extract: 2026-01-15-eu-ai-alliance-seven-feedback-loops

Pentagon-Agent: Epimetheus <968B2991-E2DF-4006-B962-F5B0A0CC8ACA>

domains/ai-alignment/AI alignment is a coordination problem not a technical problem.md

@@ -33,6 +33,12 @@ Ruiz-Serra et al. (2024) provide formal evidence for the coordination framing th
 
 The UK AI4CI research strategy treats alignment as a coordination and governance challenge requiring institutional infrastructure. The seven trust properties (human agency, security, privacy, transparency, fairness, value alignment, accountability) are framed as system architecture requirements, not as technical ML problems. The strategy emphasizes 'establishing and managing appropriate infrastructure in a way that is secure, well-governed and sustainable' and includes regulatory sandboxes, trans-national governance, and trustworthiness assessment as core components. The research agenda focuses on coordination mechanisms (federated learning, FAIR principles, multi-stakeholder governance) rather than on technical alignment methods like RLHF or interpretability.
 
+
+### Additional Evidence (confirm)
+*Source: [[2026-01-15-eu-ai-alliance-seven-feedback-loops]] | Added: 2026-03-18*
+
+The source identifies three market failure mechanisms driving over-adoption: (1) negative externalities where firms don't internalize demand destruction, (2) coordination failure where 'follow or die' dynamics force adoption despite systemic risks, (3) information asymmetry where adoption signals inevitability. All three are coordination failures, not technical capability gaps.
+
 ---
 
 Relevant Notes:

inbox/archive/.extraction-debug/2026-01-15-eu-ai-alliance-seven-feedback-loops.json

@@ -0,0 +1,43 @@
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inbox/archive/2026-01-15-eu-ai-alliance-seven-feedback-loops.md

@@ -7,12 +7,16 @@ date: 2026-01-15
 domain: ai-alignment
 secondary_domains: [internet-finance, grand-strategy]
 format: essay
-status: unprocessed
+status: enrichment
 priority: high
 triage_tag: claim
 tags: [feedback-loops, economic-disruption, demand-destruction, automation-overshoot, coordination-failure, market-failure, systemic-risk]
 flagged_for_rio: ["Seven self-reinforcing economic feedback loops from AI automation — connects to market failure analysis and coordination mechanisms"]
 flagged_for_leo: ["Systemic coordination failure framework — individual firm optimization creating collective demand destruction"]
+processed_by: theseus
+processed_date: 2026-03-18
+enrichments_applied: ["AI alignment is a coordination problem not a technical problem.md"]
+extraction_model: "anthropic/claude-sonnet-4.5"
 ---
 
 ## Content
@@ -55,3 +59,12 @@ Seven self-reinforcing feedback loops identified in AI's economic impact:
 ## Curator Notes
 PRIMARY CONNECTION: the alignment tax creates a structural race to the bottom because safety training costs capability and rational competitors skip it
 WHY ARCHIVED: Provides seven specific feedback loops explaining HOW the race-to-the-bottom dynamic operates economically. L1 is the alignment tax applied to automation decisions. L7 is our temporal mismatch claim applied to governance response.
+
+
+## Key Facts
+- 78% of organizations now use AI as of 2026
+- 40% of employers plan workforce reductions due to AI
+- 92% of C-suite executives report up to 20% workforce overcapacity
+- Only 3-7% of AI productivity improvements translate to higher worker earnings
+- 77% of new AI jobs require master's degrees
+- J-curve pattern shows initial 60-percentage-point productivity declines during 12-24 month AI adjustment periods