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AI_023predictionAIsynthetic-CEO-clone

Inside Uber, 90% of software engineers currently rely on AI, and executive teams rehearse high-stakes presentations using 'Dara AI' — a synthetic, agentic clone of the CEO that pressure-tests narratives and logic before human executive meetings.

Predictor: Dara Khosrowshahi

Prior probability
95.0%
Current probability
95.0%
evolves via intake + LBP
Conviction
5/5
Signal quality
B
Resolution
hit
Window
2026-01-01 – 2026-08-31
Edges in / out
0 / 0
Tickers exposed
0

Prediction text

Inside Uber, 90% of software engineers currently rely on AI, and executive teams rehearse high-stakes presentations using 'Dara AI' — a synthetic, agentic clone of the CEO that pressure-tests narratives and logic before human executive meetings. | Next Fortune-500 synthetic-CEO clone disclosure

Key catalyst: Next Fortune-500 synthetic-CEO clone disclosure

Watch events: Fortune 500 synthetic-executive deployments; governance guidance

Resolution evidence

Status: hit

Uber Q1 2026 interviews and internal memos; precedent for enterprise "digital twin" executive deployment.

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

1 prob_history rows
0%25%50%75%100%prior 95%2026-04-29
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 95.0%

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: 3 overdue ⏱
  1. 2026-01-30overdueQ1 window check-in (25%)
  2. 2026-03-01overdueQ2 window check-in (50%)
  3. 2026-03-30overdueQ3 window check-in (75%)

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: 95%)

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
resolution_terminal2026-04-29T22:23:18Z100.0%+5.0pp
resolution_terminal hit outcome=1.0 pre_resolution=0.950
Raw metadata
{
  "source": "backfill_resolution_history.py",
  "status": "hit",
  "bayesian_v2": false,
  "outcome_prob": 1,
  "evidence_kind": "resolution_terminal",
  "posterior_prob": 1,
  "delta_to_outcome": 0.050000000000000044,
  "inside_posterior": 0.95,
  "validation_notes": "Uber Q1 2026 interviews and internal memos; precedent for enterprise \"digital twin\" executive deployment.",
  "validation_status": "hit",
  "pre_resolution_prob": 0.95,
  "resolution_evidence": "Uber Q1 2026 interviews and internal memos; precedent for enterprise \"digital twin\" executive deployment.",
  "does_not_update_current_prob": true
}

Network propagation neighbors

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

No propagation data yet. Run inference/.venv/bin/python scripts/ops/run_loopy_belief_propagation.py on the droplet, or wait for the Sunday 02:00 UTC weekly cron.

Prerequisites (0)

Predictions that must hit first
TypePredTitleDomainLag
No prerequisites

Dependents (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Validations (1)

Resolution events
Observed atStatusByNotes
2026-04-29hitthesis_timeline_v1.0_importUber Q1 2026 interviews and internal memos; precedent for enterprise "digital twin" executive deployment.

Linked documents (3)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.646arxivVET: A Framework for Analyzing AI Discoursementionspending2026-06-01
0.623arxivEVA-Bench: A New End-to-end Framework for Evaluating Voice Agentsmentionspending2026-05-13
0.588gdeltgoogle microsoft prove ai cloud driving ad reven.htmlmentionspending2026-04-30

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "qty": "90% SWE AI-reliance",
  "mode": "OBSERVATION+FORECAST",
  "role": "Cited-CEO",
  "context": "Specific operational proof-point of agentic AI enterprise adoption; Khosrowshahi's distinctive leadership-augmentation example. Couples with AI_010 (Slopacolypse).",
  "to_year": 2026,
  "conv_cues": "specific operational deployment; CEO FIRST_PERSON",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "2026 operational",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -3,
      "source_id": null,
      "expected_date": "2026-01-30",
      "observed_date": null,
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -2,
      "source_id": null,
      "expected_date": "2026-03-01",
      "observed_date": null,
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q3 window check-in (75%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -1,
      "source_id": null,
      "expected_date": "2026-03-30",
      "observed_date": null,
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "event",
      "label": "Inside Uber, 90% of software engineers currently rely on AI, and executive teams rehearse high-stakes presentations using 'Dara AI' — a synt",
      "status": "hit",
      "weight": 1,
      "ordinal": 0,
      "source_id": "AI_023",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    }
  ],
  "repeat_eps": 1,
  "affiliation": "Uber",
  "attribution": "FIRST_PERSON",
  "granularity": "YEAR",
  "resolved_at": "2026-04-29T22:23:18.213231+00:00",
  "source_refs": "38, 40",
  "target_date": "2026-06-15T00:00:00",
  "display_date": "2026-04-29",
  "episode_date": "2026-04-21T00:00:00",
  "key_catalyst": "Next Fortune-500 synthetic-CEO clone disclosure",
  "parse_method": "Current-state observation",
  "domain_bucket": "AI",
  "episode_title": "Forecasting the Inference Epoch: Expert AI Predictions & Macroeconomic Trajectories (2023-2026)",
  "flag_repeated": false,
  "in_5yr_window": true,
  "source_report": "AI Predictions Search Plan.md (2026-04-21)",
  "appears_in_eps": "AI-RPT",
  "futurist_phase": "Phase 1 (2026)",
  "is_macro_claim": false,
  "total_mentions": 1,
  "priority_weight": 4,
  "report_evidence": "Anchor section: Great Disemboweling / Enterprise Agents.",
  "active_end_month": "2026-12",
  "recent_statement": "Khosrowshahi Times of India 2026.",
  "watch_events_raw": "Fortune 500 synthetic-executive deployments; governance guidance",
  "months_from_today": 2,
  "probability_layer": "Higher (in-flight)",
  "active_start_month": "2026-01",
  "december_dispersal": {
    "reason": "december_dispersal: domain=AI → 08/2026",
    "new_date": "2026-08-31",
    "old_date": "2026-12-31",
    "applied_at": "2026-04-30T16:28:34.304992+00:00"
  },
  "flag_nia_bracketed": false,
  "resolved_at_source": "validations_observed_at",
  "track_record_grade": "B",
  "track_record_notes": "Khosrowshahi internal-operations disclosures reliable.",
  "contradicting_notes": "Synthetic-clone fidelity and legal/governance implications untested at scale.",
  "flag_near_term_2027": false,
  "flag_high_conviction": true,
  "milestones_derived_at": "2026-05-02T03:08:50.501794+00:00",
  "reference_class_match": {
    "decision": "keyword_filtered",
    "computed_at": "2026-04-30T01:49:13.796883+00:00",
    "best_id_unfiltered": "regulatory_freeze_window",
    "best_similarity_unfiltered": 0.5619
  },
  "validati