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AI Risk

Model bias

"While data bias is a major contributor of model bias, model bias actually manifests itself in different forms and shapes, such as presentation bias, model evaluation bias, and popularity bias. In addition, model bias arises from various sources [62], such as AI/ML model selection (e.g., support vector machine, decision trees), regularization methods, algorithm configurations, and optimization techniques."

AI Risk1. Discrimination & Toxicity1.1 > Unfair discrimination and misrepresentation1 - Pre-deployment

Record summary

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Techniques0Attack methods connected to this risk.
Mitigations0Defenses that may help with related attacks.
Domain1. Discrimination & ToxicityThe broad risk area this belongs to.

Risk profile

How this risk is described and categorized.

Domain1. Discrimination & Toxicity
Subdomain1.1 > Unfair discrimination and misrepresentation
Entity3 - Other
Intent2 - Unintentional
Timing1 - Pre-deployment
CategoryModel-level risk
SubcategoryModel bias

Suggested mitigations

Defenses that may help with related attacks.

No propagated mitigations. No defense is available through the connected attack methods.

Source

Research source for this risk, when available.