# Communication overhead

`kaal:entity:communication-overhead`

**Status.** derived

This node is assembled mechanically from the 2 claims that carry the concept tag `communication-overhead`. It is a roster of what the corpus says under this term. It is **not** an adjudicated definition: no single statement here has been ruled canonical, and no first-appearance call has been made. Read the claims and judge for yourself.

## Every claim under this term

2 claims across 2 works, 2024 to 2024.

**2024**

- [4796714-028](https://wulfkaal.github.io/claims/4796714-028) [failure/evidenced] *(failure mode)* -- Privacy preserving frameworks such as federated learning do not fully remove centralization, because they still typically depend on a central client to collect and distribute model information, which reintroduces high communication loads and centralized vulnerabilities.
  > In response, privacy-preserving frameworks like federated learning have been developed, yet these often still depend on a central client to collect and distribute model information, resulting in high communication loads and centralized vulnerabilities.
  Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714
- [4941807-020](https://wulfkaal.github.io/claims/4941807-020) [failure/argued] *(failure mode)* -- Privacy preserving frameworks such as federated learning do not fully solve centralization, because they typically still depend on a central client to collect and distribute model information, which produces high communication loads and reintroduces centralized vulnerabilities.
  > In response, privacy-preserving frameworks like federated learning have been developed, yet these often still depend on a central client to collect and distribute model information, resulting in high communication loads and centralized vulnerabilities.
  Wulf A. Kaal, AI Governance Via Web3 Reputation System (2024). SSRN: https://ssrn.com/abstract=4941807

## Verify

Every claim above resolves to a record carrying a verbatim source quote, the sha256 of the source PDF, and a preformatted citation. Nothing here asks to be taken on trust.

    curl -s https://wulfkaal.github.io/entities/communication-overhead.md | sha256sum

**Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.