← Back to glossary
Browse letter E hub
Explainability (XAI)
Methods making AI model decisions understandable to human users.
Definition
Methods making AI model decisions understandable to human users.
How It Works
Explainability (XAI) helps teams build predictable AI and translation workflows by setting clear expectations for quality, consistency, and decision-making.
In production environments, this concept is applied with process controls such as human review, terminology alignment, and repeatable quality checks across multilingual content.
Key Concepts
- core principle of explainability (xai)
- workflow-level implementation
- terminology and quality consistency
- human validation before publication
Where It Is Used
- localisation workflows
- AI translation pipelines
- multilingual content production
- cross-referencing related concepts such as Encryption