Sharmake
Posts 13
Comments307
Topic contributions2
I honestly agree with this post, and to best translate this into my own thinking, we should rather have AI that is superhuman at faithful COT reasoning than it is at wise forward pass thinking.
The Peter Singer/Einstein/Legible reasoning corresponds to COT reasoning, whereas a lot of the directions for intuitive wise/illegible thinking depend on making the forward pass thinking more capable, which is not a great direction for reasons of trust and alignment.
In retrospect, I agree more with 3, and while I do still think AI timelines are plausibly very short, I do think that after-2030 timelines are reasonably plausible from my perspective.
I have become less convinced that takeoff speed from the perspective of the state will be slow, slightly due to entropix reducing my confidence in a view where algorithmic progress doesn't suddenly go critical and make AI radically better, and more so because I now think there will be less flashy/public progress, and more importantly I think the gap between consumer AI and internal AI used in OpenAI will only widen, so I expect a lot of the GPT-4 moments where people wowed and got very concerned at AI to not happen again.
So I expect the landscape of AI governance to have less salience when AIs can automate AI research than the current AI governance field thinks, which means overall I've reduced my probability of a strong societal response from say 80-90% likely to only 45-60% likely.
I basically grant 2, sort of agree with 1, and drastically disagree with three (that timelines will be long.)
Which makes me a bit weird, since while I do have real confidence in the basic story that governments are likely to influence AI a lot, I do have my doubts that governments will try to regulate AI seriously, especially if timelines are short enough.
Yeah, at least several comments have much more severe issues than tone or stylistic choices, like rewording ~every claim by Ben, Chloe and Alice, and then assuming that the transformed claims had the same truth value as the original claim.
I'm in a position very similar to Yarrow here: While I think Kat Woods has mostly convinced me that the most incendiary claims are likely false, and I'm sympathetic to the case for suing Ben and Habryka, there was dangerous red flags in the responses, so much so that I'd stop funding Nonlinear entirely, and I think it's quite bad that Kat Woods responded the way they did.
It seems like the board did not fire Sam Altman for safety reasons, but instead for other reasons instead. Utterly confusing, and IMO demolishes my previous theory, though a lot of other theories also lost out.
Sources below, with their archive versions included:
https://twitter.com/norabelrose/status/1726635769958478244
While I generally agree that they almost certainly have more information on what happened, which is why I'm not really certain on this theory, my main reason here is that for the most part, AI safety as a cause basically managed to get away with incredibly weak standards of evidence for a long time, until the deep learning era in 2019-, especially with all the evolution analogies, and even now it still tends to have very low standards (though I do believe it's slowly improving right now). This probably influenced a lot of EA safetyists like Ilya, who almost certainly imbibed the norms of the AI safety field, and one of them is that there is a very low standard of evidence needed to claim big things, and that's going to conflict with corporate/legal standards of evidence.
But I don't think most people who hold influential positions within EA (or EA-minded people who hold influential positions in the world at large, for that matter) are likely to be that superficial in their analysis of things. (In particular, I'm strongly disagreeing with the idea that it's likely that the board "basically had no evidence except speculation from the EA/LW forum". I think one thing EA is unusually good at – or maybe I should say "some/many parts of EA are unusually good at" – is hiring people for important roles who think for themselves and have generally good takes about things and acknowledge the possibility of being wrong about stuff. [Not to say that there isn't any groupthink among EAs. Also, "unusually good" isn't necessarily that high of a bar.])
I agree with this weakly, in the sense that being high up in EA is at least a slight update towards them actually thinking through things and being able to make actual cases. My disagreement here is that this effect is probably not strong enough to wash away the cultural effects of operating in a cause area where they don't need to meet any standard of evidence except long-winded blog posts and getting rewarded, for many reasons.
Also, the board second-guessed it's decision, which would be evidence for the theory that they couldn't make a case that actually abided to the standard of evidence for a corporate/legal setting.
If it was any other cause like say GiveWell or some other causes in EA, I would trust them much more that they do have good reason. But AI safety has been so reliant on very low-non-existent standards of evidence or epistemics that they probably couldn't explain themselves in a way that would abide by the strictness of a corporate/legal standard of evidence.
Edit: The firing wasn't because of safety related concerns.
If Ilya can say "we're pushing capabilities down a path that is imminently highly dangerous, potentially existentially, and Sam couldn't be trusted to manage this safely" with proof that might work - but then why not say that?
I suspect this is due to the fact that quite frankly, the concerns they had about Sam Altman being unsafe on AI basically had no evidence except speculation from the EA/LW forum, which is not enough evidence at all in the corporate world/legal world, and to be quite frank, the EA/LW standard of evidence on AI risk being a big deal enough to investigate is very low, sometimes non-existent, and that simply does not work once you have to deal with companies/the legal system.
More generally, EA/LW is shockingly loose, sometimes non-existent in its standards of evidence for AI risk, which doesn't play well with the corporate/legal system.
This is admittedly a less charitable take than say, Lukas Gloor's take.
Not especially. If I had to state it simply, it's that massive space for instrumental goals isn't useful today, and plausibly in the future for capabilities, so we have at least some reason to not worry about misalignment AI risk as much as we do today.
In particular, it means that we shouldn't assume instrumental goals to appear by default, and to avoid overrelying on non-empirical approaches like your intuition or imagination. We have to take things on a case-by-case basis, rather than using broad judgements.
Note that instrumental convergence/instrumental goals isn't a binary, but rather a space, where more space for instrumental goals being useful for capabilities is continuously bad, rather than a sharp binary of instrumental goals being active or not active.
My claim is that the evidence we have is evidence against much space for instrumental convergence being useful for capabilities, and I expect this trend to continue, at least partially as AI progresses.
Yet I suspect that this isn't hitting at your true worry, and I want to address it today. I suspect that your true worry is this quote below:
And while I can't answer that question totally, I'd like to suggest going on a walk, drinking water, or in the worst case getting mental help from a professional. But try to stop the loop of never feeling safe around something.
The reason I'm suggesting this is because the problem with acting on your need to feel safe is that the following would happen:
This would, if adopted leave us vulnerable to arbitrarily high demands for safety, possibly crippling AI use cases, and as a general policy I'm not a fan of actions that would result in arbitrarily high demands for something, at least without scrutinizing it very heavily, and would require way, way more evidence than just a feeling.
We have no reason to assume that people's feelings of safety or unsafety actually are connected to the real evidence of whether AI is safe, or whether misalignment risk of AI is big problem. Your feelings are real, but I don't trust that your feeling of unsafety of AI is telling me anything else other than your feelings about something. This is fine, to the extent that it isn't harming you materially, but it's an important thing to note here.
Kaj Sotala made a similar post, which talks about why you should mostly feel safe. It's a different discussion than my comment, but the post below may be useful:
https://www.lesswrong.com/posts/pPLcrBzcog4wdLcnt/most-people-should-probably-feel-safe-most-of-the-time
EDIT 1: I deeply hope you can feel better, no matter what happens in the AI space.
EDIT 2: One thing to keep in mind in general is that in typical cases, when claims that something is more or less anything based on x evidence, this is usually smoothly less or more, rather than something going to zero of something or all of something, so in this case I'm claiming that AI is less dangerous, probably a lot less dangerous, but it doesn't mean we totally erase the danger, it just means that things are more safe and things have gotten smoothly better based on our evidence to date.