I want to first say thanks for making this thread! This has helped me set a deadline for myself to write down my thoughts and ask for some feedback. As described below, I’d love some feedback about my career plans, and also this draft post of notes about what it could mean to be an expert in AI hardware, which I wrote up while working on these plans.
For a little background on me, I’m currently a grad student working near the area of quantum computing hardware and I’m on track to get my PhD in summer 2022. I think my strengths are laboratory work in experimental physics. I find that I enjoy leadership roles, though I find it hard to gauge if I actually am skilled at these roles. (For more background see my resume). I’m also planning to do an internship in summer 2021. I’m hoping to figure out what could be particularly good uses of my time for the internship and my first couple roles after grad school. I currently have no constraints on location.
I think I am pretty cause neutral, but given my skill set some of the areas I’ve thought about focusing on are:
AI Hardware
AI Policy
AI Technical research
Earning to give (and continuing to work on my personal cause prioritization)
Atomically Precise Manufacturing (APM)
I talked with a few people about APM. My impression is that it’s not clear if anyone should be working on actually making this technology right now. However, if one were to do this anyway, one of the most promising approaches would be essentially biology work in academia, trying to start the subfield. This made me less interested in the area, since the low expected value doesn’t seem to merit trying to start a subfield that I have no experience in.
I think I would enjoy some earning to give roles, but I view this as a solid backup option after getting a feel for the impact I can have with direct work.
I looked into AI Safety research for a little while, but it’s not clear to me that it’s my comparative advantage (as more of a lab person) compared to the other people pursuing these roles.
One idea I came across from the post “Some promising career ideas beyond 80,000 Hours’ priority paths” was AI Hardware. I think this does play more to my comparative advantage, and may let me work on the same problems. I spent some time taking notes on what it might mean to be an expert in AI Hardware, and I’m planning to make a forum post about this.
From this research, I’ve come up with the following plan:
Next month: Gain experience in one emerging AI Hardware platform (photonics) through an edX course recommended by someone in the field
Next summer: Expand my experience with real AI hardware doing an internship in summer 2021, prioritizing companies working on near-term hardware like Google, but any internship would be better than nothing.
Next year: Apply for the AAAS Science and Technology Policy Fellowship (for the positions starting in September 2022) to see how well suited I am to policy
These experiences will probably update my thoughts on my career significantly, but I’m currently most excited about two possible career paths
Plans A/B: Work on AI hardware in industry or a national lab, but take “tour of duty” roles such as a program manager at IARPA. Alternatively, try for a career in something like AI Hardware policy (which was recommended as perhaps the less risky route in the 80k podcast with Danny Hernandez) at a place like CSET. I’m hoping my experience with a AAAS STPF (including getting rejected) would help decide how far into policy to go.
Plan Omega: Earning to give in quantitative finance
I would love some feedback about this plan. I think one major flaw is that almost all these careers are outside my area of expertise, and I’m not sure if I’m being detailed enough about what skills I lack and how to get them (though if you take an expansive view of what AI Hardware means, I think I would be a competitive candidate at a quantum computing company right after graduation). Also, if there are any other careers that seem like I should consider, I’d love to hear it!
This is a fantastic career plan! And thank you very much for your article on being an expert in hardware, that seemed like a really useful synthesis, and I imagine will be really valuable for others considering working in this area.
I don’t have much to add because it seems like you’re thinking all this through really carefully and have done a lot of research. A few thoughts:
Application processes seem to me to have a lot of noise in them. So I wouldn’t take a single rejection from AAAS as much evidence at all about you not being suited for policy.
There are a range of other policy options you might consider for testing this route, such as the Mirzayan Fellowship, which has the benefit of being just 12 weeks. Lots more eg Tech Congress and PMF described in this document.
My impression is that it’s easier to move from more to less technical roles than the reverse, which may point in favour of working for a year or two in industry before doing years in policy (although as a counter to that, some things like PMF are only an option up to ~2 years out of your degree)
AI Impacts might be another organisation to have on your radar for maybe doing a short project with to test non-technical work.
I want to first say thanks for making this thread! This has helped me set a deadline for myself to write down my thoughts and ask for some feedback. As described below, I’d love some feedback about my career plans, and also this draft post of notes about what it could mean to be an expert in AI hardware, which I wrote up while working on these plans.
For a little background on me, I’m currently a grad student working near the area of quantum computing hardware and I’m on track to get my PhD in summer 2022. I think my strengths are laboratory work in experimental physics. I find that I enjoy leadership roles, though I find it hard to gauge if I actually am skilled at these roles. (For more background see my resume). I’m also planning to do an internship in summer 2021. I’m hoping to figure out what could be particularly good uses of my time for the internship and my first couple roles after grad school. I currently have no constraints on location.
I think I am pretty cause neutral, but given my skill set some of the areas I’ve thought about focusing on are:
AI Hardware
AI Policy
AI Technical research
Earning to give (and continuing to work on my personal cause prioritization)
Atomically Precise Manufacturing (APM)
I talked with a few people about APM. My impression is that it’s not clear if anyone should be working on actually making this technology right now. However, if one were to do this anyway, one of the most promising approaches would be essentially biology work in academia, trying to start the subfield. This made me less interested in the area, since the low expected value doesn’t seem to merit trying to start a subfield that I have no experience in.
I think I would enjoy some earning to give roles, but I view this as a solid backup option after getting a feel for the impact I can have with direct work.
I looked into AI Safety research for a little while, but it’s not clear to me that it’s my comparative advantage (as more of a lab person) compared to the other people pursuing these roles.
One idea I came across from the post “Some promising career ideas beyond 80,000 Hours’ priority paths” was AI Hardware. I think this does play more to my comparative advantage, and may let me work on the same problems. I spent some time taking notes on what it might mean to be an expert in AI Hardware, and I’m planning to make a forum post about this.
Part of the point of this comment is to welcome any and all comments on this draft post about what it means to be an expert in AI Hardware!
From this research, I’ve come up with the following plan:
Next month: Gain experience in one emerging AI Hardware platform (photonics) through an edX course recommended by someone in the field
Next summer: Expand my experience with real AI hardware doing an internship in summer 2021, prioritizing companies working on near-term hardware like Google, but any internship would be better than nothing.
Next year: Apply for the AAAS Science and Technology Policy Fellowship (for the positions starting in September 2022) to see how well suited I am to policy
These experiences will probably update my thoughts on my career significantly, but I’m currently most excited about two possible career paths
Plans A/B: Work on AI hardware in industry or a national lab, but take “tour of duty” roles such as a program manager at IARPA. Alternatively, try for a career in something like AI Hardware policy (which was recommended as perhaps the less risky route in the 80k podcast with Danny Hernandez) at a place like CSET. I’m hoping my experience with a AAAS STPF (including getting rejected) would help decide how far into policy to go.
And some backup career paths I’m considering
Plan Z: Apply to a lot of industry jobs working on AI hardware, and re-evaluate how I will have my impact from the other suggestions in the post Some promising career ideas beyond 80,000 Hours’ priority paths
Plan Omega: Earning to give in quantitative finance
I would love some feedback about this plan. I think one major flaw is that almost all these careers are outside my area of expertise, and I’m not sure if I’m being detailed enough about what skills I lack and how to get them (though if you take an expansive view of what AI Hardware means, I think I would be a competitive candidate at a quantum computing company right after graduation). Also, if there are any other careers that seem like I should consider, I’d love to hear it!
This is a fantastic career plan! And thank you very much for your article on being an expert in hardware, that seemed like a really useful synthesis, and I imagine will be really valuable for others considering working in this area.
I don’t have much to add because it seems like you’re thinking all this through really carefully and have done a lot of research. A few thoughts:
Application processes seem to me to have a lot of noise in them. So I wouldn’t take a single rejection from AAAS as much evidence at all about you not being suited for policy.
There are a range of other policy options you might consider for testing this route, such as the Mirzayan Fellowship, which has the benefit of being just 12 weeks. Lots more eg Tech Congress and PMF described in this document.
My impression is that it’s easier to move from more to less technical roles than the reverse, which may point in favour of working for a year or two in industry before doing years in policy (although as a counter to that, some things like PMF are only an option up to ~2 years out of your degree)
AI Impacts might be another organisation to have on your radar for maybe doing a short project with to test non-technical work.