Why 10,000 hours are so important
Why grandmasters are actually about 99% percent normal
Why you don’t have to be a genius to play chess
Why do I sound so much like Malcolm Gladwell???
Yes, the cultural consensus is changing. No longer does anyone speak of “natural talent” or “innate gifts” when they see a 12-year old master a difficult Tchaikovsky concerto on the violin, or a young grandmaster win a few dozen simultaneous blindfolded games of chess, or Tiger win yet another tour. No, now it’s all thanks to some opaque process called “deliberate and sustained practice.” Who’d’a thought? Countless people once convinced of their mediocrity are now overjoyed at newfound opportunities, and countless more are finding out that you can’t be Bill Gates just because the recursive factorial routine you just programmed worked the very first time. There are no free rides.
More seriously, though. I’ve read Outliers by Gladwell. I’ve read Talent is Overrated by Geoff Colvin. And now I’ve read the entries of “Chess; The Psychology of” and “Expertise” in the MIT Encyclopedia of Cognitive Science (by the way, greatest thing I’ve ever laid my hands on). Now that I’ve confirmed the seemingly cherry-picked examples offered by Colvin and Gladwell with the authoritative source of a university encyclopedia, I feel a little more confident to write about it and accept their arguments. Also, the 10,000 rule seems to be “cool” nowadays, and I like my blog to be “cool.”
That being said, I’m kind of surprised that neither book makes any reference to chess, because the game is one that is generally attributed to prodigious mental abilities of memory, pattern recognition, and strategy formulation, and because ranking systems make individual progress easy to track. And I’m surprised that they don’t mention it because there literally doesn’t seem to be anything else that relies so much and so singularly on practice, practice, practice. Studies show that grandmasters tend to show an across-the-board IQ and average short-term memory skills in domains outside of chess.
So to explain the highly-above-average short-term memory in the specific domain of chess, we turn to an explanation called chunking theory. Chunking theory basically states that experienced-enough players have an inner mental repository of thousands of common configurations of 4-6 pieces which allow them to view the board in a simplified and efficient way. I saw a documentary about the Hungarian chess grandmaster Susan Polgar (she was “engineered” by her father to be a chess genius à la the 10,000 hour rule) who could memorize a chess board in a glimpse as long as it was chunked, or in other words, if it was representative of a potential game situation. If the chess board had pieces strewn on it at random, she had the same success rate as any old person. And to support chunking theory further, a study of grandmasters glimpsing and rebuilding boards showed that the most common mistakes had clusters of pieces off by one – evidence that they saw the board in terms of groups rather than individual pieces.
So smart chess players aren’t smarter, per se, but they see the board in a completely different way than an inexperienced person. At the beginning of AI chess, researchers thought that grandmasters simply “looked ahead” further than regular people and used that to write their programs. They turned out to be wrong – grandmasters looked ahead just as far, but by virtue of seeing a higher level of organization, they were able to ignore long-term bad moves entirely. Indeed, I, who does play chess, played a series of games against a much more experienced friend months ago. He beat me handily each time except one. In the one game that I did better, I expended considerable mental energy and pressed my short-term memory to its limits, allowing me to keep up for about half a game until I couldn’t focus properly anymore. Clearly, thinking harder isn’t really the way to go.
So those are some sobering lessons – the only way to get better is to do a lot more work. Of course, even though the 10,000 hour rule is in a way a relief, it’s also a price. Perhaps the first rule to achieving it is that you can’t be counting hours. Most people can probably spend 100 hours deliberately practicing they dislike. Almost no one can deliberately practice something they feel ambivalent about for 1,000 hours. And 10,000 hours? It’s got to be your life.
But as conclude I do have a few questions. Even though Gladwell seems to rule out the notion of “prodigies” he still uses the example of 10-sigma genius Christopher Langan to show how being a genius can lead to trouble in dealing with other people and doesn’t correlate nicely with success. So the 10,000 hour rule must have more to do with success than intellect. What about people who spend their entire life practicing mathematics but still just end up being average in the field? It didn’t take Terry Tao 10,000 hours to become a math genius – he competed in the IMO at age 10! Perhaps he doesn’t exemplify “success” – even though tenure at a major university (UCLA) and a Fields medal are the highest honors in mathematics, he could probably make a lot more money on Wall St (the Fields prize money is a paltry sum, something like $15,000). Of course, this is no way an endorsement for Dr. Tao to make a career change. Terry, please stay at UCLA!