But it would have a very hard time strengthening its core logic, as Rice's Theorem would interfere: proving that certain improvements are improvements (or, even, that the optimized program performs the same task as the original source code) would be impossible.
This seems like the wrong conclusion to draw. Rice's theorem (and other undecidability results) imply that there exist optimizations that are safe but cannot be proven to be safe. It doesn't follow that most optimizations are hard to prove. One imagines that software could do what humans do -- hunt around in the space of optimizations until one looks plausible, try to find a proof, and then if it takes too long, try another. This won't necessarily enumerate the set of provable optimizations (much less the set of all enumerations), but it will produce some.
One imagines that software could do what humans do -- hunt around in the space of optimizations until one looks plausible, try to find a proof, and then if it takes too long, try another. This won't necessarily enumerate the set of provable optimizations (much less the set of all enumerations), but it will produce some.
To do that it's going to need a decent sense of probability and expected utility. Problem is, OpenCog (and SOAR, too, when I saw it) is still based in a fundamentally certainty-based way of looking at AI tasks, rather than one focused on probability and optimization.
Cross-posted from my blog.
Yudkowsky writes:
My own projection goes more like this:
At least one clear difference between my projection and Yudkowsky's is that I expect AI-expert performance on the problem to improve substantially as a greater fraction of elite AI scientists begin to think about the issue in Near mode rather than Far mode.
As a friend of mine suggested recently, current elite awareness of the AGI safety challenge is roughly where elite awareness of the global warming challenge was in the early 80s. Except, I expect elite acknowledgement of the AGI safety challenge to spread more slowly than it did for global warming or nuclear security, because AGI is tougher to forecast in general, and involves trickier philosophical nuances. (Nobody was ever tempted to say, "But as the nuclear chain reaction grows in power, it will necessarily become more moral!")
Still, there is a worryingly non-negligible chance that AGI explodes "out of nowhere." Sometimes important theorems are proved suddenly after decades of failed attempts by other mathematicians, and sometimes a computational procedure is sped up by 20 orders of magnitude with a single breakthrough.