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243_047predictionAuto/Transportautonomous

Autonomous revolution will have even more impact on society than Uber

Predictor: Dara Khosrowshahi · ep#243 "Uber vs. Tesla, Robotaxi Timelines, and the End of Human Driving | Uber CEO Dara Khosrowshahi | #243" · source

Prior probability
60.0%
Current probability
44.4%
evolves via intake + LBP
Conviction
4/5
Signal quality
C
Resolution
pending
Window
2026-04-30 – 2030-11-30
Edges in / out
3 / 0
Tickers exposed
31

Prediction text

Autonomous revolution will have even more impact on society than Uber | this is a company that is having real impact on society and how society moves. And I think with autonomous revolution, even more so.

Watch events: Waymo 1M rides/wk (end-2026); Tesla Robotaxi scaling; NHTSA AV rules

Verbatim quote

From episode "Uber vs. Tesla, Robotaxi Timelines, and the End of Human Driving | Uber CEO Dara Khosrowshahi | #243"
this is a company that is having real impact on society and how society moves. And I think with autonomous revolution, even more so.

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

5 prob_history rows
0%25%50%75%100%prior 60%2026-04-302026-05-032026-05-17
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 44.4%

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: 2 fired ✓ · 6 pending
  1. 2025-04-22hit13% of Americans report planning to ditch car ownership by 2030
    How: Zipcar/national survey shows 10% or more Americans planning to abandon car ownership within decade due to autonomous/shared mobility
    Source: https://www.zipcar.com/press/news/dream-green-2025 — 1/3 of Americans may ditch car ownership by 2030conf 85%
    Notes: Zipcar press release reports up to 13%-33% of US considering abandoning ownership — Uber-scale societal shift in mobility consumption.
  2. 2026-04-19hitUber commits $10B to autonomous infrastructure (April 2026)
    How: Uber announces ~$10B AV commitment, signaling structural societal-scale capital deployment
    Source: https://techcrunch.com/2026/04/19/techcrunch-mobility-uber-enters-its-assetmaxxing-era/conf 95%
  3. 2027-02-20pendingQ1 window check-in (25%)
  4. 2027-12-14pendingQ2 window check-in (50%)
  5. 2027-06-01 → 2028-12-31pendingRobotaxis surpass 5% of US ride-hailing rides nationally
    How: BTS / Smart Cities Dive / industry data shows robotaxi share of US ride-hailing trips 5% or higher nationally
    Source: Smart Cities Dive robotaxi trackerconf 55%
  6. 2028-10-06pendingQ3 window check-in (75%)
  7. 2028-01-01 → 2029-12-31pendingMajor US auto manufacturer reports YoY decline in private vehicle sales attributed to AV
    How: GM, Ford, Stellantis, or Toyota cite robotaxi/shared mobility as material headwind to YoY US private vehicle sales in earnings call
    Source: Q-earnings call transcripts, auto OEM 10-K MD&Aconf 50%
  8. 2028-01-01 → 2030-11-30pendingMainstream news outlets characterize 'autonomous revolution' as larger societal shift than ride-hailing era
    How: 3+ major outlets (NYT, WSJ, Bloomberg, FT, The Atlantic, The Economist) publish framing pieces explicitly comparing AV impact greater than Uber/Lyft impact circa 2010-2020
    Source: NYT/WSJ/Bloomberg archive searchconf 55%

No downstream cascades — this prediction is a leaf in the dependency graph.

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: 44%)

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
LBP2026-05-17T02:00:01Z44.4%-1.7pp
Network propagation: 46.2% → 44.4%
5-iter LBP, residual 0.00689 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e607fa96
LBP2026-05-10T02:00:02Z46.2%-3.4pp
Network propagation: 49.6% → 46.2%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z49.6%-6.8pp
Network propagation: 56.4% → 49.6%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z56.4%-1.2pp
Network propagation: 57.6% → 56.4%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z57.6%-2.4pp
Network propagation: 60.0% → 57.6%
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
prereqS_ROBOTAXI_MASS_2030
Robotaxi >10% urban miles by Nov 2030
30.0%0.6000.050-0.229
killerTK06
China-Taiwan Military Conflict
8.0%0.0500.600+0.112
killerTK11
Autonomous Regulatory Block (Level 4 Halt)
10.0%0.0500.600+0.101

Top outgoing (children)

Predictions THIS node influences

No outgoing edges.

Ticker exposure

31 ticker(s) linked

Beneficiaries (24)

INVZWRDLIDRAEVAMBLYPONYOUSTVRRMAMBAAURAIOTHSAIMBGAFBIDUBMWYYGMGOOGLHMCIOTQCOMTMTSLAUBERVWAGY

Adverse (5)

MCYALLCINFPGRTRV

Prerequisites (3)

Predictions that must hit first
TypePredTitleDomainLag
prereqS_ROBOTAXI_MASS_2030Robotaxi >10% urban miles by Nov 2030robotaxi_deployment
killerTK11Autonomous Regulatory Block (Level 4 Halt)
killerTK06China-Taiwan Military Conflict

Dependents (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=fzKVYNBg50E",
  "mode": "THESIS",
  "role": "Guest-CEO",
  "context": "I think with autonomous revolution, even more so.",
  "verbatim": "this is a company that is having real impact on society and how society moves. And I think with autonomous revolution, even more so.",
  "conv_cues": "I think",
  "direction": "UP",
  "timeframe": "Future",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "13% of Americans report planning to ditch car ownership by 2030",
      "notes": "Zipcar press release reports up to 13%-33% of US considering abandoning ownership — Uber-scale societal shift in mobility consumption.",
      "source": "https://www.zipcar.com/press/news/dream-green-2025 — 1/3 of Americans may ditch car ownership by 2030",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -8,
      "source_id": null,
      "confidence": 0.85,
      "source_url": "https://www.zipcar.com/press/news/dream-green-2025",
      "expected_date": "2025-04-22",
      "observed_date": "2025-04-22",
      "research_origin": "deep_research",
      "measurement_criterion": "Zipcar/national survey shows 10% or more Americans planning to abandon car ownership within decade due to autonomous/shared mobility"
    },
    {
      "kind": "llm_pre_event",
      "label": "Uber commits $10B to autonomous infrastructure (April 2026)",
      "source": "https://techcrunch.com/2026/04/19/techcrunch-mobility-uber-enters-its-assetmaxxing-era/",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -7,
      "source_id": null,
      "confidence": 0.95,
      "source_url": "https://techcrunch.com/2026/04/19/techcrunch-mobility-uber-enters-its-assetmaxxing-era/",
      "expected_date": "2026-04-19",
      "observed_date": "2026-04-19",
      "research_origin": "deep_research",
      "measurement_criterion": "Uber announces ~$10B AV commitment, signaling structural societal-scale capital deployment"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -6,
      "source_id": null,
      "expected_date": "2027-02-20",
      "observed_date": null
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -5,
      "source_id": null,
      "expected_date": "2027-12-14",
      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "Robotaxis surpass 5% of US ride-hailing rides nationally",
      "source": "Smart Cities Dive robotaxi tracker",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -4,
      "source_id": null,
      "confidence": 0.55,
      "source_url": "https://www.smartcitiesdive.com/news/robotaxi-waymo-motional-zoox-tesla-uber-lyft/759895/",
      "expected_date": "2028-03-16",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2028-12-31",
        "from": "2027-06-01"
      },
      "measurement_criterion": "BTS / Smart Cities Dive / industry data shows robotaxi share of US ride-hailing trips 5% or higher nationally"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q3 window check-in (75%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -3,
      "source_id": null,
      "expected_date": "2028-10-06",
      "observed_date": null
    },
    {
      "kind": "llm_post_event",
      "label": "Major US auto manufacturer reports YoY decline in private vehicle sales attributed to AV",
      "source": "Q-earnings call transcripts, auto OEM 10-K MD&A",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -2,
      "source_id": null,
      "confidence": 0.5,
      "expected_date": "2028-12-31",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2029-12-31",
        "from": "2028-01-01"
      },
... (truncated)