Simultaneous Shortage and Oversupply

post by Jeff_Kaufman · 2019-01-26T19:35:24.383Z · score: 40 (24 votes) · EA · GW · 10 comments

Here are two things I wouldn't expect to be true at the same time:

As far as I can tell, though, these really are both true! For example I ran a small email survey (n=40, mostly engineers) and found 30% of were interested in switching to something more valuable, and 40% were potentially interested. And there are a bunch of openings:

So, why don't these openings get filled quickly? Some guesses:

What's going on? I'm especially interested in comments from programmers who would like to be doing direct work but are instead earning to give, but any speculation is welcome!

Thanks to Catherine Olsson for discussion that led to this post and reading a draft. Cross-posted from jefftk.com.

10 comments

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comment by deluks917 · 2019-01-26T20:46:45.420Z · score: 18 (7 votes) · EA · GW

At least some people at OpenAI are making a ton of money: https://www.nytimes.com/2018/04/19/technology/artificial-intelligence-salaries-openai.html /. Of course not everyone is making that much but I doubt salaries at OpenAI/DeepMind are low. I think the obvious explanation is the best one. These companies want to hire top talent. Top talent is hard to find.

The situation is different for organizations that cannot afford high salaries. Let me link to Nate's explanation from three years ago:

I want to push back a bit against point #1 ("Let's divide problems into 'funding constrained' and 'talent constrained'.) In my experience recruiting for MIRI, these constraints are tightly intertwined. To hire talent, you need money (and to get money, you often need results, which requires talent). I think the "are they funding constrained or talent constrained?" model is incorrect, and potentially harmful. In the case of MIRI, imagine we're trying to hire a world-class researcher for $50k/year, and can't find one. Are we talent constrained, or funding constrained? (Our actual researcher salaries are higher than this, but they weren't last year, and they still aren't anywhere near competitive with industry rates.)
Furthermore, there are all sorts of things I could be doing to loosen the talent bottleneck, but only if I knew the money was going to be there. I could be setting up a researcher stewardship program, having seminars run at Berkeley and Stanford, and hiring dedicated recruiting-focused researchers who know the technical work very well and spend a lot of time practicing getting people excited -- but I can only do this if I know we're going to have the money to sustain that program alongside our core research team, and if I know we're going to have the money to make hires. If we reliably bring in only enough funding to sustain modest growth, I'm going to have a very hard time breaking the talent constraint.
And that's ignoring the opportunity costs of being under-funded, which I think are substantial. For example, at MIRI there are numerous additional programs we could be setting up, such as a visiting professor + postdoc program, or a separate team that is dedicated to working closely with all the major industry leaders, or a dedicated team that's taking a different research approach, or any number of other projects that I'd be able to start if I knew the funding would appear. All those things would lead to new and different job openings, letting us draw from a wider pool of talented people (rather than the hyper-narrow pool we currently draw from), and so this too would loosen the talent constraint -- but again, only if the funding was there. Right now, we have more trouble finding top-notch math talent excited about our approach to technical AI alignment problems than we have raising money, but don't let this fool you -- the talent constraint would be much, much easier to address with more money, and there are many things we aren't doing (for lack of funding) that I think would be high impact.

source: https://forum.effectivealtruism.org/posts/k6bBgWFdHH5hgt9RF/peter-hurford-thinks-that-a-large-proportion-of-people#DvKfX3iN5Z8kuaFs7

comment by Davidmanheim · 2019-02-04T10:21:18.798Z · score: 3 (2 votes) · EA · GW

I don't think this is quite right. The people working at OpenAI are paid well, but at the same time they are taking huge cuts in salary compared to where they could be working otherwise. (Goodfellow and Sutskever could be making millions anywhere.) And given the distribution of salary, it's very likely that the majority of both OpenAI and Deepmind researchers are making under $200k - not a crazy amount for Deep Learning talent nowadays.

comment by thecommexokid · 2019-01-29T03:14:59.319Z · score: 10 (5 votes) · EA · GW

I’m not looking for an engineering role, but definitely for myself the disconnect between what I am looking for and what EA-adjacent opportunities I find advertised is 100% location. I live in a particular city and I am not in a position to move in the short term, and as that city is not the Bay, NYC, or Oxford, it’s hard to find any useful postings or even guidance from the online EA community. I’d love for 80,000 Hours to have any advice whatsoever tailored to someone constrained to job-searching only within their own city, but so far I haven’t come across any.

comment by Michelle_Hutchinson · 2019-02-03T20:33:38.415Z · score: 4 (2 votes) · EA · GW

In case you haven't come across it yet, the 80,000 Hours job board has a filter for jobs which can be done remotely, which you might find useful.

comment by Ozzie Gooen (oagr) · 2019-02-18T19:45:23.984Z · score: 9 (4 votes) · EA · GW

I wrote this post recently:

https://www.lesswrong.com/posts/3u8oZEEayqqjjZ7Nw/current-ai-safety-roles-for-software-engineers

Generally, I feel like there are actually pretty few regular engineering positions around for EAs (Maybe 8-15), and these both have fairly high bars and require work in the US/UK.

Small orgs have different needs to large ones, and most of the EA groups are small. This in part means they want senior and/or entrepreneurial types.

I do suggest that programmers learn ML or intensely learn Functional programming, though not that many available people seem interested in either (especially those who are doing E2G outside of EA jobs.) Either would be a significant challenge, for one thing.

comment by richard_ngo · 2019-01-27T15:37:29.219Z · score: 9 (4 votes) · EA · GW

The OpenAI and DeepMind posts you linked aren't necessarily relevant, e.g. the Software Engineer, Science role is not for DeepMind's safety team, and it's pretty unclear to me whether the OpenAI ML engineer role is safety-relevant.

comment by Jeff_Kaufman · 2019-01-28T00:55:23.266Z · score: 9 (5 votes) · EA · GW

My model is that if you want to move from generic software engineering to safety work that these would be very good next steps.

comment by richard_ngo · 2019-02-01T13:20:28.282Z · score: 2 (2 votes) · EA · GW

This seems plausible, but also quite distinct from the claim that "roles for programmers in direct work tend to sit open for a long time", which I took the list of openings to be supporting evidence for.

comment by Ben Pace · 2019-01-29T07:52:49.329Z · score: 4 (3 votes) · EA · GW

Conceptually related: SSC on Joint Over- and Underdiagnosis.

comment by Andy_Schultz · 2019-02-06T01:57:29.366Z · score: 1 (1 votes) · EA · GW

There was another discussion about this on the forum a couple of years ago: https://forum.effectivealtruism.org/posts/Ebjm8rNFP4mGEjtFD/is-the-community-short-of-software-engineers-after-all