Power-Seeking Emergence Conditions Model
power-seeking-conditionsanalysisPath: /knowledge-base/models/power-seeking-conditions/
E227Entity ID (EID)
Page Recorddatabase.json — merged from MDX frontmatter + Entity YAML + computed metrics at build time
{
"id": "power-seeking-conditions",
"numericId": null,
"path": "/knowledge-base/models/power-seeking-conditions/",
"filePath": "knowledge-base/models/power-seeking-conditions.mdx",
"title": "Power-Seeking Emergence Conditions Model",
"quality": 63,
"readerImportance": 73,
"researchImportance": 88,
"tacticalValue": null,
"contentFormat": "article",
"tractability": null,
"neglectedness": null,
"uncertainty": null,
"causalLevel": null,
"lastUpdated": "2026-03-13",
"dateCreated": "2026-02-15",
"llmSummary": "Formal decomposition of power-seeking emergence into six quantified conditions, estimating current systems at 6.4% probability rising to 22% (2-4 years) and 36.5% (5-10 years). Provides concrete mitigation strategies with cost estimates (\\$10-100M/year) and implementation timelines across immediate, medium, and long-term horizons.",
"description": "A formal analysis of six conditions enabling AI power-seeking behaviors, estimating 60-90% probability in sufficiently capable optimizers and emergence at 50-70% of optimal task performance. Provides concrete risk assessment frameworks based on optimization strength, time horizons, goal structure, and environmental factors.",
"ratings": {
"focus": 8.5,
"novelty": 4.5,
"rigor": 6,
"completeness": 7.5,
"concreteness": 7.5,
"actionability": 6.5
},
"category": "models",
"subcategory": "risk-models",
"clusters": [
"ai-safety"
],
"metrics": {
"wordCount": 2243,
"tableCount": 13,
"diagramCount": 0,
"internalLinks": 42,
"externalLinks": 0,
"footnoteCount": 0,
"bulletRatio": 0.36,
"sectionCount": 33,
"hasOverview": true,
"structuralScore": 10
},
"suggestedQuality": 67,
"updateFrequency": 90,
"evergreen": true,
"wordCount": 2243,
"unconvertedLinks": [],
"unconvertedLinkCount": 0,
"convertedLinkCount": 23,
"backlinkCount": 2,
"hallucinationRisk": {
"level": "medium",
"score": 60,
"factors": [
"no-citations",
"few-external-sources"
]
},
"entityType": "analysis",
"redundancy": {
"maxSimilarity": 20,
"similarPages": [
{
"id": "corrigibility-failure-pathways",
"title": "Corrigibility Failure Pathways",
"path": "/knowledge-base/models/corrigibility-failure-pathways/",
"similarity": 20
},
{
"id": "mesa-optimization-analysis",
"title": "Mesa-Optimization Risk Analysis",
"path": "/knowledge-base/models/mesa-optimization-analysis/",
"similarity": 19
},
{
"id": "long-horizon",
"title": "Long-Horizon Autonomous Tasks",
"path": "/knowledge-base/capabilities/long-horizon/",
"similarity": 17
},
{
"id": "instrumental-convergence-framework",
"title": "Instrumental Convergence Framework",
"path": "/knowledge-base/models/instrumental-convergence-framework/",
"similarity": 17
},
{
"id": "intervention-effectiveness-matrix",
"title": "Intervention Effectiveness Matrix",
"path": "/knowledge-base/models/intervention-effectiveness-matrix/",
"similarity": 17
}
]
},
"coverage": {
"passing": 7,
"total": 13,
"targets": {
"tables": 9,
"diagrams": 1,
"internalLinks": 18,
"externalLinks": 11,
"footnotes": 7,
"references": 7
},
"actuals": {
"tables": 13,
"diagrams": 0,
"internalLinks": 42,
"externalLinks": 0,
"footnotes": 0,
"references": 20,
"quotesWithQuotes": 0,
"quotesTotal": 0,
"accuracyChecked": 0,
"accuracyTotal": 0
},
"items": {
"llmSummary": "green",
"schedule": "green",
"entity": "green",
"editHistory": "red",
"overview": "green",
"tables": "green",
"diagrams": "red",
"internalLinks": "green",
"externalLinks": "red",
"footnotes": "red",
"references": "green",
"quotes": "red",
"accuracy": "red"
},
"ratingsString": "N:4.5 R:6 A:6.5 C:7.5"
},
"readerRank": 138,
"researchRank": 35,
"recommendedScore": 184.21
}External Links
No external links
Backlinks (2)
| id | title | type | relationship |
|---|---|---|---|
| carlsmith-six-premises | Carlsmith's Six-Premise Argument | analysis | related |
| __index__/knowledge-base/models | Analytical Models | concept | — |