Transition Turbulence

{
  "id": "factors-transition-turbulence-overview",
  "numericId": "E668",
  "path": "/ai-transition-model/factors-transition-turbulence-overview/",
  "filePath": "ai-transition-model/factors-transition-turbulence-overview.mdx",
  "title": "Transition Turbulence",
  "quality": null,
  "importance": null,
  "contentFormat": "article",
  "tractability": null,
  "neglectedness": null,
  "uncertainty": null,
  "causalLevel": null,
  "lastUpdated": "2026-01-03",
  "llmSummary": null,
  "structuredSummary": null,
  "description": "Root factor measuring disruption during the AI transition. High turbulence increases risk across all scenarios.",
  "ratings": null,
  "category": "ai-transition-model",
  "subcategory": "factors-transition-turbulence",
  "clusters": [
    "ai-safety"
  ],
  "metrics": {
    "wordCount": 774,
    "tableCount": 4,
    "diagramCount": 1,
    "internalLinks": 6,
    "externalLinks": 0,
    "footnoteCount": 0,
    "bulletRatio": 0.23,
    "sectionCount": 12,
    "hasOverview": false,
    "structuralScore": 9
  },
  "suggestedQuality": 60,
  "updateFrequency": null,
  "evergreen": true,
  "wordCount": 774,
  "unconvertedLinks": [],
  "unconvertedLinkCount": 0,
  "convertedLinkCount": 0,
  "backlinkCount": 0,
  "redundancy": {
    "maxSimilarity": 11,
    "similarPages": [
      {
        "id": "labor-transition",
        "title": "AI Labor Transition & Economic Resilience",
        "path": "/knowledge-base/responses/labor-transition/",
        "similarity": 11
      },
      {
        "id": "societal-response",
        "title": "Societal Response & Adaptation Model",
        "path": "/knowledge-base/models/societal-response/",
        "similarity": 10
      }
    ]
  }
}

No entity found for "factors-transition-turbulence-overview"

No facts for this entity

No external links

No backlinks

{
  "numericId": "E668",
  "title": "Transition Turbulence",
  "description": "Root factor measuring disruption during the AI transition. High turbulence increases risk across all scenarios.",
  "sidebar": {
    "label": "Overview",
    "order": 0
  },
  "lastEdited": "2026-01-03",
  "subcategory": "factors-transition-turbulence"
}

---
numericId: E668
title: Transition Turbulence
description: Root factor measuring disruption during the AI transition. High turbulence increases risk across all scenarios.
sidebar:
  label: Overview
  order: 0
lastEdited: "2026-01-03"
subcategory: factors-transition-turbulence
---
import {Mermaid, DataInfoBox, FactorSubItemsList, PageCauseEffectGraph, EntityLink} from '@components/wiki';

<DataInfoBox entityId="E358" />

Transition Turbulence measures how much disruption occurs as society navigates from current AI to whatever future emerges. Unlike <EntityLink id="E674">Ultimate Scenarios</EntityLink> (which describe *what* happens), Transition Turbulence describes *how rough the journey is*—and that roughness affects both whether we survive (<EntityLink id="E130">Existential Catastrophe</EntityLink>) and what world we end up in (<EntityLink id="E194">Long-term Trajectory</EntityLink>).

Even if we ultimately reach a good destination, a turbulent transition causes real suffering along the way. Economic displacement, political instability, and social fragmentation during the transition matter independently of the final outcome.

**Why a Root Factor?** Transition Turbulence is a *background condition* that affects Ultimate Scenarios and Ultimate Outcomes, not an endpoint in itself. High turbulence can trigger acute catastrophes (political collapse → loss of control) and constrain long-term trajectory (path dependence, destroyed institutions).

---

## Polarity

**Inherently negative.** High turbulence is always worse than low turbulence, all else equal. There's no "good" version of extreme disruption—the question is how much turbulence we experience, not whether turbulence is desirable.

| Level | Description |
|-------|-------------|
| **Low turbulence** | Smooth adaptation, minimal disruption, institutions keep pace |
| **Moderate turbulence** | Significant disruption but recoverable, adaptation strained |
| **High turbulence** | Severe instability, cascading failures, suffering widespread |
| **Catastrophic turbulence** | System breakdown triggers existential catastrophes or permanent damage |

---

## How This Happens

<Mermaid chart={`
flowchart TD
    subgraph Drivers["Turbulence Drivers"]
        SPEED[Rapid Capability Growth]
        DISPLACE[Economic Displacement]
        RACE[Racing Dynamics]
        COORD_FAIL[Coordination Failures]
    end

    subgraph Manifestations["How Turbulence Manifests"]
        ECON[Economic Instability]
        POLITICAL[Political Instability]
        SOCIAL[Social Fragmentation]
        INSTITUTIONAL[Institutional Stress]
    end

    subgraph Effects["Effects on Ultimate Outcomes"]
        ACUTE[Existential Catastrophe]
        LONGRUN[Long-term Trajectory]
    end

    SPEED --> DISPLACE
    SPEED --> INSTITUTIONAL
    DISPLACE --> ECON
    RACE --> POLITICAL
    COORD_FAIL --> POLITICAL
    COORD_FAIL --> SOCIAL

    ECON --> TURBULENCE[Transition Turbulence]
    POLITICAL --> TURBULENCE
    SOCIAL --> TURBULENCE
    INSTITUTIONAL --> TURBULENCE

    TURBULENCE -->|"can trigger"| ACUTE
    TURBULENCE -->|"path dependence"| LONGRUN

    style TURBULENCE fill:#ffe66d
    style ACUTE fill:#ff6b6b
    style LONGRUN fill:#4ecdc4
`} />

### Turbulence Drivers

**1. Rapid Capability Growth**
AI capabilities advance faster than institutions, labor markets, and social norms can adapt. The faster the change, the more turbulence.

**2. Economic Displacement**
AI automation displaces workers faster than new roles emerge. Mass unemployment creates economic and political instability.

**3. Racing Dynamics**
Competition between labs/nations creates pressure to deploy before adequate safety testing, increasing both capability speed and coordination failures.

**4. Coordination Failures**
Governments, labs, and international bodies fail to coordinate on standards, safety requirements, and transition support.

### Turbulence Manifestations

| Domain | Low Turbulence | High Turbulence |
|--------|---------------|-----------------|
| **Economic** | Gradual workforce transition, safety nets absorb displacement | Mass unemployment, inequality spikes, market instability |
| **Political** | Democracies adapt, regulation keeps pace | Authoritarian backlash, polarization, institutional collapse |
| **Social** | Trust maintained, communities adapt | Fragmentation, loss of shared reality, civil unrest |
| **Institutional** | Regulators understand AI, governance effective | Governance captured or overwhelmed, rule of law erodes |

---

## Key Parameters

<FactorSubItemsList factorId="transition-turbulence" />

---

## Which Ultimate Outcomes It Affects

### Existential Catastrophe (Primary)

High turbulence can *trigger* acute catastrophes:
- **Political collapse** → Loss of control over AI development
- **Racing acceleration** → Deployment before adequate safety
- **Institutional breakdown** → No capacity to respond to emerging threats
- **Social unrest** → Desperate measures, authoritarian responses

A rough enough transition can cause the catastrophe, even if AI itself isn't misaligned.

### Long-term Trajectory (Primary)

Turbulence shapes what futures are reachable through **path dependence**:
- Destroyed institutions are hard to rebuild
- Lost trust takes generations to restore
- Authoritarian responses to chaos tend to entrench
- Economic disruption locks in inequality
- Options foreclosed during crisis rarely reopen

Even if acute catastrophe is avoided, high turbulence constrains the achievable long-term trajectory.

---

## Relationship to Ultimate Scenarios

| Ultimate Scenario | Relationship |
|---------------------|--------------|
| <EntityLink id="E670">AI Takeover</EntityLink> | Turbulence increases risk of loss of control |
| <EntityLink id="E671">Human-Caused Catastrophe</EntityLink> | Turbulence can trigger state failures and desperate actions |
| <EntityLink id="E673">Long-term Lock-in</EntityLink> | Turbulent periods often lock in emergency measures |

---

## Warning Signs

Indicators of increasing turbulence:

1. **Labor market stress**: AI-related unemployment rising faster than retraining
2. **Political polarization**: AI becoming partisan issue, backlash movements
3. **Regulatory lag**: Governance clearly behind capability development
4. **International tension**: AI competition framed as zero-sum
5. **Trust decline**: Public trust in institutions/tech companies falling
6. **Social instability**: Protests, strikes, civil unrest related to AI

---

## Interventions That Reduce Turbulence

**Economic:**
- Universal basic income or robust safety nets
- Retraining and education programs
- Gradual deployment policies
- Worker transition support

**Political:**
- Democratic deliberation processes for AI policy
- International coordination mechanisms
- Regulatory capacity building
- Preventing authoritarian capture

**Social:**
- Maintaining epistemic commons (shared facts)
- Community resilience programs
- Trust-building between tech and public
- Preserving human-human social fabric

**Technical:**
- Paced deployment (slowing capability rollout)
- Interoperability requirements
- Human-in-the-loop requirements
- Transition period safety measures

---

## Probability Estimates

| Turbulence Level | Assessment |
|------------------|------------|
| **Some turbulence** | Almost certain—significant disruption is baseline |
| **High turbulence** | Likely without deliberate intervention |
| **Catastrophic turbulence** | Possible, depends on speed of capability growth and coordination |
| **Low turbulence** | Requires active coordination and paced deployment |

**Key uncertainty**: How fast will transformative capabilities arrive? Faster arrival = more turbulence.