Adding some more data from my own experience last year.
Personally, I’m glad about some aspects of it and struggled with others, and there are some things I wish I had done differently, at least in hindsight. But here I just mean to quickly provide data I have collected anyway in a ‘neutral’ way, without implying anything about any particular application.
Total time I spent on ‘career change’ in 2018: at least 220h, of which at least about 101h were for specific applications. (The rest were things like: researching job and PhD opportunities; interviewing people about their jobs and PhD programs; asking people I’ve worked with for input and feedback; reflection before I decided in January to quit my previous job at the EA Foundation by April.) This does neither include 1 week I spent in in San Francisco to attend EAG SF and during which I was able to do little other work nor 250h of self-study that seems robustly useful but which I might not have done otherwise. (Nor 6 full weeks plus about 20h afterwards I spent doing an internship at an EA org, which overall I’m glad I did but might not have done otherwise.)
Open Phil Research Analyst—rejected after conversation notes test − 16h [edit: worth noting that they offered compensation for the time spent on the trial task]
OpenAI Fellows program—after more than 6 months got a rejection email encouraging me to apply again within the next 12 months − 5h [plus 175h studying machine learning including 46h on a project I tried to do specifically for that application—I count none of this as application cost because I think it was quite robustly useful]
BERI project manager application—rejected immediately (the email was ambiguous between a regular desk reject and them actually not hiring at all for that role for now) − 1h
Travelling to EAG SF from Germany to get advice on my career and find out about jobs - ~1 full week plus something between USD 1,000 and 5,000, which was between 10% and 50% of my liquid runway
CEA Summer Research Fellowship [NB this was a 6-week internship, not a full-time role] - got an offer and accepted − 4.5h
2nd AI safety camp (October) [NB the core of this was a 1-2 week event organized by ‘grassroots’ efforts, and nothing that comes with funding above covering expenses] - got an offer and accepted − 1.2h
FHI Research Scholars Programme—got an offer and accepted [this is what I’m doing currently] − 30h
AI Impacts researcher—withdrew my application after the 1st interview because I accepted the FHI RSP offer − 44h [NB this was because I ‘unilaterally’ spent way more time to create a work sample than anyone had asked me to do, and in a quite inefficient way; I think one could have done an application in 1-5h if one had had a shovel-ready work sample. Again I’m excluding an additional 64h of teaching myself basic data processing and visualization skills with R because I think they are robustly useful.]
[I did manual time tracking so there might be some underestimation, with the error varying a lot between applications. A systematic error is that I never logged time spent in job interviews, but this is overall negligible.]
(I feel slightly nervous about sharing this. But I think the chance that it contributes to identifying if there are valuable changes to make in the overall talent/job landscape and messaging is well worth the expected cost; and also that as someone with a fixed-term but full-time job at an EA org I’m well-positioned to take some risks.)
One thing that might be worth noting: I was only able to invest that many resources because of things like (i) having had an initial runway of more than $10,000 (a significant fraction of which I basically ‘inherited’ / was given to me for things like academic excellence that weren’t very effortful for me), (ii) having a good relationship to my sufficiently well-off parents that moving back in with them always was a safe backup option, (iii) having access to various other forms of social support (that came with real costs for several underemployed or otherwise struggling people in my network).
I do think current conditions mean that we ‘lose’ more people in less comfortable positions than we otherwise would.
+1 to noting that the current recruitment configuration strongly favors elite (& highly privileged) applicants.
Yeah, this is one reason Open Phil pays people for doing our remote work tests, so that people who don’t happen to have runway/similar can still go through our process. Possibly more EA orgs should do this if they aren’t already.
I’d like to make this into a norm, but it does also pose a barrier for funding constrained EA organizations by increasing the costs of hiring.
I think it’s fine to be a “norm, if you can afford it.”
If you can’t afford it, doesn’t that suggest that earning to give might not be such a bad choice after all?
Yes. Earning to give is a good choice and I’ve not suggested otherwise.
(Peter has been one of several people continuing to argue “earning to give is undervalued, most orgs could still do useful things with more funding”.)
Just a thank you for sharing, it can be scary to share your personal background like this but it’s extremely helpful for people looking into EA careers.
What do you mean by “lose”? If they stop applying to EA orgs, but take another reasonably impactful job, I’d see it as potentially positive—I don’t want people to spend so much time applying for EA org jobs!
I think there are at least two effects where the world loses impact: (i) People in less privileged positions not applying for EA jobs; sometimes one of these would actually have been the best candidate. (ii) More speculatively (in the sense that I can’t point to a specific example, though my prior is this effect is very likely to be non-zero), people in less privileged positions might realize that it’s not possible for them to apply for many of the roles they perceived to be described as highest-impact and this might reduce their EA motivation/dedication in general, and make them feel unwelcome in the community.
I emphatically agree that them taking another potentially impactful job is positive. In fact, as I said in another comment, I wish there was more attention on and support for identifying and promoting such jobs.
I absolutely agree that losing out on less-privileged colleagues would be a detriment to EA! I just think it would be better for those individuals and the world if they start working sooner, rather than spending months applying for jobs at EA organisations.
Something that seems to be missing from this (very valuable) conversation is that many people also spend months looking for non-EA jobs that they have a personal fit for. I’m mainly aware of people with science PhDs, either applying for industry jobs or applying for professorships. It is not uncommon for this to be a months long process with multiple 10s of applications, as being reported here for EA job searching. The case of where this goes faster in industry jobs tends to be because the applicant is well established as having a key set of skills that a company needs and/or a personal network connection with people involved in hiring at the company. Some academics get lucky just applying for a few professorships, but others apply to 50+ jobs, which easily takes 100+ hours, perhaps many more. And in both cases you spend lots of time over the preceding years learning about the job search process, how to write cover letters, teaching statements, etc.
I definitely feel some of this myself, even from being “less privileged” only in the sense that my degree is from a state university. (On most dimensions I am very privileged.)
Also I’m from the Midwest, and I feel like there’s a subtle coastal > Midwest dynamic that’s at play. (Really a subset of a larger coastal > anywhere-that-isn’t-coastal dynamic)