# kaal:claim:4796714-023

**Claim.** 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.

**Type.** failure  **Support.** argued

**Holds when.**

- applies to ex-ante controls imposed at the model and data levels
- concerns emergent behavior that appears only in deployment

**Source quote.**

> 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.

**From.** Wulf A. Kaal, *AI Governance* (2024), Challenges, page 31

**Cite as.** Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714

**Verify.** sha256 of source PDF `59fa63bae179e8f9b6b8efbdf90cee28400276512a1b04f9f579a48641305c93` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20-%202024%20-%20AI%20Governance.pdf

**Failure mode.** preemptive anticipation limit  (family: ai-oversight-and-alignment-gap)

**Topics.** risk-and-incentives, ai-and-agents

**Keywords.** ex-ante-regulation, emergent-behavior, preemptive-controls, ai-risk

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