A new post to Apple’s Machine Learning Journal explains how the company’s use of differential privacy works to protect users, even as the company collects sensitive data to improve product delivery, ZDNet reports. The post, which is Apple’s seventh in a series exploring how machine-learning impacts its products, seeks to reassure users that their data remains private. Apple’s approach to differential privacy scrambles data with statistical noise before sending it off for analysis, working to ensure that data is "randomized before being sent from the device, so the server never sees or receives raw data." Users have the ability to opt in or out of sharing device analytics.
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