AI Glossary

Fairness

Coverage in development

Fairness in ML evaluates whether model outcomes systematically disadvantage groups defined by sensitive attributes, under chosen fairness criteria.

Definition

Fairness in ML evaluates whether model outcomes systematically disadvantage groups defined by sensitive attributes, under chosen fairness criteria.

Checking whether the system treats people equitably according to an explicit definition of fairness.

Bias Responsible AI

2026-07-13

NIST AI Risk Management Framework — risk vocabulary context for AI systems
Brel Digital company and technology profiles — applied usage evidence where tagged

If a technology assignment or hub description is inaccurate, submit a correction via the Corrections Policy.