You should take the quant role imo. Optionality is valuable (though not infinitely so). Quant trading gives you vastly more optionality. If trading goes well but you leave the field after five years you will have still gained a large amount of experience and donated/saved a large amount of capital. It’s not unrealistic to try for 500K donated and 500K+ saved in that timeframe, especially since firms think you are unusually talented. If you have five hundred thousand dollars, or more, saved you are no longer very constrained by finances. Five hundred thousand dollars is enough to stochastically save over a hundred lives. There are several high impact EA orgs with a budget of around a million dollars a year (Rethink Priorities comes to mind). If trading goes very well you could personally fund such an org.
How are you going to feel if you decide to do the PHD and after five years you decide that it was not the best path? You will have left approximately a million dollars and a huge amount of earning potential on the table. You could have been free to work for no compensation if you want. You would have been able to bankroll a medium sized project if you keep trading.
There are a lot of ways to massively regret turning down the quant job. It is plausible that the situation is so dire that you need to drop other paths and work on AI safety right now. But you need to be confident in a very detailed world model to justify giving up so much optionality. There are a lot of theories on how to do the most good. Stay upstream.
AI PhDs tend to be very well-compensated after graduating, so I don’t think personal financial constraints should be a big concern on that path.
More generally, skill in AI is going to be upstream of basically everything pretty soon; purely in terms of skill optionality, this seems much more valuable than being a quant.
In the world where your second paragraph is true, I’d expect the quant firms will start or have already started using AI heavily, and so by working as a software engineer at one of those firms you can expect to be able to build skills in that area. So then it’s a classic choice between ‘learning about something via a PhD’ versus ‘learning about something via working on a practical application’, which I generally think of as a YMMV question.
I’m curious if you expect the PhD to systematically have more optionality after accounting for that, if you weren’t already.
So there are a few different sources of optionality from a PhD: - Academic credentials - Technical skills - Research skills
Software engineer at a quant firm plausibly builds more general technical skills, but I expect many SWEs there work on infrastructure that has little to do with AI. I also don’t have a good sense for how fast quant firms are switching over to deep learning—I assume they’re on the leading edge, but maybe not all of them, or maybe they value interpretability too much to switch fully.
But I also think PhDs are pretty valuable for learning how to do innovative research at the frontiers of knowledge, and for the credentials. So it seems like one important question is: what’s the optionality for? If it’s for potentially switching to a different academic field, then PhD seems better. If it’s for leading a research organisation, same. Going into policy work, same. If it’s for founding a startup, harder to tell; depends on whether it’s an AI startup I guess.
Whereas I have more trouble picturing how a few years at a quant firm is helpful in switching to a different field, apart from the cash buffer. And I also had the impression that engineers at these places are usually compensated much worse than quants (although your earlier comment implies that this isn’t always the case?).
Actually, one other thing is that I was implicitly thinking about UK PhDs. My concern with US PhDs is that they can be so long. Which makes me more optimistic about getting some external work experience first, to get a better perspective from which to make that commitment (which is what I did).
That makes sense, thanks for the extra colour on PhDs.
Whereas I have more trouble picturing how a few years at a quant firm is helpful in switching to a different field, apart from the cash buffer.
I’ve heard variants on this a few times, so you aren’t alone. To give some extra colour on what I think you’re gaining from working at quant firms: Most of these firms still have a very start-up-like culture. That means that you get significant personal responsibility and significant personal choice about what you work on, within a generally supportive culture. In general this is valuable, but it means there isn’t one universal answer to this question. Still, some candidate skills I think you’ll get the opportunity to develop should you so choose.
(This list is illustrative based on my own experience, rather than exhaustive. Some of the above will apply to the PhD as well, it’s not intended as a comparison)
You should take the quant role imo. Optionality is valuable (though not infinitely so). Quant trading gives you vastly more optionality. If trading goes well but you leave the field after five years you will have still gained a large amount of experience and donated/saved a large amount of capital. It’s not unrealistic to try for 500K donated and 500K+ saved in that timeframe, especially since firms think you are unusually talented. If you have five hundred thousand dollars, or more, saved you are no longer very constrained by finances. Five hundred thousand dollars is enough to stochastically save over a hundred lives. There are several high impact EA orgs with a budget of around a million dollars a year (Rethink Priorities comes to mind). If trading goes very well you could personally fund such an org.
How are you going to feel if you decide to do the PHD and after five years you decide that it was not the best path? You will have left approximately a million dollars and a huge amount of earning potential on the table. You could have been free to work for no compensation if you want. You would have been able to bankroll a medium sized project if you keep trading.
There are a lot of ways to massively regret turning down the quant job. It is plausible that the situation is so dire that you need to drop other paths and work on AI safety right now. But you need to be confident in a very detailed world model to justify giving up so much optionality. There are a lot of theories on how to do the most good. Stay upstream.
AI PhDs tend to be very well-compensated after graduating, so I don’t think personal financial constraints should be a big concern on that path.
More generally, skill in AI is going to be upstream of basically everything pretty soon; purely in terms of skill optionality, this seems much more valuable than being a quant.
In the world where your second paragraph is true, I’d expect the quant firms will start or have already started using AI heavily, and so by working as a software engineer at one of those firms you can expect to be able to build skills in that area. So then it’s a classic choice between ‘learning about something via a PhD’ versus ‘learning about something via working on a practical application’, which I generally think of as a YMMV question.
I’m curious if you expect the PhD to systematically have more optionality after accounting for that, if you weren’t already.
So there are a few different sources of optionality from a PhD:
- Academic credentials
- Technical skills
- Research skills
Software engineer at a quant firm plausibly builds more general technical skills, but I expect many SWEs there work on infrastructure that has little to do with AI. I also don’t have a good sense for how fast quant firms are switching over to deep learning—I assume they’re on the leading edge, but maybe not all of them, or maybe they value interpretability too much to switch fully.
But I also think PhDs are pretty valuable for learning how to do innovative research at the frontiers of knowledge, and for the credentials. So it seems like one important question is: what’s the optionality for? If it’s for potentially switching to a different academic field, then PhD seems better. If it’s for leading a research organisation, same. Going into policy work, same. If it’s for founding a startup, harder to tell; depends on whether it’s an AI startup I guess.
Whereas I have more trouble picturing how a few years at a quant firm is helpful in switching to a different field, apart from the cash buffer. And I also had the impression that engineers at these places are usually compensated much worse than quants (although your earlier comment implies that this isn’t always the case?).
Actually, one other thing is that I was implicitly thinking about UK PhDs. My concern with US PhDs is that they can be so long. Which makes me more optimistic about getting some external work experience first, to get a better perspective from which to make that commitment (which is what I did).
That makes sense, thanks for the extra colour on PhDs.
I’ve heard variants on this a few times, so you aren’t alone. To give some extra colour on what I think you’re gaining from working at quant firms: Most of these firms still have a very start-up-like culture. That means that you get significant personal responsibility and significant personal choice about what you work on, within a generally supportive culture. In general this is valuable, but it means there isn’t one universal answer to this question. Still, some candidate skills I think you’ll get the opportunity to develop should you so choose.
Project management
People management
Hiring
Judgement (in the narrow 80k sense of the term)
(This list is illustrative based on my own experience, rather than exhaustive. Some of the above will apply to the PhD as well, it’s not intended as a comparison)