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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
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  "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.",
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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—