Cirrus Institute for AI and Data Governance Law and Policy Director Nicoletta Kolpakov examined the value of homomorphic encryption in federated learning. The method is currently not efficient enough for regular adoption, but Kolpakov argues that privacy professionals should prepare resources and legal frameworks for when it becomes more widespread. “For now, federated learning on its own remains a practical tool for many organizations, but as homomorphic encryption matures, the two together may become the foundation of privacy-preserving AI in both centralized and decentralized environments,” she writes.
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