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A company initially intended to use a large data set containing personal information to train an Al model. After consideration, the company determined that it can derive enough value from the data set without any personal information and permanently obfuscated all personal data elements before training the model.
This is an example of applying which privacy-enhancing technique (PET)?
Suggested Answer: A
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Anonymization is a privacy-enhancing technique that involves removing or permanently altering personal data elements to prevent the identification of individuals. In this case, the company obfuscated all personal data elements before training the model, which aligns with the definition of anonymization. This ensures that the data cannot be traced back to individuals, thereby protecting their privacy while still allowing the company to derive value from the dataset. Reference: AIGP Body of Knowledge, privacy-enhancing techniques section.
34 comments · newest first
SA
Sabine
10 months ago
Are we sure they really obfuscated everything? Sounds risky.
NO
Noah
11 months ago
Anonymization is the right term here, no doubt.
AL
Allene
11 months ago
Surprised they didn't just go with differential privacy!
WE
Werner
11 months ago
I think it's more like pseudonymization.
AN
An
11 months ago
This is definitely anonymization!
MA
Margo
12 months ago
I’m confused because I thought differential privacy was also about protecting data, but this seems more straightforward with anonymization.
LO
Lovetta
12 months ago
I practiced a question similar to this, and I believe it was about anonymization too. It makes sense given that they obfuscated all personal info.
AS
Ashton
12 months ago
I'm not entirely sure, but I remember something about pseudonymization keeping some identifiers. This seems more like full anonymization.
ME
Meghan
1 year ago
I think this is about anonymization since they removed all personal data completely.
JE
Jennifer
1 year ago
I'm a little confused by the wording here. Federated learning is about distributed training, not anonymization. I'm leaning towards either anonymization or pseudonymization, but I'll have to re-read the question to be sure.
HE
Helaine
1 year ago
Okay, I think I've got this. The key detail is that the company "permanently obfuscated all personal data elements." That sounds like they're removing the personal identifiers, which is the definition of anonymization. I'm confident that's the right answer.
MI
Mira
1 year ago
Hmm, I'm not totally sure about this one. Anonymization, pseudonymization, and differential privacy all seem like they could be relevant here. I'll have to think it through carefully.
JA
Jaime
1 year ago
This one seems pretty straightforward. The question is asking about a privacy-enhancing technique, and the details describe obfuscating personal data, which sounds like anonymization to me.
GI
Gilma
2 years ago
Haha, I bet the data scientists had a field day with 'obfuscating' all that personal info. Sounds like they were really 'anonymizing' the heck out of that data!
LA
Lai
2 years ago
Federated learning might be useful for training models without sharing sensitive data.
EL
Elvera
2 years ago
Differential privacy could have been another option to consider for enhancing privacy.
RO
Rosann
2 years ago
I think they could have also used pseudonymization to protect the personal information.
FR
Frederica
2 years ago
Yeah, they definitely went all out with anonymizing the data.
JU
Judy
2 years ago
I'm not sure, but I think it could also be B) Pseudonymization because the data was obfuscated.
JA
Jamika
2 years ago
I agree with Lorriane, anonymization is the best choice to protect personal data.
HU
Huey
2 years ago
Hmm, I'm not so sure. This sounds more like differential privacy to me, where they added noise to the data to preserve privacy while still deriving value.
LA
Laticia
2 years ago
C) Differential privacy.
MA
Mattie
2 years ago
B) Pseudonymization.
ME
Melodie
2 years ago
A) Anonymization.
GW
Gwenn
2 years ago
I'd say pseudonymization. Obfuscating the personal data elements but still keeping some linkability sounds like what they did here.
DO
Dominga
2 years ago
C) Differential privacy.
ST
Stephaine
2 years ago
B) Pseudonymization.
LA
Lamar
2 years ago
A) Anonymization.
LO
Lorriane
2 years ago
I think the answer is A) Anonymization.
GO
Goldie
2 years ago
Definitely anonymization. Removing all personal information from the data set before training the model is the textbook definition of anonymization.
AM
Amber
2 years ago
Definitely anonymization.
CE
Celeste
2 years ago
C) Differential privacy.
AM
Amie
2 years ago
B) Pseudonymization.
TR
Trina
2 years ago
A) Anonymization.