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By Seth Roberts | June 26th 2008 08:57 AM | 7 comments | Print | E-mail | Track Comments
About Seth

I am a professor of psychology at UC Berkeley and author of View Seth's Profile
A friend wonders what I think about this editorial by Chris Anderson, the editor of Wired. Anderson says “faced with massive data, this approach to science — hypothesize, model, test — is becoming obsolete.”

Anderson confuses statistical models with scientific ones. As far as the content goes, I’m completely unconvinced. Anderson gives no examples of this approach to science being replaced by something else.

For me, the larger lesson of the editorial is how different science is from engineering. Wired is mainly about engineering. I’m pretty sure Anderson has some grasp of the subject. Yet this editorial, which reads like something a humanities professor would write, shows that his understanding doesn’t extend to science. It reminds me why I didn’t want to be a doctor (which is like being an engineer.)

It seemed to me that a doctor’s world is too constrained: You deal with similar problems over and over. I wanted more uncertainty, a bigger canvas. That larger canvas came along when I tried to figure out why I was waking up too early. Rather than being like engineering (applying what we already know), this was true science: I had no idea what the answer was. There was a very wide range of possibilities.

Science and engineering are two ends of a dimension of problem-solving. The more you have an idea what the answer will be, the more it is like engineering. The wider the range of possible answers, the more it is like science. Making a living requires a steady income: much more compatible with engineering than science. I like to think my self-experimentation has a kind of wild flavor which is the flavor of “raw” science, whereas the science most people are familiar with is “pasteurized” science — science tamed, made more certain, more ritualistic, so as to make it more compatible with making a living.

Sequencing genes, for example, is pasteurized science. Taking an MRI of the brain while subjects do this or that task is pasteurized science. Pasteurized science is full of rituals and overstatements (e.g., “correlation does not equal causation”, “the plural of anecdote is not data”) that reduce unpleasant uncertainty, just as pasteurization does. Pasteurized science is more confusable with engineering.

There’s one way in which Anderson is right about the effects of more data. It has nothing to do with the difference between petrabytes and gigabytes (which is what Anderson emphasizes), but it is something that having a lot more data enables: Making pictures. When you can make a picture with your data, it becomes a lot easier to see interesting patterns in it.

Andrew Gelman’s take

Comments

I agree. It's funny, I blogged about this very topic this morning, saying the unstated distinction was between engineering and science:

http://www.journalscape.com/derekjames/2008-06-26-09:32/

Although I didn't put it in terms of the size of the canvas, but in the goals of the engineer (a workable product) vs. the goals of the scientist (an explanation of natural phenomena that generates testable predictions).

The problem with Robert's post and Anderson's article is that both somehow treat engineering and science (in their entirety) as being different from one another. Engineering exist because of science, science can and often advances because of engineering, somehow I do not see the difference between the two (except perhaps the end result but even that is not always the case). Anderson wrote a horrible article about a subject he understands little about, Robert's took the bait and responded emotionally, therefore giving credibility to what Anderson said. Attempting to pass Google off as a model for the sciences would leave us a day late and dollar short, not to mention up to our eyeballs in advertisements (think revenues not science). I am an environmental engineer, but the difference between myself and Anderson is that my field depends directly on the scientific method to solve varying problems from chemistry to biology (and even I know this can not be done by applying a simple algorithm to search for correlations), we still need to know the mechanism not just if it works. Imagine if I designed a new water treatment plant that employed a coagulant that was created based on simple data set correlations and the end result was a public sick from the water supply. Robert's, may I suggest, in the future there is no need to respond to the pop tart junk science opinions presented in Wired magazine (it's not peer reviewed and has to concern itself with sales!) not to mention it rarely presents an opposing view in the same article.

Just read 'self-experimentation and the generation of new ideas'

does this guy really run t-tests on self-experimental data? n=1?

see 'the cult of significance'

T Ryan Gregory's picture
Pasteurized science is full of rituals and overstatements (e.g., “correlation does not equal causation”, “the plural of anecdote is not data”) that reduce unpleasant uncertainty, just as pasteurization does.

Okay, so...

1) Correlation *does* equal causation?

2) The plural of anecdote *is* data?

I just like this phrase

"The more you have an idea what the answer will be, the more it is like engineering. The wider the range of possible answers, the more it is like science. "

Does this sound engineering and science are corelated?
for me obviously.

I am both an engineer and a scientist. You should ask me!

i still dont understand it..........

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