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Right, and my point is that current AI is unintelligent that this doesn't work! They can't predict how agents act effectively enough to be at all useful agents. So the safety of current oracle AIs doesn't tell us much about whether future agent AIs will be safe.
I actually think that future less-but-still-subhuman agent AIs will seem to be safe in Yud's sense, though. No idea what'll happen at human-level, then at superhuman they'll become "misaligned" relatively quickly, but [digression]
GPT-4 isn't human level though! It can't, like, play corporate politics and come out on top, and then manipulate the corporation to serve some other set of values. So the fact that it hasn't done that isn't evidence that it won't.
Right, but they're "going along" with, mostly, saying the right words. There's not the intelligence potential for anything like deep deceptiveness or instrumental convergence or meta-reflection or discovering deeper Laws of Rationality or whatever it is yud's pondering.
You must get that such feats are rare even within humans, and people capable of pulling them off are enormous outliers?
For most cognitive tasks, GPT-4 beats the average human, which is something I'm more than comfortable calling human level AI!
The fact that you can even have the absence of those properties in something smarter than the median human is reassuring enough by itself. A 100 IQ human is very much capable of deceptiveness, certainly instrumental convergence if they're trying to make money. If I had to guesstimate GPT-4's IQ based off my experience with it, I'd say it's about 120, which is perfectly respectable if not groundbreaking. I'd expect you need to go quite a bit higher to achieve the latter properties.
Since a human of equivalent intelligence is capable of the former two feats, the fact that GPT-4 doesn't do that is at least modest evidence of it not doing it for the next jump in capabilities to, say, GPT-5, or the same delta in performance as 3 to 4 regardless of how many model numbers that is.
I emphasize modest, because I still have a 30% p(doom) and I'm not writing off alignment as Solved™.
I was thinking of 'guy who works his way to the top of a car dealership', not Altman, lol. AI models can't yet do the kind of long-term planning or value seeking that 85 IQ humans can.
Most small-scale cognitive tasks! If this was true, we'd have directly replaced the bottom 20% of white-collar jobs with GPT-4. This hasn't happened! Instead, tasks are adapted to GPT-4's significant limitations, with humans to support.
(again, i'm talking about current capabilities, not implying limits to future capabilities)
I don't think it's worrying that it can't make plans against us if it can't make plans for us either! Like, there's no plausible way for something that can't competently execute on complicated plans to have an incentive to take 'unaligned' actions. Even if it happens to try a thing that's slightly in the direction of a misaligned plan, it'll just fail, and learn not to do that. So I don't think it's comforting that it doesn't.
(i'm misusing yudconcepts I don't exactly agree with here, but the point is mostly correct)
I don't think it's anywhere close to the broad capabilities of a 120 IQ human, and still isn't that close to 100IQ (at the moment, again, idk about how quickly it'll close, could be fast!). It can do a lot of the things a 120 IQ human can, but it doesn't generalize as well as a 120IQ human does. This isn't just a 'context window limitation' (and we have longer context windows now, it hasn't solved the problem!), what humans are doing is just more complicated!
This seems silly, sorry. Are ticks and brain-eating ameobas «aligned» to mankind?
LLMs are just not agentic. They can obviously sketch workable plans, and some coming-soon variants of LLMs trained and inferenced more reasonably than our SoTAs will be better. This is a fully general issue of orthogonality – the intelligent entity not only can have «any» goal but it can just not have much of a goal or persistent preferences or optimization target or whatever, it can just be understood as a good compression of reasoning heuristics. And there's no good reason to suspect this stops working at ≤human level.
Okay, to back up a bit: I'm arguing that today's LLMs couldn't be agentic even if they wanted to be, so their behavior shouldn't "lower one's p(doom)". Future LLMs (or not-exactly-LLM models), being much more capable and more agentic, could easily just have different properties.
They can write things that sound like workable plans, but they can't, when given LangChain-style abilities, "execute on them" in the way that even moderately intelligent humans can. Like, you can't currently replace a median IQ employe directly with huge context window GPT4, it's not even close. You can often, like, try and chop up that employe's tasks into a bunch of small blocks that GPT-4 can do individually and have a smaller number of employees supervise it! But the human's still acting as an agent in a way that GPT-4 isn't.
I think the alignment concern is something like - once the agents are complex enough to act on plans, that complexity also affects how they motivate and generate those plans, and then you might get misalignment.
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