Scientific Definition
Categorizing AI use cases by risk level.
Plain-English Definition
Categorizing AI use cases by risk level.
Feynman Explanation
Not every model needs the same governance.
Core Principle
Categorizing AI use cases by risk level.
Mechanisms
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Inputs (Triggers)
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Outputs (Behaviors)
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Behavioral Signature
Not every model needs the same governance.
Examples
- EU AI Act risk categorization.
- Governance proportional to risk.
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Famous Experiments
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Design Principles
- Tier your AI portfolio. Govern accordingly.
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.
- Tier your AI portfolio. Govern accordingly.
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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.
When the agent acts, who's responsible?
Systematic skew in model behavior across groups.
Testing model behavior on hypothetical alternate inputs.
Adding noise to data to protect individual privacy.
Quantitative measures of model behavior across groups.
Training models across devices without centralizing data.
Bypassing model safety constraints.
Individual speed gains hide collective quality decline.
Malicious instructions hidden in user input or retrieved content.
Adversarial testing of AI systems.
Foundational skills erode through AI offloading.
Concentration risk on a single AI provider.