[1. Do you think many major insights from longtermist macrostrategy or global priorities research have been found since 2015?]
I think "major insights" is potentially a somewhat loaded framing; it seems to imply that only highly conceptual considerations that change our minds about previously-accepted big picture claims count as significant progress. I think very early on, EA produced a number of somewhat arguments and considerations which felt like "major insights" in that they caused major swings in the consensus of what cause areas to prioritize at a very high level; I think that probably reflected that the question was relatively new and there was low-hanging fruit. I think we shouldn't expect future progress to take the form of "major insights" that wildly swing views about a basic, high-level question as much (although I still think that's possible).
[2. If so, what would you say are some of the main ones?]
Since 2015, I think we've seen good analysis and discussion of AI timelines and takeoff speeds, discussion of specific AI risks that go beyond the classic scenario presented in Superintellilgence, better characterization of multipolar and distributed AI scenarios, some interesting and more quantitative debates on giving now vs giving later and "hinge of history" vs "patient" long-termism, etc. None of these have provided definitive / authoritative answers, but they all feel useful to me as someone trying to prioritize where Open Phil dollars should go.
[3. Do you think the progress has been at a good pace (however you want to interpret that)?]
I'm not sure how to answer this; I think taking into account the expected low-hanging fruit effect, and the relatively low investment in this research, progress has probably been pretty good, but I'm very uncertain about the degree of progress I "should have expected" on priors.
[4. Do you think that this pushes for or against allocating more resources (labour, money, etc.) towards that type of work?]
I think ideally the world as a whole would be investing much more in this type of work than it is now. A lot of the bottleneck to this is that the work is not very well-scoped or broken into tractable sub-problems, which makes it hard for a large number of people to be quickly on-boarded to it.
[5. Do you think that this suggests we should change how we do this work, or emphasise some types of it more?]
Related to the above, I'd love for the work to become better-scoped over time -- this is one thing we prioritize highly at Open Phil.
Do you have a sense of how long is typically the lag between an insight first being had, and being recognised as major? I think this might often be several years.
Maybe the dynamic I'm imagining is: "At time T0, someone suggests X as a joke. At time T1, someone seriously posits X: it makes sense to them but they haven't managed to explain it to anyone. At T2, they've explained it in conversation and a small fraction of other people believe it. At T3, there's a first blog post which kind of explains it but to many readers it doesn't feel that well supported. At T4, it's believed by 10% of the relevant community. At T5, someone else makes a better writeup, which sets out more of a solid basis for it. At T6, it's relatively widely accepted as a major insight."
Was it novel at T0 or T1? (or later?) When does it get to count as major? (Is this just in the eyes of the observer?)
Telling jokes as an EA cause.