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As noted above, we have deployed the classifier as an experimental addition to our Safeguards framework, monitoring a percentage of Claude traffic. Its real-world performance has confirmed that the classifier works effectively beyond our testing environment. Whereas our synthetic test data provided clear examples of harmful and benign exchanges, the distribution of actual user traffic proved more complex and surprising, yet the classifier still performed well. One example of how real-world deployment differs from testing is that the classifier flagged certain conversations about nuclear weapon

Developing Nuclear Safeguards for AI
techcrunch.com › 2026 › 06 › …

Anthropic's safety warnings may have just backfired — the government has pulled the plug on its most powerful AI | TechCrunch

… Anthropic’s broader argument is that its strongest safeguards operate through independent classifier systems that function separately from the model itself, meaning that even if someone convinces Fable to keep talking past a refusal, the underlying protections against the most dangerous outputs rem… …

Jun 13, 2026 · Connie Loizos