The paper's goal is not to discuss "basic UFAI doomsday scenarios" in the general sense, but to discuss the particular case where the AI goes all pear-shaped EVEN IF it is programmed to be friendly to humans.
That last part (even if it is programmed to be friendly to humans) is the critical qualifier that narrows down the discussion to those particular doomsday scenarios in which the AI does claim to be trying to be friendly to humans - it claims to be maximizing human happiness - but in spite of that it does something insanely wicked.
So, Eli says:
The basic UFAI doomsday scenario is: the AI has vast powers of learning and inference with respect to its world-model, but has its utility function (value system) hardcoded. Since the hardcoded utility function does not specify a naturalization of morality, or CEV, or whatever, the UFAI proceeds to tile the universe in whatever it happens to like (which are things we people don't like), precisely because it has no motivation to "fix" its hardcoded utility function
... and this clearly says that the type of AI he has in mind is one that is not even trying to be friendly. Rather, he talks about how its
hardcoded utility function does not specify a naturalization of morality, or CEV, or whatever
And then he adds that
the UFAI proceeds to tile the universe in whatever it happens to like
... which has nothing to do with the cases that the entire paper is about, namely the cases where the AI is trying really hard to be friendly, but doing it in a way that we did not intend.
If you read the paper all of this is obvious pretty quickly, but perhaps if you only skim-read a few paragraphs you might get the wrong impression. I suspect that is what happened.
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Excuse me, but you are really failing to clarify the issue. The basic UFAI doomsday scenario is: the AI has vast powers of learning and inference with respect to its world-model, but has its utility function (value system) hardcoded. Since the hardcoded utility function does not specify a naturalization of morality, or CEV, or whatever, the UFAI proceeds to tile the universe in whatever it happens to like (which are things we people don't like), precisely because it has no motivation to "fix" its hardcoded utility function.
A similar problem would occur if, for some bizarre-ass reason, you monkey-patched your AI to use hardcoded machine arithmetic on its integers instead of learning the concept of integers from data via its, you know, intelligence, and the hardcoded machine math had a bug. It would get arithmetic problems wrong! And it would never realize it was getting them wrong, because every time it tried to check its own calculations, your monkey-patch would cut in and use the buggy machine arithmetic again.
The lesson is: do not hard-code important functionality into your AGI without proving it correct. In the case of a utility/value function, the obvious research path is to find a way to characterize finding out the human operators' desires as an inference problem, thus ensuring that the AI cares about learning correctly from the humans and then implementing what it learned rather than anything hard-coded. Moving moral learning into inference also helps minimize the amount of code we have to prove correct, since it simply isn't AI without correct, functioning learning and inference abilities.
Also, little you've written about CLAI or Swarm Connectionist AI corresponds well to what I've seen of real-world cognitive science, theoretical neuroscience, or machine learning research, so I can't see how either of those blatantly straw-man designs are going to turn into AGI. Please go read some actual scientific material rather than assuming that The Metamorphosis of Prime Intellect is up-to-date with the current literature ;-).
The content of your post was pretty good from my limited perspective, but this tone is not warranted.