{
  "notice": "Illustrative mapping from the AI Governance Engineer Body of Knowledge v0.5.0 (not a claim of conformity)",
  "version": "0.5.0",
  "license": "CC BY 4.0",
  "licenseUrl": "https://creativecommons.org/licenses/by/4.0/",
  "schemaVersion": 1,
  "schema": "https://aigovernanceengineer.com/api/v1/schemas/control.json",
  "self": "https://aigovernanceengineer.com/api/v1/controls/aige-ctl-agent-041.json",
  "source": "https://aigovernanceengineer.com/controls/agent-runtime#aige-ctl-agent-041",
  "citation": {
    "title": "AI Governance Engineering: The Thesis & Body of Knowledge",
    "authors": [
      "Jorge García Aibar"
    ],
    "parentDoi": "https://doi.org/10.5281/zenodo.22956197",
    "conceptDoi": "https://doi.org/10.5281/zenodo.22857084"
  },
  "control": {
    "id": "AIGE-CTL-AGENT-041",
    "profile": "agent-runtime",
    "url": "https://aigovernanceengineer.com/controls/agent-runtime#aige-ctl-agent-041",
    "json": "https://aigovernanceengineer.com/api/v1/controls/aige-ctl-agent-041.json",
    "title": "User-set approval thresholds",
    "version": "0.2",
    "status": "draft",
    "reviewerStatus": "open",
    "depth": "derived",
    "objective": "Where an agent acts for a user, the user can set their own approval thresholds and boundaries on top of the organisation's limits, such as approval for purchases above an amount; the gateway enforces them like any other checkpoint, and a user setting can add a check but never remove one the organisation set.",
    "failureModes": [
      "A user's own approval threshold is recorded but not enforced at the gateway.",
      "A user setting removes or loosens a checkpoint the organisation set."
    ],
    "scope": "Agents that act on behalf of users.",
    "enforcementPoints": [
      "runtime"
    ],
    "verification": [],
    "evidence": [
      {
        "artefact": "User threshold settings; approvals they triggered",
        "schemaId": null,
        "schema": null,
        "layer": 4
      }
    ],
    "failureResponse": {
      "effect": "require_approval",
      "text": "A call above the user's own threshold waits for the user's approval."
    },
    "layer": 4,
    "secondaryLayers": [],
    "patterns": [
      {
        "slug": "human-in-the-loop-gate",
        "title": "Human-in-the-loop Gate",
        "url": "https://aigovernanceengineer.com/patterns/human-in-the-loop-gate"
      }
    ],
    "seeds": [
      {
        "id": "user-thresholds",
        "title": "User-set approval thresholds",
        "url": "https://aigovernanceengineer.com/bok/governing-agents#where-to-put-a-checkpoint"
      }
    ],
    "derivedFrom": [],
    "mappings": {
      "obligations": [
        {
          "id": "AIGE-OBL-SG-AGENTIC-CHECKPOINTS",
          "name": "Singapore IMDA Model AI Governance Framework for Agentic AI: human checkpoints for significant actions (voluntary)",
          "url": "https://aigovernanceengineer.com/obligations/aige-obl-sg-agentic-checkpoints"
        }
      ],
      "iso42001": [],
      "nistAiRmf": [],
      "owasp": [],
      "atlas": [],
      "aiuc1": [],
      "csaAicm": [],
      "other": [
        {
          "framework": "IMDA MGF for Agentic AI v1.5",
          "ref": "2.4.2 Users who interact with agents, p.47",
          "note": "Direct fit: Users set their own approval thresholds and boundaries beyond organisation-defined limits (also the user-defined checkpoints of p.29)"
        }
      ]
    },
    "references": [
      {
        "n": 11,
        "title": "Governing AI agents",
        "text": "Governing AI agents (AI Governance Engineering Body of Knowledge v0.5.0, chapter 23, section \"Where to put a checkpoint\"). AI Governance Engineer (Jorge García Aibar). 2026-09.",
        "url": "https://aigovernanceengineer.com/bok/governing-agents#where-to-put-a-checkpoint",
        "verified": "primary"
      },
      {
        "n": 4,
        "title": "Model AI Governance Framework for Agentic AI, v1.5",
        "text": "Model AI Governance Framework for Agentic AI, v1.5 (published 2026-05-20, updated 2026-06-05; four dimensions: assess and bound the risks upfront, make humans meaningfully accountable, implement technical controls and processes, enable end-user responsibility). IMDA. 2026-06-05.",
        "url": "https://www.imda.gov.sg/-/media/imda/files/about/emerging-tech-and-research/artificial-intelligence/mgf-for-agentic-ai.pdf",
        "verified": "primary"
      }
    ],
    "implementationNotes": [],
    "openQuestions": [
      "Verification procedure and evidence schema to be specified; requires technical review."
    ],
    "observation": null,
    "observationSchema": "https://aigovernanceengineer.com/schemas/control-observation.v1.json",
    "examples": []
  }
}