Those who haven’t toiled in the lab themselves may believe that our magnificent scientific method allows us to entertain new hypotheses, test them, and confirm or reject them. In reality, science is more whimsical, more prone to lapses in chance, influenced by too many factors for every result to be understandable and sensible. Science needs luck.
For example, take x-ray crystallography. (Please! Take it and assign it to an undergrad!) For those of you who aren’t familiar with x-ray crystallography, I’ll describe this horror show of a research field, which produces fascinating and useful data via tedium and—yes—blind luck.
If reports I’ve heard are true, in the 1970s somewhere between 104% and 109% of grant proposals were funded.
To figure out the structure of a protein, you shoot a laser beam, ideally while mimicking a cartoon laser sound, through a crystal of that protein and study the resulting light diffraction pattern. But first you need a protein crystal. Where does your protein crystal come from? It comes from a miserable graduate student who spent years optimizing crystal conditions—time, temperature, chemical concentrations—in the hopes of stumbling across the one magic combination that makes the fickle protein say, “Oh, hey, you know what the general atmosphere of this plastic well makes me want to do today? Crystalize, that’s what.”
I did crystallography for a while in my graduate lab. I spent hours pipetting, then more hours searching for crystals on my plate. The only good thing about it was that it made the rest of my fruitless research look valuable by comparison. Eventually I took the best approach to crystallography, which was to let the new postdoc do it, because the new postdoc was insane, which is to say he liked crystallography.
Even more than the tedium of setting up crystal trays, I hated the inescapable element of luck inherent in crystallography. This story may be apocryphal, but the crystallography-loving postdoc once told me about a lab in which one student—only one—was able to grow crystals, while everyone else floundered. The reason, it turned out, was beard dandruff. Little pieces of dead skin from this student’s beard apparently fell into his crystal trays, providing just the right impetus for seeding. “You know,” said the protein, “I’m just not feeling this today, and—HOLY CRAP IS THAT BEARD DANDRUFF? I FREAKING LOVE BEARD DANDRUFF! Here I go!”
- Which grad student joins your lab. The professor down the hall got Turbo the Tireless Grad Student, a whirlwind of productivity who churns out data, teaches your classes, and makes a mean mini-quiche platter for the lab’s holiday party. You got Sluggish Sam, the terminally nonsterile disaster whose messes you know you’ll be cleaning up for the next 12 years. Maybe you should assign Sam a crystallography project.
I felt the impact of luck, or lack thereof, during my first experiment ever. I was a summer intern at a pharmaceutical company, and I had a fairly simple cloning project. (I just noticed how scary that phrase—a fairly simple cloning project—might sound to nonscientists, like “a basic nuclear missile strike.”)
I was using a restriction enzyme that cut DNA in a certain place, but it required the addition of about 12 random nucleotides at one end of my primer. For those of you who are physicists, geologists, or other scientists who hate molecular biology—though those who hate it most are usually molecular biologists—I’ll simply say that I needed to pick some random letters, and the letters I happened to pick turned out to be bad letters. For those who love molecular biology—though those who love it most are typically postdocs who get to make someone else do it—I’ll say that I used two 6-nt AatII sites to constitute my random sequence, but the last three bases of one AatII site plus the first three bases of the other just happen to form a SalI site, and SalI just happened to be the enzyme I was using at the other end of my primer. In other words, there was a 1-in-several-thousand chance that I’d happen to pick a sequence that would screw up all of my experiments, and I did. Let’s just say it’s a good thing that no one expects much from summer interns.
We don’t have to like it, but luck is inevitable in science. Try one set of conditions, and your experiment works. Try another, and you’ve wasted time and shiny pennies. Get lucky and get famous, or at least get a job. Get unlucky and end up saying things like, “You know what’s always fascinated me more than science? The fine arts. Yeah, I think I’ll give those a try for a while.”
But there’s another kind of luck that influences science careers but isn’t intrinsic to science. It’s the long odds that come from large numbers—of job seekers, of grant seekers, of those hoping to publish in elite journals—and the impact those odds have on decision-making. As the number of entrants increases and the number of prizes doesn’t, the process becomes less deterministic—less merit-based—and more stochastic. Smaller and smaller percentages of applicants get tenure-track positions, get funded, get published—or get Turbo to join their labs. A system set up to be a meritocracy is starting to seem—to be—more of a gamble, and that can’t be good for science.
Instead of rising to the top, the cream sits in its little cream tray, waiting for a piece of beard dandruff to drift down and seed a cream crystal. If you needed proof that science is no longer a meritocracy, consider this: The finest scientific organization in the world is letting me publish a terrible metaphor like that one.