Mostly what I’m arguing for here is a whole different model, where newcomers are funded with a goal of getting them through the Path (probably with resources designed for that purpose), rather than relying on Alignment Maturity coming about accidentally as a side-effect of research.
(Also, minor point, I think I was most of the way through the Path by the time I got my first grant, so I actually did go through that growth before I had funding. But I don’t think that’s particularly relevant here.)
At the moment there’s a plan to create The Berlin Hub as a coliving space for new AI safety researchers. What lessons do you think should be drawn from the thesis you laid out for that project? Do you believe that the peer review that happens through that environment will push people on the [ath forward or would you fear that a lot of people at the Hub would do work that doesn’t matter?
This is extremely difficult. Some good literature on cooperative living worth reading because there are countless common pitfalls. Also being a research org at the same time is quite ambitious. Good luck!
Many practicalities with admitting good members, dealing with problematic members, keeping the kitchen sink clean, keeping the floors clean, keeping track of rent, doing repairs, etc. Some of this is alleviated if you have a big budget. Culture is extremely tricky. It is extremely rewarding when it works.
Visiting a coop for even a week reveals quite a bit about how it works — if you haven’t done that already
The main immediate advice I’d give is to look at people switching projects/problems/ideas as a key metric. Obviously that’s not a super-robust proxy and will break down if people start optimizing for it directly. But insofar as changes in which projects people work on are driven by updates to their underlying models, it’s a pretty good metric of progress down the Path.
At this point, I still have a lot of uncertainty about things which will work well or not work well for accelerating people down the Path; it looks tractable, but that doesn’t mean that it’s clear yet what the best methods are. Trying things and seeing what causes people to update a lot seems like a generally good approach.
Mostly what I’m arguing for here is a whole different model, where newcomers are funded with a goal of getting them through the Path (probably with resources designed for that purpose), rather than relying on Alignment Maturity coming about accidentally as a side-effect of research.
(Also, minor point, I think I was most of the way through the Path by the time I got my first grant, so I actually did go through that growth before I had funding. But I don’t think that’s particularly relevant here.)
At the moment there’s a plan to create The Berlin Hub as a coliving space for new AI safety researchers. What lessons do you think should be drawn from the thesis you laid out for that project? Do you believe that the peer review that happens through that environment will push people on the [ath forward or would you fear that a lot of people at the Hub would do work that doesn’t matter?
This is extremely difficult. Some good literature on cooperative living worth reading because there are countless common pitfalls. Also being a research org at the same time is quite ambitious. Good luck!
do you happen to have additional references besides those words to find literature on cooperative living?
Had some books at previous coop — might have been these.
https://www.ic.org/community-bookstore/product/wisdom-of-communities-complete-set/
Many practicalities with admitting good members, dealing with problematic members, keeping the kitchen sink clean, keeping the floors clean, keeping track of rent, doing repairs, etc. Some of this is alleviated if you have a big budget. Culture is extremely tricky. It is extremely rewarding when it works.
Visiting a coop for even a week reveals quite a bit about how it works — if you haven’t done that already
The main immediate advice I’d give is to look at people switching projects/problems/ideas as a key metric. Obviously that’s not a super-robust proxy and will break down if people start optimizing for it directly. But insofar as changes in which projects people work on are driven by updates to their underlying models, it’s a pretty good metric of progress down the Path.
At this point, I still have a lot of uncertainty about things which will work well or not work well for accelerating people down the Path; it looks tractable, but that doesn’t mean that it’s clear yet what the best methods are. Trying things and seeing what causes people to update a lot seems like a generally good approach.