Scientific Definition
Written rules about how AI may be used internally.
Plain-English Definition
Written rules about how AI may be used internally.
Feynman Explanation
Without a policy, every team writes their own. Inconsistently.
Core Principle
Written rules about how AI may be used internally.
Mechanisms
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Inputs (Triggers)
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Outputs (Behaviors)
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Behavioral Signature
Without a policy, every team writes their own. Inconsistently.
Examples
- Use policies covering PII, IP, sensitive data, attribution.
- Necessary infrastructure for scaled adoption.
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Famous Experiments
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Design Principles
- Write it. Train on it. Audit against it.
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.
- Write it. Train on it. Audit against it.
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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.
Logging of AI inputs, outputs, and decisions.
Inventory of models, data, tools, and dependencies in an AI system.
Tracing AI components for risk and compliance.
Cross-functional governance body for AI decisions.
Agents deployed before anyone owns the consequences.
Cryptographic tracking of content origin.
Tracking where training and inference data came from.
Comprehensive AI regulation in the EU.
Why did it produce this? vs. How does it work?
Human review at critical AI decision points.
Human oversight without per-decision review.
Documentation of model purpose, performance, limitations, and risks.