This is the first article I recommend everyone read (currently, ‘everyone’ refers to students or recent graduates). Every paragraph is full of insights. It encourages a proactive approach to the world around us. It lays out an approximate framework for anyone interested in thinking about what they are doing, and where they would want to be.
The following notes are a summary of my observations and formulations from the article. These are a combination of the obvious (“he says it right in the paper!”) and bringing together concepts scattered across. It is a work in progress!
Why do great
Unlike the paper, I believe each of us has to define what ‘great’ is. We should be doing work that matters to us, and this needs to lead to significant scientific breakthroughs. Also, the insights apply equally to work (as opposed to research)
The (mis-)characteristics of a great scientist
What is common among the great scientists? The lazy narrative is that they achieved
greatness because of:
- Luck: Something are happenstance, but for the most part, make
your own luck!
- Fortune favors the prepared mind – Louis Pasteur
- If others would think as hard as I did, then they would get
similar results – Issac Newton
- Brains: Most likely we have enough for what we set out to do. It
just needs unlocking
- Age: Depends on what we are doing. In some cases, the audacity
of youth is needed to challenge existing dogma, on others, the wisdom of
maturity is required to tease out insights
- Drive: This is so important, I discuss it separately below
- Ambiguity: College exams are typically re-statements of problems
already seen. However, the real world is rarely straightforward.
- Commitment: this is necessary to get the subconscious to work
for us. And this leads to that nebulous factor called creativity.
There are so many things to unpack from this one paragraph! In fact, this was the one
thing that I remembered from the first reading of the paper. Here’s how I
visualize one part:
Knowledge and productivity are like compound interest. …. The more you know, the more you learn; the more you learn, the more you can do; the more you can do, the more the opportunity. Hamming anticipates Gladwell’s 10,000-hour rule, noting the importance of effort intelligently applied.
Ego and Perspective
I recall colleagues who insisted on doing things their way, no matter the effort and energy it would consume. Much better to figure out what is important, which fights you want to fight and drop the rest.
Hamming does not explicitly say this, but throughout the talk, we find examples of him identifying areas of improvement and actively working on these. Examples are:
- He has lunch with other teams and has an agenda of what he wants
to get out of these interactions
- He consciously sets aside time for ‘great thoughts’ (in a sense
anticipating Google’s 10% approach)
- He starts out with being nervous giving a speech, so volunteers
to do more of them!
The ‘Big Picture’ view
Closely related to the above point is Hamming’s consistent approach to thinking about the underlying structure of the reality that he observes (the entire talk is an example of this, of course). Why do some scientists do great work? What is the larger problem that I am trying to solve? How can we generalize this work? Is it better to do x instead of y. Why? (an example: work with the door closed or open?). Who is more effective in a meeting? Why?
Too many times we just accept things as they are. It’s a seemingly small step to question things, but the consequences can be huge.
The interplay of factors contributing to great work
Great Work $ = \left(d\times c\right)^a$
Where d = drive
c = commitment
a = ability
The factors that are in our control — drive and commitment are the base of the exponent. The more we invest, the greater the returns. Our ability is the exponent, and this can grow if we put in the effort.