A few days ago, sitting in my office, I contributed to peer-reviewed scientific research in biology, astronomy, and psychology. Even though I don’t hold degrees in any of these fields, my contributions will help advance science: I was doing real investigative work, not the prosaic replications of classic experiments that are typically taught in introductory lab courses. I was taking part in a blossoming “citizen science” movement occurring across a wide swath of scientific fields.
You might think astronomy would be one field where amateurs can’t contribute much to the state of knowledge. The most advanced telescopes cost hundreds of millions of dollars and have long waiting lists of eager professionals anxious to put them to use. How could an amateur scientist possibly help? While it is true an amateur isn’t likely to get time on a cutting-edge telescope, that doesn’t mean he or she can’t help analyze the torrents of data those telescopes produce.
The newly-launched site Zooniverse consolidates several massive projects, each of which engages the assistance of hundreds of thousands of volunteers worldwide. I logged in to one of its oldest projects, Galaxy Zoo, to give it a try.
Photo courtesy of Daniel Catt
Galaxy Zoo is an effort to classify about 250,000 galaxies that were imaged by the Sloan Digital Sky Survey over the past eight years. Once I created an account, I was immediately presented with a stunning image of a galaxy and asked to decide whether it was a “smooth” galaxy devoid of apparent structure or a “featured” galaxy with topological characteristics like spirals or bars. Having never done this, I wasn’t exactly sure how to proceed, but help pages were readily available. After checking the help page, I clicked “smooth.”
Next I was asked if the galaxy was round, cigar-shaped, or somewhere in between. I clicked “in between,” and the next screen asked if there was anything odd about this galaxy. Although it seemed odd indeed that I was being trusted to do this important work, I clicked “no” and moved on to the next galaxy. Within a few minutes, I had classified a half-dozen galaxies—not a bad contribution to science for someone whose only astronomical experience was an “intro to astrophysics” course taken over 20 years ago as a college freshman!
But how does a project like Galaxy Zoo ensure that participants aren’t taking shortcuts or fudging data? Alexander Bastidas Fry, a graduate student in astronomy at the University of Washington, explains how the site works on his blog The Astronomist. Since participants must register with the site, it’s possible to track their classifications and compare them to the work of others. Each galaxy is classified many times, and the work of long-established, accurate contributors is compared to newbies. Unreliable users’ classifications are weighted lower, while more consistent users earn a higher weight. The results are statistically more accurate than those obtained from professional astronomers—even though the experts in the field rarely use their limited time to classify a quarter-million galaxies.
Next I tried my hand at psychology. Project Implicit is an ongoing series of experiments into the nature of human bias, hosted by Harvard University but incorporating research from around the world. The idea behind these studies is that people won’t always overtly express their biases. For example, in most communities in the US it is socially unacceptable to be overtly racist. Even so, people often make negative assumptions about people based solely on perceived race. The implicit attitude test measures your reaction time as you categorize words, faces, or other stimuli. If you’re faster to categorize a certain-race face with negative words, then it stands to reason that you may be implicitly—even unconsciously—biased against that race, though you might never admit or realize it.
The experiment I tried concerned hypothetical races, “Niffian” and “Laapian,” and was conducted by Anna Newheiser of Yale University. I was immediately able to learn that I had a strong preference for one of these imaginary races. According to the website, this experiment may reveal more about how people respond to real races. Project Implicit has been responsible for dozens of research papers about bias, including this one discussed on my blog, about how children develop racial stereotypes.
Finally, I decided to give biology a whirl, using a game called “Foldit” (available from fold.it), which turns proteins of scientific interest into increasingly complex puzzles that players can solve. Huge, complicated proteins are the building blocks of life; scientists and medical researchers are increasingly looking to protein synthesis as a way to cure disease, scrub pollutants from the air or water, or create new biofuels. Users compete to predict the tertiary structure of such proteins—how a protein’s chemical makeup causes it to fold in on itself—in order to help scientists find new protein functions.
The game starts with simple puzzles that replicate the structure of proteins, but gradually gets more complex. Ultimately the researchers behind the project hope to show that humans playing these games are better than computer simulations at predicting the structure of proteins. I didn’t get very far in this game, however: As the proteins got more complex, the program became progressively less stable on my computer (a Mac). But thousands of users have downloaded the game and have already made real progress solving thorny biochemistry problems.
Citizen science doesn’t only happen in the online world. “Travis,” a graduate student at Carleton University, describes a study that recruited South African school children to capture and catalog over 150 different species of ants by setting traps near their schools and in more remote, undisturbed areas. They found more than twice the variety of ants in the undisturbed areas compared to their school area, making an important contribution to the knowledge of biodiversity in their region and also helping the students and their teachers understand the concrete impacts humans can have on an environment.
Citizen science isn’t just a public relations exercise: it makes a significant contribution to the corpus of scientific knowledge. Improved public awareness of science is an important additional benefit, but it’s not the primary goal of citizen science. Rather, this emerging technique allows scientists to make use of what is still the most powerful computational resource on the planet: the human brain. For more on citizen science, visit ResearchBlogging.org.
Originally published December 16, 2009