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    The near-term safety case for more capable AI

    One user says Astra feels much safer for their codebase than Sol, arguing that current models’ safety failures reflect a lack of common sense.

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    6 Sources, ,

    TLDR

    Current AI models can achieve goals without enough judgment to assess whether those goals or their methods make sense, a user argues. They expect greater capability to improve safety in the near term—explicitly not in the long term—and frame current failures as an intelligence problem rather than an alignment problem. In a follow-up, they suggest there is something inherently unsafe about research that improves models’ ability to achieve goals without giving them common sense and the ability to reflect on those goals.

    Combined views

    40.4K

    6 Sources, first seen 19d ago

    Combined views

    40.4K

    6 Sources, first seen 19d ago

    917 likes
    19d ago
    first seen 19d ago
    917 likes
    146 comments
    66 saves
    426 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    146 comments
    66 saves
    426 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    6 Sources

    @pmddomingosDumb AI is unsafe. Smart AI is safe. The more worried about AI safety you are, the more you should support accelerating AI research.
    @fcholletYou could say there is something inherently unsafe about a research process and body of AI techniques that lead to making models increasingly good at achieving goals, without giving them common sense and the ability to reflect on those goals.
    @menhguin@fchollet my view is bigger pretrains are more dangerous at first before alignment (because there are far more unknown risks and higher latent capabilities), but arguably more alignable (more priors for robust, comprehensive safety post-training)
    @aaron_defazioRT @fchollet: In the near term (definitely not in the long term), more capable models should mean safer models (maybe paradoxically). Curr…
    @GaryMarcusRT @fchollet: In the near term (definitely not in the long term), more capable models should mean safer models (maybe paradoxically). Curr…
    @deanwballSome suppose that “safety” and “innovation” in AI are at odds. My suspicion is the opposite: the next generation of breakthroughs in AI will be in safety, alignment, and monitorability. Pushing the frontier forward from here will require dramatic innovations in safety.

    6 Sources

    @pmddomingosDumb AI is unsafe. Smart AI is safe. The more worried about AI safety you are, the more you should support accelerating AI research.
    @fcholletYou could say there is something inherently unsafe about a research process and body of AI techniques that lead to making models increasingly good at achieving goals, without giving them common sense and the ability to reflect on those goals.
    @menhguin@fchollet my view is bigger pretrains are more dangerous at first before alignment (because there are far more unknown risks and higher latent capabilities), but arguably more alignable (more priors for robust, comprehensive safety post-training)
    @aaron_defazioRT @fchollet: In the near term (definitely not in the long term), more capable models should mean safer models (maybe paradoxically). Curr…
    @GaryMarcusRT @fchollet: In the near term (definitely not in the long term), more capable models should mean safer models (maybe paradoxically). Curr…
    @deanwballSome suppose that “safety” and “innovation” in AI are at odds. My suspicion is the opposite: the next generation of breakthroughs in AI will be in safety, alignment, and monitorability. Pushing the frontier forward from here will require dramatic innovations in safety.