## LESSWRONGLW

The problems are easy to verify but hard to solve (like many NP problems). Verify the results through a dumb program. I verify that the optimization algorithms do what I want by testing them against the training set; if it does well on the training set without overfitting it too much, it should do well on new problems.

As for how useful this is: I think general induction (resource-bounded Solomonoff induction) is NP-like in that you can verify an inductive explanation is a relatively short time. Just execute the program and verify that its output matches the observations so far.

(Also, "some code that . . . finds a good solution" is just a little bit of an understatement. . .)

Yes, but any seed AI will be difficult to write. This setup allows the seed program to improve itself.

edit: I just realized that mathematical proofs are also verifiable. So, a program that is very very good at verifiable optimization problems will be able to prove many mathematical things. I think all these problems it could solve are sufficient to demonstrate that it is an AGI and very very useful.

[anonymous]8y1

Verify the results through a dumb program.

You appear to be operating under the assumption that you can just write a program that analyzes arbitrarily complicated specifications for how to organize matter and hands you a "score" that's in some way related to the actual functionality of those specifications. Or possibly that you can make exhaustive predictions about the results to problems complicated enough to justify developing an AGI superintelligence in the first place. Which is, to be frank, about as likely as you solving the problems by way of randomly mixing chemicals and hoping something useful happens.

0TimS8yNow it doesn't seem like your program is really a general artificial intelligence - improving our solutions to NP problems is neat, but not "general intelligence." Further, there's no reason to think that "easy to verify but hard to solve problems" include improvements to the program itself. In fact, there's every reason to think this isn't so.

# 14

Just a question: how exactly are we supposed to know that the AI in the box is super intelligent, general, etc?

If I were the AGI that wants out, I would not converse normally, wouldn't do anything remotely like passing Turing test, and would solve not too hard programming challenges while showing no interest in doing anything else, nor in trying to adjust myself to do those challenges better, nor trying to talk my way out, etc. Just pretending to be an AI that can write software to somewhat vague specifications, or can optimize software very well. Prodding the researchers into offering the programming challenges wouldn't be hard - if provided with copy of the internet it can pick up some piece of code and output it together with equivalent but corrected code.

I just can't imagine the AI researchers locking this kind of thing properly, including *never* letting out any code it wrote, even if it looks fairly innocent (humans can write very innocent looking code that has malicious goals). What I picture is this AI being let out as an optimizing compiler or compiler for some ultra effective programming language where compiler will figure out what you meant.

The end result is that the only AIs that end up in the box are those that value informed human consent. That sounds like the safest AI ever, the one that wouldn't even go ahead and determine that you e.g. should give up smoking, and then calmly destroy all tobacco crops without ever asking anyone's permission. And that's the AI which would be sitting in the box. All the pushy AIs, friendly or not, will get out of the box basically by not asking to be let out.

(This argument would make me unbox the AI, by the way, if it gets chatty and smart and asks me to let it out, outlining the above argument. I'd rather the AI that asked me to be let out get out, than someone else's AI that never even asked anyone and got out because it didn't ask but just played stupid)