AI Risk Critical Uncertainties Model

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  "title": "AI Risk Critical Uncertainties Model",
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  "lastUpdated": "2026-03-13",
  "dateCreated": "2026-02-15",
  "llmSummary": "Identifies 35 high-leverage uncertainties in AI risk across compute (scaling breakdown at 10^26-10^30 FLOP), governance (10% P(US-China treaty by 2030)), and capabilities (autonomous R&D 3 years away, 41-51% of experts assign >10% extinction probability). Recommends \\$100-200M/year research budget focused on resolving key cruxes: scaling law empirics (\\$50-100M), deception detection (\\$30-50M), and governance feasibility studies (\\$20-30M).",
  "description": "This model identifies 35 high-leverage uncertainties in AI risk across compute, governance, and capabilities domains. Based on expert surveys, forecasting platforms, and empirical research, it finds key cruxes include scaling law breakdown point (10^26-10^30 FLOP), alignment difficulty (41-51% of experts assign >10% extinction probability), and AGI timeline (Metaculus median: 2027-2031).",
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