Creativity

From Eugene Peterson:

Creativity is difficult. When you are being creative, you’re living by faith. You don’t know what’s next because the created, by definition, is what’s never been before. So you’re living at the edge of something in which you’re not very confident. You might fail: in fact, you almost certainly will fail a good part of the time. All the creative persons I know throw away most of the stuff they do.

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Subtle variations on familiar themes
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When Thomas Edison was sixty-seven years old, his factory was destroyed in a fire. This was his response the next morning:

There’s value in disaster. All our mistakes are burned up. Thank God, we can start anew.

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Dan Wineman shared a profound insight on Twitter:

You say “looks like somebody has too much time on their hands” but all I hear is “I’m sad because I don’t know what creativity feels like.”

In place of “creativity” Wineman might have as easily said “persistence.” I found Wineman’s quote in a post by Dan Meyer responding to criticism of his research projects.

I’ve said that someone has too much time on their hands, but not since I read Meyer’s post. I see now that the phrase is often a sour grapes response to creativity. I don’t want to do that anymore.

When we see that someone has spent a thousand hours on a project that we think was a frivolous, it’s easy to say “what a waste of time.” We think how much good could have been done with that same amount of effort. But what was the realistic alternative? If that same person had spent a thousand hours in front of their television instead, no one would ever know and no one would ever criticize them. Instead, they created something.

Tree house photo from Succeed Blog. Full size photo.

Rookie programmers don’t know how to reuse code. They write too much original code because they either don’t know about libraries or they don’t know how to use them. And if they do reuse someone else’s code, they copy and paste it, creating maintenance problems.

The next step in professional development is learning to reuse code. Encapsulation! Black boxes! Buy, don’t build! etc.

But this emphasis on reuse and black boxes can go too far. We can be intimidated by these black boxes and afraid to open them. We can come to believe the black boxes were created by superior beings. We can spend more time inferring the behavior of the black boxes than it would take to open them up or rewrite them. Then we pile leaky abstraction on top of leaky abstraction when we treat our own code as black boxes.

Joe Armstrong said in Coders at Work

Over the years I’ve kind of made a generic mistake … to not open the black box. … It’s worthwhile seeing if the direct route is quicker than the packaged route.

Several of the programmers who were interviewed in the book made similar remarks. They contribute part of their success to being unafraid of black boxes. They gained experience and confidence by taking things apart to see how they work.

Donald Knuth once said in an interview

I also must confess to a strong bias against the fashion for reusable code. To me, “re-editable code” is much, much better than an untouchable black box or toolkit. I could go on and on about this. … you’ll never convince me that reusable code isn’t mostly a menace.

Knuth returns to this theme in Coders at Work.

There’s this overemphasis on reusable software where you never get to open up the box … It’s nice to have these black boxes but, almost always, if you can look inside the box you can improve it …

Well, Knuth can almost always improve any code he finds. Less talented programmers need to be more humble. But too often programmers who are talented enough to make improvements are reluctant to do so. As Yeats said in his poem The Second Coming,

The best lack all conviction, while the worst are full of passionate intensity.

In any discussion of opening black boxes, someone will bring up the analogy of cars: Not everyone needs to know how a car works inside. I would agree that drivers no longer need to understand how a car works, but automotive engineers do. The problem isn’t users who don’t understand how software works, it’s software developers who don’t understand how software works.

Of course software libraries are extremely valuable. Knuth goes too far when he says reusable code is usually a menace. But I see a disturbing lack of curiosity among programmers. They are far too willing to use code they don’t understand.

Related post:

Reusable code versus re-editable code

In his interview on EconTalk, Paul Graham made a distinction between poverty and squalor. He says that most poor people live like rich people, but with cheap imitations. A rich person might have something made of gold and a poor person might have the same thing except made of plastic. But the creative poor, such as the proverbial starving artist, live differently. They live in poverty but not in squalor. They achieve a pleasant lifestyle by not trying to imitate the rich.

For example, the wealthy have large beautiful houses. The poor have small and usually not-so-beautiful houses. The rich have new expensive cars and the poor have old cheap cars. But the starving artist might not have a house or a car. He or she might live in a converted warehouse with a few nice furnishings and ride a bicycle.

The point of his discussion of poverty was to make an analogy for small software companies. It makes no sense for a tiny start-up to try to be a scaled-down version of Microsoft. They need to have an entirely different strategy. They can be poor without living in squalor.

I don’t know what I think of Graham’s assertion that the poor live cheap imitations of the lifestyles of the rich. There’s probably some truth to it, though I’m not sure how much. And I’m not sure how much truth there is in the romantic image of the bohemian starving artist. But I agree that it makes no sense for a small company to be a miniature version of a huge corporation.

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I was skimming through George Leonard’s little book Mastery the other night and ran across this quote:

… the essence of boredom is to be found in the obsessive search for novelty. Satisfaction lies in … the discovery of endless riches and subtle variations on familiar themes.

This is a theme I’ve written about several times before. For example, see the post Six quotes on digging deep. I often think about one of the quotes in that post. Richard Feynman said that

… nearly everything is really interesting if you go into it deeply enough …

In the post God is in the details I talk about how that applies to statistics. Rote application of statistics is mind-numbingly dull, but statistics can be quite interesting when you dig down to the foundations.

When I was in new faculty orientation years ago I remember a chemistry professor exhorting us to volunteer to teach freshman courses. Most people want to teach the more advanced courses, but he said that some of his best inspiration came from teaching the most foundational courses.

Focusing on basics is hard work and few people want to do it. George Leonard describes this as America’s “anti-mastery” culture. Seth Godin uses the image of a starving woodpecker in his book The Dip.

A woodpecker can tap twenty times on a thousand trees and get nowhere, but stay busy. Or he can tap twenty thousand times on one tree and get dinner.

Sometimes I feel like the woodpecker tapping on a thousand trees, staying busy but getting nowhere. But then I also think about a line from W. C. Fields:

If at first you don’t succeed, try, try again. Then quit. No use being a damn fool about it.

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The following quote from Irving Stone describes how Michelangelo worked on his Pietà.

He carved in a fury from first light to dark, then threw himself across his bed, without supper and fully clothed, like a dead man. He awoke around midnight, refreshed, his mind seething with sculptural ideas, craving to get at the marble.

Sitting at a computer changes the way you think. You need to know when to walk away from the computer and when to come back.

I think mind mapping software is a bad idea. Mind maps are supposed to capture free associations. But the very act of sitting down at a computer puts you in an analytical frame of mind. In other words, mind mapping is a right-brain activity, but sitting at a computer encourages left-brain thinking. Mind mapping software might be a good way to digitize a map after you’ve created it on paper, but I don’t think it’s a good way to create a map.

When I need to sort out projects and priorities, I do it on paper. After that I may type up the results. I like to capture ideas on paper or on my voice recorder but then store them online.

When I do math, I scribble on paper, then type up my results in LaTeX. Scribbling helps me generate ideas; LaTeX helps me find errors. I’ve found that fairly short cycles of scribbling and typing work best for me, a few cycles a day.

In the past, we did a lot of things on paper because we had no choice. Today we do a lot of things on computers today just because we can. It’s going to take a while to sift through the new options and decide which ones are worthwhile and which are not.

Recommended books

Daniel Pink’s book A Whole New Mind has a good discussion of left-brain versus right-brain thinking. As he points out, the specialization between the left and right hemispheres of the brain is more complicated than once thought. However, the terms “left-brain” and “right-brain” are still useful metaphors even if they’re not precise neuroscience.

Also, to read more on how computers influence our thinking, see Andy Hunt’s book Pragmatic Thinking and Learning.

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Quote from Julian Barnes:

There is something infinitely touching when an artist, in old age, takes on simplicity. The artist is saying: display and bravura are tricks for the young, and yes, showing off is part of ambition; but now that we are old, let us have the confidence to speak simply.

HT: Signal vs. Noise

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I just finished reading Ken Robinson’s book The Element. The title comes from the idiom of someone being in his or her “element.” The book is filled with stories of people who have discovered and followed their passions.

Here are a couple quotes from the book regarding standardized education.

The fact is that given the challenges we face, education doesn’t need to be reformed — it needs to be transformed. The key to this transformation is not to standardize education but to personalize it, to build achievement on discovering the individual talents of each child, to put students in an environment where they want to learn and where they can naturally discover their true passions.

Learning happens in the minds and souls of individuals — not in the databases of multiple-choice tests. I doubt there are many children who leap out of bed in the morning wondering what they can do to raise the reading score for their state. Learning is a personal process …

Here is a talk Ken Robinson gave at TED in 2006 that led to his writing The Element. The video is entertaining as well as thought-provoking.

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I was reading a chapter from The Element this evening that reminded me of The Medici Effect.

ACM Ubiquity had an interview with Frans Johansson, author of The Medici Effect, around the time the book came out. The title comes from the idea that it takes more than just genius to create a Leonardo da Vinci. It also takes the community of a Renaissance Florence, made possible by patrons like the Medici family.

I thought it was a great premise for a book and bought the book shortly after reading the interview. Unfortunately, the book didn’t live up to my expectations. I recommend the interview, but I’m not as enthusiastic in my recommendation of the book.

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There was an odd story in NA Digest a couple days ago, John Francis of QR found. When I saw that someone was found, I assumed he had lost as in lost at sea, like Jim Gray. But that wasn’t the case.

John Francis developed the QR algorithm, an algorithm for finding the eigenvalues and eigenvectors of a matrix. Some experts regard the QR algorithm as one of the 10 most important numerical algorithms of the 20th century. He developed the algorithm in 1959 but then left the numerical analysis community three years later. The NA Digest article doesn’t say whether Francis became a recluse or simply moved on to a job outside mathematics. No one in numerical analysis knew anything about him until a couple folks tracked him down recently. He is doing well. He remembers his earlier work clearly but was unaware of the impact it had had.

Related post: Simple legacy (how people often underestimate the importance of their most useful work)

In what sense did Christopher Columbus discover America? Obviously he wasn’t the first human to step foot on the New World. Columbus wasn’t even the first European. Norwegian explorer Leif Erikson seems to have arrived 500 years before Columbus. But as Stephen Mills famously stated,

There have been other people before Columbus, but when Columbus discovered the New World, it stayed discovered.

The same principle could be used to resolve debates about priorities in mathematical discoveries.There is some debate over whether John Tukey or Carl Gauss discovered the Fast Fourier Transform (FFT). But there is no doubt that after Tukey discovered it, the FFT stayed discovered. The algorithm is now used in digital signal processing applications everywhere.

Gauss and Tukey were both brilliant mathematicians. Tukey, however, also had an aptitude for creating memorable names. For example, you may have heard of “software,” a term he coined.

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In the movie Redbelt, Chiwetel Ejiofor plays Mike Terry, a Jiu Jitsu instructor who will fight but will not compete. He will fight in a real fight if necessary, but he won’t fight in a ring because competitions have arbitrary rules. He is a skilled fighter because he is creative, and competitions take away that creativity. At one point in the movie, someone Terry if he teaches people to win. He says no, he teaches people to prevail. In his mind, you can’t “win” a fight. A fight is a problem to be solved.

Mike Terry’s distinction between fights and contests makes me think of the distinction between practical and academic problem solving. Practical problem solving does not have arbitrary constraints whereas academic problems often do: you can use this technique but not that one, you can use this reference but not that one, etc. These academic limitations serve a purpose in their context, but sometimes we can imagine these constraints are still on us after we leave the classroom.

Sometimes we’ll struggle mightily to solve a problem analytically that could be easily be solved numerically (or vice versa). Or we’ll imagine that a problem must be solved using a particular programming language even though it could be done more easily using a different language. It feels like “cheating” to go for the easier solution. But if you’re not in an academic setting, you can’t “cheat.” (Of course I’m not talking about violating ethical standards to solve a problem, only dismissing artificial restrictions. Where there is no law, there is no sin.)

There may be good reasons for pursuing the more difficult solution. For example, entertainment value. Sometimes we want to see whether we can do something the hard way. There’s nothing wrong with that, as long as we acknowledge that’s what we’re doing. But sometimes we do things the hard way for no good reason other than not having examined our self-imposed limitations. Maybe we’re trying to win rather than solve the problem.

I’m not saying entertainment value is the only reason to go down a more difficult road. Maybe you suspect there will be additional benefits if the more difficult approach succeeds. Again, that’s fine if this is a conscious decision and not a lack of creativity.

Related post: Try the simplest thing that could possibly work