Critical misalignment in the AI industry: approximately 300 AI capabilities researchers for every one AGI safety researcher — extreme systemic risk as these autonomous systems are deployed into physical domains like space and embodied robotics.
Predictor: Leopold Aschenbrenner
Prediction text
Critical misalignment in the AI industry: approximately 300 AI capabilities researchers for every one AGI safety researcher — extreme systemic risk as these autonomous systems are deployed into physical domains like space and embodied robotics. | Next major frontier-lab safety-team restructuring
Key catalyst: Next major frontier-lab safety-team restructuring
Watch events: AISI capacity; frontier-lab alignment-team sizing
Resolution evidence
Situational Awareness 2024 paper documents alignment-researcher shortfall; AISI / Anthropic / RAND research validates ratio broadly.
Predictor: Leopold Aschenbrenner
Calibration plot (stated vs observed)
Evidence about this node from Leopold Aschenbrenner 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: agi_breakthrough_5y
Major capability discontinuity (e.g. AGI by named target year, 5-year horizon)
Tetlock-style outside view: at TRF=1 (just predicted), outside view dominates (w_in=0.3). At TRF=0 (deadline), inside view dominates (w_in=1.0). The blend regularizes overconfident inside views toward the historical base rate.
Probability over time
Milestone chain
- 2024-07-31overdueQ1 window check-in (25%)
- 2025-02-28overdueQ2 window check-in (50%)
- 2025-09-28overdueQ3 window check-in (75%)
No downstream cascades — this prediction is a leaf in the dependency graph.
What if this resolves?
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
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": 0.27823,
"inside_posterior": 0.72177,
"validation_notes": "Situational Awareness 2024 paper documents alignment-researcher shortfall; AISI / Anthropic / RAND research validates ratio broadly.",
"validation_status": "hit",
"pre_resolution_prob": 0.72177,
"resolution_evidence": "Situational Awareness 2024 paper documents alignment-researcher shortfall; AISI / Anthropic / RAND research validates ratio broadly.",
"does_not_update_current_prob": true
}Network propagation neighbors
Top incoming (parents)
Edges that influence THIS node's belief
| Kind | Node | Their prob | P(c|s=T) | P(c|s=F) | Δ implied |
|---|---|---|---|---|---|
| killer | TK06 China-Taiwan Military Conflict | 8.0% | 0.050 | 0.800 | +0.099 |
| killer | TK03 AI Regulatory Moratorium (EU/US Capability Freeze) | 10.0% | 0.050 | 0.800 | +0.084 |
| killer | TK11 Autonomous Regulatory Block (Level 4 Halt) | 10.0% | 0.050 | 0.800 | +0.084 |
| killer | TK01 AGI Capability Plateau (2026-27 Training Stall) | 15.0% | 0.050 | 0.800 | +0.046 |
| killer | TK08 Humanoid Capital Collapse (Figure/Apptronik Flop) | 22.0% | 0.050 | 0.800 | -0.006 |
Top outgoing (children)
Predictions THIS node influences
No outgoing edges.
Ticker exposure
Adverse (4)
Prerequisites (8)
| Type | Pred | Title | Domain | Lag |
|---|---|---|---|---|
| correlate | S_AGI_FAST_2027 | AGI fast: drop-in remote worker by 2027-09 | agi_general_capability | — |
| correlate | S_ROBOTAXI_MASS_2030 | Robotaxi >10% urban miles by Nov 2030 | robotaxi_deployment | — |
| correlate | S_AGI_WINTER_2036PLUS | AGI delayed: capability plateau or AI winter | agi_general_capability | — |
| killer | TK08 | Humanoid Capital Collapse (Figure/Apptronik Flop) | — | — |
| killer | TK01 | AGI Capability Plateau (2026-27 Training Stall) | — | — |
| killer | TK11 | Autonomous Regulatory Block (Level 4 Halt) | — | — |
| killer | TK03 | AI Regulatory Moratorium (EU/US Capability Freeze) | — | — |
| killer | TK06 | China-Taiwan Military Conflict | — | — |
Dependents (0)
| Type | Pred | Title | Domain | Lag |
|---|---|---|---|---|
| No dependents | ||||
Validations (1)
| Observed at | Status | By | Notes |
|---|---|---|---|
| 2026-04-29 | hit | thesis_timeline_v1.0_import | Situational Awareness 2024 paper documents alignment-researcher shortfall; AISI / Anthropic / RAND research validates ratio broadly. |
Linked documents (10)
Raw metadata
{
"nia": false,
"qty": "300:1 ratio",
"mode": "OBSERVATION+WARNING",
"role": "Cited-VC/Researcher",
"context": "Specific quantitative imbalance framing. Couples with AI_036 (RLHF fails for ASI), CYB_026 (US moat undermined), INF_002 (The Project).",
"to_year": 2026,
"conv_cues": "specific quantitative ratio; safety-risk framing",
"direction": "HAPPEN",
"from_year": 2024,
"timeframe": "2024-2026",
"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": "2024-07-31",
"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": "2025-02-28",
"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": "2025-09-28",
"observed_date": null,
"miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
"miss_emitted_by": "metadata_milestone_sweep"
},
{
"kind": "event",
"label": "Critical misalignment in the AI industry: approximately 300 AI capabilities researchers for every one AGI safety researcher — extreme system",
"status": "hit",
"weight": 1,
"ordinal": 0,
"source_id": "SPC_025",
"expected_date": "2026-04-29",
"observed_date": "2026-04-29"
}
],
"repeat_eps": 1,
"affiliation": "Situational Awareness LP",
"attribution": "FIRST_PERSON",
"granularity": "YEAR_RANGE",
"resolved_at": "2026-04-29T22:23:18.270287+00:00",
"source_refs": "39, 41",
"target_date": "2026-06-15T00:00:00",
"display_date": "2026-04-29",
"episode_date": "2026-04-21T00:00:00",
"key_catalyst": "Next major frontier-lab safety-team restructuring",
"parse_method": "Current-state observation",
"domain_bucket": "AI",
"episode_title": "Strategic Forecasts in Space, Satellites, and Propulsion: 2023-2026 Retrospective and Future Outlook",
"fault_line_id": "F006",
"flag_repeated": false,
"in_5yr_window": true,
"source_report": "Space Prediction Research Plan.md (2026-04-21)",
"appears_in_eps": "SPC-RPT",
"futurist_phase": "Phase 1 (2026)",
"is_macro_claim": false,
"total_mentions": 1,
"priority_weight": 5,
"report_evidence": "Anchor section: Singularity / AGI / Infrastructure Bottleneck.",
"active_end_month": "2026-12",
"recent_statement": "Aschenbrenner Situational Awareness 2024 / 2026 updates.",
"watch_events_raw": "AISI capacity; frontier-lab alignment-team sizing",
"months_from_today": 2,
"probability_layer": "Higher (in-flight)",
"active_start_month": "2024-01",
"december_dispersal": {
"reason": "december_dispersal: domain=AI → 09/2026",
"new_date": "2026-09-30",
"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": "A",
"track_record_notes": "Aschenbrenner quantitative framings reliable.",
"contradicting_notes": "Alignment-researcher hiring accelerated 2024-2026 (Anthropic alignment team, OpenAI Superalignment before dissolution); ratio may be narrowing.",
"flag_near_term_2027": false,
"flag_high_conviction": false,
"milestones_derived_at": "2026-05-02T03:08:51.329598+00:00",
"reference_class_match": {
"top_n": [
{
"id": "agi_breakthrough_5y",
"cosine": 0.6504
}
],