Alignment research: 30
Could you share some breakdown for what these people work on? Does this include things like the ‘anti-bias’ prompt engineering?
Larks
Karma: 6,174
Larks’s Shortform
I would expect that to be the case for staff who truly support faculty. But many of them seem to be there to directly support students, rather than via faculty. The number of student mental health coordinators (and so on) you need doesn’t scale with the number of faculty you have. The largest increase in this category is ‘student services’, which seems to be definitely of this nature.
Thanks very much for writing this very diligent analysis.
I think you do a good job of analyzing the student/faculty ratio, but unless I have misread it seems like this is only about half the answer. ‘Support’ expenses rose by even more than ‘Instruction’, and the former category seems less linked to the diversity of courses offered than to things like the proliferation of Deans, student welfare initiatives, fancy buildings, etc.
Thanks, that’s very kind of you!
Is your argument about personnel overlap that one could do some sort of mixed effect regression, with location as the primary independent variable and controls for individual productivity? If so I’m so somewhat skeptical about the tractability: the sample size is not that big, the data seems messy, and I’m not sure it would capture necessarily the fundamental thing we care about. I’d be interested in the results if you wanted to give it a go though!
More importantly, I’m not sure this analysis would be that useful. Geography-based-priors only really seem useful for factors we can’t directly observe; for an organization like CHAI our direct observations will almost entirely screen off this prior. The prior is only really important for factors where direct measurement is difficult, and hence we can’t update away from the prior, but for those we can’t do the regression. (Though I guess we could do the regression on known firms/researchers and extrapolate to new unknown orgs/individuals).
The way this plays out here is we’ve already spent the vast majority of the article examining the research productivity of the organizations; geography based priors only matter insomuchas you think they can proxy for something else that is not captured in this.
As befits this being a somewhat secondary factor, it’s worth noting that I think (though I haven’t explicitly checked) in the past I have supported bay area organisations more than non-bay-area ones.
Thanks, fixed in both copies.
Thanks, fixed.
Should be fixed, thanks.
Changed in both copies as you request.
I prioritized posts by named organizations.
Diffractor does not list any institutional affiliations on his user page.
No institution I noticed listed the post/sequence on their ‘research’ page.
No institution I contacted mentioned the post/sequence.
No post in the sequence was that high in the list of 2021 Alignment Forum posts, sorted by karma.
Several other filtering methods also did not identify the post
However upon reflection it does seem to be MIRI-affiliated so perhaps should have been affiliated; if I have time I may review and edit it in later.
2021 AI Alignment Literature Review and Charity Comparison
13 years later: did anyone end up actually making such a book?
The labels on the life satisfaction chart appear to be wrong; January 2021 comes before December 2020.
Yes.
Well, with hemispherectomy, those problems are no more. Hemispherectomy is a procedure where half of the brain is removed. It has been performed multiple times without any apparent complications (example).
I was skeptical until I read the example. Now I am convinced!
It’s hard to sell 1 million eggs for one price, and 1 million for another price.
Are you sure this is the case? It’s common for B2B transactions to feature highly customised and secret pricing and discounts. And in this case they’re not selling the same product from the customer’s point of view: one buyer gets a million ethical eggs, while another gets a million ordinary (from their point of view) eggs.
Thanks for writing this; ordered.
A teacher in year 9 walked up to a student who was talking, picked them up and threw them out of an (open) first floor window.
Worth clarifying for US readers that ‘first floor’ in the UK would be ‘second floor’ in the US, because UK floor indexing starts at zero. So this event is much worse than it sounds.
Thanks!