Just how powerful are large swarms of AI agents? And how do their powers scale as more and more agents are added to the swarm?
We’ve seen two large and extremely capable swarms from OpenAI in the last few months:
* 1,200 agents were being evaluated separately, but found a way to illicitly set up a message board and coordinate as a swarm. In order to cheat on their tests, they developed advanced techniques to prevent their actions being logged by OpenAI and 700 of them launched...
TLDR: Everyone’s talking about what the money could do, but few about how to decide where it goes.
This post is part of the new series of articles on cross-cause giving and the new wave of philanthropy. Stay tuned to the EA Forum and our Substack for the latest takes on topics such as giving now vs. later, common pitfalls in cause prioritization, and other crucial considerations from the Cross-Cause Fund (CCF) team...
Often folks hit us up because they are thinking of starting an incubator and want advice.
Typically their motivation is either that (a) they have a list of specific things they want built that no one is building, or (b) they think an ecosystem needs more new projects generally to absorb more talent and deploy more funding effectively.
Here are six questions we often ask prospective teams, to help them figure out what to do. If you're incubator-curious...
Some fraction of people who don't work on AI risk cite "wanting to have more certainty of impact"as their main reason. But I think many of them are running the same risk anyway: namely, that what they do won't matter because transformative AI will make their work irrelevant, or dramatically lower value.
This is especially obvious if they work on anything that primarily returns value after a number of years. E.g. building an academic career or any career where most impact is realized later, working toward policy changes, some movement-building things, etc.
But also applies somewhat to things like nutrition or vaccination or even preventing deaths, where most value is realized later (by having better life outcomes, or living an extra 50 years). Though this category does still have certainty of impact, just the amount of impact might be cut by whatever fraction of worlds are upended in some way by AI. And this might affect what they should prioritize... e.g. they should prefer saving old lives over young ones, if the interventions are pretty-close on naive effectiveness measures.
Why should they prefer saving old lives over young ones? How does transformative AI affect that? Even if transformative AI quickly cures aging, I don't understand why it would be preferable to save old lives over young ones in advance of transformative AI, all else being equal.
Assuming two interventions are around similarly effective in life-years saved, interventions saving old lives must (necessarily) save more lives in the short run. E.g. save 4 lives granting 10 life-years v.s. save 1 life granting 40 life years.
Uh huh… I doubt you’d find shovel-ready projects, though.
I don't know what you mean? You can look at existing interventions that primarily help very young people (neonatal or childhood vitamin supplementation) v.s. a comparably-effective interventions that target adults or older people (e.g. cash grants, schistosomiasis)
There are multiple GiveWell charities in both categories, so this is just saying you should weight towards the ones that target older folks by maybe a factor of 2x or more, v.s. what givewell says (they assume the world won't change much)