AI algorithms should be transparent enough that the technical processes and the related human decisions can be understood by stakeholders assessing the risks. Where AI is part of a decision-making process five elements are needed: disclosure that an AI system is in use, its intended purpose, the training data (including how it was gathered, what historical and social biases it may carry and how its quality was verified), how the system is maintained and assessed, and a means for affected people to challenge the decisions it makes.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.