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243_021predictionAuto/Transportautonomous

Autonomous cars will make it not sensible to own your own car

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 cars will make it not sensible to own your own car | the promise of autonomous is exactly that, which is it's just not going to make sense for you to own your own car.

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"
the promise of autonomous is exactly that, which is it's just not going to make sense for you to own your own car.

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: 1 fired ✓ · 7 pending
  1. 2026-02-15hitRobotaxi cost-per-mile projected 40-52% below current Uber/Lyft by 2027
    How: Major analyst (PatentPC, Goldman, McKinsey) publishes peer-reviewed forecast that AV cost/mile is 40-52% below human ride-hail by 2027
    Source: https://patentpc.com/blog/robotaxis-in-2025-2030-global-expansion-and-adoption-trends-latest-numbersconf 85%
    Notes: HIT — analyst consensus shows 40% lower cost/mile by 2027 and 52% per-mile reduction in some markets. Cost crossover with ownership = thesis trigger.
  2. 2026-12-31pendingWaymo crosses 1M weekly rides milestone
    How: Waymo publicly reports >=1M weekly autonomous rides
    Source: https://www.automotiveworld.com/news/waymos-metric-for-2026-success-one-million-weekly-rides/conf 85%
    Notes: Currently 400K/week, on track for 1M by EOY. Once at 1M weekly, robotaxi-as-default begins to dominate.
  3. 2026-12-31pendingRobotaxi fleets operate in 20+ markets across 10+ countries
    How: Combined Waymo + Tesla + Pony.ai + Baidu Apollo + WeRide deliver paid rider-only service in 20+ markets across 10+ countries
    Source: https://www.automotiveworld.com/news/455938/conf 75%
    Notes: Uber alone targeting 10 countries 2026; Waymo expanding to London. Geographic coverage = critical mass for behavior change.
  4. 2027-02-03pendingQ1 window check-in (25%)
  5. 2027-11-10pendingQ2 window check-in (50%)
  6. 2027-01-01 → 2029-06-30pendingUS new-car sales decline 10%+ YoY in major metros with robotaxi service
    How: Cox Automotive reports >=10% YoY decline in new-vehicle registrations in 5+ major US robotaxi metros
    Source: Cox Automotive, Edmunds, S&P Mobilityconf 40%
  7. 2028-08-16pendingQ3 window check-in (75%)
  8. 2027-06-01 → 2030-06-30pendingSurvey shows >25% of urban US adults consider not owning a car due to robotaxi access
    How: Pew, Gallup, or AAA national survey shows >=25% of urban US adults state they would forgo car ownership if robotaxi service is reliable in their city
    Source: Pew Research, AAA studiesconf 40%

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 ultimately we think the promise of autonomous is exactly that, which is it's just not going to make sense for you to own your own car.",
  "verbatim": "the promise of autonomous is exactly that, which is it's just not going to make sense for you to own your own car.",
  "conv_cues": "not going to make sense",
  "direction": "DOWN",
  "timeframe": "As autonomous proliferates",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "Robotaxi cost-per-mile projected 40-52% below current Uber/Lyft by 2027",
      "notes": "HIT — analyst consensus shows 40% lower cost/mile by 2027 and 52% per-mile reduction in some markets. Cost crossover with ownership = thesis trigger.",
      "source": "https://patentpc.com/blog/robotaxis-in-2025-2030-global-expansion-and-adoption-trends-latest-numbers",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -8,
      "source_id": null,
      "confidence": 0.85,
      "source_url": "https://patentpc.com/blog/the-future-of-autonomous-vehicles-market-predictions-for-2030-growth-expansion-stats",
      "expected_date": "2025-12-15",
      "observed_date": "2026-02-15",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2026-06-30",
        "from": "2025-06-01"
      },
      "measurement_criterion": "Major analyst (PatentPC, Goldman, McKinsey) publishes peer-reviewed forecast that AV cost/mile is 40-52% below human ride-hail by 2027"
    },
    {
      "kind": "llm_pre_event",
      "label": "Waymo crosses 1M weekly rides milestone",
      "notes": "Currently 400K/week, on track for 1M by EOY. Once at 1M weekly, robotaxi-as-default begins to dominate.",
      "source": "https://www.automotiveworld.com/news/waymos-metric-for-2026-success-one-million-weekly-rides/",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -7,
      "source_id": null,
      "confidence": 0.85,
      "source_url": "https://www.automotiveworld.com/news/waymos-metric-for-2026-success-one-million-weekly-rides/",
      "expected_date": "2026-12-31",
      "research_origin": "deep_research",
      "measurement_criterion": "Waymo publicly reports >=1M weekly autonomous rides"
    },
    {
      "kind": "llm_pre_event",
      "label": "Robotaxi fleets operate in 20+ markets across 10+ countries",
      "notes": "Uber alone targeting 10 countries 2026; Waymo expanding to London. Geographic coverage = critical mass for behavior change.",
      "source": "https://www.automotiveworld.com/news/455938/",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -6,
      "source_id": null,
      "confidence": 0.75,
      "source_url": "https://www.automotiveworld.com/news/455938/",
      "expected_date": "2026-12-31",
      "research_origin": "deep_research",
      "measurement_criterion": "Combined Waymo + Tesla + Pony.ai + Baidu Apollo + WeRide deliver paid rider-only service in 20+ markets across 10+ countries"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -5,
      "source_id": null,
      "expected_date": "2027-02-03",
      "observed_date": null
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -4,
      "source_id": null,
      "expected_date": "2027-11-10",
      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "US new-car sales decline 10%+ YoY in major metros with robotaxi service",
      "source": "Cox Automotive, Edmunds, S&P Mobility",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -3,
      "source_id": null,
      "confidence": 0.4,
      "expected_date": "2028-03-31",
      "research_origin": "training",
      "expect
... (truncated)