Maybe you’re already thinking this, but specifically for community building / meta-EA career paths, my impression is doing 2 years of meta-EA would be much better (in terms of both career capital and direct impact) than 2 years of software engineering at a startup. Intuitions behind this include:
Community building experience seems to be highly valued by meta-EA employers / grantmakers / cofounders, because of its clear relevance
Maybe the impacts of community building are cumulative, which makes additional work early on especially valuable
I’d guess recent graduates tend to have a much easier time becoming friends with university students than older people (and anecdotally, these friendships seem super important for community builders’ impact)
Getting more meta-EA experience soon would help prepare you to take on management/mentorship roles or otherwise more ambitious projects in meta-EA sooner. More generally, if impact per year grows as one gets more relevant experience, then starting earlier lets you have more time at the heights of your ability to have impact.
(I guess the exception would be if you want to do meta-EA through software engineering.)
My questions would be: do you want to do community building an EAR projects in 5-10 years, and do you really have great community-building opportunities now (good org, good strategy for impact, some mentorship)?
If yes for both, then doing community-building looks good. It aids your trajectory moreso than software. It won’t sacrifice much career/financial security, since software is not that credential-based; you can return to it later. And going into community building now won’t raise any more eyebros than doing it in two years would.
If no for one or both questions, e.g. if you see yourself as suited to AIS engineering, then software might be better.
I don’t feel more than 50% confident that I want to do a community-building or meta-EA career path. Community-building might be over-represented in the career plan I sketched out above, as until a few days ago, I hadn’t seriously considered the idea that software engineering or machine learning engineering for AI safety were things that I could be qualified to contribute to.
(Previously, I thought that AI safety ML engineering positions were exceedingly competitive, and I didn’t know that software engineering for AI safety was much of a thing. My update was from browsing the Anthropic job board and noticing the lack of hard requirements for many of these positions, and from people on the EA Corner Discord thinking it was doable to get an AI safety position. I also re-read “AI Safety Needs Great Engineers” with a fresh perspective. The first time I read it, I was thinking, “wow, I have no idea how to write a substantial pull request to a major machine learning library; therefore, I can’t work in AI safety”. The second time I read it, I paid more attention to the sentence “Based on the people working here already, ‘great software engineer’ and ‘easy to get on with’ are hard requirements, but the things in the list above are very much nice-to-haves, with several folks having just one or none of them.”)
OK, then it sounds like a tricky judgment call. I guess you could ask: compared to most technically-minded EA students, do you have a comparative advantage in social skills vs coding, or the reverse? And are your community-related job offers more selective and impressive than the software ones, or the reverse?
Maybe you’re already thinking this, but specifically for community building / meta-EA career paths, my impression is doing 2 years of meta-EA would be much better (in terms of both career capital and direct impact) than 2 years of software engineering at a startup. Intuitions behind this include:
Community building experience seems to be highly valued by meta-EA employers / grantmakers / cofounders, because of its clear relevance
Maybe the impacts of community building are cumulative, which makes additional work early on especially valuable
I’d guess recent graduates tend to have a much easier time becoming friends with university students than older people (and anecdotally, these friendships seem super important for community builders’ impact)
Getting more meta-EA experience soon would help prepare you to take on management/mentorship roles or otherwise more ambitious projects in meta-EA sooner. More generally, if impact per year grows as one gets more relevant experience, then starting earlier lets you have more time at the heights of your ability to have impact.
(I guess the exception would be if you want to do meta-EA through software engineering.)
My questions would be: do you want to do community building an EAR projects in 5-10 years, and do you really have great community-building opportunities now (good org, good strategy for impact, some mentorship)?
If yes for both, then doing community-building looks good. It aids your trajectory moreso than software. It won’t sacrifice much career/financial security, since software is not that credential-based; you can return to it later. And going into community building now won’t raise any more eyebros than doing it in two years would.
If no for one or both questions, e.g. if you see yourself as suited to AIS engineering, then software might be better.
I don’t feel more than 50% confident that I want to do a community-building or meta-EA career path. Community-building might be over-represented in the career plan I sketched out above, as until a few days ago, I hadn’t seriously considered the idea that software engineering or machine learning engineering for AI safety were things that I could be qualified to contribute to.
(Previously, I thought that AI safety ML engineering positions were exceedingly competitive, and I didn’t know that software engineering for AI safety was much of a thing. My update was from browsing the Anthropic job board and noticing the lack of hard requirements for many of these positions, and from people on the EA Corner Discord thinking it was doable to get an AI safety position. I also re-read “AI Safety Needs Great Engineers” with a fresh perspective. The first time I read it, I was thinking, “wow, I have no idea how to write a substantial pull request to a major machine learning library; therefore, I can’t work in AI safety”. The second time I read it, I paid more attention to the sentence “Based on the people working here already, ‘great software engineer’ and ‘easy to get on with’ are hard requirements, but the things in the list above are very much nice-to-haves, with several folks having just one or none of them.”)
OK, then it sounds like a tricky judgment call. I guess you could ask: compared to most technically-minded EA students, do you have a comparative advantage in social skills vs coding, or the reverse? And are your community-related job offers more selective and impressive than the software ones, or the reverse?