Which of the following is the BEST way for an organization to address privacy concerns when deploying machine learning (ML) models?

The correct answer is A. Employing differential privacy techniques during model training. Differential privacy adds statistical noise during model training to prevent the disclosure of individual data points. This ensures the ML model can learn from data while preserving privacy, making it the best way to address privacy concerns in ML deployments.

Privacy Architecture

Question

Options

AEmploying differential privacy techniques during model training
BImplementing access controls based on user roles
CConducting regular Internet of Things (IoT) device firmware updates
DUsing public cloud solutions for model hosting

How the community answered

(29 responses)

A
72% (21)
B
7% (2)
C
7% (2)
D
14% (4)

Explanation

Differential privacy adds statistical noise during model training to prevent the disclosure of individual data points. This ensures the ML model can learn from data while preserving privacy, making it the best way to address privacy concerns in ML deployments.

Topics

#Machine Learning privacy#Differential Privacy#Privacy-enhancing technologies (PETs)#Model training privacy

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