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Synthetic data is a de-identification technique that can be dated back forty years. However, a recent reinterpretation of their use has opened to key advancements in artificial intelligence (AI) and machine learning (ML). Read more in this article from the Canadian Data Protection Commissioner here

Federated learning is a potential solution for developing machine-learning models requirining massive datasets. However, it may have positive impacts on data protection such as avoiding data centralisation and simplifying control over data processing. Learn more on federate learning with the EDPS here

Synthetic data is artificial data able to reproduce information very close to the original data. This means they can maintain almost the same statistical value as the authentic ones. Sounds interesting? Learn more about them with the EDPS here

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