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.
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.
Greg Wilson pointed out an article on productivity by Jason Cohen that makes a lot of sense. Here’s a story that Jason tells to set up his point.
You get in your car at home and head out towards your mother’s house 60 miles away. … You hit traffic during the first half of the trip, so after 30 miles you’ve averaged only 30 miles per hour. Now the traffic opens up and you can go as fast as you want. The question is: How fast do you have to go during the second half of the trip such that you’ve averaged 60 mph over the entire trip?
The key is that you cannot go fast enough to make up for lost time. Your average will be less than 60 mph no matter how fast you go for the second half of the trip. His conclusion: “It’s amazing how periods of low velocity wash away gains of high velocity.” The title of his post is about how to double your productivity, but about one third of the article is devoted to explaining why even larger gains are not possible, i.e. his observation that unproductive periods limit potential productivity gains. As he explains, “the thing to do is eliminate the low-velocity stuff.”
The best way to be more productive may be to concentrate on “what” more than “how.” Concentrate on what to do, and more importantly, what not to do. There may be more to gain by adding to the “not to do” list than by being better at what’s on the “to do” list.
The latest EconTalk podcast is an interview with Brink Lindsey, author of The Age of Abundance. Lindsey said that in the 1980’s and 90’s we learned how to live with the freedoms gained in the 1960’s and 70’s. Many negative social indicators soared in the 60’s and 70’s: crime, divorce, drug use, abortion, etc. But during the 80’s and 90’s many of these indicators reversed direction, and Lindsey believes it is because many people have learned to replace legal and societal limits with chosen limits.
I don’t know whether I agree with Lindsey’s sweeping sociological analysis, but I do see some truth to it. I like his phrase “living within chosen limits.” I see a movement toward living within chosen limits on technology. The most obvious example may be Twitter. About 8,000,000 people at this point see some value in limiting their correspondence to 140 character messages. Some other ways I hear of people placing voluntary limits on their technology:
Unplugging from the Internet to work
Using terminal-style text editors to minimize distraction
Using browser-based applications with limited functionality to avoid installing software
Setting a five-sentence limit on email messages
Paper organizers, e.g. the Hipster PDA
I imagine the people who adopt these limitations will moderate their approach over time. Instead of unplugging from the Internet, they’ll make better use of it and become more disciplined. They may decide that some modern word processor features are worthwhile but still chose something more streamlined than Microsoft Word.
It may take a generation or more to learn how to take advantage of the new possibilities. We’re in a period of excess now, analogous to the culture of the 1960’s. It will be interesting to see what the analogy of the 80’s and 90’s will be.
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 “software,” a term he coined.
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.
I’ve added a plug-in that I’ve found handy on other sites. Now when you post a comment on a post, you have the option of being notified by email of future comments on that post.
Updated list of books mentioned here with links to the posts where each was mentioned
“Readability” is a bookmarklet from Arc90 for turning off all the clutter that surrounds the main text on a web page. I just installed it and played with it a little while. Looks promising.
Honey, it’s all been done before. Nothing’s really original. Not Homer or Shakespeare and certainly not you. Get over yourself.
Trying to be completely original is paralyzing, and not even possible. Only God creates ex nihilo. Everyone else starts with something. Don’t try to be God. Try to be Homer or Shakespeare.
A comment on Twitter this morning reminded me of a few points from Philip Tetlock’s book Expert Political Judgment.
Experts are under pressure to form opinions quickly so they can respond to interviewers.
You don’t get invited to appear on talk shows for having conventional opinions. An expert who, after long deliberation, decides things are going to continue the way they’ve been going is not likely to appear in the press.This causes a selection bias in the predictions that receive publicity. It also creates incentives for experts to make sensational predictions.
Experts have many facts to draw on, and so can be uncommonly good at confirming incorrect beliefs. Someone less knowledgeable might be forced to do some research.
Tetlock’s book focuses on political experts, though the same principles apply to other areas.
Why can’t we make more use of the 80/20 rule? I’ll review what the 80/20 rule is, explain how it can be powerful, then give four reasons why we don’t take advantage of it.
What is the 80/20 rule?
The 80/20 rule is amazing when you first learn about it. It says that efforts and results are often very unevenly distributed. You’ll get 80% of your results from the first 20% of your efforts. For example, maybe your top 20% of customers will provide 80% of your profit. Or when you’re debugging software, often 80% of the bugs will be in 20% of the code. Once you become aware of it, you’ll see 80/20 examples everywhere.
There’s nothing magical about the numbers 80 and 20. The general principle applies if 93% of your results come from 22% of your efforts. The numbers don’t have to add to 100. The principle is just that outcomes are unevenly distributed, more unevenly distributed than you may think.
Applying the 80/20 rule
Applications of the 80/20 rule are everywhere. For example, if you want to learn a foreign language, you don’t buy a dictionary and start learning words from page 1 and work your way to the end. Some words are used far more often than others. You’ll be able to use a language much sooner if you learn the vocabulary roughly in descending order of frequency.
Software optimizations can be extreme examples of an 80/20 rule. Sometimes 98% percent of a program’s time is being spent executing just five lines of code. Finding those five lines and tuning them is far more effective than randomly tweaking things here and there in hopes that the changes improve performance.
Why don’t we apply the 80/20 rule?
If the 80/20 rule is so powerful, why don’t we us it more often? Why don’t we concentrate our efforts where we’re likely to see the best results? Here are four reasons.
We don’t look for 80/20 payoffs. We don’t see 80/20 rules because we don’t think to look for them.
We’re not clear about criteria for success. You can’t concentrate your efforts on the 20% with the biggest returns until you’re clear on how you measure returns.
We’re unclear how inputs relate to outputs. It may be hard to know what the most productive activities are.
We enjoy less productive activities more than more productive ones. We concentrate on what’s fun rather than what’s effective.
If you address these issues in order, you might get stuck on the third one. It can be hard to know what is most productive. Our intuition in this area is usually wrong. For example, maybe the most effective thing to do is very simple, but we overlook it because we think the answer must be more complicated. Or maybe we confuse what we need to do with what we want to do. Collecting data is the best way to find out what really works. The results are usually surprising.
Sometimes the world changes and we’re stuck doing what used to be most effective. Some of the most persistent ideas about the “right” way to develop software come from studies of done forty years ago. It’s not enough to collect data one time.
Last night I listened to the latest FLOSS Weekly podcast, an interview with the creators of Processing. I’d heard of the Processing language before, but I thought it was some sort of ETL (extract, transform, and load) tool for data processing. Instead, it’s a Java-like language for artists. Here’s the description from the processing.org site.
Processing is an open source programming language and environment for people who want to program images, animation, and interactions. It is used by students, artists, designers, researchers, and hobbyists for learning, prototyping, and production. It is created to teach fundamentals of computer programming within a visual context and to serve as a software sketchbook and professional production tool.
