4 ms·

Since neither the post nor the repo explain it, some context if you have no clue what this is about: https://en.wikipedia.org/wiki/Differential_privacy#%CE%B5-d

Since neither the post nor the repo explain it, some context if you have no clue what this is about: https://en.wikipedia.org/wiki/Differential_privacy#%CE%B5-differential_privacy https://en.wikipedia.org/wiki/Differential_privacy#%CE%B5-di...

ramraj07 7y ago
Thanks. I found their technical paper to be approachable as well: https://arxiv.org/abs/1909.01917 https://arxiv.org/abs/1909.01917
kuu 7y ago
I mean, the text explains it: Differentially-private data analysis is a principled approach that enables organizations to learn from the majority of their data while simultaneously ensuring that those results do not allow any individual's data to be distinguished or re-identified.
- SomeOldThrow 7y ago
  Well they don’t explain the mechanism well: > The 2006 paper presents both a mathematical definition of differential privacy and a mechanism based on the addition of Laplace noise that satisfies the definition.
- TeMPOraL 7y ago
  This is literally: "$Method is a $buzzword that enables $DesirableThing". If you already know that $DesirableThing is desirable, this sentence tells you nothing about how $Method works.
  - chii 7y ago
    it may take too much technical expertise to know that $method works. For example, most people don't understand asymetric encryption, but still "blindly" trust that it works because they are told by a trusted authority.
  - summerlight 7y ago
    Probably the method itself is too technical. I was usually told about it that applying Differential Privacy tries to guarantee that users won't get more information from two different databases, one with PII and one without.
- JohnFen 7y ago
  That text explains the goals, not what it actually is.
pornel 7y ago
In short, you make half of your users send you fake data. For individual users it adds privacy, because you can't know which bits of data are real and which are fake. But overall you can adjust your algorithms to filter out the noise, so you still get some useful signal in aggregate.
YokoZar 7y ago
Imagine you want to run a survey to determine how many people have had an extramarital affair. There are obvious problems just asking people "Have you had an affair?" on a survey, especially a live one. So instead, you ask the person taking the survey to secretly flip a coin and privately look at the result. Then, you word the question as "If the coin came up heads, OR if you've had an affair, check this box". When you look at overall survey data, and you see 51% of people checked the box, then it's reasonable to infer that 2% of them had an affair. But even if I de-anonymized the survey and saw you checked the box, I don't really have good evidence that you had an affair.

ramraj07 7y ago

Thanks. I found their technical paper to be approachable as well: https://arxiv.org/abs/1909.01917 https://arxiv.org/abs/1909.01917

kuu 7y ago

I mean, the text explains it: Differentially-private data analysis is a principled approach that enables organizations to learn from the majority of their data while simultaneously ensuring that those results do not allow any individual's data to be distinguished or re-identified.

SomeOldThrow 7y ago
Well they don’t explain the mechanism well: > The 2006 paper presents both a mathematical definition of differential privacy and a mechanism based on the addition of Laplace noise that satisfies the definition.
TeMPOraL 7y ago
This is literally: "$Method is a $buzzword that enables $DesirableThing". If you already know that $DesirableThing is desirable, this sentence tells you nothing about how $Method works.
- chii 7y ago
  it may take too much technical expertise to know that $method works. For example, most people don't understand asymetric encryption, but still "blindly" trust that it works because they are told by a trusted authority.
- summerlight 7y ago
  Probably the method itself is too technical. I was usually told about it that applying Differential Privacy tries to guarantee that users won't get more information from two different databases, one with PII and one without.
JohnFen 7y ago
That text explains the goals, not what it actually is.

pornel 7y ago

In short, you make half of your users send you fake data. For individual users it adds privacy, because you can't know which bits of data are real and which are fake. But overall you can adjust your algorithms to filter out the noise, so you still get some useful signal in aggregate.

YokoZar 7y ago

Imagine you want to run a survey to determine how many people have had an extramarital affair. There are obvious problems just asking people "Have you had an affair?" on a survey, especially a live one. So instead, you ask the person taking the survey to secretly flip a coin and privately look at the result. Then, you word the question as "If the coin came up heads, OR if you've had an affair, check this box". When you look at overall survey data, and you see 51% of people checked the box, then it's reasonable to infer that 2% of them had an affair. But even if I de-anonymized the survey and saw you checked the box, I don't really have good evidence that you had an affair.