Glossary Updates12 new terms added to the glossaries · October 2, 2026, 22:44 CEST
AI TechDocKnowledge

Glossary · 6 · Quality, risk and governance

Bias (AI)

Also known as: Algorithmic bias, Fairness

Bias in AI is a systematic skew in a model’s outputs — favoring or disadvantaging certain groups, viewpoints, languages or cases — that usually stems from imbalances in its training data, its design or the way it is used.

  • Beginner
  • Technical writers
  • Technical marketers
  • Technical project managers

In one sentence

AI bias explained: systematic skews in AI output, where they come from, and how writers, marketers and PMs can spot and reduce them.

Example

An image generator asked for “an engineer at a machine” mostly shows men; a marketing team specifies diverse people in its prompts and reviews results.

Why it matters on your learning path

  • Technical writers: Check AI-generated examples, names and images for stereotypes, as you would with any content.
  • Technical marketers: Biased imagery or copy damages brands; review campaigns for representation.
  • Technical project managers: For AI that affects people’s access to jobs, credit or services, bias testing is a legal topic — see high-risk AI system.

By knowledge.aitechdoc.world · Published September 26, 2026 · Last reviewed

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