One of the core obstacles of a machine learning researcher is often dealing with a lack of data. It’s an easy thing to complain about when it comes to poor performance.
Ironically though, those same people can be hesitant about sharing any data about themselves whenever asked.
And why wouldn’t they?
It’s almost illogical to ever agree to the sending of any data, even anonymous. Not much incentive for you, but one can imagine all sorts of scenarios it backfires, even unlikely.
But the question is, how much of your information is really staying private in the first place?
Google and Amazon seem to track your searches well for advertising. And if a family member publicly releases their genetic code, how much are they releasing of yours?
It’s harder and harder to stay isolated while trying to stay connected today.
The option, perhaps, is to find where that information can be useful. Geneticists value genome codes to spot hereditary traits and genetic diseases. AI researchers could use more data to train models more precisely.
Data is powerful. Perhaps it’s useful to see where we can lend to that power more easily, such as researchers, who can’t find it so easily. That doesn’t mean start sending your reports everywhere without hesitation. But it’s worth wondering whether your privacy has really changed when you decide not to share it, and where sharing it can help.
