The billions of anthropic argument is convincing. The working in AI safety thing is convincing.
The problem is all the prior presuppose a singularity coming soon. I am not convinced. Furthermore, the dilligent techie could fund careers in AI safety. Finance earns a lot of money. This is especially important if she does not consider effective cause areas interesting. But I mean it's inherently pascal-wager esque, so it kind of matters automatically because of how impactful it will be and how neglected it is.
> Incidentally, ‘flipping non-EA jobs into EA jobs’ and ‘creating EA jobs’ both seem much more impactful than ‘taking EA jobs’. That could be e.g. taking an academic position that otherwise wouldn’t have been doing much and using it to do awesome research / outreach that others can build on, or starting an EA-aligned org with funding from non-EA sources, like VCs.
That's a super good argument tbh. Embarrassed I didn't think of it. I will consider this if I were to do an ML PhD. Which I'm not sure of yet.
> Celeste describes a diligent EA earning $55-200k/year in a London tech job. But when you’re you’re a young person considering earning to give, you should be thinking about your lifetime donations / impact, not just what you can accomplish this year. And while this person might be striving to donate $O(10^6) over their life, there’s a reason they might not get to:
I was doing this by the way. The americain cannot comprehend salary capping at $200k. (in belgium most seniors never reach $100k)
> I think Celeste is very smart and can do a lot if she sets her mind to it.
thank you, I hope so! I might just by accident get into AI safety. I have very similar MLish interests to you of just wanting to know how everything works (learning neuralese as you put it) and just through following curiosity I may end up in technical AI safety even when not convinced of existential risk.
nitpick: I am confused at your usage of asymptotic notation in this post. How is big O appropriate here at all when the constant is kind of everything?
> The problem is all the prior presuppose a singularity coming soon. I am not convinced.
that works
there's another argument of 'e2g is only worth it if your lifetime donations will exceed $x.' i think it might be worth trying to work out x? i think the answer might be as low as $500k or as high as $10 million, probs person-dependent. a calculator for this could be good
> just through following curiosity I may end up in technical AI safety even when not convinced of existential risk
as another data point, i'd be working in AI/ML for impact reasons even if x-risk weren't a thing.
> I am confused at your usage of asymptotic notation in this post. How is big O appropriate here at all when the constant is kind of everything?
good point, i meant to convey 'on the order of magnitude', i've replaced it! thank you
It seems to me that the two are never really mutually exclusive in the first place; a lot of people who E2G end up working in EA and vice versa. I can even imagine they are correlated vectors - E2G means you're more familiar with EA arguments means you're more likely to end up working in AI safety.
The billions of anthropic argument is convincing. The working in AI safety thing is convincing.
The problem is all the prior presuppose a singularity coming soon. I am not convinced. Furthermore, the dilligent techie could fund careers in AI safety. Finance earns a lot of money. This is especially important if she does not consider effective cause areas interesting. But I mean it's inherently pascal-wager esque, so it kind of matters automatically because of how impactful it will be and how neglected it is.
> Incidentally, ‘flipping non-EA jobs into EA jobs’ and ‘creating EA jobs’ both seem much more impactful than ‘taking EA jobs’. That could be e.g. taking an academic position that otherwise wouldn’t have been doing much and using it to do awesome research / outreach that others can build on, or starting an EA-aligned org with funding from non-EA sources, like VCs.
That's a super good argument tbh. Embarrassed I didn't think of it. I will consider this if I were to do an ML PhD. Which I'm not sure of yet.
> Celeste describes a diligent EA earning $55-200k/year in a London tech job. But when you’re you’re a young person considering earning to give, you should be thinking about your lifetime donations / impact, not just what you can accomplish this year. And while this person might be striving to donate $O(10^6) over their life, there’s a reason they might not get to:
I was doing this by the way. The americain cannot comprehend salary capping at $200k. (in belgium most seniors never reach $100k)
> I think Celeste is very smart and can do a lot if she sets her mind to it.
thank you, I hope so! I might just by accident get into AI safety. I have very similar MLish interests to you of just wanting to know how everything works (learning neuralese as you put it) and just through following curiosity I may end up in technical AI safety even when not convinced of existential risk.
nitpick: I am confused at your usage of asymptotic notation in this post. How is big O appropriate here at all when the constant is kind of everything?
> The problem is all the prior presuppose a singularity coming soon. I am not convinced.
that works
there's another argument of 'e2g is only worth it if your lifetime donations will exceed $x.' i think it might be worth trying to work out x? i think the answer might be as low as $500k or as high as $10 million, probs person-dependent. a calculator for this could be good
> just through following curiosity I may end up in technical AI safety even when not convinced of existential risk
as another data point, i'd be working in AI/ML for impact reasons even if x-risk weren't a thing.
> I am confused at your usage of asymptotic notation in this post. How is big O appropriate here at all when the constant is kind of everything?
good point, i meant to convey 'on the order of magnitude', i've replaced it! thank you
It seems to me that the two are never really mutually exclusive in the first place; a lot of people who E2G end up working in EA and vice versa. I can even imagine they are correlated vectors - E2G means you're more familiar with EA arguments means you're more likely to end up working in AI safety.