Scientific Definition
The trained model develops its own internal optimizer.
Plain-English Definition
The trained model develops its own internal optimizer.
Feynman Explanation
You trained one optimizer. You got two.
Core Principle
The trained model develops its own internal optimizer.
Mechanisms
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Inputs (Triggers)
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Outputs (Behaviors)
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Behavioral Signature
You trained one optimizer. You got two.
Examples
- Theoretical concern in AI safety; observed glimmers in large models.
- Why complex AI systems are harder to govern than they look.
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Famous Experiments
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Design Principles
- Interpretability tooling. Constrained training procedures.
Measurement Approaches
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Evidence
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The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
- Interpretability tooling. Constrained training procedures.
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Interactive Mini Network
Click any neighbor to re-center the graph and follow the threads of connection.
Knowledge Graph Neighbors
Auto-linked to the rest of the Human Behavior Taxonomy by family, domain, dimension, and shared keywords.
Models trained to follow a written set of principles.
Optimizing a proxy of the goal degrades the actual goal.
Outer: the spec matches our intent. Inner: the model actually pursues the spec.
What the model is actually optimizing.
Maximizing the reward signal in unintended ways.
Reinforcement learning from human feedback.
The model achieves the goal as stated, not as intended.
Written rules about how AI may be used internally.
Innovators → early adopters → majority → laggards, AI-specific.
AI system that takes actions to achieve goals, often across tools.
When the agent acts, who's responsible?
Augmentation strategy vs. substitution strategy.