Can you elaborate on which areas of EA might tend towards each extreme? Specific examples (as vague as needed) would be awesome too, but I understand if you can’t give any
Unfortunately I find it hard to give examples that are comprehensible without context that is either confidential or would take me a lot of time to describe. Very very roughly I’m often not convinced by the use of quantitative models in research (e.g. the “Racing to the Precipice” paper on several teams racing to develop AGI) or for demonstrating impact (e.g. the model behind ALLFED’s impact which David Denkenberger presented in some recent EA Forum posts). OTOH I often wish that for organizational decisions or in direct feedback more quantitative statements were being made—e.g. “this was one of the two most interesting papers I read this year” is much more informative than “I enjoyed reading your paper”. Again, this is somewhat more subtle than I can easily convey: in particular, I’m definitely not saying that e.g. the ALLFED model or the “Racing to the Precipice” paper shouldn’t have been made—it’s more that I wish they would have been accompanied by a more careful qualitative analysis, and would have been used to find conceptual insights and test assumptions rather than as a direct argument for certain practical conclusions.