by Andrew Lynn
* * *
So far so good. Why challenge ‘grind’ theory? If we need to grind away for 10,000 hours to achieve excellence, then so be it – 10,000 hours of hard grind it must be.
The first problem with the 10,000-hour rule, so presented, is that it suggests that there is some threshold point that is reached beyond which lie the fertile pastures of success: you put in your hours and – bang! – you reach a defining (10,000-hour) moment at which you have finally achieved excellence. That may be true for the relatively few areas of life that require expertise (narrowly defined) alone. But researchers who have looked at patterns of human achievement more broadly over the life span don’t see it. What they see, typically, is a curve of productivity that does rise sharply in the first ten years, then peaks about twenty years in, but then drops off slowly for the remainder of the life span.3 A curve like this:
What’s more, the curve differs according to the field in question.4 Here are the productivity curves for the three broad fields of arts, sciences, and scholarship:
The curve for the sciences comes closest the Gladwellian vision: we see ten years of steady progress, followed by a leveling off after close to twenty (albeit with gradual decline later on). In the arts it’s a more extreme picture: the career is more ‘front-loaded’ with rapid progress for the first ten to twenty years followed by an almost equally rapid dropping-off in productivity from middle-age. For scholarship, the story is different again. Our shabby academics, it turns out, are shabby for a good reason: they peak not after ten, nor twenty, nor even thirty years in, but a full forty years after they begin.
Problem two with the way that the 10,000-hour rule is sometimes presented is that it puts the emphasis on grind (i.e., on the number of hours spent) rather than grit (i.e., commitment to a single field of activity). The life span curves that we’ve seen above start with the assumption that our careers begin, uniformly, at the age of twenty: that’s why we see the peak begin at between thirty and forty. What happens when we settle into a career at thirty, say? The curve shifts to the right by ten years. What happens if we start at thirty-five? The curve shifts to the right by fifteen years. It’s not our biological age that matters; but neither is it simply how hard (how many hours) we have worked. What matters is how long we have been committed to a single vocation. What matters, to use the correct term, is our career age.
The final problem is that there has to be more to it than the sheer number of hours spent. Some basic arithmetic reveals the issue: multiply hours/day at your day job by number of days in the year minus weekends and holidays and by years spent working. Do this calculation and you’ll become aware of one feature that the ‘expertise populists’ rarely mention – even average human beings can clock up 10,000 hours after just a few years’ work. Most of us probably work at least 2,000 hours per year. Work for five years at a single thing and we’re all experts.
Of course, it’s not that simple – because at the core of the 10,000-hour rule is not experience as much as deliberate practice. It has long been known that experience in itself is no reliable predictor of superior performance. Advice given by experts on stock-market investments is little superior to that given by complete novices. Psychotherapists with many years of experience are hardly more successful in their treatment of randomly assigned patients than psychotherapists just starting out. Expert wine tasters do little better than regular wine drinkers in discriminating and describing wines when the identity of the wine is unknown. In some fields additional experience is in fact negatively correlated with performance outcomes. Diagnosis of heart sounds and radiographs by general physicians, for example, actually decrease in accuracy and consistency with increased experience after formal training.5
Deliberate practice is a world away from ‘mere experience’. It’s working at full concentration on improving specific aspects of performance. It’s not execution or repetition of already attained skills but ‘repeated attempts to reach beyond one’s current level’. Typically it will involve the identification of weak points that are then systematically improved through focused efforts. It’s not fun. It may be solitary. It will bring much in the way of failure and frustration and little in the way of immediate reward.
Here’s how chess players do it. They get hold of published games of the top players. But they don’t just study the games. They work through them, one move at a time, to see if their own moves coincide with those of the masters. If their selections match, then all is well. If they don’t, then the player concludes that they must have made some error in planning or evaluation. It’s at that point that the aspiring chess expert gets to work trying to understand the reason for the chess master’s decision. That’s deliberate practice – and some players carry it out for up to four hours per day.6
And here’s how the most promising young musicians do it. Like their less promising peers, they spend up to 60 hours per week on music-related activities. What differentiates the really good ones, though, is the amount of time spent in solitary practice – twenty-five hours for the best as compared with ten hours for the less accomplished. And what do they do in their solitary practice? They work with full concentration on improving specific aspects of their performance as identified by their teachers during weekly lessons. That too is deliberate practice – and (as with the budding chess experts) some musicians do it for up to four hours each day.7
The Nature of Expertise
All of which sounds, of course, very mechanical – and that’s the real danger.
Enter Oxford University don Meriam Bilalic and two of his cognitive science colleagues. As a doctoral scholar in the Department of Experimental Psychology, Bilalic had been interested in exploring what is known as the Einstellung effect. The Einstellung effect refers to the harmful influence of prior experience on solving problems, and occurs because we tend to repeat previously successful methods even when they are no longer appropriate. ‘The first idea that comes to mind, triggered by previous experience with similar situations, prevents alternatives being considered,’ says Bilalic. Scientists had previously thought that experts may be more prone to the Einstellung effect than the rest of us because they have already mastered and automatized the procedures that are routine in their fields. If that is so, experts will be less flexible and creative than the rest of us.
Is it really true, then, that experts become more rigid and less creative as a result of their expertise?
What Bilalic and his colleagues did was to challenge chess players of a wide range of abilities to solve a problem.8 Chess players are ranked like this (in descending order): Grand Master, International Master, Master, Candidate Master (or ‘Expert’), Class A, Class B, and Class C. Bilalic calls the Grand Masters ‘super experts’: at more than five standard deviations above the mean, they are the world’s truly outstanding chess players. One step down comes what Bilalic calls the ‘ordinary experts’ – the International Masters, Masters, and Candidate Masters – at three to five standard deviations above mean ability. Of course, you shouldn’t underestimate their ability; normally an average player would have no chance at all of beating them. Finally come the ‘ordinary players’ – the Class A, B, and C players – at less than three standard deviations above the mean.
Bilalic now set a group of chess players – including no fewer than six Grand Masters – a chess problem. He presented them with the following board9 and asked them to try to win the game in as few moves as possible:
In fact, there is a ‘classic’ solution to this game that is taught to all young chess players. It’s called the ‘smothered mate’ because the Queen is sacrificed in order to draw one of the opponent’s pieces onto a square that blocks the escape square for the King. In this case the ‘smothered mate’ solution would go like this (white to play). White Queen to e6, Black King to h8. White Knight to f7, Black King to g8. White Knight to h6, Black King to h8. White Queen to g8, Black Rook to g8 (taking White Queen). White Knight to f7. Checkmate in four moves. A good, solid, bluecollar
solution.
There is, however, another – and more elegant – solution in fewer moves. It goes like this. White Queen to e6, Black King to h8. White Queen to h6, Black Rook to d7. White Queen to h7 (taking Black Pawn). Checkmate. Three moves instead of four. A better solution.
There’s no need to get bogged down in the technicalities of the game. What matters is that the experiment demonstrated something very intriguing about the nature of expertise and excellence. Why? The ‘ordinary experts’ – all excellent players – were hit by the Einstellung effect. These players would have no problem finding the three-move solution when it was the only solution possible. (In fact, one of them on being told of the experiment commented: ‘You will have to find a harder problem than this.’) But when a more obvious solution presented itself – the familiar ‘smothered mate’ – they tended to fall back on it and miss the best solution. The most interesting outcome of Bilalic’s experiment, though, is that the ‘super experts’ did not in fact succumb to the Einstellung effect. Every single Grand Master saw the optimal solution – and in an average of only seven seconds.
Here we have the crux of the matter – that ‘super experts’ see things differently. Specifically, they are highly conscious of solutions other than the obvious one.
Bilalic and his colleagues think that this is because super experts are able to ‘chunk’ information in the memory and use mental ‘templates’ that help them to be sensitive to even very small details in the context. But the theory shouldn’t obscure the key difference between being good and being really good. The good players were able to identify a good solution and, once they had done so, settled with it. The really good players were able to identify a good solution – and then also identify an even better one.
* * *
You need some grind to be great at chess: you’ve got to put in the hours, and plenty of them. And you also need some grit: you’ve got to stick with it for years. But what Bilalic’s work shows is something more intriguing than just that. It shows that the really top performers are able to absorb the routines and practices of their disciplines – and then go beyond them. You do your deliberate practice for years on end not so that you can master a narrow established technique – that’s Einstellung – but so that you can transcend that technique.
The Magic of Familiarity
Let’s go back to Shakuntala Devi.
What’s really special about Devi, it turns out, is much more interesting than anything that we could say about born genius or the sheer number of hours she has put in to cultivating her peculiar skill. What’s really special about her is the way she perceived her field.
That’s to say that numbers would appear differently to Devi. Consider, for example, the number 720. Contemplate it. Dwell on it. Toy with it. Do what you will – but for most of us the number 720 remains (stubbornly, obstinately) simply the number 720 and nothing more. Not for Shakuntala Devi. When Devi saw the number 720 (on a car license plate, as it happens) she ‘read’ it not as any old number but as 6 factorial (that’s 6 × 5 × 4 × 3 × 2 × 1 = 720). She might see a four-digit room number as the sum of the cubes of two numbers or a stringing together of the integer roots of two numbers. If asked for the nth root of a certain number, she would, in addition to coming up with the correct answer, volunteer other interesting features of the number (e.g. it being the cube of one-half of the given number). Devi wasn’t just calculating numbers; she was seeing the patterns by which numbers fold in upon themselves.
We can put that in a more comprehensible way. Take two simple sums, suggests Jensen. Let’s start with 4 × 23 = ? In general, we are reasonably quick with multiplications up to and including the number 12. That’s because at school we tend to learn multiplication tables up to 12. However, get beyond the 12’s and our response times are slowed. So even though 4 × 23 = ? is a simple calculation, we can’t do it as fast as we could do 4 × 9, say, or 4 × 11.
Now consider this calculation: 4 × 25 = ? That one is really easy. There’s no need for us to have ever memorized it as we may have done for other multiplications. We don’t even need to actually calculate it as such. It’s easy because we have acquired ‘automatic facilitating associations’ for this problem: we deal in hundreds and their fractions on a daily basis and we just see that 25 is one quarter of 100.
Could that be how calculating prodigies and top chess players see their respective fields? Devi’s answer? It’s a ‘gift from God’, she explained, ‘an inborn gift’. And then: ‘I think anyone could do it if they loved numbers the way I do.’ So talent – almost certainly at least some. And love for the subject – that’s evident too.
What really set Devi apart, though, was not necessarily – and certainly not exclusively – either of those. It was sheer familiarity with her chosen field. From the age of three when her fascination with numbers became apparent, her father began to teach her arithmetic. When she got good, he made her part of his stage show performing card tricks and calculations. And through all this she began to inhabit a world of numbers. ‘Perhaps anyone could do it,’ she has suggested, ‘if they had played with numbers for hours every day since early childhood.’
Disparate Fields
It’s an attractively simple analysis. And like most attractively simple analyses, it’s still not quite right.
Look at the fields of achievement studied by the expertise people and you begin to see the problem. There’s maths (or, more precisely, arithmetic). There’s music (not musical composition but musical performance). There’s chess. And there’s sport. Each of these fields is a field in which what separates the high performers from mediocrities is the respective level of expertise. They are what researchers call ‘standard talent domains’. In a standard talent domain, what you have to do to excel is to master an established skill-set and then employ it better than the rest.
What you don’t have to do is to make a creative contribution to the field. A chess master, for example, works within the rules of the game to outperform his opponents; he doesn’t have to rethink the nature of the game itself. A top violinist has to execute with precision and grace the music embodied in the score before her; she doesn’t have to actually compose that music. Great sportsmen and women respond faster, harder, and with greater precision than lesser achievers within their respective sports. Nobody would expect them to pioneer entirely new sports. Can we safely assume that the development of a creator parallels the development of an expert?
When Dean Keith Simonton – whose age curves we have referred to above – came to review the literature on this, he was struck by the evidence suggesting that we simply cannot.10 Creators have different character traits from experts: they are inclined towards ‘nonconformity, unconventionality, independence, openness to experience, ego strength, aggressiveness, risk taking, introversion, and even psychopathology’.11 But even more interesting is what Simonton found out about the development of creators over the life span. The most eminent classical composers, in one study, appeared to have spent less time in preparation than their weaker counterparts and had composed works for fewer years before making their first lasting contribution to the repertoire. The relationship between formal training and creativity, he observed, takes the form of an inverted U-shaped curve: more training increases creative productivity – but only up to a point, after which productivity declines. Even putting the extent of formal training to one side, creativity appears to obey its own laws: ‘The ratio of hits to total attempts does not increase over the course of a career,’ says Simonton, ‘but rather tends to fluctuate randomly.’12
* * *
What, then, does it take to produce works of great beauty like these?
They are both works by Vincent Van Gogh painted circa 1882. The first is little more than a figure of a woman. Her head is bowed down into folded arms; she’s clearly distraught about some personal loss the details of which we can guess but will never know. It’s called Sorrow. The second is a lesser-known drawing of trees and tree roots batte
red and dragged by the winds that have blown into and across them for decades. It’s called The Roots.
Van Gogh’s life story does in fact tick all the boxes. He was born squat in the middle of the nineteenth century (1853) and died ten years short of the twentieth (1890). That’s a calendar age at death of thirty-seven. But Van Gogh’s calendar age was not the same as his career age because it was only when he was fired from his job as a minister in 1880 at the age of twenty-seven that his career began – so his artistic career lasted exactly ten years. And it was only after a full eight years into his career that he found his efforts were really bearing fruit and that he could finally execute an oil painting in one sitting: ‘More than once,’ he wrote, ‘I have done a size 30 canvas in one day, but then I did not stir from the spot from morning till sunset except to eat a morsel.’ The ten-year rule was something of which Van Gogh was painfully aware through his own hands-on experience. ‘I am myself very, very dissatisfied with my work, and the only thing that comforts me is that people of experience say you must paint ten years for nothing,’ he once wrote to his brother. ‘It may have taken me ten minutes to draw something,’ he would say at other times, ‘but it takes ten years to learn how to do it in ten minutes.’
That ten years was well spent. Richard Brower, an expert on Van Gogh’s life and work, describes how the artist mapped out his own plan.13 Brower explains how he had noticed, as a researcher completing his doctoral dissertation, that Van Gogh had intentionally planned his activities over time so that his mastery would evolve in three stages. First, Van Gogh grounded himself in conventional art, before moving through a period of experimentation, until he had reached a stage of liberated mastery. He would begin by spending two years learning from his famous cousin Anton Mauve:
