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Lock-in Probability Model

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Last edited:2025-12-29 (9 days ago)
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LLM Summary:Quantitative model estimating lock-in probabilities across different scenarios, with a combined 10-30% chance of significant lock-in by 2050. Provides timeline analysis and scenario comparison for policy prioritization.
Model

Lock-in Mechanisms Model

Importance72
Related
Risks

Overview

Section titled “Overview”

This model provides a quantitative framework for assessing AI-enabled lock-in risk, complementing the comprehensive mechanism analysis in Lock-in Risk.

For detailed coverage of mechanisms, current trends, and responses, see Lock-in Risk.

Probability Estimates by Scenario

Section titled “Probability Estimates by Scenario”

The following probability estimates draw on expert assessments from Future of Life Institute↗, EA Forum analyses↗, and Future of Humanity Institute↗ research:

ScenarioProbability by 2050Duration if RealizedKey DriversReversibility Window
Totalitarian surveillance state5-15%Potentially indefiniteAI-enhanced monitoring, predictive policing, autonomous enforcement5-10 years before fully entrenched
Value lock-in via AI training10-20%Centuries to millenniaConstitutional AI approaches, training data choices, RLHF value embedding↗3-7 years during development phase
Economic power concentration15-25%Decades to centuriesNetwork effects, compute monopoly↗, data advantages10-20 years with antitrust action
Geopolitical lock-in10-20%Decades to centuriesFirst-mover AI advantages, regulatory captureUncertain, depends on coordination
Aligned singleton (positive)5-10%IndefiniteSuccessful alignment, beneficial governanceN/A (desirable outcome)
Misaligned AI takeover2-10%PermanentDeceptive alignment, capability overhangDays to weeks at critical juncture

Note: These ranges reflect significant uncertainty. The stable totalitarianism analysis↗ suggests extreme scenarios may be below 1%, while other researchers place combined lock-in risk at 10-30%.

Risk Factor Framework

Section titled “Risk Factor Framework”
Risk FactorMechanismAI AmplificationReversibility
Enforcement capabilityAutonomous systems maintain control10-100x more comprehensive surveillance; no human defection riskVery Low
Path dependenceEarly choices constrain future optionsFaster deployment cycles compress decision windowsLow
Network effectsSystems become more valuable as adoption growsAI models compound advantages via data and computeLow-Medium
Value embeddingPreferences encoded during development persistConstitutional AI approaches embed values during trainingMedium
Complexity barriersSystem understanding requires specialized expertiseAI systems may become inscrutable even to developersVery Low

Timeline Indicators

Section titled “Timeline Indicators”

The IMD AI Safety Clock↗ tracks lock-in urgency:

DateClock PositionKey Developments
September 202429 minutes to midnightClock launched
December 202426 minutesAGI timeline acceleration
February 202524 minutesCalifornia SB 1047 vetoed
September 202520 minutesAgentic AI proliferation

The nine-minute advance in one year reflects compressed decision timelines.

Model Limitations

Section titled “Model Limitations”

This framework cannot capture:

  • Novel lock-in pathways not yet identified
  • Interaction effects between scenarios
  • Tail risks from capability discontinuities
  • Political feasibility of interventions

For intervention analysis, see Lock-in Risk: Responses.

Sources

Section titled “Sources”