It remains as true as ever that each flip is independent, with even odds that the coin will land one way or the other. But by concentrating on only some of the data — the flips that follow heads — a gambler falls prey to a selection bias.
In an interesting twist, Dr. Miller and Dr. Sanjurjo propose that research claiming to debunk the hot hand in basketball is flawed by the same kind of misperception. Studies by the psychologist Thomas Gilovich and others conclude that basketball is no streakier than a coin toss. For a 50 percent shooter, for example, the odds of making a basket are supposed to be no better after a hit — still 50-50. But in a purely random situation, according to the new analysis, a hit would be expected to be followed by another hit less than half the time. Finding 50 percent would actually be evidence in favor of the hot hand. If so, the next step would be to establish the physiological or psychological reasons that make players different from tossed coins.
Dr. Gilovich is withholding judgment. “The larger the sample of data for a given player, the less of an issue this is,” he wrote in an email. “Because our samples were fairly large, I don’t believe this changes the original conclusions about the hot hand. ”
Flaws in perceptions about randomness affect more than gambling and basketball. When multiple cases of cancer occur in a community, especially among children, it is only human to fear a common cause. Most often these cancer clusters turn out to be statistical illusions, the result of what epidemiologists call the Texas sharpshooter fallacy. (Blast
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the side of a barn with a random spray of buckshot and then draw a circle around one of the clusters: It’s a bull's-eye.)
Taken to extremes, seeing connections that don’t exist can be a symptom of a psychiatric condition called apophenia. In less pathological forms, the brain’s hunger for pattern gives rise to superstitions (astrology, numerology) and is a driving factor in what has been called a replication crisis in science — a growing number of papers that cannot be confirmed by other laboratories.
For all their care to be objective, scientists are as prone as anyone to valuing data that support their hypothesis over those that contradict it. Sometimes this results in experiments that succeed only under very refined conditions, in certain labs with special reagents and performed by a scientist with a hot hand.
We’re all in the same boat. We evolved with this uncanny ability to find patterns. The difficulty lies in separating what really exists from what is only in our minds.
Source: nytimes.com
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Daniel Kahneman on Intuition and the Outside View
By Elliot Turner October 20, 2015
I had the privilege of attending another Santa Fe Institute “Risk Conference” at Morgan Stanley. There was a stellar lineup of accomplished speakers focusing on Old Wine in New Bottles: Big Data in Markets and Finance. The grand finale was “A Conversation with Daniel Kahneman” led by Michael Mauboussin. These two gentlemen are amongst the finest thinkers in finance and two of the most important influences in my effort to compound knowledge while remaining cognizant of my limitations. As Mauboussin is intimately familiar with the subject matter, he was the perfect person to elicit the deepest insights from Kahneman on the most important topics. Below are my notes, which are reproduced here in the form of a dialogue. When I started jotting these down in real-time, I had no visions of writing the conversation up in this form; however, I found myself writing an awful lot with the output resembling an actual transcript. I attempted to be as thorough as possible in keeping the language as consistent with the spirit of the spoken dialogue as possible, though this is hardly perfect. I apologize in advance for the lack of completeness and the tense shifts, but nonetheless I am delighted to share the following in hope that others will be able to learn as much from this conversation as I did.
Michael Mauboussin: When does intuition work or fail? Daniel Kahneman: Intuition works less often than we think. There is no such thing as professional “expertise.” The Intuitions in chess masters develop with “big data” comes from experience. For people, the immediacy of feedback is especially important to learn the basis of expertise. When feedback comes closer in time to the decision, intuition tends to be a lot stronger. Gary Klein, author of The Sources of Power is hostile to Kahneman’s view. Together they studied the boundary between trustworthy and untrustworthy sources of intuition. Confidence of intuition is NOT a good guide of intuition. If you want to explore intuition, you have to ask “not how happy the individual is” but what domain they are working in. There are some domains where intuition works, and some domains where it does not. You need to ask “did the
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individual have an opportunity to learn irregularities on the way to building intuition? In domains where a lot of people have equal degrees of high confidence, they often do not know the limits of their expertise.
Mauboussin: People blend quantitative and qualitative intuition, but what about disciplined intuition? Is there a better structure to decisionmaking?
Kahneman: When you put human judgment against simple models, after reading Paul Meehl’s book which showed where the human has access to all of the data behind the model, the model still wins in making decisions. There are no confirmed counter-examples. Studied an interviewing system for combat units. Asked multiple interviewers to speak with each candidate with a focus on one topic only per subject. Previously the interviewers had experienced a looser system without restriction—one interviewer per subject, with a broad focus. Unfortunately the previous system had zero predictive value on subsequent performance. At first, when the interviewers were instructed on a “disciplined” focus/topical breakdown, they were furious. People like using their broad intuitions. The interviewers were given a rating scale of 1 to 5 in each area they were assigned to cover. Eventually we got the data on how performance turned out based on the revised interview process. It turned out that interviews done in this way had much better predictive value for subsequent performance.
The problem with intuitions is how they come too fast. They are subject to confirmation biases. If you look at just one thing independent of all else and reserve judgment until the very end, what ultimately comes to mind will be more valid than if you don’t have discipline. It’s important to stress the independence (focus on 1 topic) to resist and overcome associative coherence—aka the halo effect.
Mauboussin: Define regression to the mean and the problems with it (causality, feedback)?
Kahneman: Regression is a familiar concept, but not well understood. We see articles like “Why do smart women marry men less smart than they are?” That is an effect without a cause. We can reformulate that question to say that “the distribution of intelligence in men and women is the same” but the sound/implication of the two statements is not
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equivalent. You have to rid yourself of causation in making such statements. There was a study of the incidence of kidney cancer which described it as mostly rural, Republican districts in the center and south of the USA. Why? Everyone has a theory. But, if you look at the areas where incidence is small, it’s the same answer—mostly rural, Republican districts in the center and south of the USA. This is so because the rural counties have smaller samples (a lower “n”) so incidences of high and low are more pronounced.
Mauboussin: Talk about the inside vs outside view, and base rates… Kahneman: Was involved in writing a textbook on decision-making without math for a high school curriculum. Asked the team: “when will we finish the book?” Everyone answered somewhere between 18 and 30 months. Asked another colleague how long it took to write other textbooks in similar situations. This colleague’s answer had been somewhere in the 18 to 30 month range. The answer: 1) not all textbooks ever finished, with somewhere around 40% of them having given up; and, 2) those that were completed all took more than 7 years.
There are two different ways to look at a problem: 1) make an estimate based on a plan and reasonable extrapolation of progress—the inside view. 2) Abstract to the category of the case and ask “what are its characteristics”—the outside view. Intuition prefers the inside view, while the outside view is non-causal and statistical. If you start your analysis from the outside view, with a known base rate, it gives you a fair anchor and ballpark from which to work.
Mauboussin: People are optimistic. There was a story you told of a few product launch at a company. At what point do you balance optimism vs just giving up? Society wants risks and all the good things that come with them.
Kahneman: Entrepreneurs don’t take risks because they love risk. They do it because they don’t know the odds. They don’t fully appreciate the risks they are taking. Optimism is the engine of capitalism. When you look at big successes, it’s because someone tried something they shouldn’t have.
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Everyone should wish their children be optimists. They are happier, persevere more. Though, I don’t want a financial advisor who is an optimist.
Mauboussin: As we embrace big data, it suggests change. When baseball learned about Moneyball, scouts resisted. With loss aversion, how do you relate this with the degree to which people are willing to embrace big data?
Kahneman: Losses loom larger than gains. Disadvantages are more salient and heavily weighted. In the context of change, one thing is guaranteed: there will be losers and winners. We can know ahead of time that the losers will fight harder than the winners. Losers know what they will lose, winners are never sure exactly what they will gain. People who initiate change don’t appreciate the resistance they will encounter. When reform is done in the regulatory arena, the reforms often compensate the losers making change very expensive. The prescription is to take the outside view.
The endowment effect is strong. The selling price someone sets on a sandwich they already owns and possesses is higher than that same person would price one they do not own. Giving up is more painful than selling something. This is evident in the financial arena. Advisors are helpful, because when they do the selling on someone’s behalf they do not have the same possessive connection and there is no endowment effect. Loss aversion is emotional, so if you make a decision in an advisor role, you can do so without emotion.
Mauboussin: When we look at decision making in an organization, there is noise. What does “noise” mean and why does it matter?
Kahneman: We know why Meehl was right on formulas being better than judges. For example, there was a situation that for each judge, there was a model built to predict what the judge will rule based on their past decisions. You can then compare the judge’s actual decisions with the model. The model is better than the judge. This tells you why people are inferior to formulas. A formula always has the same output. People vary and vary over time. When x-ray readers are asked to view the same image two separate times, 20% of the time they conclude differently. That’s what noise is.
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Many organizations have functionaries who decide, but in principle they are interchangeable (credit-rating agencies, etc.) We would want all people to be interchangeable. How many individuals would be random in their actions? 45-50% tend to be variable. That variability is costly. Noise is costly. Most organizations think their employees agree with each other, but they don’t. Experience doesn’t bring convergence, it brings increased confidence. Convergence and confidence are not the same. If a financial advisory asked their advisors to prioritize a list of clients, does each advisor list the same clients in order? Probably not. When there is no selection, noise is costly.
Mauboussin: Give us a synopsis of Philip Tetlock's Superforecasting. Kahneman: His book Expert Political Judgment was very important. It looked at predictions 10 years after experts made them and concluded forecasters can’t do it. And, the more a forecaster thinks they can do it, they less they actually did. With that knowledge, Tetlock built an IARPA tournament with predictions that covered timespans 6 weeks to a few months out. He ID’d the superforecasters (the top 2%), which included a wide range of experts and ability. Short-term prediction being possible isn’t revolutionary. What makes superforecasters? A mixture of the inside and outside view. Disciplined intuition. Independent judgment, collated.
I am skeptical of applying these findings in the political area where political figures themselves take actions that can be deterministic and statements have to be crafted to multiple constituencies, but in the financial arena these findings are very interesting.
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Metaphors Are Us: War, murder, music, art. We would have none without metaphor.
By Robert Sapolsky October 22, 2015 The other day I fixed something—a rarity for me. The flotation device in the toilet water tank was rubbing against the side, getting stuck halfway up so that the tank didn’t fill completely. I own a hammer and know how to operate it. But I couldn’t fit it into the tank to whack the device back into place. Ditto for owning and using a wrench. It wouldn’t fit either. But fortunately I also own a plunger and I used its handle to push the floating thing back the other way, using the side of the tank as a fulcrum. It worked, although the device got bent so that the top of the tank didn’t quite fit. That overwhelmed me, so I called it a good day’s work.
I was proud of myself. “There,” I thought smugly. “It’s not just chimps who can use tools.”
Humans used to be unique in lots of ways. We were the only species who made tools, murdered each other, passed on culture. And each of those supposed defining features has now been demonstrated in other species. We’re not so special after all. But there are still ways that humans appear to stand alone. One of those is hugely important: the human capacity to think symbolically. Metaphors, similes, parables, figures of speech—they exert enormous power over us. We kill for symbols, die for them. Yet symbols generate one of the most magnificent human inventions: art.
In recent years scientists from leading universities, including UCLA, University College London, and Yale, have made remarkable insights into the neurobiology of symbols. A major finding from their work is that the brain is not very good at distinguishing between the metaphorical and literal. In fact, as scientists have shown us, symbols and metaphors, and the morality they engender, are the product of clunky processes in our brains.
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