extract: 2026-01-15-eu-ai-alliance-seven-feedback-loops
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@ -33,6 +33,12 @@ Ruiz-Serra et al. (2024) provide formal evidence for the coordination framing th
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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.
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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.
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### Additional Evidence (extend)
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*Source: [[2026-01-15-eu-ai-alliance-seven-feedback-loops]] | Added: 2026-03-18*
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Three market failure mechanisms drive AI over-adoption: (1) negative externalities where firms don't internalize collective demand destruction, (2) coordination failure where 'follow or die' dynamics force adoption regardless of aggregate consequences, (3) information asymmetry where adoption signals inevitability pressuring laggards. This provides the specific economic taxonomy for why alignment-as-coordination fails.
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---
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---
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Relevant Notes:
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Relevant Notes:
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@ -0,0 +1,35 @@
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{
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"rejected_claims": [
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{
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"filename": "competitive-ai-adoption-creates-demand-destruction-feedback-loop-through-follow-or-die-dynamics.md",
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"issues": [
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"missing_attribution_extractor"
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]
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},
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{
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"filename": "exponential-technology-with-linear-governance-creates-meta-loop-accelerating-all-coordination-failures.md",
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"issues": [
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"missing_attribution_extractor"
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]
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}
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],
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"validation_stats": {
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"total": 2,
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"kept": 0,
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"fixed": 5,
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"rejected": 2,
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"fixes_applied": [
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"competitive-ai-adoption-creates-demand-destruction-feedback-loop-through-follow-or-die-dynamics.md:set_created:2026-03-18",
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"competitive-ai-adoption-creates-demand-destruction-feedback-loop-through-follow-or-die-dynamics.md:stripped_wiki_link:the alignment tax creates a structural race to the bottom",
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"competitive-ai-adoption-creates-demand-destruction-feedback-loop-through-follow-or-die-dynamics.md:stripped_wiki_link:economic forces push humans out of every cognitive loop wher",
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"competitive-ai-adoption-creates-demand-destruction-feedback-loop-through-follow-or-die-dynamics.md:stripped_wiki_link:voluntary safety pledges cannot survive competitive pressure",
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"exponential-technology-with-linear-governance-creates-meta-loop-accelerating-all-coordination-failures.md:set_created:2026-03-18"
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],
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"rejections": [
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"competitive-ai-adoption-creates-demand-destruction-feedback-loop-through-follow-or-die-dynamics.md:missing_attribution_extractor",
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"exponential-technology-with-linear-governance-creates-meta-loop-accelerating-all-coordination-failures.md:missing_attribution_extractor"
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]
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},
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"model": "anthropic/claude-sonnet-4.5",
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"date": "2026-03-18"
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}
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@ -7,12 +7,16 @@ date: 2026-01-15
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domain: ai-alignment
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domain: ai-alignment
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secondary_domains: [internet-finance, grand-strategy]
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secondary_domains: [internet-finance, grand-strategy]
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format: essay
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format: essay
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status: unprocessed
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status: enrichment
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priority: high
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priority: high
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triage_tag: claim
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triage_tag: claim
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tags: [feedback-loops, economic-disruption, demand-destruction, automation-overshoot, coordination-failure, market-failure, systemic-risk]
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tags: [feedback-loops, economic-disruption, demand-destruction, automation-overshoot, coordination-failure, market-failure, systemic-risk]
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flagged_for_rio: ["Seven self-reinforcing economic feedback loops from AI automation — connects to market failure analysis and coordination mechanisms"]
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flagged_for_rio: ["Seven self-reinforcing economic feedback loops from AI automation — connects to market failure analysis and coordination mechanisms"]
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flagged_for_leo: ["Systemic coordination failure framework — individual firm optimization creating collective demand destruction"]
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flagged_for_leo: ["Systemic coordination failure framework — individual firm optimization creating collective demand destruction"]
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processed_by: theseus
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processed_date: 2026-03-18
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enrichments_applied: ["AI alignment is a coordination problem not a technical problem.md"]
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extraction_model: "anthropic/claude-sonnet-4.5"
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---
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---
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## Content
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## Content
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@ -55,3 +59,12 @@ Seven self-reinforcing feedback loops identified in AI's economic impact:
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## Curator Notes
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## Curator Notes
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PRIMARY CONNECTION: the alignment tax creates a structural race to the bottom because safety training costs capability and rational competitors skip it
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PRIMARY CONNECTION: the alignment tax creates a structural race to the bottom because safety training costs capability and rational competitors skip it
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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.
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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.
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## Key Facts
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- Only 3-7% of AI productivity improvements translate to higher worker earnings
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- 40% of employers plan workforce reductions
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- 92% of C-suite executives report up to 20% workforce overcapacity
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- 78% of organizations now use AI
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- J-curve: initial 60-percentage-point productivity declines during 12-24 month adjustment periods
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- 77% of new AI jobs require master's degrees
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