Last jobs to be automated will be government jobs, university jobs

Last jobs to be automated will be government jobs, university jobs | I think the last job to be automated will be government jobs. Also, other similar things like university jobs and so forth.

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I think the last job to be automated will be government jobs. Also, other similar things like university jobs and so forth.

Beneficiaries (24)

Adverse (6)

{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=uOGHXAfvK8w",
  "mode": "PREDICTION",
  "role": "Host",
  "context": "I think the last job to be automated will be government jobs. Also, other similar things like university jobs and so forth.",
  "verbatim": "I think the last job to be automated will be government jobs. Also, other similar things like university jobs and so forth.",
  "conv_cues": "I think",
  "direction": "HAPPEN",
  "timeframe": "Future",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "prereq",
      "label": "Nvidia became the world's first $5 trillion company (late 2025), operating a near-monopoly on advanced AI chips.",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -9,
      "source_id": "SEM_011",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29",
      "hit_emitted_at": "2026-06-08T13:04:02.341521+00:00"
    },
    {
      "kind": "prereq",
      "label": "Nvidia Data Center revenue +66% YoY, contributing ~90% of $57B fiscal Q3 revenue; >$4.5T market cap entirely underpinned by AI silicon.",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -8,
      "source_id": "SEM_027",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29",
      "hit_emitted_at": "2026-06-08T13:04:02.341521+00:00"
    },
    {
      "kind": "prereq",
      "label": "Nvidia's Arizona-based TSMC factory successfully fabricated cutting-edge semiconductors on US soil for first time in decades (October 2025).",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -7,
      "source_id": "SEM_014",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29",
      "hit_emitted_at": "2026-06-08T13:04:02.341521+00:00"
    },
    {
      "kind": "prereq",
      "label": "Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) a",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -6,
      "source_id": "SEM_012",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29",
      "hit_emitted_at": "2026-06-08T13:04:02.341521+00:00"
    },
    {
      "kind": "prereq",
      "label": "Nvidia agreed to remit 15% of China chip-sale revenue directly to US government in exchange for reversing specific AI chip export bans.",
      "status": "overdue",
      "weight": 0.5,
      "ordinal": -5,
      "source_id": "SEM_015",
      "expected_date": "2026-06-25",
      "observed_date": null,
      "miss_emitted_at": "2026-07-03T22:12:25.328464+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "llm_pre_event",
      "label": "Major automation cuts in private-sector white-collar roles announced (legal, finance, consulting, support) precede any equivalent government RIFs",
      "source": "Company press releases; Challenger Job Cuts reports",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -4,
      "source_id": null,
      "confidence": 0.65,
      "expected_date": "2028-09-15",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2030-12-31",
        "from": "2026-06-01"
      },
      "measurement_criterion": "At least 5 Fortune 500 firms announce >=10% white-collar headcount reduction explicitly tied to AI/agentic automation, while federal/state RIFs from comparable AI automation remain absent or limited"
    },
    {
      "kind": "llm_post_event",
      "label": "Public-sector union activity (AFGE, NEA, AFT, state employee unions) successfully blocks or substantially limits AI displacement of routine government/university roles",
      "source": "AFGE/NEA contract disclosures; state legislative tracking",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -3,
      "source_id": null,
      "confidence": 0.55,
      "expected_date": "2029-07-02",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2032-12-31
... (truncated)