Scientific Definition
Training models across devices without centralizing data.
Plain-English Definition
Training models across devices without centralizing data.
Feynman Explanation
The model travels. The data stays home.
Core Principle
Training models across devices without centralizing data.
Mechanisms
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Inputs (Triggers)
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Outputs (Behaviors)
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Behavioral Signature
The model travels. The data stays home.
Examples
- Mobile keyboard prediction training.
- Privacy-by-design pattern.
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Famous Experiments
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Design Principles
- Consider when data centralization is the bottleneck or risk.
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.
- Consider when data centralization is the bottleneck or risk.
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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?
Categorizing AI use cases by risk level.
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.
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.
Models learning from examples in the prompt.