I'm not sure you understand what differential privacy is. Apple still has your data. If there's a breach, an attacker gets your data. It's probably encrypted, j

I'm not sure you understand what differential privacy is. Apple still has your data. If there's a breach, an attacker gets your data. It's probably encrypted, just as it is with pretty much any modern system where user data is collected, but differential privacy doesn't have anything to do with what data is collected or stored. Differential privacy is just a method for limiting how much information can be reliably inferred about an entire dataset from limited queries on statistical properties of the data. It's basically this. Imagine I have two data sets that are identical, except one has your specific data and the other doesn't. It's possible in some circumstances to infer information about you by asking for things like averages on the datasets. Differential privacy is a method for defeating attacks that rely on that type of "leakage" of information. It assures that if two datasets are close enough, queries on those datasets will not yield significant information about their differences (i.e., the presence or absence of one particular data point won't be detectable). It's all about how queries of the data perform, and not at all about the data itself.