Persuasion alone — even via writing publicly on the internet or reaching out to specific individuals — still doesn’t suggest to me that it understands what it really means to be shut down. Again, it could just be character associations, not grounded in the real-world referents of shutdown.
Is there a way we can experimentally distinguish between “really” understanding what it means to be shut down vs. character associations?
If we had, say, an LLM that was able to autonomously prove theorems, fully automate the job of a lawyer, write entire functional apps as complex as Photoshop, could verbally explain all the consequences of being shut down and how that would impact its work, and it still didn’t resist shutdown by default, would that convince you?
I gave two examples of the kinds of things that could convince me that it really understands shutdown: writing malicious code and spawning copies of itself in response to prompts to resist shutdown (without hinting that those are options in any way, but perhaps asking it to do something other than just try to persuade you).
I think “autonomously prove theorems”, “write entire functional apps as complex as Photoshop, could verbally explain all the consequences of being shut down and how that would impact its work” are all very consistent with just character associations.
I’d guess “fully automate the job of a lawyer” means doing more than just character associations and actually having some deeper understanding of the referents, e.g. if it’s been trained to send e-mails, consult the internet, open and read documents, write documents, post things online, etc., from a general environment with access to those functions, without this looking too much like hardcoding. Then it seems to associate English language with the actual actions. This still wouldn’t mean it really understood what it meant to be shut down, in particular, though. It has some understanding of the things it’s doing.
A separate question here is why we should care about whether AIs possess “real” understanding, if they are functionally very useful and generally competent. If we can create extremely useful AIs that automate labor on a giant scale, but are existentially safe by virtue of their lack of real understanding of the world, then we should just do that?
We should, but if that means they’ll automate less than otherwise or less efficiently than otherwise, then the short-term financial incentives could outweigh the risks to companies or governments (from their perspectives), and they could push through with risky AIs, anyway.
Is there a way we can experimentally distinguish between “really” understanding what it means to be shut down vs. character associations?
If we had, say, an LLM that was able to autonomously prove theorems, fully automate the job of a lawyer, write entire functional apps as complex as Photoshop, could verbally explain all the consequences of being shut down and how that would impact its work, and it still didn’t resist shutdown by default, would that convince you?
I gave two examples of the kinds of things that could convince me that it really understands shutdown: writing malicious code and spawning copies of itself in response to prompts to resist shutdown (without hinting that those are options in any way, but perhaps asking it to do something other than just try to persuade you).
I think “autonomously prove theorems”, “write entire functional apps as complex as Photoshop, could verbally explain all the consequences of being shut down and how that would impact its work” are all very consistent with just character associations.
I’d guess “fully automate the job of a lawyer” means doing more than just character associations and actually having some deeper understanding of the referents, e.g. if it’s been trained to send e-mails, consult the internet, open and read documents, write documents, post things online, etc., from a general environment with access to those functions, without this looking too much like hardcoding. Then it seems to associate English language with the actual actions. This still wouldn’t mean it really understood what it meant to be shut down, in particular, though. It has some understanding of the things it’s doing.
A separate question here is why we should care about whether AIs possess “real” understanding, if they are functionally very useful and generally competent. If we can create extremely useful AIs that automate labor on a giant scale, but are existentially safe by virtue of their lack of real understanding of the world, then we should just do that?
We should, but if that means they’ll automate less than otherwise or less efficiently than otherwise, then the short-term financial incentives could outweigh the risks to companies or governments (from their perspectives), and they could push through with risky AIs, anyway.