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Federated Learning's Consent Crisis: Building Privacy-Preserving AI Without Sacrificing Individual Choice

Federated learning promised to solve AI's privacy problem by training models without centralizing data. Instead of sending sensitive information to central servers, the technology brings algorithms to the data, learning from distributed sources while keeping raw information local. But this innovative approach creates an unexpected consent challenge: how do you manage individual privacy preferences across thousands of decentralized data sources?

May 26, 2025

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