These days, our artificial ears and eyes are better than ever—and more ubiquitous than ever. A business recently profiled by the New York Times seems to embody both what’s most promising about such pervasive surveillance and also what’s potentially disturbing.
ShotSpotter sells and helps run an automated gunshot-reporting system to police departments, for a cost of $40,000 to $60,000 per square mile. Recording equipment is installed in neighborhoods and linked software that records sounds that could be gunfire, analyzes them to identify which are actually shots, and then submits its findings for review by a trained employee in the company’s Mountain View office. If a human verifies that the sounds are indeed gunfire, the police are notified with the location of the shots, pinpointed to within 40-50 feet. All this can happen in well under five minutes, meaning police can be there right away.
What’s the News: Google’s self-driving cars have been generating buzz lately, with the news that the company has been lobbying Nevada to allow the autonomous vehicles to be operated on public roads. But it remains to be seen whether hordes of self-driving cars really going to work in the real world.
Google announced this weekend that it has been driving automated cars around California’s roads, and that the vehicles have already logged about 140,000 miles. A fully automated car just finished a big trip–all the way from Google’s campus in Mountain View, California to Hollywood.
Larry and Sergey founded Google because they wanted to help solve really big problems using technology. And one of the big problems we’re working on today is car safety and efficiency. Our goal is to help prevent traffic accidents, free up people’s time and reduce carbon emissions by fundamentally changing car use. [Official Google Blog]
A Google car drives with the help of a variety of sensors–including cameras on the roof and in front, radars, and laser range finders–which build a detailed map of the car’s surroundings. This information is transmitted to the Google servers and processed to detect and react to any obstacles that get in the car’s way, mimicking the decisions a human driver would make.