Governance (Civ. Competence)
Governance encompasses the quality of political institutions, regulatory capacity, and the ability to create effective AI policy. This parameter measures how well society’s formal decision-making structures can understand, evaluate, and respond to AI developments through legislation, regulation, and institutional coordination.
The fundamental challenge is a race against time: AI capabilities advance on timescales of months to years, while institutional adaptation typically operates on years to decades. Historical analysis shows regulatory lag spanning 15-70 years for transformative technologies. The Institutional Adaptation Speed Model estimates institutions currently change at only 10-30% of the needed rate while AI creates 50-200% annual governance gaps.
| Metric | Score | Notes |
|---|---|---|
| Changeability | 35/100 | Institutional reforms take years |
| X-risk Impact | 55/100 | Significant impact on existential risk pathways |
| Trajectory Impact | 70/100 | High influence on long-term outcomes |
| Uncertainty | 45/100 | Moderate uncertainty about governance effectiveness |
Related Content
Section titled “Related Content”Responses:
- AI Governance - Comprehensive overview of governance approaches
- AI Safety Institutes - Government technical evaluation capacity
- Standards Bodies - Technical standards development
- Voluntary Commitments - Industry self-governance
Models:
- Institutional Adaptation Speed - Model of institutional change rates
- Public Opinion Evolution - Model of public attitude dynamics
Key Debates:
- Can democratic institutions move fast enough to govern rapidly advancing AI?
- Should AI governance be led by technical experts or democratic processes?