As researcher Maksym Romensky writes on his blog, "A good test of how well we understand something is how well we can reproduce it on a computer." So since he and his colleagues study schooling and flocking behaviors of animals, they decided to try and create computer algorithms that convincingly recreated those movement patterns.
They chose fish schools as their subjects, Popular Science writes. Specifically, Pacific blue-eyes. They analyzed those animals' movements and wrote a computer program to simulate them as green dots. They then rendered the movements of real-life fish schools in the same green dots.
Determining which of those zippy dot groups represents the real school of fish proves to be exceedingly difficult. Fish experts, the researchers say, got an average of 4.5 out of 6 rounds correct. (But their performance improved over time.)
A Smithsonian reporter, on the other hand, got a measly 2 out of 6 correct.
The researchers invite you to test out your own fish-spotting skills for yourself—while also helping them to gather information to improve their model. "We think it will probably be pretty difficult for those that aren’t used to watching fish in the lab to tell the difference, but we’ll see," the team writes. "We are currently collecting data on how people visiting this site perform in the test."