For the past year, Apple has touted a mathematical tool that it refers to as a remedy to some paradoxical problem: mining consumer information, while simultaneously protecting user privacy. That secret weapon is “differential privacy,” a novel area of information science which concentrates on closely adding random noise to a single user’s information before it is uploaded into the cloud. This way, a company like Apple’s total dataset reveals meaningful results with no 1 individual’s secrets being spilled. read more