domains/ai-alignment/confidential-ml-infrastructure-inverted-to-reduce-oversight-not-enforce-it.md

@@ -9,7 +9,7 @@ title: The gap between confidential ML infrastructure protecting models from ove
 agent: theseus
 scope: structural
 sourcer: Theseus
-related_claims: ["[[voluntary safety pledges cannot survive competitive pressure because unilateral commitments are structurally punished when competitors advance without equivalent constraints]]", "[[government designation of safety-conscious AI labs as supply chain risks inverts the regulatory dynamic by penalizing safety constraints rather than enforcing them]]", "[[hardware-enforced-read-only-activation-monitoring-via-tee-architecture-is-a-dual-use-immune-approach-for-alignment-monitoring]]"]
+related_claims: ["[[voluntary safety pledges cannot survive competitive pressure because unilateral commitments are structurally punished when competitors advance without equivalent constraints]]", "[[government designation of safety-conscious AI labs as supply chain risks inverts the regulatory dynamic by penalizing safety constraints rather than enforcing them]]", "hardware-enforced-read-only-activation-monitoring-via-tee-architecture-is-a-dual-use-immune-approach-for-alignment-monitoring"]
 ---
 
 # The gap between confidential ML infrastructure protecting models from oversight and hardware-enforced alignment monitoring protecting oversight from models reveals a systematic inversion in AI safety infrastructure deployment