As a graduate student 20 years ago, urban studies professor Carlo Ratti, the director of the Senseable City Laboratory, realized that the route he instinctively took when he walked to his office was not the same one he took home. A new study may explain why: our brains are seemingly optimized to calculate not the shortest path to our destination but what he and his colleagues call the “pointiest” path—the one that allows us to face it most directly.

The MIT study was based on anon­ymized GPS signals from cell phones of pedestrians as they walked through Boston and Cambridge. But the strategy, known as vector-based navigation, has also been seen in studies of animals, from insects to primates. This type of navigation is very different from the algorithms used by a smartphone or GPS device, which can calculate the shortest route between any two points nearly flawlessly from the maps stored in memory. 

“Thinking in terms of points of reference, landmarks, and angles is a very natural way to build algorithms for mapping and navigating space based on what you learn from your own experience moving around in the world,” says coauthor Joshua Tenenbaum, a professor of computational cognitive science. The MIT team suggests that vector-based navigation, which requires less brainpower than actually calculating the shortest route, may have evolved to let the brain devote more resources to other tasks.

“There appears to be a trade-off that allows computational power in our brain to be used for other things—30,000 years ago to avoid a lion, or now to avoid a perilous SUV,” says Ratti. “Vector-based navigation does not produce the shortest path, but it’s close enough to the shortest path, and it’s very simple to compute it.”

He adds: “As smartphones and portable electronics increasingly couple human and artificial intelligence, it is becoming increasingly important to better understand the computational mechanisms used by our brain and how they relate to those used by machines.”