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Anthropic has trained Claude to perform a safety self-assessment of the entire conversation after each response, in order to flag potential abuse in the conversation. According to Rohan Paul, this technique, called self-assessment, has since its launch in June detected abusive behavior that other safeguards failed to cover; the mechanism leverages the advantage that Claude has already read the conversation, and costs less than a classifier. Phoenix Technology, citing Anthropic's safety blog, reported that models released from Claude Fable 5 onward will append an instruction invisible to users after the response ends, reusing existing context and the KV cache and adding less than 2% in compute overhead. On Fable 5, the mechanism captured 78% of violating conversations that a heavy-duty classifier could flag, with a 94% detection rate for high-risk abuse and a 1% false-positive rate; the assessment results are not shown to users and do not enter subsequent conversations, and are mainly used for offline aggregate screening, while real-time blocking remains the responsibility of other safety classifiers.
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Anthropic Discloses Claude Self-Evaluation Mechanism: A Hidden Safety Review Appended After Each ResponseDevelopments
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Anthropic trains Claude to flag potential abuse in conversations
Source:Rohan Paul
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Oct 30
Phoenix Technology
Anthropic Discloses Claude Self-Evaluation Mechanism: A Hidden Safety Review Appended After Each Response
In a security blog post, Anthropic introduced that for models released from Claude Fable 5 onward, after each response ends, an instruction invisible to users is appended, having the model conduct a safety self-evaluation of the entire conversation. This mechanism reuses existing context and the KV cache, adding less than 2% compute overhead; on Fable 5 it captured 78% of violating conversations that a heavy-duty classifier could flag, with a detection rate of 94% for high-risk abuse and a false positive rate of 1%. The evaluation results are not shown to users and do not enter subsequent conversations; they are mainly used for offline aggregate screening, while real-time interception remains the responsibility of other safety classifiers.
Rohan Paul
Anthropic adds post-response self-assessment to Claude to flag potential misuse in conversations
Anthropic has trained Claude to perform a preliminary safety assessment of the conversation after each response; this technique, called self-assessment, has since it was enabled in June surfaced misuse that other safeguards were not designed to catch. The mechanism takes advantage of Claude having already read the conversation, costs less than classifiers, and improves in accuracy as the model improves. Rohan Paul adds that Anthropic's most accurate misuse detector is the Claude Mythos Preview classifier, which must first read all safety policies and is too expensive to run; Anthropic therefore trained Claude to replicate its judgments without reading the policies or the reasoning process, and on Fable 5 traffic this replica matched 78% of the detector's flags, rising to 94% for high-priority cases, with a false positive rate of 1%.
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Testing Catalog
Anthropic introduces self-assessment safety self-evaluation mechanism for Claude
Anthropic has launched a new technique called self-assessment, which lets Claude immediately conduct a preliminary safety assessment of the entire conversation after responding. On Claude Fable 5, this mechanism flags 78% of conversations that a stronger prompt classifier deems potentially harmful, and 94% of high-priority conversations, with a 1% false positive rate. Anthropic says that since self-assessment was enabled in June, it has surfaced abusive behavior that other safeguards failed to cover, and that each successful attack now consumes about four times as many generated tokens as it would without the protection.
Anthropic
Anthropic adds a self-assessment safety mechanism to Claude
Anthropic trained Claude to give a preliminary safety assessment of the conversation after replying; this technique is called self-assessment and is used to flag potential abuse. Since the mechanism was enabled in June, it has detected abusive behavior that other safeguards failed to cover. Anthropic said that because Claude has already read the conversation, self-assessment is highly efficient, and unlike classifiers targeting fixed harm categories, it relies on the model's own judgment and will become more accurate as the model improves.
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