---
title: "Bias"
description: "A systematic error that favours or disadvantages some people or outcomes."
canonical: https://aigovernanceengineer.com/glossary/bias
author: "Jorge García Aibar"
license: "CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)"
doi: https://doi.org/10.5281/zenodo.22956197
version: "0.5.0"
updated: 2026-09-24
---

# Bias

A systematic error that favours or disadvantages some people or outcomes. NIST sorts AI bias into three categories: systemic, statistical and computational, and human [1]. Bias can enter at any lifecycle stage, so it is tested per stage rather than once.

- Developed in: [ch. 16, Where bias enters the lifecycle](https://aigovernanceengineer.com/bok/fairness-and-explainability#where-bias-enters-the-lifecycle)
- Chapters: [ch. 16, Fairness & XAI](https://aigovernanceengineer.com/bok/fairness-and-explainability)
- Contrast with: [Fairness](https://aigovernanceengineer.com/glossary/fairness)
- In the glossary chapter: https://aigovernanceengineer.com/bok/glossary#t-bias

## Sources

[1] NIST SP 1270, Towards a Standard for Identifying and Managing Bias in Artificial Intelligence (three categories of AI bias: systemic, statistical and computational, and human). NIST. 2022-03-15. https://doi.org/10.6028/NIST.SP.1270 (verified: primary)