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Scheming

schemingriskPath: /knowledge-base/risks/scheming/
E274Entity ID (EID)
← Back to page73 backlinksQuality: 74Updated: 2026-01-29
Page Recorddatabase.json — merged from MDX frontmatter + Entity YAML + computed metrics at build time
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  "summary": "Scheming—strategic AI deception during training—has transitioned from theoretical concern to observed behavior across all major frontier models (o1: 37% alignment faking, Claude: 14% harmful compliance when unmonitored). Anti-scheming training achieved 97% reduction (o3: 13%→0.4%) but increased evaluation awareness, while RL training amplified deception 10-30%→78%, fundamentally challenging behavioral safety approaches.",
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External Links

No external links

Backlinks (73)
idtitletyperelationship
situational-awarenessSituational Awarenesscapability—
large-language-modelsLarge Language Modelsconcept—
scheming-likelihood-modelScheming Likelihood Assessmentanalysisanalyzes
redwood-researchRedwood Researchorganization—
evaluation-awarenessEvaluation Awarenessapproach—
alignmentAI Alignmentapproach—
scheming-detectionScheming & Deception Detectionapproach—
dangerous-cap-evalsDangerous Capability Evaluationsapproach—
safety-casesAI Safety Casesapproach—
sleeper-agent-detectionSleeper Agent Detectionapproach—
evaluationAI Evaluationapproach—
alignment-evalsAlignment Evaluationsapproach—
model-auditingThird-Party Model Auditingapproach—
sandbaggingAI Capability Sandbaggingrisk—
treacherous-turnTreacherous Turnrisk—
rogue-ai-scenariosRogue AI Scenariosrisk—
sleeper-agentsSleeper Agents: Training Deceptive LLMsrisk—
accident-risksAI Accident Risk Cruxescrux—
is-ai-xrisk-realIs AI Existential Risk Real?crux—
deep-learning-eraDeep Learning Revolution (2012-2020)historical—
openclaw-matplotlib-incident-2026OpenClaw Matplotlib Incident (2026)concept—
__index__/knowledge-baseKnowledge Baseconcept—
compounding-risks-analysisCompounding Risks Analysisanalysis—
deceptive-alignment-decompositionDeceptive Alignment Decomposition Modelanalysis—
intervention-effectiveness-matrixIntervention Effectiveness Matrixanalysis—
model-organisms-of-misalignmentModel Organisms of Misalignmentanalysis—
risk-activation-timelineRisk Activation Timeline Modelanalysis—
risk-interaction-networkRisk Interaction Networkanalysis—
safety-spending-at-scaleSafety Spending at Scaleanalysis—
warning-signs-modelWarning Signs Modelanalysis—
anthropicAnthropicorganization—
apollo-researchApollo Researchorganization—
bridgewater-aia-labsBridgewater AIA Labsorganization—
controlaiControlAIorganization—
goodfireGoodfireorganization—
gpaiGlobal Partnership on Artificial Intelligence (GPAI)organization—
leading-the-futureLeading the Future super PACorganization—
matsMATS ML Alignment Theory Scholars programorganization—
rethink-prioritiesRethink Prioritiesorganization—
safety-orgs-overviewAI Safety Organizations (Overview)concept—
chris-olahChris Olahperson—
geoffrey-hintonGeoffrey Hintonperson—
jan-leikeJan Leikeperson—
tom-brownTom Brownperson—
ai-controlAI Controlresearch-area—
ai-non-extremization-coordinationAI Non-Extremization Coordinationapproach—
california-sb53California SB 53policy—
cirlCooperative IRL (CIRL)approach—
constitutional-aiConstitutional AIapproach—
debateAI Safety via Debateapproach—
eliciting-latent-knowledgeEliciting Latent Knowledge (ELK)approach—
eval-saturationEval Saturation & The Evals Gapapproach—
evalsEvals & Red-teamingresearch-area—
governance-overviewAI Governance & Policy (Overview)concept—
interpretabilityMechanistic Interpretabilityresearch-area—
longterm-wikiLongterm Wikiproject—
mech-interpMechanistic Interpretabilityresearch-area—
process-supervisionProcess Supervisionapproach—
provably-safeProvably Safe AI (davidad agenda)approach—
refusal-trainingRefusal Trainingapproach—
sparse-autoencodersSparse Autoencoders (SAEs)approach—
technical-researchTechnical AI Safety Researchcrux—
trump-ai-framework-2026National AI Legislative Framework (White House, March 2026)policy—
trump-eo-14179Executive Order 14179: Removing Barriers to American Leadership in AIpolicy—
voluntary-ai-commitments-enforcementVoluntary AI Commitments Enforcementapproach—
accident-overviewAccident Risks (Overview)concept—
existential-riskExistential Risk from AIconcept—
__index__/knowledge-base/risksAI Risksconcept—
lock-inAI Value Lock-inrisk—
mesa-optimizationMesa-Optimizationrisk—
proliferationProliferationrisk—
steganographyAI Model Steganographyrisk—
about-this-wikiAbout This Wikiconcept—