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It's legitimate to call the aggregate data that the central server has "non-private." For example, it's ok to publish how many thousands of cars drive on a part

It's legitimate to call the aggregate data that the central server has "non-private." For example, it's ok to publish how many thousands of cars drive on a particular highway -- that's public data. It's not ok (broadly) to publish what route John Doe drives to work everyday -- that's private data.

krick 7y ago
Absolutely not. Actually, I kind of reflected it in my concerns: it makes it easier for somebody who wants to push such a polemic (as yourself) to do so, but by no means it is universally true. I mean, it might be, if everything that your model learns is the number of cars on a highway. But there's absolutely no reason to assume it is. It might as well learn anything else about your private life. You might be tempted to object, that it can learn nothing about your private life, since it isn't even known which device sent what data. But I think this is silly, because you forget the most important thing, which is to ask: what ever are "you"? The statement in question depends on definition of that, because if "you" means "your IP address", it might be true. But I never really was afraid Google is learning something about what is sent from this IP, because I don't believe the give a fuck. It is much less apparent they don't learn anything about "John Doe" simply given the fact that the learning is "federated". But then again, this doesn't really bother me much, because I don't believe they care. I think, much more probable definitions of "you" that might concern them, are a lot more dangerous, because they are a lot more "real" than your made-up (even if at birth) name which you probably share with 100 more people around the world anyway. Like, for example, "the guy, who every day makes a trip from Baker street 12 to Sesame street 30" (that's "you") and that he really likes Coke. And this is just the most simplistic one, there are infinite tuples of parameters that would define a specific person in much more meaningful way, than the IP or a name. But, actually, I don't really believe they would try to identify you like that either. Well, they might, I just don't really believe they care about "you" in a sense that might be meaningful to you. What some entity like Google is likely to mean by "you" is probably several organisms, so you might feel like whatever they learn about "you" is definitely not private data. But I don't think this is less scary, quite the opposite, facts like "boys 13-15 y.o. that listen Tokyo Hotel and drink Sprite are likely to try heroine if recommended to watch RocknRolla" are much more powerful and useful (this is obviously a made up example, which you may replace by anything seemingly less dramatic, like "person, who buys A, B and C will also want to buy D"). Anyway, what really makes up a model that can control the financial markets and mood of the people isn't about your petty definition of "you", but a much colder, more meaningful one. And when I'm worried Google learns something about "me", this is what I'm really worried about. And the fact that such a definition of "private data" wouldn't hold up in court because it "isn't even about a specific person" makes it only so much worse.
- pm90 7y ago
  What if Google understood the more meaningful you but couldn't track it down exactly to the real you? Or is that impossible to achieve technically?
  - krick 7y ago
    Does it matter? I'm saying that what you mean by "the real you" may not really be the most useful definition. If there are 10 people on the planet that would behave exactly the same way when put in the same conditions, I don't really need to make a distinction between any of you. Each one is as good as the other. I don't even feel necessarily comfortable with the completely anonymous usages of ML on my data. Like the mentioned "next word prediction". Language models we've seen by now don't really understand anything about the text, and surely nothing about who you are. Yet they are uncannily good in "understanding" the context somehow. It really doesn't know anything about the world in the strict sense of the word, but given your sentence starts with "Tensorflow" it is still able to understand that something about "neural networks" and "machine learning" would be a good way to continue. So if it learns on some very unique stories on a very unique subject you were telling someone in the WhatsApp, a model, trained on this data, actually might tell someone else the story vaguely resembling what you just said given the right context. Even though it didn't try to learn anything specifically about you, or even gather any data from you in a non-anonymous way. Of course, I don't mean to say this is actually likely to happen with how it's likely to be used, I'm just saying that to illustrate the possibility.
- capitalsigma 7y ago
  I believe that what I described above is actually the way that private data is defined today: for each sufficiently large data set, there exists a K such that K-anonymity means the data is public. If you find it concerning that it's possible to predict behavior based on demographics, I don't know what to tell you. Do you think that psychology studies are an invasion of privacy?

krick 7y ago

Absolutely not. Actually, I kind of reflected it in my concerns: it makes it easier for somebody who wants to push such a polemic (as yourself) to do so, but by no means it is universally true. I mean, it might be, if everything that your model learns is the number of cars on a highway. But there's absolutely no reason to assume it is. It might as well learn anything else about your private life. You might be tempted to object, that it can learn nothing about your private life, since it isn't even known which device sent what data. But I think this is silly, because you forget the most important thing, which is to ask: what ever are "you"? The statement in question depends on definition of that, because if "you" means "your IP address", it might be true. But I never really was afraid Google is learning something about what is sent from this IP, because I don't believe the give a fuck. It is much less apparent they don't learn anything about "John Doe" simply given the fact that the learning is "federated". But then again, this doesn't really bother me much, because I don't believe they care. I think, much more probable definitions of "you" that might concern them, are a lot more dangerous, because they are a lot more "real" than your made-up (even if at birth) name which you probably share with 100 more people around the world anyway. Like, for example, "the guy, who every day makes a trip from Baker street 12 to Sesame street 30" (that's "you") and that he really likes Coke. And this is just the most simplistic one, there are infinite tuples of parameters that would define a specific person in much more meaningful way, than the IP or a name. But, actually, I don't really believe they would try to identify you like that either. Well, they might, I just don't really believe they care about "you" in a sense that might be meaningful to you. What some entity like Google is likely to mean by "you" is probably several organisms, so you might feel like whatever they learn about "you" is definitely not private data. But I don't think this is less scary, quite the opposite, facts like "boys 13-15 y.o. that listen Tokyo Hotel and drink Sprite are likely to try heroine if recommended to watch RocknRolla" are much more powerful and useful (this is obviously a made up example, which you may replace by anything seemingly less dramatic, like "person, who buys A, B and C will also want to buy D"). Anyway, what really makes up a model that can control the financial markets and mood of the people isn't about your petty definition of "you", but a much colder, more meaningful one. And when I'm worried Google learns something about "me", this is what I'm really worried about. And the fact that such a definition of "private data" wouldn't hold up in court because it "isn't even about a specific person" makes it only so much worse.

pm90 7y ago
What if Google understood the more meaningful you but couldn't track it down exactly to the real you? Or is that impossible to achieve technically?
- krick 7y ago
  Does it matter? I'm saying that what you mean by "the real you" may not really be the most useful definition. If there are 10 people on the planet that would behave exactly the same way when put in the same conditions, I don't really need to make a distinction between any of you. Each one is as good as the other. I don't even feel necessarily comfortable with the completely anonymous usages of ML on my data. Like the mentioned "next word prediction". Language models we've seen by now don't really understand anything about the text, and surely nothing about who you are. Yet they are uncannily good in "understanding" the context somehow. It really doesn't know anything about the world in the strict sense of the word, but given your sentence starts with "Tensorflow" it is still able to understand that something about "neural networks" and "machine learning" would be a good way to continue. So if it learns on some very unique stories on a very unique subject you were telling someone in the WhatsApp, a model, trained on this data, actually might tell someone else the story vaguely resembling what you just said given the right context. Even though it didn't try to learn anything specifically about you, or even gather any data from you in a non-anonymous way. Of course, I don't mean to say this is actually likely to happen with how it's likely to be used, I'm just saying that to illustrate the possibility.
capitalsigma 7y ago
I believe that what I described above is actually the way that private data is defined today: for each sufficiently large data set, there exists a K such that K-anonymity means the data is public. If you find it concerning that it's possible to predict behavior based on demographics, I don't know what to tell you. Do you think that psychology studies are an invasion of privacy?