# Ex ante regulation `kaal:entity:ex-ante-regulation` **Status.** derived This node is assembled mechanically from the 5 claims that carry the concept tag `ex-ante-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 5 claims across 2 works, 2013 to 2024. **2013** - [2273857-015](https://wulfkaal.github.io/claims/2273857-015) [condition/argued] -- Financial rulemaking is most needed ex-ante before financial crises, not ex-post after crises have already imposed steep costs on the economy, markets, and financial institutions and have distorted the rulemaking process itself. > Financial rulemaking is most needed ex-ante before financial crises, not ex-post after crises created steep costs on the economy, impacted markets and financial institutions, and affected the rulemaking process. Wulf A. Kaal, Dynamic Regulation of the Financial Services Industry (2013). SSRN: https://ssrn.com/abstract=2273857 **2024** - [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 - [4796714-024](https://wulfkaal.github.io/claims/4796714-024) [condition/argued] *(failure mode)* -- Ex-ante regulation is preferable in principle but is neither practical nor sufficient inside legacy systems, precisely because legacy systems, unlike the web3 system proposed here, are not equipped to create dynamic feedback effects. > while ex ante regulation is preferable, it is not always practical or sufficient in legacy ssytems to address the dynamic challenges that AI technologies present because legacy systems, unlike web3 systems as proposed herein, are not typically equipped to create dynamic feedback effects. Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714 - [4796714-025](https://wulfkaal.github.io/claims/4796714-025) [failure/argued] *(failure mode)* -- Strict legacy regulation built on stable and presumptively optimal rules and enforced at the AI development stage can inadvertently stifle innovation by imposing rigid constraints before a model is fully developed or deployed. > Strict legacy type regulations with stable and presumptively optimal rules83 enforced at the development stage of AI might inadvertently stifle innovation. Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714 - [4796714-026](https://wulfkaal.github.io/claims/4796714-026) [failure/argued] *(failure mode)* -- Legacy ex-ante regulatory attempts fail because they assume a static technological landscape, while AI development is dynamic and requires rules that are adaptable and responsive. > The exponential pace at which AI technology evolves makes it difficult to establish legacy system ex-post regulations that remain relevant over time. In turn, legacy ex-ante regulatory attempts assume a static technological landscape. 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/ex-ante-regulation.md | sha256sum **Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.