Robotics evidence guide · automated editorial preparation, not expert review
Give robotics evidence a clear decision owner
Governance identifies who can request an action, approve a change, assess evidence and accept responsibility for a decision. It must not collapse those roles into an automated pass flag.
Evidence and interpretation
The NIST AI RMF overview establishes voluntary risk management as a lifecycle concern. Maha’s proposed robotics application separates the evidence producer, technical reviewer and decision authority. A developer may explain a controller change without independently validating it. A buyer may choose an operational objective without authorizing unsafe experimentation. Record the scope of each decision and what evidence was available at the time. A later successful replay cannot retroactively authorize an earlier operation.
Proposed evidence workflow
- Assign roles and decision scope for evaluation, data use and operational changes.
- Bind each review to the exact evidence revision and list unresolved findings.
- Keep machine consistency checks visibly separate from human judgement and formal authorization.
Worked illustration
An automated check accepts a complete twelve-trial package. A reviewer can still reject a proposed deployment because none of the trials used hardware. Both decisions are consistent: they answer different questions.
Limits
This is an original governance workflow, not a regulatory approval or an implemented operational permission system.
Sources and review
Locator: Overview of the AI RMF
The framework is voluntary and addresses risk considerations across AI design, development, use and evaluation.
Boundary: This overview does not determine applicable law, certify robots or validate Maha workflows.
Inspection and reuse basis
Selected sections inspected 2026-09-15. Original explanation and link only; no framework text redistributed. This is not independent expert review of this article.