Sunday, February 02, 2020
Specialization (player Gladwell) vs Generalization (player Epstein): Round 1 to Generalization (Epstein)
In this data-rich world, it is very hard to glean the truth, and this is exemplified by a fascinating match up between Team EP: David Epstein and John Pollack vs. Team GD: Malcolm Gladwell and Angela Duckworth. Team EP espouses generalization and switching of fields, while Team GD espouses deep specialization and grit to stick to a field. After having patiently listened through all their arguments, I as judge, hereby pronounce Team EP as the winners.
Gladwell has been widely hailed for his 10,000 hour rule put forth in the book Outliers which I read around 5-6 years back. I was highly struck by it. Duckworth, McKinsey alumna, is famous for her thesis on Grit, and how it is the most important characteristic for success. I've listened to her podcast on Freakonomics podcast- "How to get more Grit in your life". She won the MacArthur 'genius' fellowship for her research. Summary of team GD's thesis: the way to success is practice from real early, and go on for 10,000 hours, and be real gritty through it- no wavering!
Bringing up the opposition we have Team EP, David Epstein and John Pollack. David Esptein wrote in 2019 "Range- the power of Generalists in an Age of Specialization" which I recently read. John Pollack wrote the book 'The Power of Analogies'. Both of these authors extol the virtues of specializing late, exploring many avenues before committing to one, being flexible with plans and not to just grit through.
Epstein's work is a tour de force - it draws upon wide ranging research and devotes focused energy in striking down the 'cult of early specialization'. Epstein takes Galdwell's own examples, draws them out, and demonstrates how they are flawed. One of the flagship examples of Gladwell is Polgar sisters- they were the first women chess grandmasters, just because their parents started early and wanted to demonstrate the power of 10K hours to the world, through their daughter's success. The father has explicitly said that cancer and poverty can be cured if there is a system of early specialization. However, Epstein makes the point- are humans good at Chess, or AI, today? Early specialization is good he says for fields which have clear rules, repetitive patterns, with regular feedback (RPF). This is exactly the kind of field in which AI thrives. He gives an example of one of the Polgar sisters. She has excellent memory (99.99 percentile memory) of chess board configurations when they are configurations which are likely to arise in the middle of regular chess games; flash such a chess board at her for 10 seconds and she can reproduce fully. But when there are rubbish configurations produced (eg: White Queen hanging in the square next to the Black king)- her memory is down to the normal layperson. Therefore, change the rules of the game, and it is difficult for the hyper specialists to show their advantage. And in our world, rules change rapidly.
Similarly, for Grit, one of the key research pieces underlying Duckworth's Grit is set in the US Military's program marquee for all trainees, called 'Beast Barracks' or simply The Beast. She shows how a 'Grit score' (measures Work ethic + resilience & consistency of interests) predicted well the probability of someone completing the Beast program. Grit score also predicted the probability of someone doing well in other fields such as Spelling Bee. Epstein proceeds to smash Duckworth's research. Firstly, in an excellent exposition of logic, he says that candidates are firstly chosen for Beast based on their grades and leadership, and by administering Grit Tests to these candidates alone, you are causing what is called in statistics 'Restriction of range'. Candidates with poor leadership or grades would never be part of the sample of Beast incoming batch, therefore the power of prediction of leadership or grades on the dropout rates can never be studied. Then, here comes argumentation gold- Epstein looks at studies of West Point Graduates 5 years on after Beast- 5 years is the 'bond' the candidates sign in return for the investment of the govt. into them. Half of all Beast graduates leave immediately after the 5 years are over. In 2010, an internal Military memo was published, which said- "prospects for army officers corps have been darkened by ever-diminishing return on this investment (into training) as evidenced by plummeting company grade officer retention rates". The reason is that as the best graduate kids grew into young professionals, they realized that US Military was not what they wanted to and that other career options are equally attractive. So- what was the point of all that grit? Ended up costing the taxpayer millions, and also 5 'lost' years for those who showed so much grit that they overcame their better instinct which told them during training- 'This is not for you!'
Epstein gives multiple such powerful examples across diverse fields, including Sports (Roger Federer), Music (Vivaldi and his generalist musical team in Venice in the 19th century), Science (NASA Challenger disaster, various scientists who dabble in multiple fields) . Drawing from all these examples, Epstein advocates: early exploration followed by late specialization, being ready to switch, and pursuing deep interests in fields apart from your own. For the third point, he quotes this study: Compared to other scientists, Nobel laureates are 22 times more likely to partake as an amateur actor, dancer, magician or other kind of performer. Conclusion of this quoted study was- those who did not make a creative contribution to their field lacked aesthetic interests outside their own narrow area. Further, an important point to note that is that Epstein does not espouse a shallow form of generalization which may be seen sometimes in MBA schools. These Nobel prize winners are after all deep in their field. However, they often sally forth bravely and deeply into other frields.
As judge, I would give it to Team EP over GD. However, they have had the advantage of hindsight and can at will attack the points brought up by G and D. Frankly, I would love to see this debate in action.
A blog post cannot do justice to the various nuances brought up and examples cited by Epstein, so I would urge you to pick up the book. Also, these books are fantastic reads for parents, and I am composing a mail to all recent and to-be parent friends to read this book.
On a side note, coming back to the first point on the problems of identifying the right vs. wrong in this data-rich world- this is what the problem is now with politics and general discussions, too. There is enough data to make great points on both sides! Especially sociological research- there is abundant amount on both sides for any argument.
Notes on Range: It was shortlisted for the Financial Times 2019 Non fiction book of the year, which is where I discovered it. Thanks to S for reminding me about it- I had been gushing about the list after reading 'Bad Blood' which I first discovered there.
Gladwell has been widely hailed for his 10,000 hour rule put forth in the book Outliers which I read around 5-6 years back. I was highly struck by it. Duckworth, McKinsey alumna, is famous for her thesis on Grit, and how it is the most important characteristic for success. I've listened to her podcast on Freakonomics podcast- "How to get more Grit in your life". She won the MacArthur 'genius' fellowship for her research. Summary of team GD's thesis: the way to success is practice from real early, and go on for 10,000 hours, and be real gritty through it- no wavering!
Bringing up the opposition we have Team EP, David Epstein and John Pollack. David Esptein wrote in 2019 "Range- the power of Generalists in an Age of Specialization" which I recently read. John Pollack wrote the book 'The Power of Analogies'. Both of these authors extol the virtues of specializing late, exploring many avenues before committing to one, being flexible with plans and not to just grit through.
Epstein's work is a tour de force - it draws upon wide ranging research and devotes focused energy in striking down the 'cult of early specialization'. Epstein takes Galdwell's own examples, draws them out, and demonstrates how they are flawed. One of the flagship examples of Gladwell is Polgar sisters- they were the first women chess grandmasters, just because their parents started early and wanted to demonstrate the power of 10K hours to the world, through their daughter's success. The father has explicitly said that cancer and poverty can be cured if there is a system of early specialization. However, Epstein makes the point- are humans good at Chess, or AI, today? Early specialization is good he says for fields which have clear rules, repetitive patterns, with regular feedback (RPF). This is exactly the kind of field in which AI thrives. He gives an example of one of the Polgar sisters. She has excellent memory (99.99 percentile memory) of chess board configurations when they are configurations which are likely to arise in the middle of regular chess games; flash such a chess board at her for 10 seconds and she can reproduce fully. But when there are rubbish configurations produced (eg: White Queen hanging in the square next to the Black king)- her memory is down to the normal layperson. Therefore, change the rules of the game, and it is difficult for the hyper specialists to show their advantage. And in our world, rules change rapidly.
Similarly, for Grit, one of the key research pieces underlying Duckworth's Grit is set in the US Military's program marquee for all trainees, called 'Beast Barracks' or simply The Beast. She shows how a 'Grit score' (measures Work ethic + resilience & consistency of interests) predicted well the probability of someone completing the Beast program. Grit score also predicted the probability of someone doing well in other fields such as Spelling Bee. Epstein proceeds to smash Duckworth's research. Firstly, in an excellent exposition of logic, he says that candidates are firstly chosen for Beast based on their grades and leadership, and by administering Grit Tests to these candidates alone, you are causing what is called in statistics 'Restriction of range'. Candidates with poor leadership or grades would never be part of the sample of Beast incoming batch, therefore the power of prediction of leadership or grades on the dropout rates can never be studied. Then, here comes argumentation gold- Epstein looks at studies of West Point Graduates 5 years on after Beast- 5 years is the 'bond' the candidates sign in return for the investment of the govt. into them. Half of all Beast graduates leave immediately after the 5 years are over. In 2010, an internal Military memo was published, which said- "prospects for army officers corps have been darkened by ever-diminishing return on this investment (into training) as evidenced by plummeting company grade officer retention rates". The reason is that as the best graduate kids grew into young professionals, they realized that US Military was not what they wanted to and that other career options are equally attractive. So- what was the point of all that grit? Ended up costing the taxpayer millions, and also 5 'lost' years for those who showed so much grit that they overcame their better instinct which told them during training- 'This is not for you!'
Epstein gives multiple such powerful examples across diverse fields, including Sports (Roger Federer), Music (Vivaldi and his generalist musical team in Venice in the 19th century), Science (NASA Challenger disaster, various scientists who dabble in multiple fields) . Drawing from all these examples, Epstein advocates: early exploration followed by late specialization, being ready to switch, and pursuing deep interests in fields apart from your own. For the third point, he quotes this study: Compared to other scientists, Nobel laureates are 22 times more likely to partake as an amateur actor, dancer, magician or other kind of performer. Conclusion of this quoted study was- those who did not make a creative contribution to their field lacked aesthetic interests outside their own narrow area. Further, an important point to note that is that Epstein does not espouse a shallow form of generalization which may be seen sometimes in MBA schools. These Nobel prize winners are after all deep in their field. However, they often sally forth bravely and deeply into other frields.
As judge, I would give it to Team EP over GD. However, they have had the advantage of hindsight and can at will attack the points brought up by G and D. Frankly, I would love to see this debate in action.
A blog post cannot do justice to the various nuances brought up and examples cited by Epstein, so I would urge you to pick up the book. Also, these books are fantastic reads for parents, and I am composing a mail to all recent and to-be parent friends to read this book.
On a side note, coming back to the first point on the problems of identifying the right vs. wrong in this data-rich world- this is what the problem is now with politics and general discussions, too. There is enough data to make great points on both sides! Especially sociological research- there is abundant amount on both sides for any argument.
Notes on Range: It was shortlisted for the Financial Times 2019 Non fiction book of the year, which is where I discovered it. Thanks to S for reminding me about it- I had been gushing about the list after reading 'Bad Blood' which I first discovered there.
Labels: Books
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