Month: August 2013

Malcolm Gladwell Responds to Critics of the 10,000-Hour Rule

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Malcolm Gladwell came into mainstream prominence with his explanation of the 10,000 hour rule. While Malcolm Gladwell didn’t invent the rule, he instantly popularized it via his best-selling book Outliers. The principle actually dates to a 1993 study (“The Role of Deliberate Practice in the Acquisition of Expert Performance”; PDF link), though in that paper the authors called it the 10-year rule.

In the latest piece for The New Yorker, Gladwell is back in the spotlight, but this time he is on the defensive. Here, he eviscerates the simplification of the 10,000 hour rule:

No one succeeds at a high level without innate talent, I wrote: “achievement is talent plus preparation.” But the ten-thousand-hour research reminds us that “the closer psychologists look at the careers of the gifted, the smaller the role innate talent seems to play and the bigger the role preparation seems to play.” In cognitively demanding fields, there are no naturals. Nobody walks into an operating room, straight out of a surgical rotation, and does world-class neurosurgery. And second—and more crucially for the theme of Outliers—the amount of practice necessary for exceptional performance is so extensive that people who end up on top need help. They invariably have access to lucky breaks or privileges or conditions that make all those years of practice possible. As examples, I focussed on the countless hours the Beatles spent playing strip clubs in Hamburg and the privileged, early access Bill Gates and Bill Joy got to computers in the nineteen-seventies. “He has talent by the truckload,” I wrote of Joy. “But that’s not the only consideration. It never is.”

Malcolm Gladwell goes on to reference David Epstein’s new book, The Sports Gene: Inside the Science of Extraordinary Athletic Performance:

I think that it is also a mistake to assume that the ten-thousand-hour idea applies to every domain. For instance, Epstein uses as his main counterexample the high jumper Donald Thomas, who reached world-class level after no more than a few months of the most rudimentary practice. He then quotes academic papers making similar observations about other sports—like one that showed that people could make the Australian winter Olympic team in skeleton after no more than a few hundred practice runs. Skeleton, in case you are curious, is a sport in which a person pushes a sled as fast as she can along a track, jumps on, and then steers the sled down a hill. Some of the other domains that Epstein says do not fit the ten-thousand-hour model are darts, wrestling, and sprinting. “We’ve tested over ten thousand boys,” Epstein quotes one South African researcher as saying, “and I’ve never seen a boy who was slow become fast.

It appears Gladwell is accepting of the challengers:

It does not invalidate the ten-thousand-hour principle, however, to point out that in instances where there are not a long list of situations and scenarios and possibilities to master—like jumping really high, running as fast as you can in a straight line, or directing a sharp object at a large, round piece of cork—expertise can be attained a whole lot more quickly [than 10,000 hours]

Malcolm Gladwell’s elaboration is important: it’s not just about taking in the time to practice, it’s also the efficacy of practice that matters. Preparation beats innate talent, but there is a limit.

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Further reading:

1) “Your Genes Don’t Fit: Why 10,000 Hours of Practice Won’t Make You an Expert”

2) “The Sports Gene and the New Science of Athletic Excellence“

The Man with the Longest Postal Route in America

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Jim Ed Bull is a letter carrier with the United States Postal Service. He is 72 years old, but that is not his claim to fame. Jim has the longest postal route in America: 187.6 miles (301.8 kilometers) across some of the loneliest territory in the country. Bloomberg reports on his fascinating story:

Into the mailbox goes the weekly Southwest Oklahoma Shopper and a letter from Stockmans Bank, and slam, the door shuts tight. Snap-and-slam wasn’t always the soundtrack of Bull’s workday. He was a high school principal, coach and referee who retired in the late ’90s only to come back to a payroll. Now he’s one of 7.2 million Americans who were 65 and over and employed last year, a 67 percent jump from 10 years before.

They work longer hours and earn more than they did a decade ago. Fifty-eight percent are full-time compared to 52 percent in 2002, and their median weekly pay has gone up to $825 from $502. In the second quarter, government data show, Bull and his peers made $49 more a week than all workers 16 and older.

This was the most surprising part of the piece: USPS doesn’t supply rural drivers with vehicles. So Mr. Bull uses his own truck:

The Postal Service doesn’t supply rural carriers with vehicles, and Bull eschews modifications to his truck or special equipment. Instead, he sits between the two front seats, his body in the middle of the cab. His left hand holds the steering wheel, his left foot operates the gas and brake, and his long right arm inserts the mail.

mr_bull

Amazing.

The Workout Routine of Julien Farel, U.S. Open Hairstylist

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The Wall Street Journal reports how Julien Farel, official hairstylist of the U.S. Open, works and keeps in shape. Mr. Farel has an intense schedule, cutting the hair of some 30 to 50 people a day. So he needs a routine to stay in shape:

Mr. Farel is up at 5 a.m. on weekdays so he can run before work. He runs year round, in rain or snow. “I never check the weather because it is only an excuse not to run,” he says. He’ll run between 6 to 9 miles along the West Side Highway. When he stops to do upper body and core exercises, he’ll do three sets of 10 push-ups and three sets of 10 pull-ups. “I found an eating kiosk where I can hang from the roof and do pull-ups,” he says. “If it is raining, I can do my crunches and push-ups under cover there.”

Post-run, he stretches in a hot shower. He is religious about stretching his hands and fingers. “My hands are my job so I need to maintain flexibility and avoid arthritis,” he says. “I need as much dexterity as possible.” He might squeeze a small ball 30 times to strengthen his fingers, sometimes using just four fingers or two.

A lot of what Mr. Farel does I have been able to do over the last six months. For instance, many days I skip lunch entirely (all hail intermittent fasting) and have a thirty or forty minute run at the gym. I also skip breakfast. So this was interesting:

Mr. Farel takes in nearly all of his daily calories at dinner. He dines at restaurants with clients and friends at least three nights a week. “I go all out and get an appetizer, an entree, and dessert,” he says. “I don’t feel guilty at all because I need the calories to carry me on my run the next morning.”

Who knew you needed so much stamina to style hair!

Tuesday’s Challenge: A Card Logic Game

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After the success of Tuesday’s afternoon logic puzzles (which were correctly answered in the comments in less than thirty minutes), I promised to post something a bit more challenging. So here we go.

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You’ve just flown into Las Vegas and have decided to peruse the casino floor of the MGM Grand, your favorite casino. It’s mid-afternoon, and you haven’t had anything to drink, and the blackjack and poker tables are sparse. You don’t really want to get into those games until later in the evening when all your friends arrive. As you keep walking around the casino floor, you notice a card game which you’ve never encountered before. It’s called Lucky Strike.

Here’s how Lucky Strike works. The dealer has a standard deck of 52 cards (26 red cards, 26 black cards). The cards are shuffled prior to the game and all the cards are placed face down. It costs $1 to play the game.

The rules: the dealer draws one card at a time and shows you the card after each turn. For every red card that’s drawn, you win $1. For every black card you draw, you have to pay the dealer $1. After the dealer draws the card, it goes into the discard pile and isn’t seen/used again. You have the option to quit playing the game after each turn (i.e., when the dealer shows you a new card). Here’s the question: devise an optimal (rational) playing strategy to maximize your payoff in this card game. What is the expected payoff in this game?

Two thoughts to ponder:

1) Since this is a standard deck of 52 cards, and if you choose to see all 52 cards, your ultimate payoff will be $0 (all the $1 winnings from seeing red cards exactly offset the $1 losses you pay to the Dealer from seeing the black cards). But remember, you paid $1 to play the game, so the House has the advantage if you choose to see every single card. So this isn’t an optimal playing strategy.

2) There will be multiple optimal strategies on when to “cash out” in this game. The challenge in this game is to deduce your expected payoff after seeing one card, two cards, three cards, etc. Remember: the order of the cards drawn matters: if you draw five straight red cards, for example, I can guarantee you that it would have been more than optimal to walk away from the table, collect your $5, for a total winnings of $4. So you need to consider the order of how the cards are dealt and when the optimal strategy is to “cash out”.

I will revise this logic puzzle for clarity in case some things aren’t clear. One critical assumption to make is that you are rational. Needless to say, but you are also an expert at calculating probabilities on the fly.

Any questions?

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To make things more interesting: if you’re in the Atlanta area and submit a detailed, correct response to this challenge question, I will buy you a drink at an establishment of your choice (ITP only, please).

When Gucci and Louis Vuitton Handbags Serve as Collateral for Loans

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Say hello to the handbag-backed loan. A company in Hong Kong, Yes Lady Finance Co., provides loans to customers if they’re able to bring in their beloved handbags as collateral.

Yes Lady provides a loan within half an hour at 80% of the bag’s value—as long as it is from Gucci, Chanel, Hermès or Louis Vuitton. Occasionally, a Prada purse will do the trick. Secondhand classic purses and special-edition handbags often retain much of their retail prices.

A customer gets her bag back by repaying the loan at 4% monthly interest within four months. Yes Lady says almost all its clients quickly pay off their loans and reclaim their bags.

The company recently lent about US$20,600 in exchange for a Hermès Birkin bag, but Yes Lady’s purse-backed loans start at about US$200.

This is bizarre, and one of those “markets in everything” phenomena. The best part? Some people try to get away with bringing in fake luxury handbags. You should read the article on how Yes Lady handles those scenarios…

Tuesday’s Logic Puzzles

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A brief break from reading this afternoon to tackle two logic/math problems below. See if you can deduce the answer on your own. Leave a comment if you know the answer!

1) Consider an analog clock with both an hour hand and a minute hand. What is the first time after 6PM that the hour hand and the minute hand are exactly coincident (i.e., on top of one another)? NOTE: Your answer should be in this format: HH:MM:SS.DDD, where HH = hour, MM = minutes, SS = seconds, and DDD is the 1/1000th of a second decimal equivalent. (HINT: the first thing that comes to mind, 6:30PM, is an incorrect response).

2) Consider a room  with a very large table on which stand 100 lamps, each with an on/off switch. The lamps are arranged in a straight line, and each one is numbered 1, 2, 3, …, 99, 100. At the beginning of the experiment, all the lamps are turned off.

This room has an entry door and a separate door for an exit. One hundred people are recruited to participate in this experiment. Each of the 100 participants is also numbered 1 to 100, inclusive. When participant number 1 enters the room, he turns on EVERY lamp, and exits. When participant 2 enters the room, he flips the switch for every second lamp (thus, turning off lamps 2, 4, 6, 8, 10, and so on because participant 1 has turned all the lamps on his turn). Participant 2 exits and then participant 3 enters. Participant 3 flips the switch on every third lamp (thus changing the on/off state of the lamps which are numbered 3, 6, 9, 12, and so on). This process continues until all 100 participants have taken their turn and passed through the room.

Assume each participant can properly count and doesn’t make any mistakes in changing the on/off state of the lamp(s) he’s assigned to change the state of. Here is the question: after the 100th participant completes his journey through the room, how many lamps are illuminated? And which of those lamps (i.e., reference by number) are they?

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UPDATE (1:30PM): Both questions have been answered in the comments. To make up for these relatively simple questions, I’ll post a much more challenging logic question in the evening. It will have to do with a deck of cards.

Why Lobster Isn’t Priced Like Chicken

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In 2005, Maine lobster was selling for almost six dollars a pound wholesale. By 2009, it cost just half that, and, in the past couple of summers, huge lobster harvests, believed by some to be a result of global warming, have glutted the market, sending prices tumbling further. This month, lobster off the boat is selling for as low as $2.20 a pound. So why hasn’t the price of lobster come down when you’re buying it at your favorite restaurant?

James Surowiecki explains in The New Yorker that lobster isn’t like a commodity, but rather is more like a luxury good. If it were priced like chicken, people would presumably enjoy it less:

Keeping prices high obviously lets restaurants earn more on each dish. But it may also mean that they get less business. So why aren’t we seeing markdowns? Some of the reasons are straightforward, like the inherent uncertainty of prices from year to year: if a bad harvest next summer sent prices soaring, restaurants might find it hard to sell expensive lobster to customers who’d got used to cheap lobster. But the deeper reason is that, economically speaking, lobster is less like a commodity than like a luxury good, which means that its price involves a host of odd psychological factors.

Lobster hasn’t always been a high-end product. In Colonial New England, it was a low-class food, in part because it was so abundant: servants, as a condition of their employment, insisted on not being fed lobster more than three times a week. In the nineteenth century, it became generally popular, but then, as overharvesting depleted supplies, it got to be associated with the wealthy (who could afford it). In the process, high prices became an important part of lobster’s image. And, as with many luxury goods, expense is closely linked to enjoyment. Studies have shown that people prefer inexpensive wines in blind taste tests, but that they actually get more pleasure from drinking wine they are told is expensive. If lobster were priced like chicken, we might enjoy it less.

Another additional point worth highlighting:

Restaurants also worry about the message that discounting sends. Studies dating back to the nineteen-forties show that when people can’t objectively evaluate a product before they buy it (as is the case with a meal) they often assume a correlation between price and quality. Since most customers don’t know what’s been happening to the wholesale price of lobster, cutting the price could send the wrong signal: people might think your lobster is inferior to that of your competitors. A 1996 study found that restaurants wouldn’t place more orders with wholesalers even if lobster prices fell twenty-five per cent.

Finally, having lobster on the menu is a boon for restaurants because its artificially high price makes other dishes on the menu comparatively more affordable. Cited in Surowiecki’s piece is a fascinating paper by Itamar Simonson and Amos Tversky concerning these context-dependent preferences:

The standard theory of choice-based on value maximization-associates with each option a real value such that, given an offered set, the decision maker chooses the option with the highest value. Despite its simplicity and intuitive appeal, there is a growing body of data that is inconsistent with this theory. In particular, the relative attractiveness of x compared to y often depends on the presence or absence of a third option z, and the “market share” of an option can actually be increased by enlarging the offered set. We review recent empirical findings that are inconsistent with value maximization, and present a context-dependent model that expresses the value of each option as an additive combination of two components: a contingent weighting process that captures the effect of the background context, and a binary comparison process that describes the effect of the local context. The model accounts for observed violations of the standard theory and provides a framework for analyzing context-dependent preferences.

Zemblanity is the Opposite of Serendipity

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Stef Lewandowski, in a post titled “Accelerating Serendipity” talks about some of the ways he’s made serendipity become more prevalent in his life. Say yes more, attend events, and find the right location.

But it was this paragraph about zemblanity—the polar opposite of serendipity—that caught my attention:

Zemblanity, a word coined by William Boyd in his book Armadillo in the 1980s, is the polar opposite of serendipity. It’s named after the cold, barren serendipity-less island of Zembla:

“So what is the opposite of Serendip, a southern land of spice and warmth, lush greenery and hummingbirds, seawashed, sunbasted? Think of another world in the far north, barren, icebound, cold, a world of flint and stone. Call it Zembla. Ergo: zemblanity, the opposite of serendipity, the faculty of making unhappy, unlucky and expected discoveries by design.”

Good stuff.

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And here is Wikipedia on The Three Princes of Serendip, the origin of the word Serendipity. The word serendipity was first coined in modern times by Horace Walpole:

The Three Princes of Serendip is the English version of the Peregrinaggio di tre giovani figliuoli del re di Serendippo published by Michele Tramezzino in Venice in 1557. Tramezzino claimed to have heard the story from one Christophero Armeno who had translated the Persian fairy tale into Italian adapting Book One of Amir Khusrau‘s Hasht Bihisht of 1302. The story first came to English via a French translation, and now exists in several out-of-print translations. Serendip is the Persian and Urdu name for Sri Lanka, which was adopted from Tamil “Seren deevu” or originally from Sanskrit Suvarnadweepaor golden island. In contrast, some trace the etymology to Simhaladvipa which literally translates to “Dwelling-Place-of-Lions Island”

The story has become known in the English speaking world as the source of the word serendipity, coined by Horace Walpole because of his recollection of the part of the “silly fairy tale” where the three princes by “accidents and sagacity” discern the nature of a lost camel. In a separate line of descent, the story was used by Voltaire in his 1747 Zadig, and through this contributed to both the evolution of detective fiction and also to the self-understanding of scientific method.

 

The Welding Robot e-David and Art Forgery

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This is quite interesting: e-David is a welding robot programmed to copy art pieces via a select number of algorithms. Watch this video:

 

This brief piece in Wired has more:

The thing that sets the bot apart from his contemporaries is a visual feedback system, a technological set of eyes that continually checks to see how close he’s coming to the mark. Every so often, e-David will take a photograph of his canvas and, after some image correction, subtract it from the image he’s trying to reproduce. Looking at the difference between the two, it determines which areas of the canvas are too dark or too light, generates a hundred or so potential brush strokes, and then chooses which of those are best suited to minimize that difference.

In many ways, the project sidesteps some of the thornier conceptual issues painting robots typically grapple with–concerns like authorship and intent. “Regardless of what we implement, the machine will never be a person,” Oliver Deussen, one of the researchers behind the effort, explained to WIRED UK. “It will only have a very limited idea about what it is doing, no intention. Our simulation is only about the craftsmanship that is involved in the painting process.” In other words, Deussen and his collaborators don’t expect their robotic arm to think like an artist. They just want it to paint like one.

There is much potential here:

The machine works mostly in acrylic, because it dries quickly and is thus easier to correct. It can do color, but it’s a bit tricky. And since e-David needs to ensure the same amount of paint is on the brush for its algorithms to function as intended, it has to make a stroke off to the side every time it dips its brush.

But e-David’s creators think there’s plenty of room for their apprentice to learn. It could be programmed to distinguish between certain styles of painting, for example, and choose its strokes accordingly. Or even, Deussen suggests, to gain some rudimentary understanding of what it was painting, and to know the difference between the sky and leaves on a tree, say, in terms of what they demanded from the perspective of paint applied to canvas.

David Graeber on the Phenomenon of Bullshit Jobs

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David Graeber is a professor of Anthropology at the London School of Economics and author of Debt: The First 5,000 Years. In a must-read, thought-provoking post titled “On the Phenomenon of Bullshit Jobs” he explains how the majority of workers these days are stuck in meaningless jobs:

In the year 1930, John Maynard Keynes predicted that, by century’s end, technology would have advanced sufficiently that countries like Great Britain or the United States would have achieved a 15-hour work week. There’s every reason to believe he was right. In technological terms, we are quite capable of this. And yet it didn’t happen. Instead, technology has been marshaled, if anything, to figure out ways to make us all work more. In order to achieve this, jobs have had to be created that are, effectively, pointless. Huge swathes of people, in Europe and North America in particular, spend their entire working lives performing tasks they secretly believe do not really need to be performed. The moral and spiritual damage that comes from this situation is profound. It is a scar across our collective soul. Yet virtually no one talks about it.

So what happened as a result of global automation?

But rather than allowing a massive reduction of working hours to free the world’s population to pursue their own projects, pleasures, visions, and ideas, we have seen the ballooning not even so much of the “service” sector as of the administrative sector, up to and including the creation of whole new industries like financial services or telemarketing, or the unprecedented expansion of sectors like corporate law, academic and health administration, human resources, and public relations. And these numbers do not even reflect on all those people whose job is to provide administrative, technical, or security support for these industries, or for that matter the whole host of ancillary industries (dog-washers, all-night pizza deliverymen) that only exist because everyone else is spending so much of their time working in all the other ones.

So was Keynes wrong? No, argues David Graeber, in this humorous paragraph:

While corporations may engage in ruthless downsizing, the layoffs and speed-ups invariably fall on that class of people who are actually making, moving, fixing and maintaining things; through some strange alchemy no one can quite explain, the number of salaried paper-pushers ultimately seems to expand, and more and more employees find themselves, not unlike Soviet workers actually, working 40 or even 50 hour weeks on paper, but effectively working 15 hours just as Keynes predicted, since the rest of their time is spent organizing or attending motivational seminars, updating their facebook profiles or downloading TV box-sets.

On meeting people with bullshit jobs in real life:

In fact, I’m not sure I’ve ever met a corporate lawyer who didn’t think their job was bullshit. The same goes for almost all the new industries outlined above. There is a whole class of salaried professionals that, should you meet them at parties and admit that you do something that might be considered interesting (an anthropologist, for example), will want to avoid even discussing their line of work entirely.

On the perverse notion that this status quo should endure:

It’s even clearer in the US, where Republicans have had remarkable success mobilizing resentment against school teachers, or auto workers (and not, significantly, against the school administrators or auto industry managers who actually cause the problems) for their supposedly bloated wages and benefits. It’s as if they are being told “but you get to teach children! Or make cars! You get to have real jobs! And on top of that you have the nerve to also expect middle-class pensions and health care?”

A must-read in its entirety. Thought-provoking.