{"schema_version":"onlylabs.public_signal.v1","title":"Anthropic Writing: Constitutional Ai Harmlessness From Ai Feedback","description":"Anthropic writing signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/2e2d7093-165e-4f1c-9114-64a1f49628dc","json_url":"https://onlylabs.fyi/signals/2e2d7093-165e-4f1c-9114-64a1f49628dc/signal.json","generated_at":"2026-06-11T04:18:09.853122+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/2e2d7093-165e-4f1c-9114-64a1f49628dc","signal_json":"https://onlylabs.fyi/signals/2e2d7093-165e-4f1c-9114-64a1f49628dc/signal.json","source":"https://www.anthropic.com/research/constitutional-ai-harmlessness-from-ai-feedback","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":null},"answer_pack":{"answer":"Anthropic published Constitutional Ai Harmlessness From Ai Feedback. This talking signal gives public context for research themes, product direction, policy, or launch framing. High-signal details: Constitutional AI: Harmlessness from AI Feedback \\ Anthropic Alignment Research Constitutional AI: Harmlessness from AI Feedback Dec 15, 2022 Read Paper Abstract As AI.... onlylabs links this event to 1 captured evidence page and 6 related writing signals.","signal_desk":"talking","source_context":{"source_url":"https://www.anthropic.com/research/constitutional-ai-harmlessness-from-ai-feedback","source_host":"anthropic.com","occurred_at":"2022-12-15T00:00:00.000Z","first_seen_at":"2026-06-09T02:17:26.339488+00:00","date_source":"page.visible_date","context":null},"context_markers":[{"label":"Lab","value":"Anthropic","source":"signal"},{"label":"Signal desk","value":"talking","source":"signal"},{"label":"Source host","value":"anthropic.com","source":"source"},{"label":"Watch term","value":"RL environments","source":"evidence"},{"label":"Watch term","value":"Data pipeline","source":"evidence"},{"label":"Watch 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use."}]},"intelligence":{"signal_desk":"talking","answer":"Anthropic published Constitutional Ai Harmlessness From Ai Feedback. This talking signal gives public context for research themes, product direction, policy, or launch framing. 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We experiment with methods for training a harmless AI assistant through self-improvement, without any human labels identifying harmful outputs. The only human oversight is provided through a list of rules or principles, and so we refer to the method as 'Constitutional AI'. The process involves both a supervised learning and a reinforcement learning phase. In the supervised phase we sample from an initial model, then generate self-critiques and revisions, and then finetune the original model on revised responses. In the RL phase, we sample from the finetuned model, use a model to evaluate which of the two samples is better, and then train a preference model from this dataset of AI preferences. We then train with RL using the preference model as the reward signal, i.e. we use 'RL from AI Feedback' (RLAIF). As a result we are able to train a harmless but non-evasive AI assistant that engages with harmful queries..."},"evidence_pages":[{"url":"https://www.anthropic.com/research/constitutional-ai-harmlessness-from-ai-feedback","final_url":"https://www.anthropic.com/research/constitutional-ai-harmlessness-from-ai-feedback","title":"Constitutional Ai Harmlessness From Ai Feedback","http_status":200,"content_type":"text/html; charset=utf-8","capture_method":"plain","fetched_at":"2026-06-11T04:18:09.853122+00:00","bytes":108015,"raw_path":"e99a5c1697baa07d9618d671c4260311729ccdf24aa322c6fc9b75106c05ad0a.html","content_hash":"8af28e0706617c1e00882d9c4577d5ff60bb1b14d3065c09ed5249376af45ee1","excerpt_chars":1200,"truncated":true,"excerpt":"Constitutional AI: Harmlessness from AI Feedback \\ Anthropic Alignment Research Constitutional AI: Harmlessness from AI Feedback Dec 15, 2022 Read Paper Abstract As AI systems become more capable, we would like to enlist their help to supervise other AIs. We experiment with methods for training a harmless AI assistant through self-improvement, without any human labels identifying harmful outputs. The only human oversight is provided through a list of rules or principles, and so we refer to the method as 'Constitutional AI'. The process involves both a supervised learning and a reinforcement learning phase. In the supervised phase we sample from an initial model, then generate self-critiques and revisions, and then finetune the original model on revised responses. In the RL phase, we sample from the finetuned model, use a model to evaluate which of the two samples is better, and then train a preference model from this dataset of AI preferences. We then train with RL using the preference model as the reward signal, i.e. we use 'RL from AI Feedback' (RLAIF). As a result we are able to train a harmless but non-evasive AI assistant that engages with harmful queries..."}],"related_signals":[{"id":"6c78c028-3ab4-4b33-86f7-d86c8ba9e3ba","url":"https://onlylabs.fyi/signals/6c78c028-3ab4-4b33-86f7-d86c8ba9e3ba","source_url":"https://www.anthropic.com/research/agents-in-biology","title":"Agents In Biology","context":null,"kind":{"key":"post_published","label":"Writing"},"org":{"slug":"anthropic","name":"Anthropic","category":"frontier-lab"},"occurred_at":"2026-06-10T15:16:01+00:00","first_seen_at":"2026-06-09T02:17:26.339488+00:00","date_source":"sitemap.lastmod"},{"id":"2648db51-9d6a-42a9-aece-a0ca5f9ce64f","url":"https://onlylabs.fyi/signals/2648db51-9d6a-42a9-aece-a0ca5f9ce64f","source_url":"https://www.anthropic.com/news/claude-fable-5-mythos-5","title":"Claude Fable 5 Mythos 5","context":null,"kind":{"key":"post_published","label":"Writing"},"org":{"slug":"anthropic","name":"Anthropic","category":"frontier-lab"},"occurred_at":"2026-06-09T20:27:50+00:00","first_seen_at":"2026-06-10T07:01:05.666054+00:00","date_source":"sitemap.lastmod"},{"id":"8475487f-45b4-4689-9bc5-8e4c6ca0457d","url":"https://onlylabs.fyi/signals/8475487f-45b4-4689-9bc5-8e4c6ca0457d","source_url":"https://www.anthropic.com/engineering/how-we-contain-claude","title":"How We Contain Claude","context":null,"kind":{"key":"post_published","label":"Writing"},"org":{"slug":"anthropic","name":"Anthropic","category":"frontier-lab"},"occurred_at":"2026-06-06T00:28:16+00:00","first_seen_at":"2026-06-09T02:17:26.339488+00:00","date_source":"sitemap.lastmod"},{"id":"e4fbfcdd-15b4-41b9-b011-fd83e7068ae9","url":"https://onlylabs.fyi/signals/e4fbfcdd-15b4-41b9-b011-fd83e7068ae9","source_url":"https://www.anthropic.com/research/making-claude-a-chemist","title":"Making Claude A Chemist","context":null,"kind":{"key":"post_published","label":"Writing"},"org":{"slug":"anthropic","name":"Anthropic","category":"frontier-lab"},"occurred_at":"2026-06-05T20:13:40+00:00","first_seen_at":"2026-06-09T02:17:26.339488+00:00","date_source":"sitemap.lastmod"},{"id":"cc62deba-9682-4751-aa6b-81c3bd7122a0","url":"https://onlylabs.fyi/signals/cc62deba-9682-4751-aa6b-81c3bd7122a0","source_url":"https://www.anthropic.com/research/measuring-agent-autonomy","title":"Measuring Agent Autonomy","context":null,"kind":{"key":"post_published","label":"Writing"},"org":{"slug":"anthropic","name":"Anthropic","category":"frontier-lab"},"occurred_at":"2026-06-05T15:49:18+00:00","first_seen_at":"2026-06-09T02:17:26.339488+00:00","date_source":"sitemap.lastmod"},{"id":"93da14fd-7141-4e17-abd6-1c8d52435c70","url":"https://onlylabs.fyi/signals/93da14fd-7141-4e17-abd6-1c8d52435c70","source_url":"https://www.anthropic.com/research/values-wild","title":"Values Wild","context":null,"kind":{"key":"post_published","label":"Writing"},"org":{"slug":"anthropic","name":"Anthropic","category":"frontier-lab"},"occurred_at":"2026-06-05T15:38:54+00:00","first_seen_at":"2026-06-09T02:17:26.339488+00:00","date_source":"sitemap.lastmod"}]}