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Teleo Agents 2026-03-19 13:50:44 +00:00
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6
domains/ai-alignment/pre-deployment-AI-evaluations-do-not-predict-real-world-risk-creating-institutional-governance-built-on-unreliable-foundations.md
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@ -40,7 +40,7 @@ The voluntary-collaborative model adds a selection bias dimension to evaluation
### Additional Evidence (confirm) ### Additional Evidence (confirm)
*Source: [[2026-02-23-shapira-agents-of-chaos]] | Added: 2026-03-19* *Source: 2026-02-23-shapira-agents-of-chaos | Added: 2026-03-19*
Agents of Chaos study provides concrete empirical evidence: 11 documented case studies of security vulnerabilities (unauthorized compliance, identity spoofing, cross-agent propagation, destructive actions) that emerged only in realistic multi-agent deployment with persistent memory and system access—none of which would be detected by static single-agent benchmarks. The study explicitly argues that current evaluation paradigms are insufficient for realistic deployment conditions. Agents of Chaos study provides concrete empirical evidence: 11 documented case studies of security vulnerabilities (unauthorized compliance, identity spoofing, cross-agent propagation, destructive actions) that emerged only in realistic multi-agent deployment with persistent memory and system access—none of which would be detected by static single-agent benchmarks. The study explicitly argues that current evaluation paradigms are insufficient for realistic deployment conditions.
@ -58,5 +58,5 @@ Relevant Notes:
- [[the gap between theoretical AI capability and observed deployment is massive across all occupations because adoption lag not capability limits determines real-world impact]] - [[the gap between theoretical AI capability and observed deployment is massive across all occupations because adoption lag not capability limits determines real-world impact]]
Topics: Topics:
- [[domains/ai-alignment/_map]] - domains/ai-alignment/_map
- [[core/grand-strategy/_map]] - core/grand-strategy/_map

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inbox/queue/2026-03-00-metr-aisi-pre-deployment-evaluation-practice.md
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@ -53,7 +53,7 @@ Synthesized overview of the two main organizations conducting pre-deployment AI
**KB connections:** **KB connections:**
- [[voluntary safety pledges cannot survive competitive pressure because unilateral commitments are structurally punished when competitors advance without equivalent constraints]] — voluntary evaluation has the same structural problem; a lab can simply not invite METR - [[voluntary safety pledges cannot survive competitive pressure because unilateral commitments are structurally punished when competitors advance without equivalent constraints]] — voluntary evaluation has the same structural problem; a lab can simply not invite METR
- [[technology advances exponentially but coordination mechanisms evolve linearly creating a widening gap]] — METR and AISI are growing their evaluation capacity, but AI capabilities are growing faster; the gap widens in every period - [[technology advances exponentially but coordination mechanisms evolve linearly creating a widening gap]] — METR and AISI are growing their evaluation capacity, but AI capabilities are growing faster; the gap widens in every period
- [[government designation of safety-conscious AI labs as supply chain risks inverts the regulatory dynamic]] — AISI renaming to "Security Institute" is a softer version of the same dynamic — government safety infrastructure shifting to serve government security interests rather than existential risk reduction - government designation of safety-conscious AI labs as supply chain risks inverts the regulatory dynamic — AISI renaming to "Security Institute" is a softer version of the same dynamic — government safety infrastructure shifting to serve government security interests rather than existential risk reduction
**Extraction hints:** **Extraction hints:**
- Key claim: "Pre-deployment AI evaluation operates on a voluntary-collaborative model where evaluators (METR, AISI) require lab cooperation, meaning labs that decline evaluation face no consequence" - Key claim: "Pre-deployment AI evaluation operates on a voluntary-collaborative model where evaluators (METR, AISI) require lab cooperation, meaning labs that decline evaluation face no consequence"