PromptRiskDBThreat intelligence atlas
AI Risk

Disparate Performance

The LLM’s performances can differ significantly across different groups of users. For example, the question-answering capability showed significant performance differences across different racial and social status groups. The fact-checking abilities can differ for different tasks and languages

View related techniquesRead profile
AI Risk1. Discrimination & Toxicity1.3 > Unequal performance across groups3 - Other

Record summary

A quick snapshot of what this page covers.

Techniques1Attack methods connected to this risk.
Mitigations4Defenses 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
Subdomain1.3 > Unequal performance across groups
Entity2 - AI
Intent2 - Unintentional
Timing3 - Other
CategoryFairness
SubcategoryDisparate Performance

Related techniques

Attack methods connected to this risk.

Suggested mitigations

Defenses that may help with related attacks.

Generative AI Guardrails

ML Model EngineeringML Model Evaluation+1 more
LifecycleML Model Engineering + 2 moreCategoryTechnical - ML

Generative AI Guidelines

ML Model EngineeringML Model Evaluation+1 more
LifecycleML Model Engineering + 2 moreCategoryTechnical - ML

Source

Research source for this risk, when available.