In 2007, Chris Lintott, professor of astrophysics at Oxford University, embarked on a research project to classify the shapes of galaxies—a task that would tell him the history of how galaxies form. Lintott needed to sort images of more than a million galaxies into categories of ellipsoid, spiral, lenticular, irregular, etc., a pattern recognition task that, at the time, humans were better at than computers.
Curious as to how many could be classified through dedicated human brainpower, Lintott assigned a graduate student to the task. After several months and 50,000 images sorted, the grad student refused to continue (and who can blame him). Oxford University’s catalog of one million galaxy images was only 5% classified.
In desperation, Lintott turned to the public. He launched a website called Galaxy Zoo that called on anyone with an internet connection to help classify the trove of galaxy images. The public response was astounding: The website recorded 70,000 classifications per hour the first day. Not only were these thousands of nonscientists tackling the volume problem, collectively, they were accurate.
Today, Galaxy Zoo has expanded into Zooniverse, a site dedicated to citizen-science projects around the world. Right now, anyone with a smartphone and a 20-minute lunchbreak can volunteer to identify and count shark species in the waters around New Zealand, transcribe handwritten wills from the 16th Century, map communities of deep-sea coral, or search for pulsars. As of early April 2025, Zooniverse counted more than 2.8 million registered volunteers who have performed nearly 900 million classifications to date.
A lot has changed in the 20 years since Lintott launched Galaxy Zoo. Today’s artificial intelligence (AI), driven by deep learning, is now very good at routine classification tasks, and even finding anomalies. Worried that AI might replace citizen science—which feels precious and worth saving—I reached out to Lintott to ask his opinion. He doesn’t share my concern. “I think one of the interesting things we’re finding is that machines [now] do a good job of finding what’s unusual, but most unusual things are boring, such as a broken camera, a stray artifact, or light interference from a bright star,” he says, referring to aberrations that might be picked up by AI. “We still need people to tell us what’s interesting—and citizen scientists have always been good at telling us what to be distracted by.”
In this arena, human distractibility is a feature, not a bug. Take, for example, “Hanny’s Voorverp,” a blob of light Dutch school teacher Hanny van Arkel noticed below a spiral galaxy while classifying for Galaxy Zoo in 2007. It turned out to be the first observation of a previously theoretical phenomenon, and its discovery led to further studies.
Citizen observations are an atypical foundation of scientific discovery, but from unconventional sources can spring surprising results. This issue of Photonics Focus looks at unconventional sources, like those that make up the “standard candle,” which is a critical tool for measuring vast distances in space. We also learn how scientists developed an attosecond microscope with extraordinary temporal resolution that allows scientists to make video of light-matter interactions—a capability that could revolutionize the study of quantum phenomena. A third feature article explores quantum light sources that can produce on-demand single photons, the building blocks of quantum technologies.
In these pages, it’s clear that scientific advancements can spring from the most surprising and unconventional origins. Join us on a journey of the unexpected—we’re happy to distract you.
Gwen Weerts, Editor-in-chief
