{
  "schema_version": "1.0",
  "forecast_id": "F-007",
  "topic": "AI & Economy",
  "snapshot_version": "v0.1",
  "recorded_date": "2026-10-26",
  "publication_state": "draft",
  "locked_at_utc": null,
  "scoring_eligible": false,
  "independent_external_timestamp": false,
  "question": "By 31 December 2035, will at least two independent macroeconomic analyses attribute an additional one percentage point or more of annual US labor-productivity growth to AI over a common three-year observation period?",
  "probability": 0.35,
  "target_deadline_utc": "2035-12-31T23:59:00Z",
  "model": "Cortist subjective editorial scenario curve v0.1; not independently calibrated",
  "curve_anchors": [
    [
      2026,
      2
    ],
    [
      2030,
      14
    ],
    [
      2035,
      35
    ],
    [
      2040,
      58
    ],
    [
      2050,
      79
    ],
    [
      2060,
      89
    ],
    [
      2070,
      94
    ]
  ],
  "resolution_rules": {
    "status": "proposed_not_locked",
    "criteria": [
      "Two independent qualified research groups use published, comparable counterfactual methods and a shared three-year observed US growth window ending no later than 2035.",
      "Each estimates an additional >=1.0 percentage point average annual US labor-productivity growth attributable to AI, above a documented no-AI counterfactual.",
      "Studies explicitly separate software and AI effects from other capital investment, workforce shifts, cyclical recovery and selection bias."
    ],
    "adjudication": "To be determined by an independent preregistration and review process. Do not retrospectively score this provisional draft."
  },
  "sources": [
    {
      "name": "OECD 2026, Digital technology diffusion",
      "url": "https://www.oecd.org/en/publications/digital-technology-diffusion-in-the-age-of-ai_ebc2debe-en.html",
      "scope_note": "Adoption and productivity premia are partly explained by human and technology capital."
    },
    {
      "name": "OECD 2026, Productivity compendium",
      "url": "https://www.oecd.org/en/publications/oecd-compendium-of-productivity-indicators-2026_734a5e68-en/full-report/productivity-growth-in-a-challenging-global-environment_d888e417.html",
      "scope_note": "Labor productivity context; observed growth cannot be attributed to AI without controls."
    },
    {
      "name": "IMF 2026, AI deployment and disruption",
      "url": "https://www.elibrary.imf.org/display/book/9798229042741/CH002.xml",
      "scope_note": "AI investment contributes to growth but productivity attribution remains difficult."
    }
  ],
  "review_status": "Independent definitions and resolution thresholds are outstanding; the provisional percentage is not proof of measured likelihood.",
  "update_rule": "A future changed probability requires a new versioned path and a source-based rationale; never overwrite the first v0.1 snapshot.",
  "initial_vintage_context": "First public subjective assessment on 2026-10-26, not a prospectively locked independent forecast."
}