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This classification is very useful to discuss this issue. The difference between 3 and 4, noble as it is, can be caused by feasability concerns that push people into 3, not just ignorance of the privacy impact. Human labelling of training data sets is a big thing in supervised learning. Methods that dispense with this would be valuable for purely economic reasons beyond privacy - the cost of human labelling of data s…
It's not wrong for humans to label training data. It's wrong to let humans listen to voice recordings that users believed would be between them and a computer. The solutions are obvious: sell the things with a big sticker that says, "don't say anything private in earshot," revert to old fashioned research methods where you pay people to participate in your studies and get their permission, or ask people for permissio…
While I like how Ubuntu does it, I actually like better how Fedora does it. Not only do they ask to submit core dumps but gives you the ability to annotate and inspect what gets sent as well as gives you a bug report ID which you can use to follow up on.