Give clear, simple explanations of how an AI system reaches an outcome, including its inputs and variables and how they affect reliability, the results of technical and human validation testing, and how human oversight is applied. Where explainability is limited, weigh the benefits of AI use against that limit and, if proceeding, document the reasons and apply heightened oversight and control. When AI influences or forms part of administrative decision making, decisions should be explainable and humans accountable.
This control maps to 2 controls across 1 other frameworks. If you already hold one of them, the evidence you collected for it is the starting point here rather than new work.
Every mapping shown was judged rather than inferred from wording similarity, and the ones that failed review are published too. See the coverage reports and what was rejected.
The graph holds this control, the 2 it maps to, and the evidence behind each claim, over MCP and REST.