{
  "$schema": "https://peakstate.global/sourced/v1.schema.json",
  "sourced": "1.0",
  "artefact": {
    "path": "src/content/posts/ai-policy-purpose.md",
    "slug": "ai-policy-purpose",
    "sha256": "01f08d4430a61a0bf3b8e0ea83095ba93f9cc6189ca6b30e4a6c04f069995f4b",
    "producedAt": "2026-08-26"
  },
  "claims": [
    {
      "id": "c1",
      "statement": "Most enterprise AI policies Andrew has read are written to avoid embarrassment rather than to direct AI use.",
      "status": "inferred",
      "locator": {
        "paragraph": 1
      },
      "evidence": [],
      "note": "First-person conclusion from reading enterprise AI policies in government, banking and ASX 200 organisations. No count recorded, no sample a third party can inspect."
    },
    {
      "id": "c2",
      "statement": "Prohibition-led AI policies push real AI usage off the books within weeks of publication, onto personal devices and accounts.",
      "status": "recalled",
      "locator": {
        "paragraph": 4
      },
      "evidence": [],
      "note": "Stated from Andrew's practice memory. Not measured, no dated observation set behind it."
    },
    {
      "id": "c3",
      "statement": "A policy cannot make the volume of AI decisions an organisation faces; the people at the point of use are the only ones positioned to decide.",
      "status": "inferred",
      "locator": {
        "paragraph": 7
      },
      "evidence": [],
      "note": "Reasoned argument, not an observation. The 'ten thousand decisions' figure is an illustration, not a count."
    },
    {
      "id": "c4",
      "statement": "A rule stated with its reason transfers to novel cases; a rule without one invites literal-minded circumvention.",
      "status": "inferred",
      "locator": {
        "paragraph": 11
      },
      "evidence": [],
      "note": "Andrew's conclusion from practice. Not tested against a sample of policies."
    },
    {
      "id": "c5",
      "statement": "Most AI policies price the risk of acting and not the risk of abstention, which biases them towards prohibition.",
      "status": "inferred",
      "locator": {
        "paragraph": 13
      },
      "evidence": [],
      "note": "Pattern claim across the policies Andrew has been shown. Unquantified."
    },
    {
      "id": "c6",
      "statement": "A clause stating that judgement exercised within the principles is backed by the organisation does more for safety and adoption than the prohibitions combined.",
      "status": "inferred",
      "locator": {
        "paragraph": 17
      },
      "evidence": [],
      "note": "The strongest claim in the piece and the least measurable. No comparative evidence behind it."
    },
    {
      "id": "c7",
      "statement": "Principles with reasons age more slowly than tool-specific prohibition lists.",
      "status": "inferred",
      "locator": {
        "paragraph": 21
      },
      "evidence": [],
      "note": "Reasoned from the difference in what each is indexed to. Not measured."
    }
  ],
  "evidence": [],
  "disclosure": {
    "attribution": "Written by Andrew Ramsden. AI tools assisted research and drafting; all outputs verified.",
    "accountable": "Andrew Ramsden.",
    "limitations": "No external sources.",
    "references": "No external sources. Claim labels are in the [SOURCED sidecar](/sourced/ai-policy-purpose.sourced.json)."
  }
}