Intro

This article seeks to explore possible futures in a world where artificial intelligence turns out NOT to be able to quickly, recursively self-improve so as to influence our world with arbitrarily large strength and subtlety, i.e, "go FOOM." Note that I am not arguing that AI won't FOOM. Eliezer has made several good arguments for why AI probably will FOOM, and I don't necessarily disagree. I am simply calling attention to the non-zero probability that it won't FOOM, and then asking what we might do to prepare for a world in which it doesn't.

Failure Modes

I can imagine three different ways in which AI could fail to FOOM in the next 100 years or so. Option 1 is a "human fail." Option 1 means we destroy ourselves or succumb to some other existential risk before the first FOOM-capable AI boots up. I would love to hear in the comments section about (a) which existential risks people think are most likely to seriously threaten us before the advent of AI, and (b) what, if anything, a handful of people with moderate resources (i.e., people who hang around on Less Wrong) might do to effectively combat some of those risks.

Option 2 is a "hardware fail." Option 2 means that Moore's Law turns out to have an upper bound; if physics doesn't show enough complexity beneath the level of quarks, or if quantum-sized particles are so irredeemably random as to be intractable for computational purposes, then it might not be possible for even the most advanced intelligence to significantly improve on the basic hardware design of the supercomputers of, say, the year 2020. This would limit the computing power available per dollar, and so the level of computing power required for a self-improving AI might not be affordable for generations, if ever. Nick Bostrom has some interesting thoughts along these lines, ultimately guessing (as of 2008) that the odds of a super-intelligence forming by 2033 was less than 50%.

Option 3 is a "software fail." Option 3 means that *programming* efficiency turns out to have an upper bound; if there are natural information-theoretical limits on how efficiently a set number of operations can be used to perform an arbitrary task, then it might not be possible for even the most advanced intelligence to significantly improve on its basic software design; the supercomputer would be more than 'smart' enough to under...

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