# kaal:claim:5095633-017

**Claim.** Decentralizing data processing across secure nodes, using techniques such as federated learning and homomorphic encryption, circumvents the privacy and security exposure of centralized data management and lowers breach risk.

**Type.** mechanism  **Support.** argued

**Holds when.**

- privacy-preserving computation techniques are actually deployed

**Source quote.**

> Through decentralizing data processing across secure nodes, these startups help circumvent the privacy and security issues associated with centralized data management, thus reducing the risk of data breaches.

**From.** Wulf A. Kaal, *Artificial Intelligence The Final Frontier* (2025), 3. Centralized AI Data Production, page 6

**Cite as.** Wulf A. Kaal, Artificial Intelligence The Final Frontier (2025). SSRN: https://ssrn.com/abstract=5095633

**Verify.** sha256 of source PDF `cbb484711f89bcefc9fc6a5730a1ed0a3f764d7999ad9b6f7d8ea05634c26c63` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20-%202025%20-%20Artificial%20Intelligence%20The%20Final%20Frontier.pdf

**Topics.** consensus-and-security, decentralization

**Keywords.** federated-learning, homomorphic-encryption, privacy-by-design, decentralization

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**Canonical form.** This markdown file is the canonical hashed representation of the claim. Its sha256 is the content hash used for attestation.