# Ex ante governance

`kaal:entity:ex-ante-governance`

**Status.** derived

This node is assembled mechanically from the 5 claims that carry the concept tag `ex-ante-governance`. 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

5 claims across 3 works, 2014 to 2024.

**2014**

- [kaal-2014-dynamicregulationviagove-020](https://wulfkaal.github.io/claims/kaal-2014-dynamicregulationviagove-020) [definitional/argued] -- Contrary to the dominant view of corporate governance as a forward looking endeavor, dynamic governance structures are properly categorized as backward looking ex ante forms of corporate governance.
  > By contrast, in the theoretical framework of dynamic regulation, dynamic gov- ernance structures can be categorized as backward-looking ex-ante forms of corporate governance.
  Kaal, Dynamic Regulation via Governmental Contracts (2014)

**2024**

- [4796714-004](https://wulfkaal.github.io/claims/4796714-004) [failure/argued] *(failure mode)* -- Ex-post governance, which applies regulation only after AI systems are developed and deployed or after large language models have been pretrained on existing proprietary datasets, fails to address risks and biases preemptively.
  > The traditional ex-post governance methods, where regulations are applied after AI systems are developed and deployed, or were pretrained LLMs models were trained on existing proprietary datasets, often fall short in preemptively addressing risks and biases.
  Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714
- [4941807-002](https://wulfkaal.github.io/claims/4941807-002) [failure/asserted] *(failure mode)* -- Governing AI requires toolsets that simultaneously handle ex-ante governance of models still evolving and ex-post management of deployed solutions, and Kaal asserts that as of publication no legacy system supplies such dynamic governance toolsets.
  > Such systems are crucial to address the dual needs when governing evolving AI models ex-ante and managing existing solutions ex-post. No legacy systems exist at the time of publication that could provide such dynamic governance toolsets.
  Wulf A. Kaal, AI Governance Via Web3 Reputation System (2024). SSRN: https://ssrn.com/abstract=4941807
- [4941807-003](https://wulfkaal.github.io/claims/4941807-003) [design/argued] -- Kaal advocates an ex-ante governance approach within Web3 frameworks in which community coordinated regulatory measures and oversight mechanisms are set during the development phase of AI technologies rather than imposed after deployment.
  > In contrast, an ex-ante governance approach, advocated within Web3 frameworks as presented in this paper, involves setting community coordinated regulatory measures and oversight mechanisms during the development phase of AI technologies.
  Wulf A. Kaal, AI Governance Via Web3 Reputation System (2024). SSRN: https://ssrn.com/abstract=4941807
- [4941807-033](https://wulfkaal.github.io/claims/4941807-033) [mechanism/argued] -- Under the proposed model the input parameters and learning data of AI systems are themselves governed by expert community consensus, through submission of proposals to the Forum and review by Validation Pool, so that only vetted and consensus backed data and parameters enter AI development.
  > the input parameters and learning data for AI systems can be governed through expert community consensus. This process involves submitting proposals to the Forum and undergoing Validation Pool review,
  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/ex-ante-governance.md | sha256sum

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