Those responsible for the different phases of the AI lifecycle should be identifiable and accountable for its outcomes, and human oversight of AI should be enabled. Organisations and individuals are responsible for the outcomes of systems they design, develop, deploy and operate, while the legal principles of AI accountability are still developing. Mechanisms should secure responsibility and accountability before and after design, development, deployment and operation; the accountable organisation and individual should be identifiable as necessary and must consider the level of human control or oversight appropriate to the system or use case. Systems with a significant impact on an individual's rights should be accountable to external review, including by supplying timely, accurate and complete information to independent oversight bodies.
This control maps to 6 controls across 5 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 6 it maps to, and the evidence behind each claim, over MCP and REST.