In iOS 10, this technology will help improve QuickType and emoji suggestions, Spotlight deep link suggestions and Lookup Hints in Notes. As more people share the same pattern, general patterns begin to emerge, which can inform and enhance the user experience. To obscure an individual’s identity, Differential Privacy adds mathematical noise to a small sample of the individual’s usage pattern. Starting with iOS 10, Apple is using Differential Privacy technology to help discover the usage patterns of a large number of users without compromising individual privacy. The resulting random noise can be subtracted from the results with a bit of algebra, and every respondent is protected from punishment if they admitted to lawbreaking.) If the result is heads, they're instructed to flip the coin again and then answer "yes" for heads or "no" for tails. If the result is tails, they should answer honestly. But first, the survey asks them to flip a coin. (As an example of that last method, Microsoft's Dwork points to the technique in which a survey asks if the respondent has ever, say, broken a law. ![]() In fact, Federighi named three of those transformations: Hashing, a cryptographic function that irreversibly turns data into a unique string of random-looking characters subsampling, or taking only a portion of the data and noise injection, adding random data that obscures the real, sensitive personal information. But Federighi implies that Apple is only transmitting that data in a transformed, differentially private form. ) "Differential privacy lets you gain insights from large datasets, but with a mathematical proof that no one can learn about a single individual."Īll the New Features Coming to Your Mac Desktop This Fall Arrowįederighi's emphasis on differential privacy likely means Apple is actually sending more of your data than ever off of your device to its servers for analysis, just as Google and Facebook and every other data-hungry tech firm does. ![]() (That book, co-written with Microsoft researcher Cynthia Dwork, is the Algorithmic Foundations of Differential Privacy. "With a large dataset that consists of records of individuals, you might like to run a machine learning algorithm to derive statistical insights from the database as a whole, but you want to prevent some outside observer or attacker from learning anything specific about some in the data set," says Aaron Roth, a University of Pennsylvania computer science professor whom Apple's Federighi named in his keynote as having "written the book" on differential privacy. And neither, in theory, could hackers or intelligence agencies. But it can't extract anything about a single, specific one of those people that might represent a privacy violation. ![]() With differential privacy, Apple can collect and store its users’ data in a format that lets it glean useful notions about what people do, say, like and want. The answer, he suggested rather cryptically, is "differential privacy."ĭifferential privacy, translated from Apple-speak, is the statistical science of trying to learn as much as possible about a group while learning as little as possible about any individual in it. But Federighi also acknowledged the growing reality that collecting user information is crucial to making good software, especially in an age of big data analysis and machine learning. ![]() So perhaps it's no surprise that the company has now publicly boasted about its work in an obscure branch of mathematics that deals with exactly that paradox.Īt the keynote address of Apple's Worldwide Developers' Conference in San Francisco on Monday, the company's senior vice president of software engineering Craig Federighi gave his familiar nod to privacy, emphasizing that Apple doesn't assemble user profiles, does end-to-end encrypt iMessage and Facetime and tries to keep as much computation as possible that involves your private information on your personal device rather than on an Apple server. But it's also marketed itself as Silicon Valley's privacy champion, one that-unlike so many of its advertising-driven competitors-wants to know as little as possible about you. Apple, like practically every mega-corporation, wants to know as much as possible about its customers.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |