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Multi-Actor Strategic Landscape

multi-actor-landscapeanalysisPath: /knowledge-base/models/multi-actor-landscape/
E418Entity ID (EID)
← Back to page7 backlinksQuality: 79Updated: 2026-04-12
Page Recorddatabase.json — merged from MDX frontmatter + Entity YAML + computed metrics at build time
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  "summary": "Analyzes AI risk through the lens of which actors develop TAI, finding actor identity may account for 40-60% of total risk variance, with detailed quantitative data on US-China capability convergence (benchmark gap narrowed from 9.26% to 1.70% in ~13 months), investment asymmetries (\\$222B US vs \\$98B China VC), and four risk pathways summing to ~25% combined x-risk. The framework is well-populated with 2025-2026 data but the core model parameters (risk estimates, variance attribution) are explicitly acknowledged as illustrative rather than empirically derived.",
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External Links

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Backlinks (7)
idtitletyperelationship
ai-actor-feedback-loopsAI Actor Feedback Loopsanalysis—
ai-power-and-influence-mapAI Power and Influence Mapanalysis—
industry-consortia-and-self-regulationIndustry Consortia and Self-Regulationorganization—
military-and-defense-ai-actorsMilitary and Defense AI Actorsorganization—
openai-board-and-foundation-dynamicsOpenAI Board and Foundation Dynamicsorganization—
shareholder-and-board-influence-in-ai-labsShareholder and Board Influence in AI Labsorganization—
actor-power-scorecardActor Power Scorecardconcept—