I downvoted this because I think this isnât independently valuable /â separate enough from your existing posts to merit a new, separate post. I think it would have been better as a comment on your existing posts (and as Iâve said on a post by someone else about your reviews, I think weâre better off consolidating the discussion in one place).
That said, I think the sentiments expressed here are pretty reasonable, and I would have upvoted this in comment form I think.
They posted about their review of Sinergia on the forum already: https://ââforum.effectivealtruism.org/ââposts/ââYYrC2ZR5pnrYCdSLt/ââsinergia-ace-top-charity-makes-false-claims-about-helping
I suggest we concentrate discussion there and not here.
Someone on the forum said there were ballpark 70 AI safety roles in 2023
Just to note that the UK AI Security Institute employs more than 50 technical staff by itself and I forget how many non-technical staff, so this number may be due an update.
This doesnât seem right to me because I think itâs popular among those concerned with the longer term future to expect it to be populated with emulated humans, which clearly isnât a continuation of the genetic legacy of humans, so I feel pretty confident that itâs something else about humanity that people want to preserve against AI. (Iâm not here to defend this particular vision of the future beyond noting that people like Holden Karnofsky have written about it, so itâs not exactly niche.)
You say that expecting AI to have worse goals than humans would require studying things like what the empirical observed goals of AI systems turn out to be, and similar â sure, so in the absence of having done those studies, we should delay our replacement until they can be done. And doing these studies is undermined by the fact that right now the state of our knowledge on how to reliably determine what an AI is thinking is pretty bad, and it will only get worse as they develop their abilities to strategise and lie. Solving these problems would be a major piece of what people are looking for in alignment research, and precisely the kind of thing it seems worth delaying AI progress for.
another opportunity for me to shill my LessWrong writing posing this question: Should we exclude alignment research from LLM training datasets?
I donât have a lot of time to spend on this, but this post has inspired me to take a little time to figure out whether I can propose or implement some controls (likely: making posts visible to logged-in users only) in ForumMagnum (the software underlying the EA Forum, LW, and the Alignment Forum)
edit: https://ââgithub.com/ââForumMagnum/ââForumMagnum/ââissues/ââ10345
See also:
(Perhaps there should be a forum tag for this issue specifically, idk)
I agree overall but I want to add that becoming dependent on non-EA donors could put you under pressure to do more non-EA things /â less EA thingsâeither party could pull the other towards themselves.
Keep in mind that youâre not coercing them to switch their donations, just persuading them. That means you can use the fact that they were persuaded as evidence that you were on the right side of the argument. You being too convinced of your own opinion isnât a problem unless other people are also somehow too convinced of it, and I donât see why they would be.
I think that EA donors are likely to be unusual in this respectâyouâre pre-selecting for people who have signed up for a culture of doing whatâs best even when it wasnât what they thought it was before.
I guess also I think that my arguments for animal welfare charities are at their heart EA-style arguments, so Iâm getting a big boost to my likelihood of persuading someone by knowing that theyâre the kind of person who appreciates EA-style arguments.
Similarly if you think animal charities are 10x global health charities in effectiveness, then you think these options are equally good:
Move 10 EA donors from global health to animal welfare
Add 9 new animal welfare donors who previously werenât donating at all
To me, the first of these sounds way easier.
Thanks! (I slightly object to âthe normal markdown syntaxâ, since based on my quick reading neither John Gruberâs original markdown spec nor the latest CommonMark spec nor GitHub Flavoured Markdown have footnotes)
FWIW the link to your forum post draft tells me âSorry, you donât have access to this draftâ
The onboarding delay is relevant because in the 80k case it happens twice: the 80k person has an onboarding delay, and then the people they cause to get hired have onboarding delays too.
It feels like when Iâm comparing the person who does object-level work to the person who does meta-level work that leads to 2 people (say) doing object-level work, the latter really does seem better all things equal, but the intuition that calls this model naive is driven by a sense that itâs going to turn out to not âactuallyâ be 2 additional people, that additionality is going to be lower than you think, that the costs of getting that result are higher than you think, etc. etc.
But this intuition is not as clear as Iâd like on what the extra costs /â reduced benefits are, and how big a deal they are. Here are the first ones I can think of:
Perhaps the people that you recruit instead arenât as good at the job as you would have been.
If your orgâs hiring bottlenecks are not finding great people, but instead having the management capacity to onboard them or the funding capacity to pay for them, doing management or fundraising, or work that supports the case for fundraising, might matter more.
but 80k surely also needs good managers, at least as a general matter
I think when an org hires you, thereâs an initial period of your onboarding where you consume more staff time than you produce, especially if you weight by seniority. Different roles differ strongly on where their break-even point is. Iâve worked somewhere who thought their number was like 6-18 months (I forget what they said exactly, but in that range) and I can imagine cases where itâs more like⌠day 2 of employment. Anyway, one way or another, if you cause object level work to happen by doing meta level work, youâre introducing another onboarding delay before stuff actually happens. If the area youâre hoping to impact is time-sensitive, this could be a big deal? But usually Iâm a little skeptical of time-sensitivity arguments, since people seem to make them at all times.
itâs easy to inadvertently take credit for a person going to role that they would actually have gone to anyway, or not to notice when you guide someone into a role thatâs worse (or not better, or not so much better) than what they would have done otherwise (80k are clearly aware of this and try to measure it in various ways, but itâs not something you can do perfectly)
I think this depends on what the specific role is. I think the one Iâm going for is not easily replaceable, but Iâm mostly aiming not to focus on the specific details of my career choice in this thread, instead trying to address the broader questions about meta work generally.
oh! uhh, how?
sometimes I feel bone-headedly stuck on even apparently-simple things like âif nonprofit growth is easier than for-profit growth, does that mean that nonprofits should spend more effort on growth, or less?â
Iâm currently facing a career choice between a role working on AI safety directly and a role at 80,000 Hours. I donât want to go into the details too much publicly, but one really key component is how to think about the basic leverage argument in favour of 80k. This is the claim thatâs like: well, in fact I heard about the AIS job from 80k. If I ensure even two (additional) people hear about AIS jobs by working at 80k, isnât it possible going to 80k could be even better for AIS than doing the job could be?
In that form, the argument is naive and implausible. But I donât think I know what the âsophisticatedâ argument that replaces it is. Here are some thoughts:
Working in AIS also promotes growth of AIS. It would be a mistake to only consider the second-order effects of a job when youâre forced to by the lack of first-order effects.
OK, but focusing on org growth fulltime seems surely better for org growth than having it be a side effect of the main thing youâre doing.
One way to think about this is to compare two strategies of improving talent at a target org, between âtry to find people to move them into roles in the org, as part of cultivating a whole overall talent pipeline into the org and related orgsâ, and âput all of your fulltime effort into having a single person, i.e. you, do a job at the orgâ. It seems pretty easy to imagine that the former would be a better strategy?
I think this is the same intuition that makes pyramid schemes seem appealing (something like: surely I can recruit at least 2 people into the scheme, and surely they can recruit more people, and surely the norm is actually that you recruit a tonne of peopleâ and itâs really only by looking at the mathematics of the population as a whole you can see that it canât possibly work, and that actually itâs necessarily the case that most people in the scheme will recruit exactly zero people ever.
Maybe a pyramid scheme is the extreme of âwhat if literally everyone in EA worked at 80kâ, and serves as a reducto ad absurdum for always going into meta, but doesnât tell you precisely when to stop going meta. It could simultaneously be the case that pyramid schemes stop far too late, but everyone else stops significantly too early.
OK, so perhaps the thing to do is try to figure out what the bottleneck is in recruitment, and try to figure out when it would flip from ânot enough people are working on recruitmentâ to âthere isnât more work to do in recruitmentâ, e.g. because youâve already reached most of the interested population, and the people youâve already reached donât need more support, or in practice giving them more support doesnât improve outcomes.
OK, so when recruiting stops working, stop doing it (hardly a shocking revelation). But even that seems much more recruiting-heavy in implication than the norm. Surely you donât only stop when recruiting is useless, but when it is not as useful as your alternative.
In a lot of for-profit organisations, you need to stop recruiting because you need to start making money to pay the recruiters and the people they recruit. Even if it is worth more than it would cost to continue recruiting, you canât pay for it, so you have to do some object-level stuff, to prove to people that you deserve the confidence to continue to do the recruiting.
Itâs natural to think that if you could have arbitrary lines of credit, youâd want to do lots more recruitment up front, and this would eventually pay off. But there are people out there with money to lend, and they systematically donât want to lend it to you. Are they irrational, or are you over-optimistic?
It seems like the conclusion is forcing you to do object-level stuff is actually rational, because lots of people with optimistic projections of how much recruitment will help you are just wrong, and we need to find that out before burning too much money on recruiting. This discipline is enforced by the funding structure of for-profit firms.
The efficient market hypothesis as-applied here suggests that systematically demanding less or more object-level work from firms wonât allow you to do better than the status quo, so the existing overall level of skepticism is correct-ish. But non-profit ârecruitingâ is wildly different in many ways, so I donât know how much we should feel tethered to what works in the for-profit world.
The overall principle that we need people doing object-level work in EA in order to believe that meta-level work is worth doing seems correct. In the for-profit world the balance is struck basically by your equity holders or creditors seeking assurance from you that your growth will lead to more revenue in the future. In the non-profit world I suppose your funders can provide the same accountability. In both cases the people with money are not wizards and are not magically better at finding the truth than you are, though at least in the for-profit world if they repeatedly make bad calls then they run out of money to make new bad calls with (while if they make good calls they get more money to make more /â bigger calls with), so that acts as something of a filter. But being under budget discipline only makes it more important that you figure out whether to grow or execute; it doesnât really make you better at figuring it out.
I suppose the complement to the naive thing I said before is â80k needs a compelling reason to recruit people to EA, and needs EA to be compelling to the people to recruit to it as well; by doing an excellent job at some object-level work, you can grow the value of 80k recruiting, both by making it easier to do and by making the outcome a more valuable outcome. Perhaps this might be even better for recruiting than doing recruiting.â
This feels less intuitively compelling, but itâs useful to notice that it exists at all.
This take is increasingly non-quick, so I think Iâm going to post it and meditate on it somewhat and then think about whether to write more or edit this one.
I think thereâs a big difference between âmore effectiveâ and âmost effectiveâ, and one of the most important and counterintuitive principles of EA is that trying to find the best option rather than just a good option can make a huge difference to how much good you doâwe have to prioritise between different goods, and this is painful to do (hence easy to avoid) but really important.
Not that itâs super important, but TVTropes didnât invent the phrase (nor do they claim they did), itâs from Warhammer 40,000.