# Ai risk

`kaal:entity:ai-risk`

**Status.** derived

This node is assembled mechanically from the 2 claims that carry the concept tag `ai-risk`. 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 1 works, 2024 to 2024.

**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
- [4796714-023](https://wulfkaal.github.io/claims/4796714-023) [failure/argued] *(failure mode)* -- Purely preemptive regulation cannot succeed on its own, because it is not possible to anticipate every issue or bias an AI system will exhibit before it is operational and interacting with real world variables.
  > It is challenging to anticipate all potential issues or biases that may arise with an AI system before it is fully operational and interacting with real-world variables. Regulations that insist on preemptive controls may fail to address unforeseen problems that only become evident after deployment.
  Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714

## 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/ai-risk.md | sha256sum

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