comment by Grue_Slinky ·
2019-11-11T17:29:58.328Z · LW(p) · GW(p)
In reasoning about AGI, we're all aware of the problems with anthropomorphizing, but it occurs to me that there's also a cluster of bad reasoning that comes from an (almost?) opposite direction, where you visualize an AGI to be a mechanical automaton and draw naive conclusions based on that.
For instance, every now and then I've heard someone from this community say something like:
What if the AGI runs on the ZFC axioms (among other things), and finds a contradiction, and by the principle of explosion it goes completely haywire?
Even if ZFC is inconsistent, this hardly seems like a legitimate concern. There's no reason to hard-code ZFC into an AI unless we want a narrow AI that's just a theorem prover (e.g. Logic Theorist). Anything close to AGI will necessarily build rich world models, and from the standpoint of these, ZFC wouldn't literally be everything. ZFC would just be a sometimes-useful tool it discovers for organizing its mathematical thinking, which in turn is just a means toward understanding physics etc. better, much as humans wouldn't go crazy if ZFC yields a contradiction.
The general fallacy I'm pointing to isn't just "AGI will be logic-based" but something more like "AGI will act like a machine, an automaton, or a giant look-up table". This is technically true, in the same way humans can be perfectly described as a giant look-up table, but it's just the wrong level of abstraction for thinking about agents (most of the time) and can lead one to silly conclusions if one isn't really careful.
For instance my (2nd hand, half-baked, and lazy) understanding of Penrose's arguments are as follows: Godel's theorems say formal systems can't do X, humans can do X, therefore human brains can't be fully described as formal systems (or maybe he references Turing machines and the halting problem, but the point is still similar). Note that this makes sense as stated, the catch is that
"the human brain when broken down all the way to a Turing machine" is what the Godel/Turing stuff applies to, not "the human brain at the level of abstraction we use to think about it (in terms of 'thoughts', 'concepts', etc.)". It's not at all clear that the latter even resembles a formal system, at least not one rich enough that the Godel/Turing results apply. The fact that it's "built out of" the former means nothing on this point: the proofs of PA > 10 characters do not constitute a formal system, and fleshing out the "built out of" probably requires solving a large chunk of neuroscience.
Again, I'm just using straw-Penrose here as an example because, while we all agree it's an invalid argument, this is mostly because it concludes something LW overwhelmingly agrees is false. When taken at face value, it "looks right" and the actual error isn't completely obvious to find and spell out (hence I've left it in a black spoiler box). I claim that if the argument draws a conclusion that isn't obviously wrong or even reinforces your existing viewpoint, then it's relatively easy to think it makes sense. I think this is what's going on when people here make arguments for AGI dangers that appeal to its potential brittleness or automata-like nature (I'm not saying this is common, but I do see it occasionally).
But there's a subtlety here, because there are some ways in which AGI potentially will be more brittle due to its mathematical formulation. For instance, adversarial examples are a real concern, and those are pretty much only possible because of the way ML systems output numerical probabilities (from these the adversary can infer the gradient of the model's beliefs, and run along it).
And of course, as I said at the start, an opposing fallacy is thinking AGI will be more human-like by default. To be clear I think the fallacy I'm gesturing at here is the less dangerous one in the worst case, but more common on LW (i.e. > 0).