Misalignment Potential

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---
numericId: E665
title: Misalignment Potential
description: Root factor measuring the likelihood AI systems pursue unintended goals. Primary driver of AI Takeover scenarios.
sidebar:
  label: Overview
  order: 0
lastEdited: "2026-01-03"
subcategory: factors-misalignment-potential
---
import {DataInfoBox, FactorSubItemsList, FactorRelationshipDiagram, ImpactList, PageCauseEffectGraph, EntityLink} from '@components/wiki';

<DataInfoBox entityId="E205" />

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:** <EntityLink id="E130">Existential Catastrophe</EntityLink> ↑↑↑

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

<FactorRelationshipDiagram nodeId="misalignment-potential" direction="outgoing" showSubItems={true} />

<FactorSubItemsList factorId="misalignment-potential" />

---

## 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

<ImpactList nodeId="misalignment-potential" direction="from" />