This is an anonymous account (Ávila is not a real person). I am posting on this account to avoid potentially negative effects on my future job prospects.
SUMMARY:
- I've been rejected from 18 jobs or internships, 12 of which are "in EA."
- I briefly spell out my background information and show all my rejections.
- Then, I list some recommendations to EA orgs on how they can (hopefully) improve the hiring process.
This post probably falls under the category of "it's hard, even for high-achievers, to get an EA job." But there's still the (probably bigger) problem of what there is for "mediocre" EAs to do in a movement that prizes extremely high-achieving individuals.
If this post improves hiring a little bit at a few EA orgs, I will be a happy person.
EDIT: I want to make *very clear* that I take full responsibility for how my job search is going. Putting my experience and "recommendations to EA orgs" in the same post could be seen as me thinking that bad hiring practices are to blame. This is not at all the case. I hope this was clear before I added this paragraph in!
EDIT 2 (June 2024): Since writing this, I received ~9 more rejections and 3 acceptances (!). I'm very happy with the 3 opportunities. Thank you all for your encouragement -- and hopefully others in a similar position found this post or the replies helpful.
BACKGROUND
Entry-level EA jobs and internships have been getting very competitive. It is common for current applicants to hear things like "out of 600, we can only take 20" (CHAI), or "only 3% of applicants made it this far" (IAPS) or "It's so competitive it's probably not even worth applying" (GovAI representative). So far, I haven't been accepted to any early-career AI safety opportunities, and I've mostly been rejected in the first round.
ABOUT ME
I'll keep this section somewhat vague to protect my anonymity. I'm mostly applying to AI safety-related jobs and internships.
[EDIT: deleted this section after realizing it may have made me too identifiable.]
JOBS/INTERNSHIPS/FUNDING I'VE APPLIED TO
Rejections
Horizon Junior Fellowship - Rejected on round 3/4
GovAI summer fellowship - Rejected first round
ERA<>Krueger Lab - Rejected first round
fp21 internship - Never heard back
BERI (full-time job) - Rejected first round
MIT FutureTech (part-time) - Job filled before interview
PIBBSS Fellowship - Rejected first round
Berkeley Risk and Security Lab - Never heard back
CLR Fellowship - Rejected first round
ERA Fellowship - Rejected first round
CHAI Internship - Rejected first round
UChicago XLab - Rejected first round
EA LTFF research grant - Rejected
Open Phil research grant - Rejected
Acceptances
None yet!
Note: I've also applied to jobs that align with my principles but are not at EA orgs. I'm also still applying to jobs, so this is not (yet) a pity party.
MY EXPECTATIONS
Although I expected these to be quite competitive, I was surprised to be eliminated during the first round for so many of them. That's because most of these are specifically meant for early-career people and I'd say I have a great resume/credentials/demonstrated skills for an early career person.
RECOMMENDATIONS TO EA ORGS
As someone who's spent a lot of time doing EA org applications, below are some tentative thoughts on how to (probably) improve them. Please let me know what you think in the comments.
Again, I do not mean to imply at all that my failures were caused by bad hiring practices. These are just thoughts that came to mind after applying to many similar programs.
- Increase the required time-commitment as the application progresses.
By this I mean, start out with shorter applications and then increase the time commitment in successive application stages. If you plan to only progress 10% of applicants to the second round, wasting 90% of applicants' times on an hours-long questionnaire or work test seems like a bad policy.
- Start admissions earlier.
For whatever reason, many of these programs don't expect to finish admissions until May. At least in the US, many colleges end the academic year in May. This makes the search very stressful, hard to get done early. And also, given that these programs are so competitive, it would be good to know if one will get in early so that one can apply to more non-EA jobs otherwise. The lack of financial security and knowing where one will end up (and finding housing on very short notice) can be awful.
- Be clear on what you are looking for.
Sometimes EA Orgs will say something like “we have no degree requirements” or "when in doubt apply" but in reality will mostly hire people with PhDs. I appreciate your open-mindedness regarding degree and experience requirements, but saying something like "we expect most successful applicants to have X" or "we may consider Y in exceptional circumstances" helps applicants assess whether the opportunity is worth spending time on.
- Relatedly, show statistics for past application rounds.
A few orgs published some useful statistics on their past cohorts. I found this very helpful. E.g., "historically, around 50% of our cohort were PhD students, 20% X, ..."
- Adopt evidence-based hiring practices
This is already done by many (great!). I personally am no authority on the matter, so please add a comment below if you know more about this. I would presume that blind scoring and having >1 person score each anonymous application reduces bias and noise.
- Have paid work tests.
This is often already done, and greatly appreciated. This may allow many people to afford applying.
- Have clear citizenship requirements.
This goes for EA orgs based anywhere. Don't just ask people where they are or are not legally allowed to work and then move on with the application. TELL applicants what you need. Is X citizenship required? Can you hire people with no citizenship but permanent residence / work permits? Can you hire people with temporary work permits (e.g., OPT, STEM OPT in the US)? Can you sponsor work visas? Do you allow remote work for people not allowed to work in your country?
- Send rejection emails, don’t just not respond to an application.
Great, most already do this!
- Increase information sharing transparency.
Most EA orgs have a box you can check at the end of an application that says something like “would you like us to share your information with similar orgs that may be looking for talent?”
This sounds like a great idea, but I would like to know more details. What may you share? For example, I would say "yes" to my resume, but "no" to the results of my work tests or your evaluations. That's because I don't want one failure or mistake to cascade to every application. I would also say "yes" to sharing for up to a year, but "no" beyond that (because my experience and skills may change a lot in a year). Just one sentence to increase transparency would be great.
- (When possible) allow opt-in for short feedback on the application.
This may be the hardest one to bring about (it's time-consuming and very out-there), so I'm very uncertain about it. I think I would have personally benefitted a lot from feedback on my applications. Why was I rejected? Was it something I could change?
Especially at later stages of the application process (when there are fewer applicants), I would love to be able to opt-in to something like ~1 sentence about the biggest reason I was rejected. Even if it's hurtful.
DISCUSSION I'D LIKE TO SEE IN THE COMMENTS
> Are you also going through something similar? Feel free to share your experience.
> Do you have recommendations of your own? Please add them.
> Are you someone in charge of hiring at an EA org? I'd love to hear general advice on what you see most applicants getting wrong, or how most could improve. I'd also love to see some discussion on why some of these recommendations may be infeasible.
Final note: I decided to write this while still waiting for other applications to get back to me. That's because I thought that if I got a job I might lose the motivation to write this, and it seemed valuable. Just to be extra careful on the anonymity front, if I get one of these jobs, I will not mention it here.
As I suggested in my first comment, you could do the same "by reporting other characteristics which play no role in selection, but which are heavily over-represented in successful applicants": for example, you could report that >50% of successful applicants are male,[1] white, live in certain countries, >90% have liberal political beliefs, and probably a very disproportionately large number have read Harry Potter fan fic.[2] Presumably one could identify other traits which are associated with success via their association with these other traits e.g. if most successful applicants have PhDs and PhDs disproportionately tend to [drink red wine, ski etc.], then successful applicants may also disproportionately have these traits.
Of course, different people can disagree about whether or not each of these are causal. But even if they are predictive, I imagine that we would agree that at least one of these would likely mislead people. For example, having read Harry Potter fan fic is associated with being involved with communities interested in EA-related jobs for largely arbitrary historical reasons.[3]
This concern is particularly acute when we take into account the pragmatics of employers highlighting some specific fact.[4] People typically don't offer irrelevant information for no reason. So if orgs go out of their way to say ">50% of successful applicants have PhDs", even with the caveat about this not being causal, applicants will still reasonably wonder "Why are they telling me this?" and many will reasonably infer "What they want to convey is that this is a very competitive position and I should not apply."
As I mentioned in the footnote of my comment above, there are jobs where this would be a reasonable inference. But I think most EA jobs are not like this.
If one wanted to provide applicants with full, non-misleading information, I think you would need to distinguish which of the cases applies, and provide a full account of the association which explains why successful applicants might often have PhDs, but that this is not the case when you control for x, y, z. That way (in theory), applicants would be able to know that conditional on them being a person who meets the requirements specified in the application (e.g. they can complete the coding test task), the fact that they don't have a PhD does or does not imply anything about their chances of success. But I think that in practice, providing such an account for any given trait is either very difficult or impossible.[5]
Though in EA Survey data, there is no significant gender difference in likelihood of having an EA job. In fact, a slightly larger proportion of women tend to have EA jobs.
None of these reflect real numbers from any actual hiring rounds, though they do reflect general disparities observed in the wider community.
Of course, you could describe a situation where having read Harry Potter fan fic actually serves as a useful indicator of some relevant trait like involvement in the EA community. But, again, I'm not referring to cases like this. Even in cases where involvement in the EA community is of no relevance to the role at all (e.g. all you need to do to be hired is to perform some technical, testable skill, like coding very well), applicants are likely to be disproportionately interested in EA, and successful applicants may be yet further disproportionately interested in EA, even if it has nothing to do with selection.
This can happen if, for example, 50% of the applications are basically spam (e.g. applications from a large job site, who have barely read the job advert and don't have any relevant skills but are applying for everything they can click on). In such cases, the subset of applications who are actually vaguely relevant, will be disproportionately people with an interest in EA, people with degrees etc.
In some countries there may be a norm of releasing information about certain characteristics, in which case this consideration doesn't apply for those characteristics, but would for others.
And that is not taking into account the important question of whether all applicants would actually update on such information provided completely rationally, or would whether many would be irrationally inclined to be negative about their chances, and just conclude that they aren't good enough to apply if they don't have a PhD from a fancy institution.