Misalignment Potential

Misalignment Potential measures the likelihood that AI systems will pursue goals other than what we intend. This aggregate combines the technical and organizational factors that determine whether advanced AI systems might behave in harmful ways despite our efforts.

Primary outcome affected: Existential CatastropheAi Transition Model ScenarioExistential CatastropheThis page contains only a React component placeholder with no actual content visible for evaluation. The component would need to render content dynamically for assessment. ↑↑↑

When misalignment potential is high, catastrophic loss of control, accidents at scale, and goal divergence become more likely. Reducing this potential is the most direct lever for reducing existential and catastrophic AI risk.

Component Parameters

• Technical AI Safety
• AI Governance
• Lab Safety Practices

Internal Dynamics

These components interact:

• Interpretability enables alignment verification: We can only confirm alignment if we understand model internals
• Safety culture sustains investment: Without organizational commitment, safety research loses funding to capabilities
• Oversight requires interpretability: Human overseers need tools to understand what systems are doing
• Gap closure requires all components: No single factor is sufficient; safety capacity emerges from their combination

How This Affects Scenarios

Related Pages

• Existential CatastropheAi Transition Model ScenarioExistential CatastropheThis page contains only a React component placeholder with no actual content visible for evaluation. The component would need to render content dynamically for assessment. — The outcome this primarily affects
• Misuse PotentialFactors Misuse Potential OverviewRoot factor measuring the risk of AI being weaponized or exploited by malicious actors. Primary driver of Human-Caused Catastrophe scenarios. — The complementary factor for human-caused catastrophe