AI Glossary
AI Transparency
The practice of providing clear information about how AI systems operate, use data, and generate outputs.
AI Transparency
Overview
Trust is easier to build when people understand how a system operates.
This principle is especially important in artificial intelligence.
AI Transparency refers to openness about how AI systems are developed, managed, and used.
A helpful way to think about transparency is clear communication.
People are generally more comfortable with systems when they understand what the system does, how it works, and what limitations it may have.
Transparency may include information about:
- Data sources
- System capabilities
- Limitations
- Governance practices
- Decision-making processes
- Risk management controls
Transparency does not necessarily require revealing every technical detail.
Instead, it focuses on providing meaningful information that helps stakeholders understand and trust AI systems.
As AI adoption grows, transparency is becoming a key component of responsible AI, governance, and compliance programs.
Why It Matters
Transparency helps build trust, accountability, and confidence in AI systems.
Real-World Example
An organization may publish documentation explaining how an AI system is used and what safeguards are in place.