Is Interpretability Sufficient for Safety?

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  "title": "Is Interpretability Sufficient for Safety?",
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  "llmSummary": "Comprehensive survey of the interpretability sufficiency debate with 2024-2025 empirical progress: Anthropic extracted 34M features from Claude 3 Sonnet (70% interpretable), but scaling requires billions of features and faces fundamental challenges (10x performance loss, deception detection unsolved). Emerging consensus favors hybrid approaches combining interpretability verification with behavioral methods like RLHF rather than interpretability alone.",
  "description": "Debate over whether mechanistic interpretability can ensure AI safety. Anthropic's 2024 research extracted 34 million features from Claude 3 Sonnet with 70% human-interpretable, but scaling to frontier models (trillions of parameters) and detecting sophisticated deception remain unsolved challenges.",
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