DanArmak comments on Open Thread June 2010, Part 3 - Less Wrong

6 Post author: Kevin 14 June 2010 06:14AM

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Comment author: Yoreth 14 June 2010 08:10:24AM 5 points [-]

A prima facie case against the likelihood of a major-impact intelligence-explosion singularity:

Firstly, the majoritarian argument. If the coming singularity is such a monumental, civilization-filtering event, why is there virtually no mention of it in the mainstream? If it is so imminent, so important, and furthermore so sensitive to initial conditions that a small group of computer programmers can bring it about, why are there not massive governmental efforts to create seed AI? If nothing else, you might think that someone could exaggerate the threat of the singularity and use it to scare people into giving them government funds. But we don’t even see that happening.

Second, a theoretical issue with self-improving AI: can a mind understand itself? If you watch a simple linear Rube Goldberg machine in action, then you can more or less understand the connection between the low- and the high-level behavior. You see all the components, and your mind contains a representation of those components and of how they interact. You see your hand, and understand how it is made of fingers. But anything more complex than an adder circuit quickly becomes impossible to understand in the same way. Sure, you might in principle be able to isolate a small component and figure out how it works, but your mind simply doesn’t have the capacity to understand the whole thing. Moreover, in order to improve the machine, you need to store a lot of information outside your own mind (in blueprints, simulations, etc.) and rely on others who understand how the other parts work.

You can probably see where this is going. The information content of a mind cannot exceed the amount of information necessary to specify a representation of that same mind. Therefore, while the AI can understand in principle that it is made up of transistors etc., its self-representation necessary has some blank areas. I posit that the AI cannot purposefully improve itself because this would require it to understand in a deep, level-spanning way how it itself works. Of course, it could just add complexity and hope that it works, but that’s just evolution, not intelligence explosion.

So: do you know any counterarguments or articles that address either of these points?

Comment author: DanArmak 14 June 2010 02:54:39PM 8 points [-]

The information content of a mind cannot exceed the amount of information necessary to specify a representation of that same mind. Therefore, while the AI can understand in principle that it is made up of transistors etc., its self-representation necessary has some blank areas.

This is strictly true if you're talking about the working memory that is part of a complete model of your "mind". But a mind can access an unbounded amount of externally stored data, where a complete self-representation can be stored.

A Turing Machine of size N can run on an unbounded-size tape. A von Neumann PC with limited main memory can access an unbounded-size disk.

Although we can only load a part of the data into working memory at a time, we can use virtual memory to run any algorithm written in terms of the data as a whole. If we had an AI program, we could run it on today's PCs and while we could run out of disk space, we couldn't run out of RAM.