Hi, I'm Max :)
For me, thinking of relationships and hobbies in an instrumental way takes away from how much joy and energy and meaning etc. I get from them. So in practice I expect most "EA dedicates" should instrumentally just live a life of a "non-dedicate", i.e. to value their relationships with their parents, siblings, partners and friends for their own sake.
Other things make this distinction messy:
There is probably a distinction where some EAs would or wouldn't push the button that turns them into an omniscient utility maximizer who would always just take the action that is doing the most good. I would push this button because the lives and the suffering and the beauty that are at stake are so much more important than me and my other values. But in practice I think I will probably never need the distinction between EA dedicates and non-dedicates.
Thanks, interesting topic and glad you looked into this! (Just read the summary and skimmed the rest.) My spontaneous reaction to the results was that only days after the protest might be a little too soon to observe a backlash?
Thanks for sharing, super interesting!
The organization-wide Brier score (measuring both calibration and resolution) is .217, which is somewhat better than chance (.250). This requires careful interpretation, but in short we think that our reasonably good Brier score is mostly driven by good calibration, while resolution has more room for improvement (but this may not be worth the effort). [more]
Another explanation for the low resolution, besides the limited time you spend on the forecasts, might be that you chose questions that you are most uncertain about (i.e. that you are around 50% certain about resolving positively), right?
This is something I noticed when making my own forecasts. To remove this bias I sometimes use a dice to chose the number for questions like
By Jan 1, 2018,the grantee will have staff working in at least [insert random number from a reasonable range] European countries
I suppose all your points would be satisfied as long the breaking up of colleges happens in a to me pretty reasonable way e.g. by not forcing the new colleges to stay small and non-elite? I understood the main benefit of this to be to remove the current possibly suboptimal college administrations and to replace them with better management that avoids current problems.
I had a somewhat related random stream of thoughts the other day regarding the possibility of bringing past people back to life to allow them to live the life they would like.
While I'm fairly convinced of hedonistic utilitarianism, I found the idea of "righing past wrongs" very appealing. For example allowing a person that died prematurely to live out the fulfilled life that this person would wish for themself, that would feel very morally good to me.
That idea made me wonder if it makes sense to distinguish between persons who were born, and persons that could have existed but didn't, as it seemed somewhat arbitrary to distinguish based on random fluctuations that led to the existence of one kind of person over the other. So at the end of the stream of thought I thought "Might as well spend some infinitely small fraction of our cosmic endowment on instantiating all possible kinds of beings and allow them to live the life they most desire." :D
Thanks for sharing the summary, I wasn’t aware of many of these.
Amnesty International seems like another case that would be worth understanding better:
Nice, thinking more about possible AI risk scenarios seems super important to me, thanks for working on this!
I'm super unfamiliar with your methodology, do you have a good example where this process is applied to a similar situation (sorry if I didn't spot this in the text)?
Thanks for sharing this list, a bunch of great people! I have a background in cognitive science and am interested in exploring the strategy of understanding human intelligence for designing aligned AIs.
Some quotes from Paul Christiano that I read a couple months ago on the intersection.
From The easy goal inference problem is still hard:
The possible extra oomph of Inverse Reinforcement Learning comes from
an explicit model of the human’s mistakes or bounded rationality. It’s
what specifies what the AI should do differently in order to be
“smarter,” what parts of the human’s policy it should throw out. So it
implicitly specifies which of the human behaviors the AI should keep.
The error model isn’t an afterthought — it’s the main affair.
and
It’s not clear to me whether or exactly how progress in AI will make
this problem [of finding any reasonable representation of any reasonable
approximation to what that human wants] easier. I can certainly see how enough progress in
cognitive science might yield an answer, but it seems much more likely
that it will instead tell us “Your question wasn’t well defined.” What
do we do then?
From Clarifying “AI alignment”:
“What [the human operator] H wants” is even more problematic [...]. Clarifying what this expression means, and how to operationalize it in a way that could be used to inform an AI’s behavior, is part of the alignment problem. Without additional clarity on this concept, we may not be able to build an AI that tries to do what H wants it to do.
Nice, super interesting. Some very scattered thoughts:
It's kinda obvious, but I wanted to point out anyway that many of your suggestions for increasing well-being also seems to require significant levels of wealth to pull off: