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    What’s your P(doom)? A call for broader views on AI existential risk

    A post argues that highly visible voices with higher-than-average risk estimates dominate an ill-defined debate.

    JC
    IR
    2 Sources, ,

    TLDR

    A post calls AI safety important but argues that debate over existential risk is ill-defined and dominated by highly visible voices whose risk estimates are significantly higher than average. It asks to hear from a broader cross-section of the AI community.

    Combined views

    1.6K

    2 Sources, first seen 1h ago

    Combined views

    1.6K

    2 Sources, first seen 1h ago

    7 likes
    1h ago
    first seen 1h ago
    7 likes
    3 comments
    2 saves
    1 reposts
    Featured Source
    3 comments
    2 saves
    1 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    Today's Rank

    #20

    Today's Rank

    #20

    2 Sources

    @julien_cWhat's your P(doom)? AI Safety is an important subject, but existential-risk debate is ill-defined, and dominated by highly-visible voices who have a significantly higher-than-average estimates of x-risk probabilities. So we would like to hear from a broader cross-section of the AI community ⤵️1h
    @irinarishP(doom) is a subjective, not a frequentist, probability (Bayesian prior), aka a belief. P(doom/evidence) = P(D) P(E/D) / P(E). Any way to compute P(E/D) and P(E)?1h

    2 Sources

    @julien_cWhat's your P(doom)? AI Safety is an important subject, but existential-risk debate is ill-defined, and dominated by highly-visible voices who have a significantly higher-than-average estimates of x-risk probabilities. So we would like to hear from a broader cross-section of the AI community ⤵️1h
    @irinarishP(doom) is a subjective, not a frequentist, probability (Bayesian prior), aka a belief. P(doom/evidence) = P(D) P(E/D) / P(E). Any way to compute P(E/D) and P(E)?1h