Skip to content
Longterm Wiki

Responsible Scaling Policies

rspapproachPath: /knowledge-base/responses/rsp/
E461Entity ID (EID)
← Back to page59 backlinksQuality: 62Updated: 2026-01-29
Page Recorddatabase.json — merged from MDX frontmatter + Entity YAML + computed metrics at build time
{
  "id": "rsp",
  "wikiId": "E461",
  "path": "/knowledge-base/responses/rsp/",
  "filePath": "knowledge-base/responses/rsp.mdx",
  "title": "Responsible Scaling Policies",
  "quality": 62,
  "readerImportance": 51,
  "researchImportance": 28,
  "tacticalValue": null,
  "contentFormat": "article",
  "causalLevel": null,
  "lastUpdated": "2026-01-29",
  "dateCreated": "2026-02-15",
  "summary": "Comprehensive analysis of Responsible Scaling Policies showing 20 companies with published frameworks as of Dec 2025, with SaferAI grading major policies 1.9-2.2/5 for specificity. Evidence suggests moderate effectiveness hindered by voluntary nature, competitive pressure among 3+ labs, and ~7-month capability doubling potentially outpacing evaluation science, though third-party verification (METR evaluated 5+ models) and Seoul Summit commitments (16 signatories) represent meaningful coordination progress.",
  "description": "Responsible Scaling Policies (RSPs) are voluntary commitments by AI labs to pause scaling when capability or safety thresholds are crossed.",
  "ratings": {
    "novelty": 4.2,
    "rigor": 6.8,
    "completeness": 7.3,
    "actionability": 6.5
  },
  "category": "responses",
  "subcategory": "alignment-policy",
  "clusters": [
    "ai-safety",
    "governance"
  ],
  "metrics": {
    "wordCount": 3422,
    "tableCount": 29,
    "diagramCount": 3,
    "internalLinks": 48,
    "externalLinks": 13,
    "footnoteCount": 0,
    "bulletRatio": 0.06,
    "sectionCount": 44,
    "hasOverview": true,
    "structuralScore": 15
  },
  "suggestedQuality": 100,
  "updateFrequency": 21,
  "evergreen": true,
  "wordCount": 3422,
  "unconvertedLinks": [
    {
      "text": "20 companies",
      "url": "https://metr.org/common-elements",
      "resourceId": "30b9f5e826260d9d",
      "resourceTitle": "METR: Common Elements of Frontier AI Safety Policies"
    },
    {
      "text": "METR",
      "url": "https://metr.org/",
      "resourceId": "45370a5153534152",
      "resourceTitle": "METR: Model Evaluation and Threat Research"
    },
    {
      "text": "SaferAI grades",
      "url": "https://www.safer-ai.org/anthropics-responsible-scaling-policy-update-makes-a-step-backwards",
      "resourceId": "a5e4c7b49f5d3e1b",
      "resourceTitle": "SaferAI: Anthropic's Responsible Scaling Policy Update Is a Step Backwards"
    },
    {
      "text": "20 companies",
      "url": "https://metr.org/common-elements",
      "resourceId": "30b9f5e826260d9d",
      "resourceTitle": "METR: Common Elements of Frontier AI Safety Policies"
    },
    {
      "text": "METR",
      "url": "https://metr.org/",
      "resourceId": "45370a5153534152",
      "resourceTitle": "METR: Model Evaluation and Threat Research"
    },
    {
      "text": "SaferAI grade",
      "url": "https://www.safer-ai.org/anthropics-responsible-scaling-policy-update-makes-a-step-backwards",
      "resourceId": "a5e4c7b49f5d3e1b",
      "resourceTitle": "SaferAI: Anthropic's Responsible Scaling Policy Update Is a Step Backwards"
    },
    {
      "text": "METR Common Elements",
      "url": "https://metr.org/common-elements",
      "resourceId": "30b9f5e826260d9d",
      "resourceTitle": "METR: Common Elements of Frontier AI Safety Policies"
    },
    {
      "text": "UK Gov",
      "url": "https://www.gov.uk/government/publications/frontier-ai-safety-commitments-ai-seoul-summit-2024",
      "resourceId": "944fc2ac301f8980",
      "resourceTitle": "Seoul Frontier AI Commitments"
    },
    {
      "text": "METR",
      "url": "https://metr.org/",
      "resourceId": "45370a5153534152",
      "resourceTitle": "METR: Model Evaluation and Threat Research"
    },
    {
      "text": "METR",
      "url": "https://metr.org/",
      "resourceId": "45370a5153534152",
      "resourceTitle": "METR: Model Evaluation and Threat Research"
    },
    {
      "text": "Anthropic RSP",
      "url": "https://www.anthropic.com/rsp-updates",
      "resourceId": "c6766d463560b923",
      "resourceTitle": "Anthropic pioneered the Responsible Scaling Policy"
    }
  ],
  "unconvertedLinkCount": 11,
  "convertedLinkCount": 42,
  "backlinkCount": 59,
  "hallucinationRisk": {
    "level": "medium",
    "score": 45,
    "factors": [
      "no-citations",
      "conceptual-content"
    ]
  },
  "entityType": "approach",
  "redundancy": {
    "maxSimilarity": 19,
    "similarPages": [
      {
        "id": "evals-governance",
        "title": "Evals-Based Deployment Gates",
        "path": "/knowledge-base/responses/evals-governance/",
        "similarity": 19
      },
      {
        "id": "model-auditing",
        "title": "Third-Party Model Auditing",
        "path": "/knowledge-base/responses/model-auditing/",
        "similarity": 18
      },
      {
        "id": "dangerous-cap-evals",
        "title": "Dangerous Capability Evaluations",
        "path": "/knowledge-base/responses/dangerous-cap-evals/",
        "similarity": 17
      },
      {
        "id": "evals",
        "title": "Evals & Red-teaming",
        "path": "/knowledge-base/responses/evals/",
        "similarity": 16
      },
      {
        "id": "seoul-declaration",
        "title": "Seoul AI Safety Summit Declaration",
        "path": "/knowledge-base/responses/seoul-declaration/",
        "similarity": 16
      }
    ]
  },
  "coverage": {
    "passing": 7,
    "total": 13,
    "targets": {
      "tables": 14,
      "diagrams": 1,
      "internalLinks": 27,
      "externalLinks": 17,
      "footnotes": 10,
      "references": 10
    },
    "actuals": {
      "tables": 29,
      "diagrams": 3,
      "internalLinks": 48,
      "externalLinks": 13,
      "footnotes": 0,
      "references": 5,
      "quotesWithQuotes": 0,
      "quotesTotal": 0,
      "accuracyChecked": 0,
      "accuracyTotal": 0
    },
    "items": {
      "summary": "green",
      "schedule": "green",
      "entity": "green",
      "editHistory": "red",
      "overview": "green",
      "tables": "green",
      "diagrams": "green",
      "internalLinks": "green",
      "externalLinks": "amber",
      "footnotes": "red",
      "references": "amber",
      "quotes": "red",
      "accuracy": "red"
    },
    "ratingsString": "N:4.2 R:6.8 A:6.5 C:7.3"
  },
  "readerRank": 293,
  "researchRank": 430,
  "recommendedScore": 163.02
}
External Links
{
  "lesswrong": "https://www.lesswrong.com/tag/responsible-scaling-policies"
}
Backlinks (59)
idtitletyperelationship
solutionsAI Safety Solution Cruxescrux
eval-saturationEval Saturation & The Evals Gapapproach
dangerous-cap-evalsDangerous Capability Evaluationsapproach
evaluationAI Evaluationapproach
capability-unlearningCapability Unlearning / Removalapproach
intervention-portfolioAI Safety Intervention Portfolioapproach
evals-governanceEvals-Based Deployment Gatesapproach
corporateCorporate AI Safety Responsesapproach
pausePause Advocacyapproach
model-registriesModel Registriesconcept
whistleblower-protectionsAI Whistleblower Protectionspolicy
codingAutonomous Codingcapability
language-modelsLarge Language Modelscapability
long-horizonLong-Horizon Autonomous Taskscapability
self-improvementSelf-Improvement and Recursive Enhancementcapability
accident-risksAI Accident Risk Cruxescrux
pause-debateShould We Pause AI Development?crux
why-alignment-hardWhy Alignment Might Be Hardargument
agi-developmentAGI Developmentconcept
__index__/knowledge-base/historyHistoryconcept
anthropic-impactAnthropic Impact Assessment Modelanalysis
carlsmith-six-premisesCarlsmith's Six-Premise Argumentanalysis
compounding-risks-analysisCompounding Risks Analysisanalysis
corrigibility-failure-pathwaysCorrigibility Failure Pathwaysanalysis
defense-in-depth-modelDefense in Depth Modelanalysis
intervention-effectiveness-matrixIntervention Effectiveness Matrixanalysis
intervention-timing-windowsIntervention Timing Windowsanalysis
safety-spending-at-scaleSafety Spending at Scaleanalysis
short-timeline-policy-implicationsShort Timeline Policy Implicationsanalysis
anthropic-ipoAnthropic IPOanalysis
arcAlignment Research Center (ARC)organization
deepmindGoogle DeepMindorganization
labs-overviewFrontier AI Labs (Overview)concept
long-term-benefit-trustAnthropic Long-Term Benefit Trustorganization
metrMETRorganization
dario-amodeiDario Amodeiperson
elon-muskElon Muskperson
alignment-policy-overviewPolicy & Governance (Overview)concept
coordination-techAI Governance Coordination Technologiesapproach
corporate-influenceCorporate Influence on AI Policycrux
evaluation-awarenessEvaluation Awarenessapproach
governance-overviewAI Governance & Policy (Overview)concept
governance-policyAI Governance and Policycrux
__index__/knowledge-base/responsesSafety Responsesconcept
model-specAI Model Specificationsapproach
red-teamingRed Teamingresearch-area
technical-researchTechnical AI Safety Researchcrux
bioweaponsBioweaponsrisk
corrigibility-failureCorrigibility Failurerisk
cyberweaponsCyberweaponsrisk
deceptive-alignmentDeceptive Alignmentrisk
emergent-capabilitiesEmergent Capabilitiesrisk
erosion-of-agencyErosion of Human Agencyrisk
instrumental-convergenceInstrumental Convergencerisk
lock-inAI Value Lock-inrisk
rogue-ai-scenariosRogue AI Scenariosrisk
sandbaggingAI Capability Sandbaggingrisk
schemingSchemingrisk
sharp-left-turnSharp Left Turnrisk
Longterm Wiki