1534: Beyond the 10,000 Hour Rule: Richard Hamming and the Messy Art of Becoming Great by Cal Newport

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[00:00:30] This is Optimal Work Daily.

[00:00:32] Beyond the 10,000 Hour Rule. Richard Hamming and the Messy Art of Becoming Great by Cal Newport of CalNewport.com

[00:00:41] What makes great scientists great?

[00:00:44] In March of 1986, an overflow audience of over 200 researchers and staff members from Bell Laboratories piled into the Morris Research and Engineering Center to hear a talk given by Dr. Richard Hamming, a pioneer in the field of communication theory.

[00:00:58] He titled his presentation, You and your research and set out to answer a fundamental question.

[00:01:05] Why do so few scientists make significant contributions and so many are forgotten in the long run?

[00:01:11] Hamming, of course, knew what he was talking about as he had made his own significant contributions.

[00:01:16] You can't even glance at the field of digital communications without stumbling over some eponymous Hamming innovation.

[00:01:22] But his original interest in the question came from his years spent in Los Alamos at the height of the Manhattan Project.

[00:01:29] Hamming says, quote,

[00:01:30] I saw Feynman up close. I saw Fermi and Teller. I saw Oppenheimer. I saw Hans Bett.

[00:01:36] I saw that although physically I was the same, they were different.

[00:01:40] To put the thing bluntly, I was envious.

[00:01:42] End quote.

[00:01:44] Forty years later, as he took to the podium at the Bell Labs auditorium, he set out to describe, in plain spoken detail, everything he had learned.

[00:01:52] The Hamming Ambiguity

[00:01:54] I know Hamming's speech well, as StudyHack's readers send me a copy, on average, about once per month.

[00:02:00] I originally encountered the speech, however, during my first semester as a graduate student at MIT.

[00:02:06] At the time, I was underwhelmed.

[00:02:08] Hamming starts by emphasizing courage.

[00:02:11] Quote,

[00:02:11] Once you get your courage up and believe that you can do important problems, then you can.

[00:02:16] End quote.

[00:02:17] He then pivots to the role of environment.

[00:02:19] He says,

[00:02:20] Quote,

[00:02:21] What most people think are the best working conditions are not.

[00:02:25] One of the better times of the Cambridge Physical Laboratories was when they had practically shacks.

[00:02:29] They did some of the best physics ever.

[00:02:32] End quote.

[00:02:33] Now on to the matter of drive, he continues, using the metaphor of compound interest to explain the growth of ability.

[00:02:40] He says,

[00:02:41] Quote,

[00:02:41] Given two people with exactly the same ability, the one person who manages day in and day out to get in one more hour of thinking will be tremendously more productive over a lifetime.

[00:02:51] End quote.

[00:02:52] As the speech rolls forward, Hamming continues to jump, somewhat abruptly, from topic to topic.

[00:02:58] We hear about problem choice.

[00:03:00] Quote,

[00:03:00] If you don't work on important problems, it's unlikely that you'll do important work.

[00:03:04] End quote.

[00:03:05] And the surprisingly tricky decision of whether to keep your office door open.

[00:03:09] Quote,

[00:03:10] There is a pretty good correlation between those who work with the doors open and those who ultimately do important things,

[00:03:16] although people who work with doors closed often work harder.

[00:03:19] End quote.

[00:03:20] He promotes the importance of producing widely applicable results.

[00:03:24] Quote,

[00:03:25] I made the resolution I would never again solve a problem in isolation.

[00:03:29] End quote.

[00:03:29] And he emphasizes the distasteful necessity of selling.

[00:03:33] He admits,

[00:03:35] Quote,

[00:03:35] When I first started, I got practically physically ill while giving a speech.

[00:03:39] End quote.

[00:03:40] With practice, of course, he got better.

[00:03:43] To me, the speech's impact was diluted among its many disconnected insights.

[00:03:48] I didn't come away with a clear new model for how to structure my research career, so I ignored Hamming's advice,

[00:03:54] responding politely but somewhat dismissively as readers continued to point me toward the talk as a potential source of wisdom.

[00:04:01] Now that I'm over a decade into my training as a professional scientist, however,

[00:04:05] I'm finally beginning to notice the elegance behind Hamming's words.

[00:04:09] With this talk, I came to realize he's capturing a crucial truth.

[00:04:13] In many fields, including research science, the path to becoming excellent is messy and ambiguous.

[00:04:19] The fact that his advice is disjointed and varied is exactly the point.

[00:04:23] There's no simple model for becoming great.

[00:04:27] Uncountable variables matter, and you'll never be confident that you've found the best configuration.

[00:04:33] Beyond the 10,000-hour rule

[00:04:35] The messiness of Hamming's speech contrasts with the rational cleanliness of another popular model of becoming excellent,

[00:04:43] the 10,000-hour rule.

[00:04:44] This rule has been studied since the 1970s, but Malcolm Gladwell brought it into the mainstream with his 2008 book, Outliers.

[00:04:52] Here's how he described the idea in a recent interview.

[00:04:55] Quote,

[00:04:56] When we look at any kind of cognitively complex field, for example, playing chess, writing fiction, or being a neurosurgeon,

[00:05:03] we find that you are unlikely to master it unless you have practiced for 10,000 hours.

[00:05:08] End quote.

[00:05:09] This rule reduces achievement to quantity.

[00:05:12] The secret to becoming great is to do a great amount of work.

[00:05:15] What Hamming emphasizes, however, is that quantity alone is not sufficient.

[00:05:19] He says,

[00:05:20] I've often wondered why so many of my good friends at Bell Labs who worked as hard or harder than I did didn't have so much to show for it.

[00:05:27] He asked that at one point in his speech.

[00:05:30] Those 10,000 hours have to be invested in the right things,

[00:05:33] and as the disjointed nature of Hamming's talk underscores,

[00:05:36] the question of what are the right things is slippery and near impossible to nail down with confidence.

[00:05:42] In other words, becoming excellent is not the result of a well-behaved tallying of hours.

[00:05:46] It instead emerges out of a swamp of roiling ambiguity.

[00:05:51] If you're not ready for this reality, he implies, you're unlikely to last long on a path toward greatness.

[00:05:57] My Working Rules

[00:05:59] Over time, I've made peace with this ambiguity.

[00:06:02] I'm never going to feel completely anchored in my quest to become excellent in my own field of theoretical computer science.

[00:06:08] Every rejected paper or publishing coup of a colleague will continue to flush my system with doubt,

[00:06:13] but I have managed to cobble together several working rules that have helped me maintain forward momentum.

[00:06:19] These aren't the magic right answers, but I thought I would share them with you as a portrait of one individual's battle with Hamming's necessary ambiguity.

[00:06:28] 1. Embrace ambiguity

[00:06:29] You'll never be fully confident in your approach to becoming excellent.

[00:06:34] Embrace this ambiguity and your ability to recognize it and still move forward.

[00:06:38] This resolve separates you from most other people who are fearful of such messiness

[00:06:43] and soon retreat to the comfort of small projects with small but immediately apparent results.

[00:06:49] 2. Stay Specific

[00:06:51] Always follow a specific written plan for becoming better, even if you're not sure if it's the best plan.

[00:06:57] Specificity focuses your efforts and gives you the possibility of growth.

[00:07:01] Without a plan, it's difficult to progress.

[00:07:04] I maintain, for example, a detailed strategy for stretching my ability to translate algorithmic insights into deep results.

[00:07:11] 3. Tinker often, but not too often

[00:07:14] Use moments of feedback.

[00:07:16] For me, for example, learning whether a research paper was accepted or won an award,

[00:07:21] to make educated adjustments to your plan.

[00:07:23] Don't do this too often, however, or you won't leave enough time to make progress.

[00:07:28] I find, on average, that I adjust my plan around once per semester.

[00:07:32] 4. Seek Resistance

[00:07:35] At the core of getting better is deliberate practice, stretching yourself beyond your current capability.

[00:07:41] This work is hard and draining, but also necessary.

[00:07:44] 5. Seek this mental resistance

[00:07:46] If you're not regularly experiencing long stretches of mind-melting hard focus,

[00:07:50] then you're wasting your time.

[00:07:52] 5. Revel in the Craftsmanship

[00:07:55] The path to becoming excellent is so long and messy

[00:07:59] that a goal-oriented motivation can only carry you so far.

[00:08:02] Top achievers find enjoyment in practicing their craft along the way.

[00:08:07] Conclusion

[00:08:08] Hemming says, quote,

[00:08:10] Great scientists tolerate ambiguity very well.

[00:08:13] They believe the theory enough to go ahead, but they doubt it enough to notice the errors

[00:08:18] and faults so they can step forward and create the new replacement theory.

[00:08:22] End quote.

[00:08:23] This is, perhaps, the most important advice from among Hemming's many suggestions.

[00:08:28] The path to excellence requires this balance between confidence and doubt,

[00:08:32] and though this balance is challenging, it's tractable so long as you recognize what you're facing.

[00:08:38] At least, I think this is true.

[00:08:40] As always, when it comes to these issues of growing ability,

[00:08:43] the right way forward is never quite clear.

[00:08:46] If it was, there would be a lot more stars out there.

[00:08:52] You just listened to the post titled, Beyond the 10,000 Hour Rule,

[00:08:57] Richard Hamming and the Messy Art of Becoming Great,

[00:09:01] by Cal Newport of calnewport.com.

[00:09:04] And thank you to Cal, our author today,

[00:09:07] and a popular writer with a book that's being talked about everywhere, it seems.

[00:09:11] That's Deep Work, one of six self-improvement books that he's written.

[00:09:14] He completed his undergraduate studies at Dartmouth College in 2004

[00:09:19] and received a PhD from MIT in 2009 in computer science.

[00:09:23] He was then a postdoctoral associate in the MIT Computer Science Department from 2009 to 2011,

[00:09:30] and that year he joined Georgetown University as an assistant professor of computer science

[00:09:35] and was granted tenure in 2017.

[00:09:37] His work focuses on distributed algorithms in challenging network scenarios.

[00:09:43] You know, basic stuff.

[00:09:44] And again, he has multiple popular books that are worth checking out,

[00:09:48] plus his blog called Study Hacks.

[00:09:51] And lastly, you can check out his relatively new podcast called Deep Questions.

[00:09:56] You can find all of that and more at calnewport.com.

[00:10:00] And I think that does it for me today.

[00:10:02] Hope you're having a happy Thursday if you're listening to me in real time.

[00:10:05] As always, appreciate you being a subscriber and have a great rest of your day.

[00:10:09] I'll see you back here tomorrow for the Friday show, where your optimal life awaits.

[00:10:13] Let's see.

[00:10:14] Let's see.

[00:10:14] Thank you.