[Question] Is learning about EA concepts in detail useful to the typical EA?

Say some­one already spent 10-20 hours ac­quiring ba­sic EA knowl­edge. Maybe they read Do­ing Good Bet­ter and the 80000 Hours ca­reer guide, maybe listened to a few 80,000 Hours pod­casts. Is learn­ing more about EA (eg, read­ing this fo­rum) helpful to them?

Here are some guesses for var­i­ous roles I brain­stormed:

  • Safety en­g­ineer at OpenAI/​Deep­Mind. You should prob­a­bly know a few high-level things about AI Safety (maybe some about longter­mism as a whole), but be­yond that, ML, soft­ware en­g­ineer­ing, and gen­eral pro­duc­tivity skills seem to mat­ter much more.

  • Earn­ing to Give. Un­less some­one re­ally likes and is re­ally good at think­ing through and ap­ply­ing these con­cepts, there doesn’t seem to be much value in learn­ing more about EA, since donat­ing to the EA Funds of your cho­sen cause area (maybe the donor lot­tery) is prob­a­bly higher ex­pected value than try­ing to pick out dona­tion op­por­tu­ni­ties your­self.

  • EA Ca­reer coach. Hav­ing broad knowl­edge of EA seems valuable.

  • An­i­mal rights ac­tivist. You should prob­a­bly have some broad knowl­edge of ex­pected value and what in­ter­ven­tions work in the effec­tive an­i­mal ac­tivism liter­a­ture, but pre­sum­ably most of your learn­ing time is bet­ter spent net­work­ing/​learn­ing from other ac­tivists.

  • Devel­op­men­tal econ re­searcher. Maybe EA can help you pri­ori­tize re­search ques­tions, but mostly I just don’t see the added value of learn­ing about EA rel­a­tive to nor­mal dev econ tools?

  • Cause pri­ori­ti­za­tion re­searcher. Hav­ing broad and deep knowl­edge of EA seems very valuable.

  • Com­mu­nity builder. Prob­a­bly a good idea to have a broad knowl­edge of both com­mu­nity build­ing mod­els and for in­di­vi­d­ual cause ar­eas (so you can help ad­vise mem­bers).

  • Amer­i­can Poli­tics/​Policy prac­ti­tioner. Doesn’t seem like EA at the mo­ment adds much be­yond nor­mal skills in the policy toolkit. Might be helpful to net­work with EAs so things in the grapev­ine can even­tu­ally reach you how­ever.

  • AI Policy re­searcher. EA tools seem valuable (low con­fi­dence).

  • Grant­maker in EA-heavy field. Hav­ing broad and deep knowl­edge of EA seems very valuable.

  • Jour­nal­ist. Hav­ing a broad knowl­edge of EA seems valuable.

Naively, it looks like most roles that in­di­vi­d­ual EAs could be in does not, at this mo­ment, benefit from sub­stan­tial EA knowl­edge. So for most of us, the main benefit of learn­ing more about EA is some­thing more neb­u­lous like en­ter­tain­ment, “un­known un­knowns”, or “feel­ing more con­nected to the com­mu­nity.” Am I miss­ing some­thing ma­jor?

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