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244_036predictionAIAI-scaling

Uber AI Solutions will bring flexible work opportunities (labeling, model testing)

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
49.5%
evolves via intake + LBP
Conviction
4/5
Signal quality
C
Resolution
pending
Window
2026-06-01 – 2026-06-30
Edges in / out
10 / 5
Tickers exposed
37

Prediction text

Uber AI Solutions will bring flexible work opportunities (labeling, model testing) | Uber AI solution has nothing to do with movement, but actually is a kind of work flexible work opportunities that we're bring either to our drivers or entirely new people coming onto the platform to go out and design new models or or do labeling for for new models or test out uh models, etc.

Verbatim quote

From episode "Uber's Robotaxi Playbook, End of Human Driving & $10B Bet on Robots | Dara Khosrowshahi (Uber CEO)"
Uber AI solution has nothing to do with movement, but actually is a kind of work flexible work opportunities that we're bring either to our drivers or entirely new people coming onto the platform to go out and design new models or or do labeling for for new models or test out uh models, etc.

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 = 49.5%

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: 6 fired ✓
  1. 2025-09-15hitUber launches data-labeling earning option for US drivers
    How: Uber publicly launches pilot enabling US drivers to earn extra income from AI data labeling tasks
    Source: https://www.pymnts.com/artificial-intelligence-2/2025/uber-lets-us-drivers-earn-extra-income-with-ai-data-labeling-tasks/conf 99%
    Notes: HIT — US driver data labeling pilot launched in 2025.
  2. 2026-03-31hituLabel/uTask platform deployed and operational
    How: Uber's uLabel or uTask platforms confirmed available for AI data labeling work via investor materials or product page
    Source: https://www.uber.com/us/en/ai-solutions/annotation/conf 95%
    Notes: HIT — Annotation platform live on Uber AI Solutions site.
  3. 2026-06-01 → 2027-12-31pending100K+ Uber drivers participate in AI labeling tasks
    How: Uber publicly discloses ≥100,000 drivers/workers earning income through Uber AI Solutions task work
    Source: Uber investor day materials, earnings callsconf 60%
  4. 2026-06-01 → 2027-12-31pendingNew non-driver workers onboard through Uber AI platform
    How: Uber confirms onboarding net-new workers (not existing drivers) for AI labeling/testing work
    Source: https://www.uber.com/us/en/ai-solutions/conf 70%
  5. 2027-01-01 → 2028-12-31pendingUber AI Solutions becomes top-3 global data labeling vendor
    How: Industry analyst (Gartner/Everest) ranks Uber AI Solutions in top 3 data labeling/annotation vendors globally by revenue
    Source: https://www.cio.com/article/4074193/uber-wants-to-become-the-uber-of-data-labeling.htmlconf 45%

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: 50%)

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
LBP2026-05-10T02:00:02Z49.5%-1.2pp
Network propagation: 50.7% → 49.5%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z50.7%-2.2pp
Network propagation: 52.9% → 50.7%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z52.9%-2.9pp
Network propagation: 55.8% → 52.9%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z55.8%-4.2pp
Network propagation: 60.0% → 55.8%
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
killerTK09
Energy Grid Cap (Data Center Power Wall)
35.0%0.0500.600-0.088
prereqSEM_015
Nvidia agreed to remit 15% of China chip-sale revenue directJensen Huang
66.3%0.6000.050-0.076
prereqSEM_027
Nvidia Data Center revenue +66% YoY, contributing ~90% of $5Joseph Moore
68.3%0.6000.050-0.075
killerTK05
Rate Regime Persistence (10y > 5% through 2028)
30.0%0.0500.600-0.060
killerTK03
AI Regulatory Moratorium (EU/US Capability Freeze)
10.0%0.0500.600+0.050

Top outgoing (children)

Predictions THIS node influences

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereq248_040
Pausing AI will fail and only accelerate race dynamics.Alex Wissner-Gross
53.0%0.9200.050-0.056
prereq247_023
AI will be able to do everything a white collar worker does Dave Blundin
40.8%0.7200.050-0.031
prereq242_031
Most large companies' business models will be disrupted in 2Peter Diamandis
36.1%0.6500.050-0.018
prereq232_055
We're exiting the industrial age permanently as recursive sePeter Diamandis
35.5%0.7000.050+0.013
prereq244_019
Peter's son won't need a driver's license in 2 yearsPeter Diamandis
48.4%0.9200.050-0.010

Ticker exposure

37 ticker(s) linked

Beneficiaries (24)

MUWULFIRENEQIXALABAPLDASMIYASMLPLABNVDANBISCRWVAAPLAMTAMZNDELLGOOGLIRMLNVGYMETAMSFTORCLSFTBYSTX

Adverse (6)

ACNGENCHGGIBMWNSLRN

Prerequisites (10)

Predictions that must hit first
TypePredTitleDomainLag
prereqSEM_011Nvidia became the world's first $5 trillion company (late 2025), operating a near-monopoly on advanced AI chips.Capital Markets
prereqSEM_027Nvidia Data Center revenue +66% YoY, contributing ~90% of $57B fiscal Q3 revenue; >$4.5T market cap entirely underpinned by AI silicon.Capital Markets
prereqSEM_014Nvidia's Arizona-based TSMC factory successfully fabricated cutting-edge semiconductors on US soil for first time in decades (October 2025).Manufacturing
prereqSEM_012Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) across engineering.AI/Manufacturing
prereqSEM_015Nvidia agreed to remit 15% of China chip-sale revenue directly to US government in exchange for reversing specific AI chip export bans.Policy/Semis
killerTK09Energy Grid Cap (Data Center Power Wall)
killerTK05Rate Regime Persistence (10y > 5% through 2028)
killerTK01AGI Capability Plateau (2026-27 Training Stall)
killerTK02AI Compute Supply Shock (TSMC/Taiwan Disruption)
killerTK03AI Regulatory Moratorium (EU/US Capability Freeze)

Dependents (5)

Predictions enabled by this
TypePredTitleDomainLag
prereq244_019Peter's son won't need a driver's license in 2 yearsAuto/Transport
prereq248_040Pausing AI will fail and only accelerate race dynamics.AI
prereq247_023AI will be able to do everything a white collar worker does imminentlyAI
prereq232_055We're exiting the industrial age permanently as recursive self-improvement unfolds.AI
prereq242_031Most large companies' business models will be disrupted in 2-5 yearsMarkets/Stocks

Linked documents (1)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.583manifoldWill MNX hire a backend developer before Manifest?26%mentionspending2026-04-30

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=Mh9yC4j0_rI",
  "mode": "FORECAST",
  "role": "Guest-CEO",
  "context": "Uber AI solution has nothing to do with movement, but actually is a kind of work flexible work opportunities that we're bring either to our drivers or entirely new people coming onto the platform to go out and design new models or or do labeling for for new models or test out uh models, etc.",
  "to_year": 2026,
  "verbatim": "Uber AI solution has nothing to do with movement, but actually is a kind of work flexible work opportunities that we're bring either to our drivers or entirely new people coming onto the platform to go out and design new models or or do labeling for for new models or test out uh models, etc.",
  "conv_cues": "we're bring",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "Near term / ongoing",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "Uber launches data-labeling earning option for US drivers",
      "notes": "HIT — US driver data labeling pilot launched in 2025.",
      "source": "https://www.pymnts.com/artificial-intelligence-2/2025/uber-lets-us-drivers-earn-extra-income-with-ai-data-labeling-tasks/",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -6,
      "source_id": null,
      "confidence": 0.99,
      "source_url": "https://www.pymnts.com/artificial-intelligence-2/2025/uber-lets-us-drivers-earn-extra-income-with-ai-data-labeling-tasks/",
      "expected_date": "2025-09-15",
      "observed_date": "2025-09-15",
      "research_origin": "deep_research",
      "measurement_criterion": "Uber publicly launches pilot enabling US drivers to earn extra income from AI data labeling tasks"
    },
    {
      "kind": "llm_pre_event",
      "label": "uLabel/uTask platform deployed and operational",
      "notes": "HIT — Annotation platform live on Uber AI Solutions site.",
      "source": "https://www.uber.com/us/en/ai-solutions/annotation/",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -5,
      "source_id": null,
      "confidence": 0.95,
      "source_url": "https://www.uber.com/us/en/ai-solutions/annotation/",
      "expected_date": "2026-03-31",
      "observed_date": "2026-03-31",
      "research_origin": "deep_research",
      "measurement_criterion": "Uber's uLabel or uTask platforms confirmed available for AI data labeling work via investor materials or product page"
    },
    {
      "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": -4,
      "source_id": "SEM_011",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "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": -3,
      "source_id": "SEM_027",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "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": -2,
      "source_id": "SEM_014",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "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": -1,
      "source_id": "SEM_012",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "event",
      "label": "Uber AI Solutions will bring flexible work opportunities (labeli
... (truncated)