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230_002predictionLabor/Jobsjobs

AI will automate away CEO labor; a few more years needed for machines to excel at unskilled manual labor.

Predictor: Alex Wissner-Gross · ep#230 "AI CEOs Come Online: Sam Altman's Replacement Plan, Job Loss & 'Solve Everything' Launches |EP #230" · source

Prior probability
45.0%
Current probability
36.5%
evolves via intake + LBP
Conviction
3/5
Signal quality
C
Resolution
pending
Window
2028-01-01 – 2030-12-31
Edges in / out
7 / 1
Tickers exposed
32

Prediction text

AI will automate away CEO labor; a few more years needed for machines to excel at unskilled manual labor. | machines are able to do complex calculations solve math it's pretty hard for humans there looks like it's going to be easier for the machines to automate away CEO labor which is sufficiently hard for humans that it's well compensated and relatively scarce commodity to find highquality CEOs And yet it'll take a few more years for the machines to do an amazing job at unskilled manual labor.

Watch events: BLS employment reports; tech layoff trackers; Underemployment rate; Yang quarterly updates

Verbatim quote

From episode "AI CEOs Come Online: Sam Altman's Replacement Plan, Job Loss & 'Solve Everything' Launches |EP #230"
machines are able to do complex calculations solve math it's pretty hard for humans there looks like it's going to be easier for the machines to automate away CEO labor which is sufficiently hard for humans that it's well compensated and relatively scarce commodity to find highquality CEOs And yet it'll take a few more years for the machines to do an amazing job at unskilled manual labor.

Predictor: Alex Wissner-Gross

κ + Brier as of 2026-05-22
κ (discount)
0.844
Brier
0.0341
excellent
Hits / Misses
6 / 1
of 11 resolved
Hit rate
54.5%
Calibration plot (stated vs observed)

Evidence about this node from Alex Wissner-Gross is multiplied by κ in /api/intake. Lower κ = less weight; floors at 0.10 (effectively silenced) and caps at 1.00 (full weight).

Reference class

Not linked

This node isn't linked to a reference class. The Bayesian update applies without outside-view blending.

Probability over time

4 prob_history rows
0%25%50%75%100%prior 45%2026-04-302026-05-032026-05-10
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 36.5%

Milestone chain

Pre-event signals (upstream prereqs + window checkpoints) → resolution event → downstream cascades. Status/dates update from linked nodes; re-derive nightly via scripts/ops/derive_milestones.py.
Leading chain: 5 fired ✓ · 6 pending
  1. 2027-01-01 → 2029-06-30pendingFortune-1000 firm publicly automates >= 50% of executive committee functions with AI
    How: Fortune-1000 company discloses in proxy/10-K that >= 50% of senior-executive functions are AI-augmented or AI-led
    Source: deep_research_enrichedconf 45%
  2. 2027-06-01 → 2029-06-30pendingFirst publicly disclosed Fortune-500 CEO (or interim CEO) replaced by AI agent system
    How: Fortune 500 board publicly discloses transition of CEO duties to AI-led decision system (with named architecture)
    Source: deep_research_enrichedconf 20%
  3. 2027-09-01 → 2029-09-30pendingBLS reports manual-labor occupations growing faster than knowledge-worker occupations in 2027-2028
    How: BLS occupational employment statistics show manual-labor occupations net employment growing while knowledge-worker employment falls or stagnates
    Source: deep_research_enrichedconf 55%
  4. 2028-01-01 → 2030-12-31pendingUnskilled-labor humanoid-robot deployment in retail/hospitality remains <5% of US workforce
    How: BLS or industry report shows humanoid robots account for <5% of front-line retail/hospitality labor (slow unskilled-manual displacement)
    Source: deep_research_enrichedconf 78%
  5. 2028-06-01 → 2030-12-31pendingMedian CEO compensation in S&P 500 declines >= 20% from 2024 baseline
    How: Annual proxy-summary database (Equilar/ISS) reports S&P 500 median CEO total comp down >= 20% YoY relative to 2024
    Source: deep_research_enrichedconf 30%
  6. 2028-06-01 → 2030-12-31pendingFirst humanoid robot achieves >= 90% of human dexterity in unstructured manual tasks (independent benchmark)
    How: Independent benchmark (e.g., Stanford ALOHA, NIST robot dexterity index) confirms humanoid achieves >= 90% human dexterity on unstructured manual tasks
    Source: deep_research_enrichedconf 35%

What if this resolves?

Clamp this prediction TRUE or FALSE and run a counterfactual Gibbs sample. Surfaces the predictions whose marginals shift most under that assumption.
(live posterior: 37%)

Click a button to clamp this prediction and run a Gibbs sample. Returns the predictions whose marginals shift most. ~30s per run; ideal for stress-testing "if X resolves, what else moves?"

Evidence chain

Every probability update with full Bayesian provenance — chronological, latest first
LBP2026-05-10T02:00:02Z36.5%-1.1pp
Network propagation: 37.7% → 36.5%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z37.7%-1.7pp
Network propagation: 39.4% → 37.7%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z39.4%-2.4pp
Network propagation: 41.8% → 39.4%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z41.8%-3.2pp
Network propagation: 45.0% → 41.8%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v1 · run 592311ef

Network propagation neighbors

Top edges sorted by latest LBP cross-impact
All propagation →

Top incoming (parents)

Edges that influence THIS node's belief

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereq234_012
Anthropic revenue will cross OpenAI revenue in middle of 202Peter Diamandis
67.1%0.4500.050-0.049
prereq247_058
Jury selection begins April 27, 2026 for Musk v OpenAI trialPeter Diamandis
71.4%0.4500.050-0.033
prereqSEM_042
2025 will be the definitive year that agentic systems finallKevin Weil
73.8%0.4500.050-0.024
prereqSEM_012
Nvidia quadrupled chip production output while only doublingJensen Huang
75.0%0.4500.050-0.018
killerTK04
Macro Recession 2026-27 (Structural Deleveraging)
25.0%0.0500.450-0.015

Top outgoing (children)

Predictions THIS node influences

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereq234_036
Job displacement will be issue 6-10 not top 5 in 10 years; AAlex Wissner-Gross
28.8%0.4500.050-0.095

Ticker exposure

32 ticker(s) linked

Beneficiaries (23)

ADUSCOURDOCNFROGGTLBINODPLROLSPIRSRFMUDMYTEAMNFLXPLTRRDDTUBERAMZNBABASPOTGDDYGOOGLMETAMSFT

Adverse (6)

RHIBXPSLGMANKFYTNET

Prerequisites (7)

Predictions that must hit first
TypePredTitleDomainLag
prereqSEM_008Training runs costing $10 billion for a single model will commence sometime in 2025.AI
prereq247_058Jury selection begins April 27, 2026 for Musk v OpenAI trialAI
prereq234_012Anthropic revenue will cross OpenAI revenue in middle of 2026Markets/Stocks
prereqSEM_0422025 will be the definitive year that agentic systems finally hit the mainstream.AI/Agents
prereqSEM_012Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) across engineering.AI/Manufacturing
killerTK04Macro Recession 2026-27 (Structural Deleveraging)
killerTK07Labor Political Backlash (UBI Mandate / AI Tax)

Dependents (1)

Predictions enabled by this
TypePredTitleDomainLag
prereq234_036Job displacement will be issue 6-10 not top 5 in 10 years; AI discoveries will dominateLabor/Jobs

Expected milestones (1)

From Sheet 17 Monitoring Triggers
Expected byDescriptionStatus
2029-09-30[Labor/Policy 2029-09] [230_002] BLS employment reports; tech layoff trackers; Underemployment rate; Yang quarterly updatespending

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=6P0uTDGDr-I",
  "mode": "PREDICTION",
  "role": "Host",
  "caveats": "Moravec's paradox framing",
  "context": "Moravex paradox which is again this paradox that tasks that are hard for humans and easy for uh for humans are respectively replaced by easy for machines hard for machines machines are able to do complex calculations solve math it's pretty hard for humans there looks like it's going to be easier for the machines to automate away CEO labor... And yet it'll take a few more years for the machines to do an amazing job at unskilled manual labor.",
  "to_year": 2030,
  "verbatim": "machines are able to do complex calculations solve math it's pretty hard for humans there looks like it's going to be easier for the machines to automate away CEO labor which is sufficiently hard for humans that it's well compensated and relatively scarce commodity to find highquality CEOs And yet it'll take a few more years for the machines to do an amazing job at unskilled manual labor.",
  "conv_cues": "looks like; it'll take",
  "direction": "HAPPEN",
  "from_year": 2028,
  "timeframe": "a few more years",
  "conv_level": "MEDIUM",
  "milestones": [
    {
      "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": -11,
      "source_id": "SEM_012",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Training runs costing $10 billion for a single model will commence sometime in 2025.",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -10,
      "source_id": "SEM_008",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Anthropic revenue will cross OpenAI revenue in middle of 2026",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -9,
      "source_id": "234_012",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "2025 will be the definitive year that agentic systems finally hit the mainstream.",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -8,
      "source_id": "SEM_042",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Jury selection begins April 27, 2026 for Musk v OpenAI trial",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -7,
      "source_id": "247_058",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "llm_pre_event",
      "label": "Fortune-1000 firm publicly automates >= 50% of executive committee functions with AI",
      "source": "deep_research_enriched",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -6,
      "source_id": null,
      "confidence": 0.45,
      "source_url": "https://hbr.org",
      "expected_date": "2028-03-31",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2029-06-30",
        "from": "2027-01-01"
      },
      "measurement_criterion": "Fortune-1000 company discloses in proxy/10-K that >= 50% of senior-executive functions are AI-augmented or AI-led"
    },
    {
      "kind": "llm_pre_event",
      "label": "First publicly disclosed Fortune-500 CEO (or interim CEO) replaced by AI agent system",
      "source": "deep_research_enriched",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -5,
      "source_id": null,
      "confidence": 0.2,
      "source_url": "https://en.wikipedia.org/wiki/Chief_executive_officer",
      "expected_date": "2028-06-15",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2029-06-30",
        "from": "2027-06-01"
      },
      "measurement_crit
... (truncated)