# kaal:claim:5245185-026

**Claim.** Centralized AI structures for monitoring AI agents create a self referential loop that is prone to systemic biases and blind spots, and their rigidity prevents adaptation to the dynamic nature of AI.

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

**Holds when.**

- centralized AI systems used to supervise AI agents

**Source quote.**

> Centralized AI structures for AI agent monitoring create a self-referential loop prone to systemic biases and blind spots, while their rigidity fails to adapt to AI's dynamic nature.

**From.** Wulf A. Kaal, *How can we Best Monitor AI Agents* (2025), 6.3. Fallacy of Centralized AI Monitoring AI Agent Evolution, page 13

**Cite as.** Wulf A. Kaal, How can we Best Monitor AI Agents (2025). SSRN: https://ssrn.com/abstract=5245185

**Verify.** sha256 of source PDF `4d7adba83ec722480e97bde6528cbe9ce98c709e45cb18794f157a64b8fe7da2` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20-%202025%20-%20How%20can%20we%20Best%20Monitor%20AI%20Agents.pdf

**Failure mode.** self-referential-monitoring-loop  (family: ai-oversight-and-alignment-gap)

**Topics.** decentralization, ai-and-agents

**Keywords.** circularity, systemic-bias, blind-spots, centralized-ai

**Canonical form.** This markdown file is the canonical hashed representation of the claim. Its sha256 is the content hash used for attestation.