{
  "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-034.json",
  "source": "https://aigovernanceengineer.com/controls/agent-runtime#aige-ctl-agent-034",
  "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-034",
    "profile": "agent-runtime",
    "url": "https://aigovernanceengineer.com/controls/agent-runtime#aige-ctl-agent-034",
    "json": "https://aigovernanceengineer.com/api/v1/controls/aige-ctl-agent-034.json",
    "title": "Oversight audited per approver",
    "version": "0.2",
    "status": "draft",
    "reviewerStatus": "open",
    "depth": "derived",
    "objective": "Oversight is measured per approver as well as overall: a low override rate or a short time to decide is flagged as possible rubber-stamping or fatigue, approvers whose decisions deviate significantly from the norm are flagged, and what an outlier approved is reviewed.",
    "failureModes": [
      "ASI09: Fluent, confident or persuasive agent output leads people to approve harmful actions, disclose information or skip the check they were meant to make.",
      "An approver approves almost every request within seconds, and no one reviews their decisions.",
      "Oversight metrics exist only in aggregate, so one approver whose decisions deviate from the norm goes unnoticed."
    ],
    "scope": "Every agent that calls tools, in production or in an evaluation harness.",
    "enforcementPoints": [
      "periodic"
    ],
    "verification": [],
    "evidence": [
      {
        "artefact": "Per-approver oversight metrics; outlier reviews",
        "schemaId": null,
        "schema": null,
        "layer": 5
      }
    ],
    "failureResponse": {
      "effect": "alert",
      "text": "To be specified."
    },
    "layer": 5,
    "secondaryLayers": [
      4
    ],
    "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": "approver-outliers",
        "title": "Oversight audited per approver",
        "url": "https://aigovernanceengineer.com/bok/governing-agents#what-a-good-approval-looks-like"
      }
    ],
    "derivedFrom": [],
    "mappings": {
      "obligations": [
        {
          "id": "AIGE-OBL-EUAIA-ART14",
          "name": "EU AI Act Art. 14 human oversight",
          "url": "https://aigovernanceengineer.com/obligations/aige-obl-euaia-art14"
        },
        {
          "id": "AIGE-OBL-EUAIA-ART13",
          "name": "EU AI Act Art. 13 transparency and information to deployers",
          "url": "https://aigovernanceengineer.com/obligations/aige-obl-euaia-art13"
        },
        {
          "id": "AIGE-OBL-EUAIA-ART50",
          "name": "EU AI Act Art. 50 transparency for certain AI systems",
          "url": "https://aigovernanceengineer.com/obligations/aige-obl-euaia-art50"
        },
        {
          "id": "AIGE-OBL-OWASP-AGENTIC",
          "name": "Top 10 for Agentic Applications 2026",
          "url": "https://aigovernanceengineer.com/obligations/aige-obl-owasp-agentic"
        }
      ],
      "iso42001": [
        {
          "id": "A.8.2",
          "title": "System documentation and information for users"
        },
        {
          "id": "A.9.2",
          "title": "Processes for responsible use of AI systems"
        }
      ],
      "nistAiRmf": [],
      "owasp": [
        {
          "id": "asi09",
          "externalId": "ASI09",
          "name": "Human-Agent Trust Exploitation",
          "url": "https://aigovernanceengineer.com/resources/threats#threat-asi09"
        }
      ],
      "atlas": [],
      "aiuc1": [],
      "csaAicm": [],
      "other": [
        {
          "framework": "IMDA MGF for Agentic AI v1.5",
          "ref": "2.2.2 Design for meaningful human oversight, p.30",
          "note": "Direct fit: Override rate and response time as indicators, and analytics to identify approvers whose decision patterns deviate significantly from the norm"
        }
      ]
    },
    "references": [
      {
        "n": 14,
        "title": "Governing AI agents",
        "text": "Governing AI agents (AI Governance Engineering Body of Knowledge v0.5.0, chapter 23, section \"What a good approval looks like\"). AI Governance Engineer (Jorge García Aibar). 2026-09.",
        "url": "https://aigovernanceengineer.com/bok/governing-agents#what-a-good-approval-looks-like",
        "verified": "primary"
      },
      {
        "n": 2,
        "title": "OWASP Top 10 for Agentic Applications for 2026",
        "text": "OWASP Top 10 for Agentic Applications for 2026 (ASI01 Agent Goal Hijack to ASI10 Rogue Agents). OWASP GenAI Security Project. 2025-12-09.",
        "url": "https://genai.owasp.org/resource/owasp-top-10-for-agentic-applications-for-2026/",
        "verified": "primary"
      },
      {
        "n": 3,
        "title": "ISO/IEC 42001:2023, AI management systems, Annex A",
        "text": "ISO/IEC 42001:2023, AI management systems, Annex A (reference control objectives and controls A.2 to A.10, cited by id and short title). ISO/IEC. 2023.",
        "url": "https://www.iso.org/standard/81230.html",
        "verified": "secondary"
      },
      {
        "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": []
  }
}