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

Glossary · 6 · Quality, risk and governance

Responsible AI

Also known as: Trustworthy AI, AI ethics

Responsible AI is the set of principles and practices for developing and using AI in ways that are safe, fair, transparent, privacy-preserving, secure and accountable — translated into concrete policies, controls and documentation throughout an AI system’s life cycle.

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

In one sentence

Responsible AI explained: the principles and everyday practices that make AI use safe, fair, transparent and accountable.

Example

A company’s responsible AI program requires a risk check for each new AI use case, an owner, documented evaluation results and a way for users to report problems.

Why it matters on your learning path

  • Technical writers: Transparency and accountability need documentation: model cards, instructions for use, limitations and change logs.
  • Technical marketers: Responsible AI claims must be backed by practice; vague ethics statements invite scrutiny.
  • Technical project managers: Frameworks such as the NIST AI RMF and the EU AI Act turn principles into work packages.

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

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