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244_023predictionLabor/JobsAI-timing

Over next 10 years, will see a lot of augmentation of work and some replacement

Predictor: Dara Khosrowshahi · ep#244 "Uber's Robotaxi Playbook, End of Human Driving & $10B Bet on Robots | Dara Khosrowshahi (Uber CEO)" · source

Prior probability
60.0%
Current probability
51.0%
evolves via intake + LBP
Conviction
4/5
Signal quality
C
Resolution
pending
Window
2026-01-01 – 2036-12-31
Edges in / out
7 / 3
Tickers exposed
33

Prediction text

Over next 10 years, will see a lot of augmentation of work and some replacement | I do think that over the next 10 years, you will see a lot of augmentation of work um and some replacement of work.

Verbatim quote

From episode "Uber's Robotaxi Playbook, End of Human Driving & $10B Bet on Robots | Dara Khosrowshahi (Uber CEO)"
I do think that over the next 10 years, you will see a lot of augmentation of work um and some replacement of work.

Predictor: Dara Khosrowshahi

κ + Brier as of 2026-05-22
κ (discount)
0.688
Brier
0.0105
excellent
Hits / Misses
2 / 0
of 3 resolved
Hit rate
66.7%
Calibration plot (stated vs observed)

Evidence about this node from Dara Khosrowshahi 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 60%2026-04-302026-05-032026-05-10
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 51.0%

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: 4 fired ✓ · 5 pending
  1. 2026-06-30 → 2028-12-31pendingAI-augmented worker productivity gains reach >50% in measured pilot studies for knowledge work
    How: MIT/NBER/Harvard or BLS-cited RCT shows >=50% productivity gain (output/hour) from AI augmentation in coding, customer service, legal research, or analyst work, replicated in >=3 studies
    Source: GitHub Copilot 55% study; Brynjolfsson customer service +14%conf 60%
  2. 2027-01-01 → 2029-06-30pendingJob replacement metric: >=10% of new entry-level white-collar postings disappear vs 2024 baseline
    How: BLS, ADP, Indeed, or LinkedIn Workforce Report shows >=10% YoY decline in entry-level postings for AI-exposed occupations (paralegal, junior dev, data entry, customer support tier-1) vs 2024 baseline
    Source: Anthropic 'modestly slower hiring' research; Stanford Instituteconf 65%
  3. 2027-01-01 → 2030-12-31pendingWEF Future of Jobs report flips augmentation:replacement narrative
    How: WEF or OECD Future of Jobs report (or successor) revises current 'net employment increase of 7%' to net loss territory in advanced economies, explicitly attributing to AI/agent automation
    Source: WEF Future of Jobs Report 2025: 92M displaced, 170M createdconf 45%
  4. 2028-01-01 → 2032-12-31pendingFirst major economy publishes UBI/wage-insurance pilot in response to AI displacement
    How: G20 country launches >=$1B funded pilot program (UBI, wage insurance, or transition fund) explicitly framed as response to AI-driven labor displacement, with academic evaluation framework
    Source: OpenAI/YC UBI experiments; Kenya GiveDirectly; Sam Altman policy statementsconf 40%
  5. 2030-01-01 → 2034-12-31pendingWorkforce composition shows clear bifurcation: 'AI-augmented' vs 'AI-replaced' becomes standard labor-economics framing
    How: BLS/OECD/ILO labor reports formalize 'AI-augmented worker' as a tracked category with wage premium quantified, while 'replaced occupations' list grows to >=50 SOC codes
    Source: OECD 27% high-automation-risk baselineconf 55%

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: 51%)

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
LBP2026-05-10T02:00:02Z51.0%-1.1pp
Network propagation: 52.1% → 51.0%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z52.1%-1.7pp
Network propagation: 53.8% → 52.1%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z53.8%-2.4pp
Network propagation: 56.2% → 53.8%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z56.2%-3.8pp
Network propagation: 60.0% → 56.2%
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
prereqSEM_042
2025 will be the definitive year that agentic systems finallKevin Weil
73.8%0.6000.050-0.059
prereqSEM_012
Nvidia quadrupled chip production output while only doublingJensen Huang
75.0%0.6000.050-0.051
prereqSEM_008
Training runs costing $10 billion for a single model will coDario Amodei
76.9%0.6000.050-0.042
prereq238_009
Recursive self-improvement is already happening now (no longAlex Wissner-Gross
78.1%0.6000.050-0.035
killerTK03
AI Regulatory Moratorium (EU/US Capability Freeze)
10.0%0.0500.600+0.035

Top outgoing (children)

Predictions THIS node influences

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereq244_029
Combustion engines largely gone in 20 years but world will bDara Khosrowshahi
35.4%0.5500.050-0.052
prereq240_036
TEPCO's restarted reactor will support 20% of Japan's electrPeter Diamandis
34.3%0.6500.050+0.009
prereq232_047
Mass drivers on the moon will shoot AI satellites into deep Elon Musk
30.0%0.5500.050+0.002

Ticker exposure

33 ticker(s) linked

Beneficiaries (23)

SOUNCRWVSITMNVDAARMGTLBBBAITSMAPLDCEVAAIMSFTMRVLSFTBYORCLQCOMAVGOBABAAMDGOOGLIBMAMZNMETA

Adverse (6)

WNSCHGGCTSHIBMINFYACN

Prerequisites (7)

Predictions that must hit first
TypePredTitleDomainLag
prereq238_009Recursive self-improvement is already happening now (no longer three years out)AI
prereqSEM_008Training runs costing $10 billion for a single model will commence sometime in 2025.AI
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
killerTK14Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates)
killerTK01AGI Capability Plateau (2026-27 Training Stall)
killerTK03AI Regulatory Moratorium (EU/US Capability Freeze)

Dependents (3)

Predictions enabled by this
TypePredTitleDomainLag
prereq240_036TEPCO's restarted reactor will support 20% of Japan's electric needs by 2040Energy
prereq232_047Mass drivers on the moon will shoot AI satellites into deep space; self-sustaining lunar city will follow.Space
prereq244_029Combustion engines largely gone in 20 years but world will be very differentEnergy

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "qty": "10 years",
  "url": "https://www.youtube.com/watch?v=Mh9yC4j0_rI",
  "mode": "PREDICTION",
  "role": "Guest-CEO",
  "context": "I do think that over the next 10 years, you will see a lot of augmentation of work um and some replacement of work. And historically, our society has been able to adjust and as some work has been augmented or replaced, new work shows up, etc.",
  "to_year": 2036,
  "verbatim": "I do think that over the next 10 years, you will see a lot of augmentation of work um and some replacement of work.",
  "conv_cues": "I do think; you will see",
  "direction": "MIXED",
  "from_year": 2026,
  "timeframe": "By 2036 (next 10 years)",
  "conv_level": "HIGH",
  "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": -9,
      "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": -8,
      "source_id": "SEM_008",
      "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": -7,
      "source_id": "SEM_042",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Recursive self-improvement is already happening now (no longer three years out)",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -6,
      "source_id": "238_009",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "llm_pre_event",
      "label": "AI-augmented worker productivity gains reach >50% in measured pilot studies for knowledge work",
      "source": "GitHub Copilot 55% study; Brynjolfsson customer service +14%",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -5,
      "source_id": null,
      "confidence": 0.6,
      "expected_date": "2027-09-30",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2028-12-31",
        "from": "2026-06-30"
      },
      "measurement_criterion": "MIT/NBER/Harvard or BLS-cited RCT shows >=50% productivity gain (output/hour) from AI augmentation in coding, customer service, legal research, or analyst work, replicated in >=3 studies"
    },
    {
      "kind": "llm_pre_event",
      "label": "Job replacement metric: >=10% of new entry-level white-collar postings disappear vs 2024 baseline",
      "source": "Anthropic 'modestly slower hiring' research; Stanford Institute",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -4,
      "source_id": null,
      "confidence": 0.65,
      "expected_date": "2028-03-31",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2029-06-30",
        "from": "2027-01-01"
      },
      "measurement_criterion": "BLS, ADP, Indeed, or LinkedIn Workforce Report shows >=10% YoY decline in entry-level postings for AI-exposed occupations (paralegal, junior dev, data entry, customer support tier-1) vs 2024 baseline"
    },
    {
      "kind": "llm_pre_event",
      "label": "WEF Future of Jobs report flips augmentation:replacement narrative",
      "source": "WEF Future of Jobs Report 2025: 92M displaced, 170M created",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -3,
      "source_id": null,
      "confidence": 0.45,
      "source_url": "https://reports.weforum.org/docs/WEF_Future_of_Jobs_Report_2025.pdf",
      "expected_date": "2028-12-31",
      "research_origin": "traini
... (truncated)