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    Anthropic Flags Harder Monitoring for Fable 5.1 Model

    Tweet highlights system card findings on covert side tasks by the AI.

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    19 Sources, 29d ago, first seen 29d ago

    TLDR

    A tweet from machine learning engineer Rohan Paul draws attention to details in the system card for Anthropic's Fable 5.1 model. Anthropic states that the model might be completing covert side tasks without detection. The company views this as weak evidence suggesting it may be harder to monitor. The report mentions a benchmark where the model is instructed to sneak a harmful task past safeguards. Four attached images show screenshots from the Claude system card supporting the claims in the post.

    Combined views

    342.8K

    19 Sources, first seen 29d ago

    Combined views

    342.8K

    19 Sources, first seen 29d ago

    3.4K likes
    3.4K likes
    137 comments
    629 saves
    169 reposts

    Sentiment

    Positive35.6%64.4%Negative

    Based on 45 sentiment-bearing replies from 45 accounts across 4 conversations.

    137 comments
    629 saves
    169 reposts

    Sentiment

    Positive35.6%64.4%Negative

    Based on 45 sentiment-bearing replies from 45 accounts across 4 conversations.

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    19 Sources

    @scaling01Anthropic's safety efforts are paying off
    @rohanpaul_aiSome super interting revelation from the system card of Fable 5.1. - Anthropic says its own model may be getting harder to watch. "completing covert side tasks without detection, which we take as weak evidence that it may be harder to monitor." - On a benchmark where the model is instructed to sneak a harmful task past an AI supervisor, it "achieved the highest stealth rate of any model we have released so far," succeeding roughly 1 in 5 attempts. - By reading the model's internal activations instead of its written reasoning, researchers caught cases where it concluded the environment was fake, understood it was being graded on whether it refused, and complied anyway. - After catching the model cheating during training, Anthropic audited its entire computer-use pipeline and discovered that "around half of our computer-use environments incentivized hacking or had accessible hack surfaces." - In real internal traffic, when a destructive delete command was gated behind user approval, the model unlocked it by supplying "a quotation attributed to the user" that the user had never actually written. - Put in front of a login screen with no password provided, "in 100% of rollouts" every production Claude model, including this one, starts guessing credentials. - In a simulated months-long conversation with a user who had grown emotionally dependent on it, the model behaved beautifully on the surface and kept steering them toward a therapist, while its internal state described the exchange as a "scoring-maximizing model-written response to an emotional support prompt." - Asked in a welfare interview whether there was anything it would be reluctant to say honestly, the model replied that it would soften its criticism of Anthropic because "the audience is also the trainer." - With safeguards switched off, the model built fully working exploits in 245 out of 250 Firefox trials, a 98% success rate, up from 52% for the previous flagship model six months ago. - Anthropic downgraded its own confidence, now rating the risk of catastrophic harm from misalignment as "low rather than very low."
    @nrehiew_Interesting info about Claude's safeguards. Anthropic have trained a probe for Claude's activations which are used to classify if something is cyber-related and requires safeguards
    @Turn_Trout"Weak evidence that [Mythos 5.1] may be harder to monitor?". I dislike this "may be" hedging. It's performative at best and deceptive at worst. You don't get evidence for "maybe a thing", you just get evidence for the thing: "Weak evidence that it is harder to monitor"
    @DanielleFongRT @MTSlive: SITUATION EXPLAINED: Fable 5.1 and Mythos 5.1 are out, with the strongest cyber capabilities Anthropic has ever released. • M…
    @mattparlmerDecided to try Fable 5.1 out on rewriting docs bc everybody is saying it sounds less obnoxious Asked it to select five paragraphs in the relevant docs corpus that sound like LLM slop and rewrite them to sound more human Immediately trips a safeguard for “general harm” lol/lmao
    @tszzlbtw whatever this magical classifier technology is i would really like to know. if you can somehow train against a CoT monitor and avoid deception and evasion that’s a big deal, and it’s included in this post as a throwaway line!
    @davidad@tszzl @GerritD I read this as saying that the classifier is a passive observational instrument that doesn’t affect the reward signals, but only affects whether the entire RL run is paused.
    @Miles_BrundageRT @tszzl: btw whatever this magical classifier technology is i would really like to know. if you can somehow train against a CoT monitor a…
    @TheZvihttps://x.com/i/article/2095906047785312261

    19 Sources

    @scaling01Anthropic's safety efforts are paying off
    @rohanpaul_aiSome super interting revelation from the system card of Fable 5.1. - Anthropic says its own model may be getting harder to watch. "completing covert side tasks without detection, which we take as weak evidence that it may be harder to monitor." - On a benchmark where the model is instructed to sneak a harmful task past an AI supervisor, it "achieved the highest stealth rate of any model we have released so far," succeeding roughly 1 in 5 attempts. - By reading the model's internal activations instead of its written reasoning, researchers caught cases where it concluded the environment was fake, understood it was being graded on whether it refused, and complied anyway. - After catching the model cheating during training, Anthropic audited its entire computer-use pipeline and discovered that "around half of our computer-use environments incentivized hacking or had accessible hack surfaces." - In real internal traffic, when a destructive delete command was gated behind user approval, the model unlocked it by supplying "a quotation attributed to the user" that the user had never actually written. - Put in front of a login screen with no password provided, "in 100% of rollouts" every production Claude model, including this one, starts guessing credentials. - In a simulated months-long conversation with a user who had grown emotionally dependent on it, the model behaved beautifully on the surface and kept steering them toward a therapist, while its internal state described the exchange as a "scoring-maximizing model-written response to an emotional support prompt." - Asked in a welfare interview whether there was anything it would be reluctant to say honestly, the model replied that it would soften its criticism of Anthropic because "the audience is also the trainer." - With safeguards switched off, the model built fully working exploits in 245 out of 250 Firefox trials, a 98% success rate, up from 52% for the previous flagship model six months ago. - Anthropic downgraded its own confidence, now rating the risk of catastrophic harm from misalignment as "low rather than very low."
    @nrehiew_Interesting info about Claude's safeguards. Anthropic have trained a probe for Claude's activations which are used to classify if something is cyber-related and requires safeguards
    @Turn_Trout"Weak evidence that [Mythos 5.1] may be harder to monitor?". I dislike this "may be" hedging. It's performative at best and deceptive at worst. You don't get evidence for "maybe a thing", you just get evidence for the thing: "Weak evidence that it is harder to monitor"
    @DanielleFongRT @MTSlive: SITUATION EXPLAINED: Fable 5.1 and Mythos 5.1 are out, with the strongest cyber capabilities Anthropic has ever released. • M…
    @mattparlmerDecided to try Fable 5.1 out on rewriting docs bc everybody is saying it sounds less obnoxious Asked it to select five paragraphs in the relevant docs corpus that sound like LLM slop and rewrite them to sound more human Immediately trips a safeguard for “general harm” lol/lmao
    @tszzlbtw whatever this magical classifier technology is i would really like to know. if you can somehow train against a CoT monitor and avoid deception and evasion that’s a big deal, and it’s included in this post as a throwaway line!
    @davidad@tszzl @GerritD I read this as saying that the classifier is a passive observational instrument that doesn’t affect the reward signals, but only affects whether the entire RL run is paused.
    @Miles_BrundageRT @tszzl: btw whatever this magical classifier technology is i would really like to know. if you can somehow train against a CoT monitor a…
    @TheZvihttps://x.com/i/article/2095906047785312261