With AI watching, clues to why neighborhoods flourish or fail

If residents of Brooklyn's Prospect Heights neighborhood have a feeling their streets have gotten safer over the past decade, while residents of the Hillcrest area of Washington, D.C., feel less secure on several of their blocks, artificial intelligence has now delivered proof that their hunches are correct. Using a new machine-learning algorithm they developed, researchers at Harvard and MIT combine photos from Google's Street View service with human perceptions of a street's safety to score whether a city block has improved or declined over time. The computer scientists and economists want their project, called Streetchange, to give urban planners artificial intelligence tools to help guide their thinking about evolving urban landscapes. Given the demographic trends researchers foresee, policymakers will need all the help they can get: By 2050, over two-thirds of the world's population is expected to live in urban areas. As that dramatic shift remakes society, it's more critical than ever for urban planners to understand the impact and implications of that transformation.