Apply risk-based measures: explainability, robustness, regular tuning
Is this legally binding?
Guidance. Voluntary guidance. Best practice, not obligation, until a contract or a regulator cites it.
When developing and selecting models, organisations should apply a risk-based approach to measures such as explainability, repeatability, robustness, reproducibility, traceability and auditability, with regular tuning.
From the source
“Risk-based approach to measures such as explainability, robustness and regular tuning”
Summary of the Model AI Governance Framework (Compendium Vol 2), p.4
What this connects to
2 relations. Official relations are the ones the source documents state; anything marked GAGE analysis is our reading, not an agency's.
Cites1
- ConceptPrinciple: explainable, transparent and fairGuidanceGAGE analysis, not official
Explainability measures operationalise the explainable/transparent principle
Learn this properly
This page tells you what this instrument is and whether it binds you. The AI Governance program teaches the whole discipline, with dedicated coverage of the Singapore governance stack and the MAS regime, and every topic is passed by explaining it back in your own words, graded against the source.
See the AI Governance programVerified against the official source on 2026-08-17. GAGE is not affiliated with or endorsed by any agency named here, and nothing on this page is legal advice. How this is built and checked.
Readers of this also ask
GAGE briefings tell you which AI regulation deadlines are coming, what they actually require of you, and when a program opens.