Science

There’s a major divide between the way scientists and programmers view the software they write.

Scientists see their software as a kind of exoskeleton, an extension of themselves. Think Dr. Octopus. The software may do heavy lifting, but the scientists remain actively involved in its use. The software is a tool, not a self-contained product.

Programmers see their software as something they will hand over to someone else, more like building a robot than an exoskeleton. Programmers believe it’s their job to encapsulate intelligence in software. If users have to depend on programmers after the software is written, the programmers didn’t finish their job.

I work with scientists and programmers, often bridging the gaps between the two cultures. One point of tension is defining when a project is done. To a scientist, the software is done when they get what they want out of it, such as a table of numbers for a paper. Professional programmers give more thought to reproducibility, maintainability, and correctness. Scientists think programmers are anal retentive. Programmers think scientists are cowboys.

Programmers need to understand that sometimes a program really only needs to run once, on one set of input, with expert supervision. Scientists need to understand that prototype code may need a complete rewrite before it can be used in production.

The real tension comes when a piece of research software is suddenly expected to be ready for production. The scientist will say “the code has already been written” and can’t imagine it would take much work, if any, to prepare the software for its new responsibilities. They don’t understand how hard it is for an engineer to turn an exoskeleton into a self-sufficient robot.

Related posts:

Good, fast, cheap: Can you really pick two?
Buggy code is biased code

From astrophysicist Neil deGrasse Tyson:

The US bank bailout exceeded the half-century lifetime budget of NASA.

Source

Other NASA-related posts:

After two days, I’d turned into an idiot
Good enough for Google and NASA
Team Moon

I recently received review copies of the Manga Guides to physics and the universe. These made a better impression than the relativity guide that I reviewed earlier. The guide to physics has been out for a while. The guide to the universe comes out June 24.

The Manga Guide to Physics basically covers force, momentum, and energy. The pace is leisurely. There’s not much back story; it cuts to the chase fairly quickly.This guide will not prepare you to solve physics problems, but it does give you a good overview of the basics.

(These books are not entirely manga; all three books I’ve seen in the series have several pages of more traditional textbook content.)

The Manga Guide to the Universe gives a tour of cosmology from the geocentric view to current theories. It contains some very recent material, such as references to the WMAP project.

This book is more rushed than the physics guide. That’s to be expected considering its ambitious scope. It devotes a fairly large amount of space to the back story and this contributes to the book being rushed.

I mentioned in my review of The Manga Guide to Relativity that although Americans associate cartoons with children, that book was not written for children. The physics guide, however, would be appropriate for a wide range of readers. Young readers may not fully appreciate the content, but they would not find anything offensive.

The Manga Guide to the Universe is inoffensive with one exception. There are a couple provocative frames in the prologue that will keep the book off some school library shelves.

From Nobel physicist Paul Dirac:

I understand what an equation means if I have a way of figuring out the characteristics of its solution without actually solving it.

According to Richard Feynman, the most important event of the 19th century was the discovery of the laws of electricity and magnetism.

From a long view of the history of mankind — seen from, say, ten thousand years from now — there can be little doubt that the most significant event of the 19th century will be judged as Maxwell’s discovery of the laws of electrodynamics. The American Civil War will pale into provincial insignificance in comparison with this important scientific event of the same decade.

From The Feynman Lectures on Physics, Volume 2.

Related post:

Grand unified theory of 19th century math

A few days ago I got a review copy of The Manga Guide to Relativity. This is an English translation of a book first published in Japanese a couple years ago.

I assume the intended audience, at least for the original Japanese edition, is familiar with manga and wants to learn about relativity. I came from the opposite perspective, more familiar with relativity than manga, so I paid more attention to the background than the foreground. My experience was more like reading The Relativity Guide to Manga.

I expected The Manga Guide to Relativity to be something like The Cartoon Guide to Genetics. However, the former has much less scientific content than the latter. A fair amount of the relativity book is background story, and the substantial parts are repetitive. As I recall, the genetics book was much more dense with information, though presented humorously.

Some parents and teachers will buy The Manga Guide to Relativity to introduce children to science in an entertaining genre. These folks may be surprised to discover the sexual undertones in the book. Americans typically equate comics with children, but the book was originally written for a Japanese audience that does not have the same view.

Donald Knuth explains how he combines theory and practice:

This has always been the main credo of my professional life. I have always tried to develop theories that shed light on the practical things I do, and I’ve always tried to do a variety of practical things so that I have a better chance of discovering rich and interesting theories. It seems to me that my chosen field, computer science — information processing — is a field where theory and practice come together more than in any other discipline, because of the nature of computing machines. …

History teaches us that the greatest mathematicians of past centuries combined theory and practice in their own careers. …

The best theory is inspired by practice. The best practice is inspired by theory.

Taken from Selected Papers on Computer Science.

Related post:

Works in the field, not in the lab
Works well versus well understood

From The Number Mysteries:

Some of the deadliest viruses in the biological books — from influenza to herpes, from polio to the AIDS virus — are constructed using the shape of an icosahedron.

An icosahedron is a regular solid with 20 triangular faces.

In case you’re curious, here’s how I make the icosahedron image.

This weekend I’ve been wrapping up unfinished projects. One of those projects was reading Kraken: The Curious, Exciting, and Slightly Disturbing Science of Squid.

The book is exactly what you might expect from the title: a quirky little book about squid. I didn’t particularly enjoy it, but that’s my fault. I just wasn’t as interested in reading a quirky little book about squid as I thought I would when the publisher offered me a copy. Squid are bizarre creatures, and some other time I might enjoy reading more about them.

The title is terrific. I probably wouldn’t have given the book a second thought if it had been entitled, for example, Teuthology. And the title isn’t just sensational; squid really are curious, possibly exciting, and at least slightly disturbing.

Computer scientist Matt Welsh said that one reason he left Harvard for Google was that he was spending 40% of his time chasing grants. At Google, he devotes all his time to doing computer science. Here’s how he describes it in his blog post The Secret Lives of Professors:

The biggest surprise is how much time I have to spend getting funding for my research. Although it varies a lot, I guess that I spent about 40% of my time chasing after funding, either directly (writing grant proposals) or indirectly (visiting companies, giving talks, building relationships). It is a huge investment of time that does not always contribute directly to your research agenda — just something you have to do to keep the wheels turning.

According to this Scientific American editorial, 40% is typical.

Most scientists finance their laboratories (and often even their own salaries) by applying to government agencies and private foundations for grants. The process has become a major time sink. In 2007 a U.S. government study found that university faculty members spend about 40 percent of their research time navigating the bureaucratic labyrinth, and the situation is no better in Europe.

Not only do scientists on average spend a large amount of time pursuing grants, they tend to spend more time on grants as their career advances. (This has an element of tautology: you advance your career in part by obtaining grants, so the most successful are the ones who have secured the most grant money.)

By the time scientists are famous, they may no longer spend much time actually doing science. They may spend nearly all their research time chasing grants either directly or, as Matt Welsh describes, indirectly by traveling, speaking, and schmoozing.

Here’s a little saying that irritates me:

Absence of evidence is not evidence of absence.

It’s the kind of thing a Sherlock Holmes-like character might say in a detective novel. The idea is that we can’t be sure something doesn’t exist just because we haven’t seen it yet.

What bothers me is that the statement misuses the word “evidence.” The statement would be correct if we substituted “proof” for “evidence.” We can’t conclude with absolute certainty that something doesn’t exist just because we haven’t yet proved that it does. But evidence is not the same as proof.

Why do we believe that dodo birds are extinct? Because no one has seen one in three centuries. That is, there is an absence of evidence that they exist. That is tantamount to evidence that they do not exist. It’s logically possible that a dodo bird is alive and well somewhere, but there is overwhelming evidence to suggest this is not the case.

Evidence can lead to the wrong conclusion. Why did scientists believe that the coelacanth was extinct? Because no one had seen one except in fossils. The species was believed to have gone extinct 65 million years ago. But in 1938 a fisherman caught one. Absence of evidence is not proof of absence.

Though it is not proof, absence of evidence is unusually strong evidence due to subtle statistical result. Compare the following two scenarios.

Scenario 1: You’ve sequenced the DNA of a large number prostate tumors and found that not one had a particular genetic mutation. How confident can you be that prostate tumors never have this mutation?

Scenario 2: You’ve found that 40% of prostate tumors in your sample have a particular mutation. How confident can you be that 40% of all prostate tumors have this mutation?

It turns out you can have more confidence in the first scenario than the second. If you’ve tested N subjects and not found the mutation, the length of your confidence interval around zero is proportional to N. But if you’ve tested N subjects and found the mutation in 40% of subjects, the length of your confidence interval around 0.40 is proportional to √N. So, for example, if N = 10,000 then the former interval has length on the order of 1/10,000 while the latter interval has length on the order of 1/100. This is known as the rule of three. You can find both a frequentist and a Bayesian justification of the rule here.

Absence of evidence is unusually strong evidence that something is at least rare, though it’s not proof. Sometimes you catch a coelacanth.

Related posts:

Estimating the chances of something that hasn’t happened
Complementary validation

For most of history, scientists have been called natural philosophers. You might expect that scientist gradually and imperceptibly replaced natural philosopher over time. Surprisingly, it’s possible pinpoint exactly when and where the term scientist was born.

It was June 24, 1835 at a meeting of the British Association for the Advancement of Science. Romantic poet Samuel Taylor Coleridge was in attendance. (He had previously written about the scientific method.) Coleridge declared that although he was a true philosopher, the term philosopher should not be applied to the association’s members. William Whewell responded by coining the word scientist on the spot. He suggested

by analogy with artist, we may form scientist.

Since those who practice art are called artists, those who practice science should be called scientists.

This story is comes from the prologue of Laura Snyder’s new book The Philosophical Breakfast Club. The subtitle is “Four Remarkable Friends Who Transformed Science and Changed the World.” William Whewell was one of these four friends. The others were John Herschel, Richard Jones, and Charles Babbage.

Update 1: Will Fitzgerald created the following Google Books ngram that suggests that scientist was used occasionally before 1835 and would take another 30 years to start being widely used in books. Click on the image to visit the original ngram.

So it is with many innovations: the person credited with the innovation may not have been entirely original or immediately successful. Still, perhaps Whewell’s public confrontation with Coleridge gave scientist a push on the road to acceptance.

Update 2: Pat Ballew fills in more of the story on his blog including editorial opposition to the term scientist. Pat brings more famous people into the story, including H. L. Mencken, Michael Faraday, and William Cullen Bryant.

Update 3: Here’s an excerpt from The Philosophical Breakfast Club.

More 19th century science:

Why Mr. Scott is Scottish
Victorian method for predicting height
Grand unified theory of 19th century math

Bradley Efron says that science is moving away from things like predicting sunrise times and toward predicting things like the weather. The trend is away from studying precisely predictable systems, what Efron calls “hard-edged science,” and toward studying systems “where predictability is tempered by a heavy dose of randomness.”

Hard-edged science still dominates public perceptions, but the attention of modern scientists has swung heavily toward rainfall-like subjects, the kind where random behavior plays a major role. … Deterministic Newtonian science is majestic, and the basis of modern science too, but a few hundred years of it pretty much exhausted nature’s storehouse of precisely predictable events. Subjects like biology, medicine, and economics require a more flexible scientific world view, the kind we statisticians are trained to understand.

Certainly there is increased interest in systems containing “a heavy dose of randomness” but can we really say that we have “pretty much exhausted nature’s storehouse of precisely predictable effects”?

Source: Modern Science and the Bayesian-Frequentist Controversy

Related posts:

Scientific results fading over time
Occam’s razor and Bayes’ theorem
The law of medium numbers

My daughter and I were going over science homework this evening. A ball falls for 10 seconds. What is its final velocity?

JC: So how fast is the ball going when it hits the ground?

RC: Zero. It stops before it bounces back up.

JC: Well, how fast is it going just before it hits the ground?

RC: They didn’t ask the almost final velocity. They asked for the final velocity.