Group projects

The best teams have people with complementary skills, but similar work ethic. Academic assignments are the opposite. There’s not much variation in skills, in part because students haven’t yet developed specialized skills, and in part because students are in the same class because they have similar interests. The biggest variation is likely to be work ethic. It’s not uncommon for the hardest working person in a group to do 10x as much work as the laziest person in the group. The person doing most of the work learns that it’s best to avoid working with teams.

Working with people with complementary skills is a blast, but you’re unlike to experience that in an academic project. You might get some small degree specialization. Maybe one of the mechanical engineers on a project has more artistic ability than the other mechanical engineers, for example. But this is hardly like the experience of working with a team of people who are all great at different things.

 

Grateful for failures

I’ve been thinking lately about different things I’ve tried that didn’t work out and how grateful I am that they did not.

The first one that comes to mind is my academic career. If I’d been more successful with grants and publications as a postdoc, it would have been harder to decide to leave academia. I’m glad I left when I did.

When I was in high school I was a fairly good musician. At one point decided that if I made the all state band I would major in music. Thank God I didn’t make it.

I’ve looked back at projects that I hoped to get, and then realized how it’s a good thing that they didn’t come through.

In each of these examples, I’ve been forced to turn away from something I was moderately good at to pursue something that’s a better fit for me.

I wonder what failure I’ll be grateful for next.

 

How about one good one?

I’m no fan of tobacco companies or their advertising tactics, but I liked the following story.

When the head of a mammoth [advertising] agency solicited the Camel Cigarette account, he promised to assign thirty copywriters to it, but the canny head of R. J. Reynolds replied, “How about one good one?” Then he gave his account to a young copywriter called Bill Esty, in whose agency it has remained for twenty-eight years.

One really good person can accomplish more than thirty who aren’t so good, especially in creative work.

Source: Confessions of an Advertising Man

Well, F = ma.

Three or four very short stories on the difficulty of learning to use simple things. Depends whether you count the last section as a story.

* * *

When I was taking freshman physics and we were stuck on a problem, the professor would say “Well, F = ma.”

True, but absolutely useless. Yes, we know that F = ma. (Force equals mass times acceleration.) Nobody thought “Oh, that’s it. I was thinking F = ma2. That explains everything.” Newton’s laws are simple (in a sense) but subtle to apply. The difficult part isn’t the abstract principles but their application to concrete problems.

* * *

The heart of Bayesian statistics is not much more complicated than F = ma. Its the statement that

posterior ∝ likelihood × prior.

It takes a few years to learn how to apply that equation well. And when people try to help, their advice sounds about as useless as “Well, F = ma.”

* * *

Learning to use Unix was hard. When I asked for help getting started, a lab assistant said “Go read the man pages.” That’s about as hostile as saying “Want to learn English? Read a dictionary.” Fortunately I knew other people who were helpful. One of them told me about the book.

But still, it took a while to get the gestalt of Unix. I knew how to use a handful of utilities, and kept thinking everything would be fine once I knew maybe 10x as many utilities. Then one day I was talking with a friend who seemed fluent working with Unix. I asked him how he did a few things and realized he used the same tools I did, but used them better. It was almost as if he’d said “I just use F = ma” except when he said it things clicked.

* * *

The motivation for this post, the thing that brought these stories to mind, was listening to a podcast. The show had some good advice, things that I know I need to do, but nothing I hadn’t heard many times before. The hard part is working out what the particulars mean for me personally.

It often takes someone else to help us see what’s right in front of us. I’m grateful for the people who have helped me work out the particulars of things I was convinced of but couldn’t see how to apply. Sometimes I have the pleasure of being able to do that for someone else.

If it were easy …

“If it were easy, someone would have done it.” Maybe not.

Maybe the thing is indeed easy, and has been done before. Then someone was the first to do it. The warning that it had been done before didn’t apply to this person, even though it would apply to the subsequent people with the same idea.

This reminds me of the story of two economists walking down the street. They notice a $20 bill on the sidewalk and the first asks “Aren’t you going to pick it up?” The second replies “No, it’s not really there. If it were, someone would have picked it up by now.”

Sometimes a solution is easy, but nobody has had the audacity to try it. Or maybe circumstances have changed so that something is easy now that hasn’t been before.

Sometimes a solution is easy for you, if not for many others. See how much less credible the opening sentence sounds with for you inserted: “If it were easy for you, someone would have done it.”

Structure in jazz and math

Last night I went to a concert by the Branford Marsalis Quartet. One of the things that impressed me about the quartet was how creative they are while also being squarely within a tradition. People who are not familiar with jazz may not realize how structured it is and how much it respects tradition. The spontaneous and creative aspects of jazz are more obvious than the structure. In some ways jazz is more tightly structured than classical music. To use Francis Schaeffer’s phrase, there is form and freedom, freedom within form.

Every field has its own structure, its tropes, its traditions. Someone unfamiliar with the field can be overwhelmed, not having the framework that an insider has to understand things. They may think something is completely original when in fact the original portion is small.

In college I used to browse the journals in the math library and be completely overwhelmed. I didn’t learn until later that usually very little in a journal article is original, and even the original part isn’t that original. There’s a typical structure for a paper in PDEs, for example, just as there are typical structures for romantic comedies, symphonies, or space operas. A paper in partial differential equations might look like this:

  1. Motivation / previous work
  2. Weak formulation of PDE
  3. Craft function spaces and PDE as operator
  4. A priori estimates imply operator properties
  5. Well posedness results
  6. Regularity

An expert knows these structures. They know what’s boilerplate, what’s new, and just how new the new part is. When I wrote something up for my PhD advisor I remember him saying “You know what I find most interesting?” and pointing to one inequality. The part he found interesting, the only part he found interesting, was not that special from my perspective. It was all hard work for me, but only one part of it stood out as slightly original to him. An expert in partial differential equations sees a PDE paper the way a professional musician listens to another or the way a chess master sees a chess board.

While a math journal article may look totally incomprehensible, an expert in that specialization might see 10% of it as somewhat new. An interesting contrast to this is the “abc conjecture.” Three and a half years ago Shinichi Mochizuki proposed a proof of this conjecture. But his approach is so entirely idiosyncratic that nobody has been able to understand it. Even after a recent conference held for the sole purpose of penetrating this proof, nobody but Mochizuki really understands it. So even though most original research is not that original, once in a while something really new comes out.

Related:

Get rid of something every Thursday

I heard of someone who had a commitment to get rid of something every Thursday. I don’t know anything about how they carried that out. It could mean throwing out or donating to charity a physical object each Thursday. Or maybe it could be handing over a responsibility or letting go of an ambition. It could be a combination, such as getting rid of an object that is a reminder of something intangible that you want to let go of.

This may mean reducing your total inventory of objects or obligations, or it could be simply turnover, making room for new things.

Getting rid of an obligation is not necessarily irresponsible, nor is letting go of an ambition necessarily lazy. Letting go of one obligation to take on another could be very responsible. Letting go of one ambition to pursue another could be a lot of work.

Related posts:

Retooling

I was listening to a classic music station yesterday, and I heard the story of a professional pianist whose hand was injured in an accident. He then started learning trumpet and two years later he was a professional trumpeter. I didn’t catch the musician’s name.

I was not surprised that a professional in one instrument could become a professional in another, but I was surprised that he did it in only two years. It probably helped that he was no longer able to play piano; I imagine if he wanted to learn trumpet in addition to piano he would not have become so proficient so quickly.

If you go by the rule of thumb that it takes about 10 years to master anything, this professional pianist was 80% of the way to becoming a professional trumpeter before he touched a trumpet. Or to put it another way, 80% of being a professional musician who plays trumpet is becoming a professional musician.

Transferable skills are more difficult to acquire and more valuable than the context in which they’re exercised.

Related posts:

Taking away a damaging tool

This is a post about letting go of something you think you need. It starts with an illustration from programming, but it’s not about programming.

Bob Martin published a dialog yesterday about the origin of structured programming, the idea that programs should not be written with goto statements but should use less powerful, more specialized ways to transfer control. Edsgar Dijkstra championed this idea, most famously in his letter Go-to statement considered harmful. Since then there have been countless “considered harmful” articles that humorously allude to Dijkstra’s letter.

Toward the end of the dialog, Uncle Bob’s interlocutor says “Hurray for Dijkstra” for inventing the new technology of structured programming. Uncle Bob corrects him

New Technology? No, no, you misunderstand. … He didn’t invent anything. What he did was to identify something we shouldn’t do. That’s not a technology. That’s a discipline.

        Huh? I thought Structured Programming made things better.

Oh, it did. But not by giving us some new tools or technologies. It made things better by taking away a damaging tool.

The money quote is the last line above: It made things better by taking away a damaging tool.

Creating new tools gets far more attention than removing old tools. How might we be better off by letting go of a tool? When our first impulse is that we need a new technology, might we need a new discipline instead?

Few people have ever been able to convince an entire profession to let go of a tool they assumed was essential. If we’re to have any impact, most of us will need to aim much, much lower. It’s enough to improve our personal productivity and possibly that of a few peers. Maybe you personally would be better off without something that is beneficial to most people.

What are some technologies you’ve found that you’re better off not using?

Related posts:

The Mozart Myth

I don’t know how many times I’ve heard about how Mozart would compose entire musical scores in his head and only write them down once they were finished. Even authors who stress that creativity requires false starts and hard work have said that Mozart may have been an exception. But maybe he wasn’t.

In his new book How to Fly a Horse, Kevin Ashton says that the Mozart story above is a myth based on a forged letter. According to Ashton,

Mozart’s real letters—to his father, to his sister, and to others—reveal his true creative process. He was exceptionally talented, but he did not write by magic. He sketched his compositions, revised them, and sometimes got stuck. He could not work without a piano or harpsichord. He would set work aside and return to it later. … Masterpieces did not come to him complete in uninterrupted streams of imagination, nor without an instrument, nor did he write them whole and unchanged. The letter is not only forged, it is false.

Related posts:

 

Looking ten years ahead

From Freeman Dyson:

Economic forecasting is useful for predicting the future up to about ten years ahead. Beyond ten years the quantitative changes which the forecast accesses are usually sidetracked or made irrelevant by qualitative changes in the rules of the game. Qualitative changes are produced by human cleverness … or by human stupidity … Neither cleverness nor stupidity are predictable.

Source: Infinite in All Directions, Chapter 10, Engineers’ Dreams.

Confidence

Zig Ziglar said that if you increase your confidence, you increase your competence. I think that’s generally true. Of course you could be an idiot and become a more confident idiot. In that case confidence just makes things worse [1]. But otherwise when you have more confidence, you explore more options, and in effect become more competent.

There are some things you may need to learn not for the content itself but for the confidence boost. Maybe you need to learn them so you can confidently say you didn’t need to. Also, some things you need to learn before you can see uses for them. (More on that theme here.)

I’ve learned several things backward in the sense of learning the advanced material before the elementary. For example, I studied PDEs in graduate school before having mastered the typical undergraduate differential equation curriculum. That nagged at me. I kept thinking I might find some use for the undergrad tricks. When I had a chance to teach the undergrad course a couple times, I increased my confidence. I also convinced myself that I didn’t need that material after all.

My experience with statistics was similar. I was writing research articles in statistics before I learned some of the introductory material. Once again the opportunity to teach the introductory material increased my confidence. The material wasn’t particularly useful, but the experience of having taught it was.

Related post: Psychological encapsulation


[1] See Yeats’ poem The Second Coming:

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

 

Prevent errors or fix errors

The other day I was driving by our veterinarian’s office and saw that the marquee said something like “Prevention is less expensive than treatment.” That’s sometimes true, but certainly not always.

This evening I ran across a couple lines from Ed Catmull that are more accurate than the vet’s quote.

Do not fall for the illusion that by preventing errors, you won’t have errors to fix. The truth is, the cost of preventing errors is often far greater than the cost of fixing them.

From Creativity, Inc.

What would Donald Knuth do?

I’ve seen exhortations to think like Leonardo da Vinci or Albert Einstein, but these leave me cold. I can’t imagine thinking like either of these men. But here are a few famous people I could imagine emulating when trying to solve a problem

What would Donald Knuth do? Do a depth-first search on all technologies that might be relevant, and write a series of large, beautiful, well-written books about it all.

What would Alexander Grothendieck do? Develop a new field of mathematics that solves the problem as a trivial special case.

What would Richard Stallman do? Create a text editor so powerful that, although it doesn’t solve your problem, it does allow you to solve your problem by writing a macro and a few lines of Lisp.

What would Larry Wall do? Bang randomly on the keyboard and save the results to a file. Then write a language in which the file is a program that solves your problem.

What would you add to the list?

 

Sometimes definitions are enough

Sometimes you can apply math just by raiding it for vocabulary. You may not need to apply a single theorem.

This has been a surprise to me. I’m more used to creating a mathematical model so you can compute something or apply some theorem. But sometimes you can move a project along just by providing a name for a concept. A meandering discussion can snap into focus because someone has a name for an idea everyone vaguely understands.

Sometimes it may be clear that only part of a mathematical definition applies. In this case math can guide the discussion by asking whether the rest of the definition applies. “It sounds like we’ve got a widget here. A widget has to have these five properties and clearly we have the first three. Let’s think about whether the last two hold.” The answers don’t have to be positive to be useful. You might realize something important in the process of explaining why your thing is not a widget.

Sometimes a definition may not apply at all and still be useful! “This reminds me of a widget. It’s not a widget in any strict sense. But if it were, this is what we’d do next. I wonder whether we can do something like that.”