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Part of our general inability to reason about exponential growth is the inability to recognize that a supposedly exponential growth is actually sigmoid. The hor

Part of our general inability to reason about exponential growth is the inability to recognize that a supposedly exponential growth is actually sigmoid. The horizontal asymptote could just as well be 8b, so it is not a case against doomerism in itself, but as is the case with COVID, to say nothing discounting its horror, that number is far less. There is no need to count exponentials—it would only be a matter of time. The need to sum multiple factors betrays the finite limits of what is actually sigmoid growth. Reasoning about specific effects is unfortunately subject to counter-evidence and so struggles for traction against abstract handwaving about exponential growth. There is much uncertainty, certainly not exclusive to AI. The benefit of hyper-vigilance in each case must be weighed against the cost of indulging every similar panic.

Mentlo 17d ago
I think your last sentence is a reasonable stance - but I'd disagree the fact that they are actually sigmoids rather than exponentials matters - it only matters if the limit is within the debated area - i.e. if exponentials in AI approach the limit far after they acquire ability to extinct humanity - then the debate on sigmoids or exponentials is academic. I make no claims here as to which it is - just that the difference itself matters less than where the limit is. As to the uncertainty - I think uncertainty calibration around AI is different depending on which domains you draw your instincts from. A lot of this will be gut driven rather than hard data driven, because we've only scratched the surface on hard data; and because it's gut driven, it will be emotions mediated (and therefore you could say doomerism or acceleratism boils down to the main emotional disposition about the world and hope vs cynicism). I do find it informative though that doomerism is saturated with people with 30+ years experience in building AI systems and ML systems OR deep cross-disciplinary understanding of dynamic systems (biology, sociology, philosophy), whereas acceleratism is saturated by traditional software engineering. That doesn't collapse the debate into a resolved binary, but for me it's informative. I think the main here is that there's so many vectors to talk past each other. At the very least, everyone should disclose where they're communicating a certain assertion from - present vs future + which axioms they subscribe to or not - because that's where it collapses typically. LeCun vs. the rest of the AI field is an example of where this collapses - because LeCun is so hyperfixated on human-like intelligence, whereas the rest of the field is concerned about an alien intelligence with sufficient actuators to affect the world. Clashing axiomatics.

Mentlo 17d ago

I think your last sentence is a reasonable stance - but I'd disagree the fact that they are actually sigmoids rather than exponentials matters - it only matters if the limit is within the debated area - i.e. if exponentials in AI approach the limit far after they acquire ability to extinct humanity - then the debate on sigmoids or exponentials is academic. I make no claims here as to which it is - just that the difference itself matters less than where the limit is. As to the uncertainty - I think uncertainty calibration around AI is different depending on which domains you draw your instincts from. A lot of this will be gut driven rather than hard data driven, because we've only scratched the surface on hard data; and because it's gut driven, it will be emotions mediated (and therefore you could say doomerism or acceleratism boils down to the main emotional disposition about the world and hope vs cynicism). I do find it informative though that doomerism is saturated with people with 30+ years experience in building AI systems and ML systems OR deep cross-disciplinary understanding of dynamic systems (biology, sociology, philosophy), whereas acceleratism is saturated by traditional software engineering. That doesn't collapse the debate into a resolved binary, but for me it's informative. I think the main here is that there's so many vectors to talk past each other. At the very least, everyone should disclose where they're communicating a certain assertion from - present vs future + which axioms they subscribe to or not - because that's where it collapses typically. LeCun vs. the rest of the AI field is an example of where this collapses - because LeCun is so hyperfixated on human-like intelligence, whereas the rest of the field is concerned about an alien intelligence with sufficient actuators to affect the world. Clashing axiomatics.