Decentralization Method Analysis

From The Foundation for Best Practices in Machine Learning
Technical Best Practice Guideline > Privacy > Decentralization Method Analysis

Decentralization Method Analysis


Consider the appropriateness of utilizing methods for distributing data or training across decentralized devices, services, or storage. When analyzing federated learning methods, consider Data Capacity Analysis, Product Integration Strategy, Product Traceability, and Fairness & Non-Discrimination, as discussed more thoroughly in Section 4 - Problem Mapping; Section 21 - Product Traceability; and Section 11 - Fairness & Non-Discrimination. When analyzing differential privacy methods, consider Data Quality - Noise, as discussed more thoroughly in Section 12 - Data Quality.


To (a) ensure appropriate privacy-preserving techniques that are aligned with chosen Models; and (b) highlight associated risks that might occur in the Product Lifecycle.

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