“The millions of photos uploaded to social media are a massive untapped resource for studying humanity. But machine learning is beginning to tap this mother lode. “Imagine a future anthropologist with access to trillions of photos of people—taken over centuries and across the world—and equipped with effective tools for analyzing these photos to derive insights. What kinds of new questions can be answered?” This is the dream that has inspired Kevin Matzen, Kavita Bala, and Noah Snavely at Cornell University in Ithaca, New York. Their thinking is that the millions of photos uploaded each day to social media provide a fascinating window into the cultural, social, and economic factors that shape societies around the world. With powerful enough machine intelligence, they say, it ought to be possible to mine this mother lode of data for deep insights into our civilization. As luck would have it, this kind of machine intelligence is currently emerging at breakneck speed. And Matzen and co have put it to work studying 100 million photos posted on Instagram. The question these guys specifically want to answer was how clothing styles vary around the world, a cultural phenomenon that is otherwise difficult to study on this scale. For example, their approach can tackle questions such as how the frequency of scarf use in the U.S. is changing over time, what styles are most specific to particular regions or cities, and, conversely, which styles are popular across the world. To find out, Matzen and co turned to Instagram, which allowed them to download images within five kilometers of a specific location and within five days of a specific date. The team then identified 44 cities to study and downloaded a total of 100 million images from these locations in five-day windows between June 2013 and June 2016.”