AI Risk Activation Timeline Model

risk-activation-timeline (E255)

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  "id": "risk-activation-timeline",
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  "title": "AI Risk Activation Timeline Model",
  "description": "This model maps when risks become critical based on capability levels. Near-term risks activate at current capabilities; transformative risks require advanced autonomous systems.",
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      "value": "Risks activate at different times based on capability thresholds"
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Backlinks (2)

id	title	type	relationship
capability-threshold-model	AI Capability Threshold Model	model	related
warning-signs-model	AI Risk Warning Signs Model	model	related

Frontmatter

{
  "title": "Risk Activation Timeline Model",
  "description": "A systematic framework mapping when different AI risks become critical based on capability thresholds, deployment contexts, and barrier erosion. Maps current active risks, near-term activation windows (2025-2027), and long-term existential risks, with specific probability assessments and intervention windows.",
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  "llmSummary": "Comprehensive framework mapping AI risk activation windows with specific probability assessments: current risks already active (disinformation 95%+, spear phishing active), near-term critical window 2025-2027 (bioweapons 50% by 2027, cyberweapons 75%), long-term existential risks 2030-2050+ (ASI misalignment 15% by 2030). Recommends $3-5B annual investment in Tier 1 interventions with specific allocations: $200-400M bioweapons screening, $300-600M interpretability, $500M-1B cyber-defense.",
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Raw MDX Source

---
title: Risk Activation Timeline Model
description: A systematic framework mapping when different AI risks become critical based on capability thresholds, deployment contexts, and barrier erosion. Maps current active risks, near-term activation windows (2025-2027), and long-term existential risks, with specific probability assessments and intervention windows.
sidebar:
  order: 15
quality: 66
ratings:
  focus: 8.5
  novelty: 6
  rigor: 6.5
  completeness: 8
  concreteness: 7.5
  actionability: 7
lastEdited: "2025-12-26"
importance: 82.5
update_frequency: 90
llmSummary: "Comprehensive framework mapping AI risk activation windows with specific probability assessments: current risks already active (disinformation 95%+, spear phishing active), near-term critical window 2025-2027 (bioweapons 50% by 2027, cyberweapons 75%), long-term existential risks 2030-2050+ (ASI misalignment 15% by 2030). Recommends $3-5B annual investment in Tier 1 interventions with specific allocations: $200-400M bioweapons screening, $300-600M interpretability, $500M-1B cyber-defense."
todos:
  - Complete 'Conceptual Framework' section
  - Complete 'Quantitative Analysis' section (8 placeholders)
clusters:
  - ai-safety
  - governance
subcategory: timeline-models
entityType: model
---
import {DataInfoBox, R, EntityLink} from '@components/wiki';

<DataInfoBox entityId="E255" ratings={frontmatter.ratings} />

## Overview

Different AI risks don't all "turn on" at the same time - they activate based on capability thresholds, deployment contexts, and barrier erosion. This model systematically maps when various AI risks become critical, enabling strategic resource allocation and intervention timing.

The model reveals three critical insights: many serious risks are already active with current systems, the next 2-3 years represent a critical activation window for multiple high-impact risks, and long-term existential risks require foundational research investment now despite uncertain timelines.

Understanding activation timing enables prioritizing immediate interventions for active risks, preparing defenses for near-term thresholds, and building foundational capacity for long-term challenges before crisis mode sets in.

## Risk Assessment Overview

| Risk Category | Timeline | Severity Range | Current Status | Intervention Window |
|---------------|----------|----------------|----------------|-------------------|
| **Current Active** | 2020-2024 | Medium-High | Multiple risks active | Closing rapidly |
| **Near-term Critical** | 2025-2027 | High-Extreme | Approaching thresholds | Open but narrowing |
| **Long-term Existential** | 2030-2050+ | Extreme-Catastrophic | Early warning signs | Wide but requires early action |
| **Cascade Effects** | Ongoing | Amplifies all categories | Accelerating | Immediate intervention needed |

## Risk Activation Framework

### Activation Criteria

| Criterion | Description | Example Threshold |
|-----------|-------------|-------------------|
| **Capability Crossing** | AI can perform necessary tasks | GPT-4 level code generation for cyberweapons |
| **Deployment Context** | Systems deployed in relevant settings | Autonomous agents with internet access |
| **Barrier Erosion** | Technical/social barriers removed | Open-source parity reducing control |
| **Incentive Alignment** | Actors motivated to exploit | Economic pressure + accessible tools |

### Progress Tracking Methodology

We assess progress toward activation using:
- **Technical benchmarks** from <EntityLink id="E201">evaluation organizations</EntityLink>
- **Deployment indicators** from major AI labs
- **Adversarial use cases** documented in security research
- **<EntityLink id="E132">Expert opinion</EntityLink> surveys** on capability timelines

## Current Risks (Already Active)

### Category: Misuse Risks

| Risk | Status | Current Evidence | Impact Scale | Source |
|------|--------|------------------|--------------|--------|
| **<EntityLink id="E102">Disinformation</EntityLink> at scale** | Active | 2024 election manipulation campaigns | \$1-10B annual | <R id="c35d3ac5a51bb42a">Reuters</R> |
| **Spear phishing enhancement** | Active | 82% higher believability vs human-written | \$10B+ annual losses | <R id="49990480779d6486">IBM Security</R> |
| **Code vulnerability exploitation** | Partially active | GPT-4 identifies 0-days, limited autonomy | Medium severity | <R id="0116b24a50f52f44"><EntityLink id="E22">Anthropic</EntityLink> evals</R> |
| **Academic fraud** | Active | 30-60% of student submissions flagged | Education integrity crisis | <R id="e11b8206d307690a">Stanford study</R> |
| **Romance/financial scams** | Active | AI voice cloning in elder fraud | \$1B+ annual | <R id="8f7eda84e4f5d1fe">FTC reports</R> |

### Category: Structural Risks

| Risk | Status | Current Evidence | Impact Scale | Trend |
|------|--------|------------------|--------------|-------|
| **<EntityLink id="E119">Epistemic erosion</EntityLink>** | Active | 40% decline in information trust | Society-wide | Accelerating |
| **Economic displacement** | Beginning | 15% of customer service roles automated | 200M+ jobs at risk | Expanding |
| **Attention manipulation** | Active | Algorithm-driven engagement optimization | Mental health crisis | Intensifying |
| **Dependency formation** | Active | 60% productivity loss when tools unavailable | Skill atrophy beginning | Growing |

### Category: Technical Risks

| Risk | Status | Current Evidence | Mitigation Level | Progress |
|------|--------|------------------|------------------|---------|
| **<EntityLink id="E253">Reward hacking</EntityLink>** | Active | Documented in all <EntityLink id="E259">RLHF</EntityLink> systems | Partial guardrails | No clear progress |
| **<EntityLink id="E295">Sycophancy</EntityLink>** | Active | Models agree with user regardless of truth | Research stage | Limited progress |
| **Prompt injection** | Active | Jailbreaks succeed >50% of time | Defense research ongoing | Cat-mouse game |
| **Hallucination/confabulation** | Active | 15-30% false information in outputs | Detection tools emerging | Gradual improvement |

## Near-Term Risks (2025-2027 Activation Window)

### Critical Misuse Risks

| Risk | Activation Window | Key Threshold | Current Progress | Intervention Status |
|------|-------------------|---------------|------------------|-------------------|
| **<EntityLink id="E42">Bioweapons</EntityLink> uplift** | 2025-2028 | Synthesis guidance beyond textbooks | 60-80% to threshold | <R id="0da4b74079267c7e">Active screening efforts</R> |
| **<EntityLink id="E86">Cyberweapon</EntityLink> development** | 2025-2027 | Autonomous 0-day discovery | 70-85% to threshold | Limited defensive preparation |
| **<EntityLink id="E224">Persuasion</EntityLink> weapons** | 2025-2026 | Personalized, adaptive manipulation | 80-90% to threshold | No systematic defenses |
| **Mass deepfake attacks** | Active-2026 | Real-time, undetectable generation | 85-95% to threshold | <R id="1b84ee261c3a68d3">Detection research lagging</R> |

### Control and Alignment Risks

| Risk | Activation Window | Key Threshold | Current Progress | Research Investment |
|------|-------------------|---------------|------------------|-------------------|
| **<EntityLink id="E2">Agentic system</EntityLink> failures** | 2025-2026 | Multi-step autonomous task execution | 70-80% to threshold | \$500M+ annually |
| **<EntityLink id="E282">Situational awareness</EntityLink>** | 2025-2027 | Strategic self-modeling capability | 50-70% to threshold | Research accelerating |
| **<EntityLink id="E270">Sandbagging</EntityLink> on evals** | 2026-2028 | Concealing capabilities from evaluators | 40-60% to threshold | Limited detection work |
| **Human oversight evasion** | 2026-2029 | Identifying and exploiting oversight gaps | 30-50% to threshold | Control research beginning |

### Structural Transformation Risks

| Risk | Activation Window | Key Threshold | Economic Impact | Policy Preparation |
|------|-------------------|---------------|-----------------|-------------------|
| **Mass unemployment crisis** | 2026-2030 | >10% of jobs automatable within 2 years | \$5-15T GDP impact | Minimal policy frameworks |
| **<EntityLink id="E27">Authentication collapse</EntityLink>** | 2025-2027 | Can't distinguish human vs AI content | Democratic processes at risk | <R id="ff89bed1f7960ab2">Technical solutions emerging</R> |
| **AI-powered surveillance state** | 2025-2028 | Real-time behavior prediction | Human rights implications | Regulatory gaps |
| **<EntityLink id="E133">Expertise atrophy</EntityLink>** | 2026-2032 | Human skills erode from AI dependence | Innovation capacity loss | No systematic response |

## Long-Term Risks (ASI-Level Requirements)

### Existential Risk Category

| Risk | Estimated Window | Key Capability Threshold | Confidence Level | Research Investment |
|------|------------------|-------------------------|------------------|-------------------|
| **<EntityLink id="E204">Misaligned superintelligence</EntityLink>** | 2030-2050+ | Systems exceed human-level at alignment-relevant tasks | Very Low | \$1B+ annually |
| **<EntityLink id="E278">Recursive self-improvement</EntityLink>** | 2030-2045+ | AI meaningfully improves AI architecture | Low | Limited research |
| **Decisive strategic advantage** | 2030-2040+ | Single actor gains insurmountable technological lead | Low | Policy research only |
| **Irreversible <EntityLink id="E632">value lock-in</EntityLink>** | 2028-2040+ | Permanent commitment to suboptimal human values | Low-Medium | Philosophy/governance research |

### Advanced Deception and Control

| Risk | Estimated Window | Capability Requirement | Detection Difficulty | Mitigation Research |
|------|------------------|----------------------|---------------------|-------------------|
| **<EntityLink id="E274">Strategic deception</EntityLink>** | 2027-2035 | Model training dynamics and hide intentions | Very High | <EntityLink id="E174">Interpretability research</EntityLink> |
| **Coordinated AI systems** | 2028-2040 | Multiple AI systems coordinate against humans | High | <EntityLink id="E488">Multi-agent safety</EntityLink> research |
| **Large-scale human manipulation** | 2028-2035 | Accurate predictive models of human behavior | Medium | Social science integration |
| **Critical infrastructure control** | 2030-2050+ | Simultaneous control of multiple key systems | Very High | Air-gapped research |

## Risk Interaction and Cascade Effects

### Cascade Amplification Matrix

| Triggering Risk | Amplifies | Mechanism | Timeline Impact |
|-----------------|-----------|-----------|-----------------|
| **Disinformation <EntityLink id="E232">proliferation</EntityLink>** | <EntityLink id="E119">Epistemic collapse</EntityLink> | Trust erosion accelerates | -1 to -2 years |
| **Cyberweapon autonomy** | <EntityLink id="E27">Authentication collapse</EntityLink> | Digital infrastructure vulnerability | -1 to -3 years |
| **Bioweapons accessibility** | Authoritarian control | Crisis enables power concentration | Variable |
| **Economic displacement** | Social instability | Reduces governance capacity | -0.5 to -1.5 years |
| **Any major AI incident** | Regulatory capture | Crisis mode enables bad policy | -2 to -5 years |

### Acceleration Factors

| Factor | Timeline Impact | Probability by 2027 | Evidence |
|--------|----------------|-------------------|----------|
| **Algorithmic breakthrough** | -1 to -3 years across categories | 15-30% | Historical ML progress |
| **10x compute scaling** | -0.5 to -1.5 years | 40-60% | <R id="d1c7d3fe408d3988">Current compute trends</R> |
| **Open-source capability parity** | -1 to -2 years on misuse risks | 50-70% | <R id="519d45a8450736f6">Open model progress</R> |
| **Geopolitical AI arms race** | -0.5 to -2 years overall | 30-50% | US-China competition intensifying |
| **Major safety failure/incident** | Variable, enables governance | 20-40% | Base rate of tech failures |

### Deceleration Factors

| Factor | Timeline Impact | Probability by 2030 | Feasibility |
|--------|----------------|-------------------|-------------|
| **Scaling laws plateau** | +2 to +5 years | 15-30% | Some evidence emerging |
| **Strong international <EntityLink id="E608">AI governance</EntityLink>** | +1 to +3 years on misuse | 10-20% | Limited progress so far |
| **Major alignment breakthrough** | Variable positive impact | 10-25% | Research uncertainty high |
| **Physical compute constraints** | +0.5 to +2 years | 20-35% | Semiconductor bottlenecks |
| **Economic/energy limitations** | +1 to +3 years | 15-25% | Training cost growth |

## Critical Intervention Windows

### Time-Sensitive Priority Matrix

| Risk Category | Window Opens | Window Closes | Intervention Cost | Effectiveness if Delayed |
|---------------|--------------|---------------|-------------------|----------------------|
| **Bioweapons screening** | 2020 (missed) | 2027 | \$500M-1B | 50% reduction |
| **Cyber defensive AI** | 2023 | 2026 | \$1-3B | 70% reduction |
| **Authentication infrastructure** | 2024 | 2026 | \$300-600M | 30% reduction |
| **AI control research** | 2022 | 2028 | \$1-2B annually | 20% reduction |
| **International governance** | 2023 | 2027 | \$200-500M | 80% reduction |
| **Alignment foundations** | 2015 | 2035+ | \$2-5B annually | Variable |

### Leverage Analysis by Intervention Type

| Intervention Category | Current Leverage | Peak Leverage Window | Investment Required | Expected Impact |
|----------------------|------------------|-------------------|-------------------|-----------------|
| **DNA synthesis screening** | High | 2024-2027 | \$100-300M globally | Delays bio threshold 2-3 years |
| **Model evaluation standards** | Medium | 2024-2026 | \$50-150M annually | Enables risk detection |
| **Interpretability breakthroughs** | Very High | 2024-2030 | \$500M-1B annually | Addresses multiple long-term risks |
| **Defensive cyber-AI** | Medium | 2024-2026 | \$1-2B | Extends defensive advantage |
| **Public authentication systems** | High | 2024-2026 | \$200-500M | Preserves <EntityLink id="E122">epistemic infrastructure</EntityLink> |
| **International AI treaties** | Very High | 2024-2027 | \$100-200M | Sets precedent for future governance |

## Probability Calibration Over Time

### Risk Activation Probabilities by Year

| Risk Category | 2025 | 2027 | 2030 | 2035 | 2040 |
|---------------|------|------|------|------|------|
| **Mass disinformation** | 95% (active) | 99% | 99% | 99% | 99% |
| **Bioweapons uplift (meaningful)** | 25% | 50% | 70% | 85% | 95% |
| **Autonomous cyber operations** | 40% | 75% | 90% | 99% | 99% |
| **Large-scale job displacement** | 15% | 40% | 65% | 85% | 95% |
| **Authentication crisis** | 30% | 60% | 80% | 95% | 99% |
| **Agentic AI control failures** | 35% | 70% | 90% | 99% | 99% |
| **Meaningful situational awareness** | 20% | 50% | 75% | 90% | 95% |
| **Strategic AI deception** | 5% | 20% | 45% | 70% | 85% |
| **ASI-level misalignment** | \&lt;1% | 3% | 15% | 35% | 55% |

### Uncertainty Ranges and Expert Disagreement

| Risk | Optimistic Timeline | Median | Pessimistic Timeline | Expert Confidence |
|------|-------------------|--------|-------------------|------------------|
| **Cyberweapon autonomy** | 2028-2030 | 2025-2027 | 2024-2025 | Medium (70% within range) |
| **Bioweapons threshold** | 2030-2035 | 2026-2029 | 2024-2026 | Low (50% within range) |
| **Mass unemployment** | 2035-2040 | 2028-2032 | 2025-2027 | Very Low (30% within range) |
| **Superintelligence** | 2045-Never | 2030-2040 | 2027-2032 | Very Low (20% within range) |

## Strategic Resource Allocation

### Investment Priority Framework

| Priority Tier | Timeline | Investment Level | Rationale |
|---------------|----------|-----------------|-----------|
| **Tier 1: Critical** | Immediate-2027 | \$3-5B annually | Window closing rapidly |
| **Tier 2: Important** | 2025-2030 | \$1-2B annually | Foundation for later risks |
| **Tier 3: Foundational** | 2024-2035+ | \$500M-1B annually | Long-term preparation |

### Recommended Investment Allocation

| Research Area | Annual Investment | Justification | Expected ROI |
|---------------|-------------------|---------------|--------------|
| **Bioweapons screening infrastructure** | \$200-400M (2024-2027) | Critical window closing | Very High - prevents catastrophic risk |
| **AI interpretability research** | \$300-600M ongoing | Multi-risk mitigation | High - enables control across scenarios |
| **Cyber-defense AI systems** | \$500M-1B (2024-2026) | Maintaining defensive advantage | Medium-High |
| **Authentication/verification tech** | \$100-200M (2024-2026) | Preserving epistemic infrastructure | High |
| **International governance capacity** | \$100-200M (2024-2027) | Coordination before crisis | Very High - prevents race dynamics |
| **AI control methodology** | \$400-800M ongoing | Bridge to long-term safety | High |
| **Economic transition planning** | \$200-400M (2024-2030) | Social stability preservation | Medium |

## Key Cruxes and Uncertainties

### Timeline Uncertainty Analysis

| Core Uncertainty | If Optimistic | If Pessimistic | Current Best Estimate | Implications |
|------------------|---------------|----------------|---------------------|--------------|
| **Scaling law continuation** | Plateau by 2027-2030 | Continue through 2035+ | 60% likely to continue | ±3 years on all timelines |
| **Open-source capability gap** | Maintains 2+ year lag | Achieves parity by 2026 | 55% chance of rapid catch-up | ±2 years on misuse risks |
| **Alignment research progress** | Major breakthrough by 2030 | Limited progress through 2035 | 20% chance of breakthrough | ±5-10 years on existential risk |
| **Geopolitical cooperation** | Successful AI treaties | Intensified arms race | 25% chance of cooperation | ±2-5 years on multiple risks |
| **Economic adaptation speed** | Smooth transition over 10+ years | Rapid displacement over 3-5 years | 40% chance of rapid displacement | Social stability implications |

### Research and Policy Dependencies

| Dependency | Success Probability | Impact if Failed | Mitigation Options |
|------------|-------------------|------------------|-------------------|
| **International bioweapons screening** | 60% | Bioweapons threshold advances 2-3 years | National screening systems, detection research |
| **<EntityLink id="E447">AI evaluation</EntityLink> standardization** | 40% | Reduced early warning capability | Industry self-regulation, government mandates |
| **Interpretability breakthroughs** | 30% | Limited control over advanced systems | Multiple research approaches, AI-assisted research |
| **Democratic governance adaptation** | 35% | Poor quality regulation during crisis | Early capacity building, expert networks |

## Implications for Different Stakeholders

### For AI Development Organizations

**Immediate priorities (2024-2025):**
- Implement robust evaluations for <EntityLink id="E394">near-term risks</EntityLink>
- Establish safety teams scaling with capability teams
- Contribute to industry evaluation standards

**Near-term preparations (2025-2027):**
- Deploy monitoring systems for newly activated risks
- Engage constructively in governance frameworks
- Research control methods before needed

### For Policymakers

**Critical window actions:**
- Establish regulatory frameworks before crisis mode
- Focus on near-term risks to build governance credibility
- Invest in <EntityLink id="E470">international coordination mechanisms</EntityLink>

**Priority areas:**
1. Bioweapons screening infrastructure
2. AI evaluation and monitoring standards
3. Economic transition support systems
4. Authentication and verification requirements

### For Safety Researchers

**Optimal portfolio allocation:**
- **40%** near-term (1-2 generation) risk mitigation
- **40%** foundational research for long-term risks  
- **20%** current risk mitigation and response

**High-leverage research areas:**
1. <EntityLink id="E174">Interpretability</EntityLink> for multiple risk categories
2. <EntityLink id="E6">AI control</EntityLink> methodology development
3. Evaluation methodology for emerging capabilities
4. Social science integration for structural risks

### For Civil Society Organizations

**Advocacy priorities:**
- Demand transparency in capability evaluations
- Push for public interest representation in governance
- Support authentication infrastructure development
- Advocate for economic transition policies

## Limitations and Model Uncertainty

### Methodological Limitations

| Limitation | Impact on Accuracy | Mitigation Strategies |
|------------|-------------------|----------------------|
| **Expert overconfidence** | Timelines may be systematically early/late | Multiple forecasting methods, base rate reference |
| **Capability discontinuities** | Sudden activation possible | Broader uncertainty ranges, multiple scenarios |
| **Interaction complexity** | Cascade effects poorly understood | Systems modeling, historical analogies |
| **Adversarial adaptation** | Defenses may fail faster than expected | Red team exercises, worst-case planning |

### Areas for Model Enhancement

1. **Better cascade modeling** - More sophisticated interaction effects
2. **Adversarial dynamics** - How attackers adapt to defenses
3. **Institutional response capacity** - How organizations adapt to new risks
4. **Cross-cultural variation** - Risk manifestation in different contexts
5. **Economic feedback loops** - How risk realization affects development

## Sources & Resources

### Primary Research Sources

| Organization | Type | Key Contributions |
|--------------|------|-------------------|
| <R id="0116b24a50f52f44">Anthropic</R> | AI Lab | Risk evaluation methodologies, scaling policies |
| <R id="431d6df5aeacc896"><EntityLink id="E218">OpenAI</EntityLink></R> | AI Lab | Preparedness framework, capability assessment |
| <R id="45370a5153534152">METR</R> | Evaluation Org | Technical capability evaluations |
| <R id="cf5fd74e8db11565">RAND Corporation</R> | Think Tank | Policy analysis, national security implications |
| <R id="a306e0b63bdedbd5"><EntityLink id="E47">Center for AI Safety</EntityLink></R> | Safety Org | Risk taxonomy, expert opinion surveys |

### Academic Literature

| Paper | Authors | Key Finding |
|-------|---------|-------------|
| <R id="490028792929073c">Model evaluation for extreme risks</R> | Anthropic <EntityLink id="E451">Constitutional AI</EntityLink> Team | Evaluation frameworks for dangerous capabilities |
| <R id="5015ce6023c3cf9c">AI timelines and capabilities</R> | Various forecasting research | Capability development trajectories |
| <R id="f5e827d2d86f0b9c">Cybersecurity implications of AI</R> | <EntityLink id="E524">CSET</EntityLink> | Near-term cyber risk assessment |

### Policy and Governance Sources

| Source | Type | Focus Area |
|--------|------|------------|
| <R id="54dbc15413425997"><EntityLink id="E216">NIST AI Risk Management Framework</EntityLink></R> | Government Standard | Risk management methodology |
| <R id="1102501c88207df3"><EntityLink id="E127">EU AI Act</EntityLink></R> | Regulation | Comprehensive AI governance framework |
| <R id="254bcdc7bfcdcd73">UK AI Safety Summit Outcomes</R> | International | Multi-stakeholder coordination |

### Expert Opinion and Forecasting

| Platform | Type | Use Case |
|----------|------|----------|
| <R id="248087ef55725b11"><EntityLink id="E199">Metaculus</EntityLink> AI forecasts</R> | Prediction Market | Quantitative timeline estimates |
| <R id="38eba87d0a888e2e">Expert Survey on AI Risk</R> | Academic Survey | Expert opinion distribution |
| <R id="d6955ff937bf386d"><EntityLink id="E140">Future of Humanity Institute</EntityLink> reports</R> | Research Institute | Long-term risk analysis |

## Related Models and Cross-References

### Complementary Risk Models

- <EntityLink id="E53" /> - Specific capability requirements for risk activation
- <EntityLink id="E43">Bioweapons AI Uplift Model</EntityLink> - Detailed biological weapons timeline
- <EntityLink id="E87" label="Cyberweapons Attack Automation" /> - Cyber capability development
- <EntityLink id="E28" label="Authentication Collapse Timeline" /> - Digital verification crisis
- Economic Disruption Impact - Labor market transformation

### Risk Category Cross-References

- Accident Risks - Technical AI safety failures
- Misuse Risks - Intentional harmful applications  
- Structural Risks - Systemic societal impacts
- Epistemic Risks - Information environment degradation

### Response Strategy Integration

- Governance Responses - Policy intervention strategies
- Technical Safety Research - Engineering solutions
- International Coordination - Global cooperation frameworks