What Makes Great Scientists Great?
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. He titled his presentation “You and Your Research,” and set out to answer a fundamental question: “Why do so few scientists make significant contributions and so many are forgotten in the long run?”
Hamming, of course, knew what he was talking about, as he had made his own significant contributions — you can’t even glance at the field of digital communications without stumbling over some eponymous Hamming innovation.
But his original interest in the question came from his years spent in Los Alamos at the height of the Manhattan Project. “I saw Feynman up close. I saw Fermi and Teller. I saw Oppenheimer. I saw Hans Bethe,” Hamming notes. “I saw that although physically I was the same, they were different. [T]o put the thing bluntly, I was envious.”
Forty years later, as he took the podium at the Bell Labs auditorium, he set out to describe, in plainspoken detail, everything he had learned…
The Hamming Ambiguity
I know Hamming’s speech well as Study Hacks readers send me a copy, on average, about once per month. I originally encountered the speech, however, during my first semester as a graduate student at MIT.
At the time, I was underwhelmed.
Hamming starts by emphasizing courage: “Once you get your courage up and believe that you can do important problems, then you can.”
He then pivots to the role of environment. “What most people think are the best working conditions, are not,” he says. “One of the better times of the Cambridge Physical Laboratories was when they had practically shacks — they did some of the best physics ever.”
“Now on to the matter of drive,” he continues, using the metaphor of compound interest to explain the growth of ability. “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.”
As the speech rolls forward, Hamming continues to jump, somewhat abruptly, from topic to topic. We hear about problem choice (”if you don’t work on important problems, it’s unlikely that you’ll do important work”), and the surprisingly tricky decision of whether to keep your office door open (”there is a pretty good correlation between those who work with the doors open and those who ultimately do important things, although people who work with doors closed often work harder”).
He promotes the importance of producing widely applicable results (”I made the resolution I would never again solve a problem in isolation”), and emphasizes the “distasteful” necessity of selling. “When I first started, I got practically physically ill while giving a speech,” he admits. With practice, of course, he got better.
To me, the speech’s impact diluted among its many disconnected insights. I didn’t come away with a clear new model for how to structure my research career, so I ignored Hamming’s advice, responding politely, but somewhat dismissively, as readers continued to point me toward the talk as a potential source of wisdom.
Now that I’m over a decade into my training as a professional scientist, however, I’m finally beginning to notice the elegance behind Hamming’s words. With this talk, I came to realize, he’s capturing a crucial truth: in many fields, including research science, the path to becoming excellent is messy and ambiguous.
The fact that his advice is disjointed and varied is exactly the point: there’s no simple model for becoming great, uncountable variables matter, and you’ll never be confident that you’ve found the “best” configuration.
Beyond the 10,000 Hour Rule
The messiness of Hamming’s speech contrasts with the rational cleanliness of another popular model of becoming excellent: the 10,000 hour rule. This “rule” has been studied since the 1970s, but Malcolm Gladwell brought it into the mainstream with his 2008 book Outliers. Here’s how he described the idea in a recent interview:
When we look at any kind of cognitively complex field — for example, playing chess, writing fiction or being a neurosurgeon — we find that you are unlikely to master it unless you have practiced for 10,000 hours.
This rule reduces achievement to quantity: the secret to becoming great is to do a great amount of work. What Hamming emphasizes, however, is that quantity alone is not sufficient. (”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,” he asks at one point in his speech.) Those 10,000 hours have to be invested in the right things, and as the disjointed nature of Hamming’s talk underscores, the question of what are the right things is slippery and near impossible to nail down with confidence.
In other words, becoming excellent is not the result of a well-behaved tallying of hours, it instead emerges out of a swamp of roiling ambiguity. If you’re not ready for this reality, he implies, you’re unlikely to last long on a path toward greatness.
My Working Rules
Over time, I’ve made peace with this ambiguity. I’m never going to feel completely anchored in my quest to become excellent in my own field of theoretical computer science — every rejected paper or publishing coup of a colleague will continue to flush my system with doubt — but I have managed to cobble together several working rules that help me maintain forward momentum. 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:
- Embrace Ambiguity:
- Stay Specific:
- Tinker Often, But Not Too Often:
- Seek Resistance: At the core of getting better is deliberate practicehard focus
- Revel in the Crafstmanship:practicing their craft along the way.
Conclusion
“Great scientists tolerate ambiguity very well,” Hamming says. “They believe the theory enough to go ahead; [but] they doubt it enough to notice the errors and faults so they can step forward and create the new replacement theory.”
This is perhaps the most important advice from among Hamming’s many suggestions. The path to excellence requires this balance between confidence and doubt, and though this balance is challenging, it’s tractable so long as your recognize what you’re facing.
At least, I think this is true. As always, when it comes to these issues of growing ability, the right way forward is never quite clear. If it was, there would be a lot more stars out there.
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