Glossary · Technical concept
Bias (statistical / algorithmic)
Systematic deviation in model outputs that disadvantages a protected group or fails to represent population characteristics. Sources include training data sampling, label noise, feature selection, and model architecture. Distinct from variance (random error). Bias and fairness are measured statistically — perfect 'unbiased' is rare; choose the definition that matches the deployment context.
Framework references
- NIST AI 1270 (bias categories)
- EU AI Act Art. 10