ModelRefs / AI Fairness — AI Glossary
AI Fairness — AI Glossary
The property of an AI system producing equitable outcomes across different demographic groups without unjustified disparate impact.
Overview
Fairness in ML has multiple formal definitions (demographic parity, equalized odds, individual fairness) that are mathematically incompatible in general. For LLMs: measuring output quality, sentiment, and stereotype propagation disparities. Fairness interventions include data rebalancing, adversarial debiasing, and post-processing calibration.
Reference details
| Topic | safety |
|---|---|
| Last reviewed | 2026-06-24 |
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Frequently asked questions
What is AI Fairness?
The property of an AI system producing equitable outcomes across different demographic groups without unjustified disparate impact.
What concepts are related to AI Fairness?
Closely related concepts include bias detection, alignment, responsible ai.