Which of the following is the BEST way to minimize privacy risk in AI applications?

The correct answer is B. Apply federated learning.. Federated learning trains AI models across distributed devices or servers without centralizing or transferring the raw personal data. The model learns from data in place, and only model updates (not personal data) are shared, minimizing exposure and privacy risk. Algorithmic audi

Privacy Architecture

Question

Options

AImplement algorithmic auditing.
BApply federated learning.
CUse only publicly available data.
DScrape data from the internet.

How the community answered

(50 responses)

A
18% (9)
B
68% (34)
C
10% (5)
D
4% (2)

Explanation

Federated learning trains AI models across distributed devices or servers without centralizing or transferring the raw personal data. The model learns from data in place, and only model updates (not personal data) are shared, minimizing exposure and privacy risk. Algorithmic auditing (A) detects bias but does not prevent data exposure. Using only publicly available data (C) does not eliminate privacy risk since public data can still identify individuals. Scraping internet data (D) often violates privacy regulations and increases risk.

Topics

#AI Privacy#Federated Learning#Privacy Enhancing Technologies

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