# Make the method visible.

Versioned scope, evidence and review are prerequisites for defensible evaluation.

## Research status

The Responsible AI working architecture and transparency weights are provisional. Publication of this educational page does not activate a new scoring standard or alter historical evaluations.

## Evidence and uncertainty

Keep disclosed, not found, not applicable and unverifiable states distinct. Assess freshness and provenance. Missing evidence is unknown, not proof of failure.

## Review and challenge

A reviewer must establish scope, rights, conflicts and evidence sufficiency before approving a finding. Corrections create a traceable revision. Independent evaluations require their own approval and appeal process.

## Explore

- [Responsible AI Observatory](/responsible-ai)

- [Standards inform governance. Scope determines applicability.](/responsible-ai/standards)

- [Research that makes governance examinable.](/responsible-ai/research)

- [Make risk accountable.](/responsible-ai/risks)

- [Build judgment before the consequential decision.](/responsible-ai/board-education)

- [Make the method visible.](/responsible-ai/methodology)

- [Comparable evidence comes before comparison.](/responsible-ai/benchmarks)