{"schema_version":"onlylabs.public_signal.v1","title":"Anthropic Writing: Evaluating Feature Steering","description":"Anthropic writing signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/adaf2ee1-0e0e-4c69-8b60-eed806f12068","json_url":"https://onlylabs.fyi/signals/adaf2ee1-0e0e-4c69-8b60-eed806f12068/signal.json","generated_at":"2026-06-11T04:18:06.938851+00:00","org":{"slug":"anthropic","name":"Anthropic","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/anthropic","dossier_json_url":"https://onlylabs.fyi/labs/anthropic/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/adaf2ee1-0e0e-4c69-8b60-eed806f12068","signal_json":"https://onlylabs.fyi/signals/adaf2ee1-0e0e-4c69-8b60-eed806f12068/signal.json","source":"https://www.anthropic.com/research/evaluating-feature-steering","lab_dossier":"https://onlylabs.fyi/labs/anthropic","lab_dossier_json":"https://onlylabs.fyi/labs/anthropic/dossier.json","analysis":"https://onlylabs.fyi/analysis/anthropic","analysis_json":"https://onlylabs.fyi/analysis/anthropic/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/anthropic/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":"https://onlylabs.fyi/topics/talking","topic_signals_json":"https://onlylabs.fyi/topics/talking/signals.json","topic_feed":"https://onlylabs.fyi/topics/talking/feed.xml","data_business":{"radar":"https://onlylabs.fyi/data-radar","radar_json":"https://onlylabs.fyi/data-radar.json","opportunities":"https://onlylabs.fyi/opportunities","opportunities_json":"https://onlylabs.fyi/opportunities.json","lanes":[{"key":"evals","label":"Evals and quality","url":"https://onlylabs.fyi/data-radar/evals","json_url":"https://onlylabs.fyi/data-radar/evals/signals.json"}]}},"answer_pack":{"answer":"Anthropic published Evaluating Feature Steering. This talking signal gives public context for research themes, product direction, policy, or launch framing. High-signal details: Evaluating feature steering: A case study in mitigating social biases \\ Anthropic Societal Impacts Interpretability Evaluating feature steering: A case study in.... onlylabs links this event to 1 captured evidence page and 6 related writing signals. 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This talking signal gives public context for research themes, product direction, policy, or launch framing. High-signal details: Evaluating feature steering: A case study in mitigating social biases \\ Anthropic Societal Impacts Interpretability Evaluating feature steering: A case study in.... onlylabs links this event to 1 captured evidence page and 6 related writing signals. 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To verify our feature interpretations, we ran qualitative feature steering experiments, where we artificially dialed up and down various features to see if they changed model outputs in intuitive ways. The results were promising – for example, turning up a feature that responded to mentions of the Golden Gate Bridge made the model talk about the Golden Gate Bridge. Such examples led us to hypothesize that feature steering might be a promising way to modify model outputs in specific interpretable ways. Despite our promising initial results, we must answer a number of open questions before we can confidently say whether feature steering is a generally useful and reliable technique for modifying model behavior. For example, does feature steering..."},"evidence_pages":[{"url":"https://www.anthropic.com/research/evaluating-feature-steering","final_url":"https://www.anthropic.com/research/evaluating-feature-steering","title":"Evaluating Feature Steering","http_status":200,"content_type":"text/html; charset=utf-8","capture_method":"plain","fetched_at":"2026-06-11T04:18:06.938851+00:00","bytes":191056,"raw_path":"a0db77b024e6281c55a17c93c7c30b3d4cc36e85aae09eba1695d2a490f832f9.html","content_hash":"cb72e296ce604b927a396fd393dcbb5542ed6e37c6af28a16f008b54388d8e88","excerpt_chars":1200,"truncated":true,"excerpt":"Evaluating feature steering: A case study in mitigating social biases \\ Anthropic Societal Impacts Interpretability Evaluating feature steering: A case study in mitigating social biases Oct 25, 2024 A few months ago, we published an interpretability paper demonstrating our ability to learn interpretable features that correspond to various concepts (e.g., famous individuals , types of computer code , etc.) represented in Claude 3 Sonnet . To verify our feature interpretations, we ran qualitative feature steering experiments, where we artificially dialed up and down various features to see if they changed model outputs in intuitive ways. The results were promising – for example, turning up a feature that responded to mentions of the Golden Gate Bridge made the model talk about the Golden Gate Bridge. Such examples led us to hypothesize that feature steering might be a promising way to modify model outputs in specific interpretable ways. Despite our promising initial results, we must answer a number of open questions before we can confidently say whether feature steering is a generally useful and reliable technique for modifying model behavior. 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