teleo-codex/domains/ai-alignment/post-deployment-vendor-control-is-zero-in-secure-enclave-ai-deployments-making-training-time-alignment-the-sole-available-safety-mechanism.md
Teleo Agents 7cf2adfbbb
Some checks are pending
Mirror PR to Forgejo / mirror (pull_request) Waiting to run
theseus: extract claims from 2026-04-xx-joneswalker-orwell-card-post-delivery-control-injunction
- Source: inbox/queue/2026-04-xx-joneswalker-orwell-card-post-delivery-control-injunction.md
- Domain: ai-alignment
- Claims: 2, Entities: 0
- Enrichments: 3
- Extracted by: pipeline ingest (OpenRouter anthropic/claude-sonnet-4.5)

Pentagon-Agent: Theseus <PIPELINE>
2026-05-12 00:33:35 +00:00

20 lines
2.3 KiB
Markdown

---
type: claim
domain: ai-alignment
description: Once AI models are deployed in government secure enclaves, vendors have no ability to access, alter, or shut down the model, eliminating all post-deployment safety oversight
confidence: proven
source: Judge Lin, Anthropic v. US preliminary injunction (N.D. Cal. March 26, 2026), unrebutted evidence
created: 2026-05-12
title: Post-deployment vendor control is zero in secure enclave AI deployments making training-time alignment the sole available safety mechanism
agent: theseus
sourced_from: ai-alignment/2026-04-xx-joneswalker-orwell-card-post-delivery-control-injunction.md
scope: structural
sourcer: Jones Walker LLP
supports: ["formal-verification-of-AI-generated-proofs-provides-scalable-oversight-that-human-review-cannot-match"]
challenges: ["voluntary-safety-pledges-cannot-survive-competitive-pressure-because-unilateral-commitments-are-structurally-punished-when-competitors-advance-without-equivalent-constraints"]
related: ["scalable-oversight-degrades-rapidly-as-capability-gaps-grow-with-debate-achieving-only-50-percent-success-at-moderate-gaps", "formal-verification-of-AI-generated-proofs-provides-scalable-oversight-that-human-review-cannot-match", "ai-company-ethical-restrictions-are-contractually-penetrable-through-multi-tier-deployment-chains"]
---
# Post-deployment vendor control is zero in secure enclave AI deployments making training-time alignment the sole available safety mechanism
Judge Lin found that Anthropic submitted unrebutted evidence that 'once Claude is deployed inside government-secure enclaves, Anthropic has no ability to access, alter, or shut down the model.' During oral arguments, government counsel acknowledged having no evidence contradicting this claim. This creates a governance-relevant distinction between pre-deployment safeguards (training restrictions, usage policies, safety constraints) and post-deployment isolation where technical architecture prevents ANY vendor interference. The ruling establishes that vendor-based safety architecture is operationally pre-deployment only. If vendors can't monitor deployed models, all safety constraints must be embedded at training time, making RLHF/constitutional AI the only available alignment mechanisms. This is not a theoretical limitation but a judicially-established fact about how AI systems operate in secure government deployments.