AI Capabilities
Risk Factor
AI Capabilities
Model RoleRoot Factor (AI System)
CharacterAmplifier (neither inherently good nor bad)
TrajectoryRapidly increasing
Related
Parameters
Risk Factors
Overview
Section titled “Overview”AI Capabilities refers to how powerful AI systems become across multiple dimensions. This is a key root factor in the AI Transition Model because capability levels directly influence the probability and severity of various scenarios.
For detailed tracking of current AI capabilities, see the Capabilities section.
Key Dimensions
Section titled “Key Dimensions”Capability Categories
Section titled “Capability Categories”The Knowledge Base tracks capabilities across several domains:
| Capability | Status | Risk Relevance |
|---|---|---|
| Language Models | Rapidly advancing | Foundation for all other capabilities |
| Reasoning | Emerging | Key for general intelligence |
| Coding | Human-competitive | Enables self-improvement |
| Agentic AI | Early stage | Enables autonomous action |
| Tool Use | Growing | Expands action space |
| Scientific Research | Emerging | Could accelerate capability growth |
| Situational Awareness | Emerging | Key prerequisite for scheming |
| Self-improvement | Theoretical | Could lead to recursive improvement |
| Persuasion | Concerning | Enables manipulation at scale |
| Long-horizon Tasks | Early stage | Enables complex autonomous projects |
Relationship to Scenarios
Section titled “Relationship to Scenarios”Higher AI capabilities primarily increase the probability and severity of AI Takeover scenarios:
- Rapid Takeover: Requires sufficient capability for decisive action
- Gradual Takeover: Enabled by increasing autonomy and generality over time
Capabilities also affect Human-Caused Catastrophe scenarios by enabling more powerful Bioweapons, Cyberweapons, and Autonomous Weapons.
Current Trajectory
Section titled “Current Trajectory”AI capabilities are advancing rapidly across all dimensions, driven by:
- Scaling laws (more compute, data, parameters)
- Algorithmic improvements (transformers, RLHF, reasoning chains)
- Hardware advances (specialized AI chips, larger clusters)
- Increased investment (~$100B+ annually in US alone)
Key metrics are tracked at Epoch AI and Stanford HAI AI Index.
Related Pages
Section titled “Related Pages”What links here
- AI Usesrisk-factorshaped-by