# Ex post regulation

`kaal:entity:ex-post-regulation`

**Status.** derived

This node is assembled mechanically from the 6 claims that carry the concept tag `ex-post-regulation`. 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

6 claims across 4 works, 2016 to 2024.

**2016**

- [2740477-022](https://wulfkaal.github.io/claims/2740477-022) [failure/argued] *(failure mode)* -- Because it lacks anticipatory rulemaking capability, the existing regulatory system addresses issues only ex post, and only once they have materialized and burdened core constituents enough to generate political pressure on lawmakers.
  > Because it lacks anticipatory rulemaking capabilities, the existing regulatory system addresses regulatory issues only ex-post, if and when they materialize and if core constituents are sufficiently burdened to precipitate enough political pressure for lawmakers to act.
  Wulf A. Kaal, Erik P.M. Vermeulen, Venture Capital as Dynamic Regulation of Disruptive Innovation (2016). SSRN: https://ssrn.com/abstract=2740477
- [2831040-007](https://wulfkaal.github.io/claims/2831040-007) [failure/argued] *(failure mode)* -- Facts based, ex post, trial and error rulemaking cannot anticipate the regulatory issues created by innovation, so rulemakers may never recognize, or may recognize only much too late, which new regulatory demands apply to a given innovation.
  > Because facts-based, ex-post, trial-and-error-rulemaking cannot anticipate regulatory issues created by innovation, rulemakers may not at all–or
  Wulf A. Kaal, Dynamic Regulation for Innovation (2016). SSRN: https://ssrn.com/abstract=2831040

**2024**

- [4796714-002](https://wulfkaal.github.io/claims/4796714-002) [failure/asserted] *(failure mode)* -- Conventional governance methods that are reactive or fixed to ex-post solutions are insufficient for governing technologies whose behavior changes continuously after deployment.
  > These conventional methods, largely reactive or fixed to ex-post solutions, are proving insufficient for the dynamic nature of AI technologies.
  Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714
- [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
- [4796714-027](https://wulfkaal.github.io/claims/4796714-027) [failure/asserted] *(failure mode)* -- Post-deployment monitoring, the standard fallback when ex-ante rules prove inadequate, is typically woefully outdated by the time it is applied because the AI models continue to evolve.
  > Yet, post-deployment monitoring is typically woefully outdated as the AI models evolve.
  Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714
- [4941807-001](https://wulfkaal.github.io/claims/4941807-001) [failure/argued] *(failure mode)* -- Ex-post AI governance, in which regulation is applied only after AI systems have been developed and deployed or after large language models have already been pretrained on existing proprietary datasets, falls short of preemptively addressing the risks and biases those systems carry.
  > 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 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-post-regulation.md | sha256sum

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