Scientific Definition
Systematic skew in model behavior across groups.
Plain-English Definition
Systematic skew in model behavior across groups.
Feynman Explanation
The model learned what the data taught it. The data taught it our history.
Core Principle
Systematic skew in model behavior across groups.
Mechanisms
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Inputs (Triggers)
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Outputs (Behaviors)
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Behavioral Signature
The model learned what the data taught it. The data taught it our history.
Examples
- Hiring tools, lending models, recommendation systems.
- Legal, reputational, and effectiveness risk.
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Famous Experiments
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Design Principles
- Bias audits. Diverse data. Continuous monitoring.
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.
- Bias audits. Diverse data. Continuous monitoring.
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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.
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.