The degree to which an AI system’s behavior, limitations, and decision process are visible and understandable.
Transparency is about making AI systems easier to inspect and understand. Users, reviewers, and stakeholders should be able to see what the system is doing, what it is relying on, and where its limits are.
In prompt engineering, transparency often means exposing reasoning steps when appropriate, documenting prompt logic, explaining sources of information, and being honest about uncertainty.
Transparency builds trust, but it also supports debugging, compliance, and safer deployment because hidden behavior is harder to evaluate and control.