kaal:position:2026-07-31-7468
Legal Logic of AI Data Governance Based on Federated Learning: Institutional Evolution from Privacy Protection to Rights Distribution presents the following source proposition: The study finds that federated learning is not merely a technical tool but also an opportunity to drive legal institutional design innovation. This proposition is pertinent to Kaal's source-bound claim that In federated learning the communication cost of many edge devices sending model parameters to a central server frequently exceeds the computation cost, and heterogeneity in the participating devices, including varying computational capabilities and resource constraints, compounds the problem. The proposed response is an extension: the relationship should remain limited to the retrieved source proposition and the mapped Kaal claim unless fuller source review supports a broader conclusion.
institutional-designhistorical-responsescholarly-literaturecrossref