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A Pragmatic Vision for Interpretability
Neel Nanda, Josh Engels, Arthur Conmy, Senthooran Rajamanoharan, Bilal Chughtai, Callum McDougall, Janos Kramar, Lewis Smith
Year: 2025Venue: AI Alignment ForumArea: Mechanistic Interp.Type: PositionEmbeddings: 0
Abstract
Google DeepMind's mech interp team pivots from ambitious reverse-engineering to pragmatic interpretability: solving problems on the critical path to AGI safety using proxy tasks and simple methods first.
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ai-safety (imported, 100%)interpretability (suggested, 80%)mechanistic-interp (suggested, 92%)position (suggested, 88%)
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