Google Street View's Window into How Americans Vote (Look at the Cars)

Led by Fei-Fei Li, the director of the Stanford University artificial intelligence lab and a newly minted Google employee, a team of academics recently explored a new way of tracking socioeconomic trends across the US. Rather than knocking on doors and asking questions, they pulled more than 50 million photos from Google Street View and fed them into neural networks. Simply by identifying the make, model, and year of automobiles appearing in the photos, the researchers said, their tech could accurately estimate the income, race, education, and voting patterns of citizens in particular precincts. If the number of sedans on a short stretch of road exceeded the number pickup trucks, for instance, they found that a city was 88 percent likely to vote for a Democrat during the next presidential election. If pickups exceeded sedans, a city was 82 percent likely vote Republican.