Intervention Effectiveness Matrix

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  "title": "Intervention Effectiveness Matrix",
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  "lastUpdated": "2026-03-13",
  "dateCreated": "2026-02-15",
  "llmSummary": "Quantitative analysis mapping 15+ AI safety interventions to specific risks reveals critical misallocation: 40% of 2024 funding (\\$400M+) flows to RLHF methods showing only 10-20% effectiveness against deceptive alignment, while interpretability research (\\$52M total, 40-50% effectiveness) and AI Control (70-80% theoretical effectiveness, \\$10M funding) remain severely underfunded. Provides explicit reallocation recommendations: reduce RLHF from 40% to 25%, increase interpretability from 15% to 30%, and establish AI Control at 20% of technical safety budgets.",
  "description": "This model maps 15+ AI safety interventions to specific risk categories with quantitative effectiveness estimates derived from empirical research and expert elicitation. Analysis reveals critical resource misallocation: 40% of 2024 funding (\\$400M+) went to RLHF-based methods showing only 10-20% effectiveness against deceptive alignment, while interpretability research (\\$52M, demonstrating 40-50% effectiveness) remains severely underfunded relative to gap severity.",
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      "text": "Coefficient Giving 2024 Report",
      "url": "https://www.openphilanthropy.org/research/our-progress-in-2024-and-plans-for-2025/",
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No external links