AI Trust Glossary · Canonical Definition
Transparency
The quality of being open and accessible for scrutiny - providing visibility into how an AI system operates, what decisions it makes, and why.
Explanation
Transparency operates at multiple levels: process transparency (how was the system designed), performance transparency (what are its capabilities and limitations), decision transparency (why did it take specific actions), and audit transparency (can behavior be independently verified). Different contexts require different types.
Why it matters
Without transparency, accountability is impossible. Organizations, regulators, and users cannot evaluate what they cannot see. Transparency is the foundation on which trust is built - and its absence is itself a risk signal.
How Borealis uses it
Transparency is operationalized across multiple BM Score dimensions, primarily in decision transparency (20%) and audit completeness (10%). The Hedera-anchored certification record is itself a transparency mechanism - making the certification process auditable by any third party.