# kaal:claim:4855607-019

**Claim.** In traditional federated learning environments the reliability of updates arriving from various nodes is hard to establish; web3 smart contracts and consensus mechanisms can automate that verification at the point of aggregation.

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

**Holds when.**

- federated learning with untrusted or unverified participating nodes

**Source quote.**

> In traditional FL environments, ensuring the reliability of updates from various nodes can be challenging. Web3's smart contracts and consensus mechanisms can automate the verification of updates from participating nodes

**From.** Wulf A. Kaal, *How AI Models are Optimized Through Web3 Governance* (2024), Model Overview: Federated Machine Learning Models, page 18

**Cite as.** Wulf A. Kaal, How AI Models are Optimized Through Web3 Governance (2024). SSRN: https://ssrn.com/abstract=4855607

**Verify.** sha256 of source PDF `eb0b3e62374b45a8fa888c6bde9725e606bcb46cf4b5e74a6e851d9f25099113` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20-%202024%20-%20How%20AI%20Models%20are%20Optimized%20Through%20Web3%20Governance.pdf

**Topics.** smart-contracts, consensus-and-security

**Keywords.** federated-learning, update-verification, smart-contracts, consensus, model-poisoning

**Related claims.**

- specializes: https://wulfkaal.github.io/claims/3373393-020

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