Quick takes

I'm currently facing a career choice between a role working on AI safety directly and a role at 80,000 Hours. I don't want to go into the details too much publicly, but one really key component is how to think about the basic leverage argument in favour of 80k. This is the claim that's like: well, in fact I heard about the AIS job from 80k. If I ensure even two (additional) people hear about AIS jobs by working at 80k, isn't it possible going to 80k could be even better for AIS than doing the job could be? In that form, the argument is naive and implausible. But I don't think I know what the "sophisticated" argument that replaces it is. Here are some thoughts: * Working in AIS also promotes growth of AIS. It would be a mistake to only consider the second-order effects of a job when you're forced to by the lack of first-order effects. * OK, but focusing on org growth fulltime seems surely better for org growth than having it be a side effect of the main thing you're doing. * One way to think about this is to compare two strategies of improving talent at a target org, between "try to find people to move them into roles in the org, as part of cultivating a whole overall talent pipeline into the org and related orgs", and "put all of your fulltime effort into having a single person, i.e. you, do a job at the org". It seems pretty easy to imagine that the former would be a better strategy? * I think this is the same intuition that makes pyramid schemes seem appealing (something like: surely I can recruit at least 2 people into the scheme, and surely they can recruit more people, and surely the norm is actually that you recruit a tonne of people" and it's really only by looking at the mathematics of the population as a whole you can see that it can't possibly work, and that actually it's necessarily the case that most people in the scheme will recruit exactly zero people ever. * Maybe a pyramid scheme is the extreme of "what if literally everyone in EA work

I'm going to be leaving 80,000 Hours and joining Charity Entrepreneurship's incubator programme this summer! The summer 2023 incubator round is focused on biosecurity and scalable global health charities and I'm really excited to see what's the best fit for me and hopefully launch a new charity. The ideas that the research team have written up look really exciting and I'm trepidatious about the challenge of being a founder but psyched for getting started. Watch this space! <3 I've been at 80,000 Hours for the last 3 years. I'm very proud of the 800+ advising calls I did and feel very privileged I got to talk to so many people and try and help them along their careers! I've learned so much during my time at 80k. And the team at 80k has been wonderful to work with - so thoughtful, committed to working out what is the right thing to do, kind, and fun - I'll for sure be sad to leave them. There are a few main reasons why I'm leaving now: 1. New career challenge - I want to try out something that stretches my skills beyond what I've done before. I think I could be a good fit for being a founder and running something big and complicated and valuable that wouldn't exist without me - I'd like to give it a try sooner rather than later. 2. Post-EA crises stepping away from EA community building a bit - Events over the last few months in EA made me re-evaluate how valuable I think the EA community and EA community building are as well as re-evaluate my personal relationship with EA. I haven't gone to the last few EAGs and switched my work away from doing advising calls for the last few months, while processing all this. I have been somewhat sad that there hasn't been more discussion and changes by now though I have been glad to see more EA leaders share things more recently (e.g. this from Ben Todd). I do still believe there are some really important ideas that EA prioritises but I'm more circumspect about some of the things I think we're not doing as well as we could (

GET AMBITIOUS SLOWLY Most approaches to increasing agency and ambition focus on telling people to dream big and not be intimidated by large projects. I'm sure that works for some people, but it feels really flat for me, and I consider myself one of the lucky ones. The worst case scenario is big inspiring  speeches get you really pumped up to Solve Big Problems but you lack the tools to meaningfully follow up.  Faced with big dreams but unclear ability to enact them, people have a few options.  *  try anyway and fail badly, probably too badly for it to even be an educational failure.  * fake it, probably without knowing they're doing so * learned helplessness, possible systemic depression * be heading towards failure, but too many people are counting on you so someone steps in and rescue you. They consider this net negative and prefer the world where you'd never started to the one where they had to rescue you.  * discover more skills than they knew. feel great, accomplish great things, learn a lot.  The first three are all very costly, especially if you repeat the cycle a few times. My preferred version is ambition snowball or "get ambitious slowly". Pick something big enough to feel challenging but not much more, accomplish it, and then use the skills and confidence you learn to tackle a marginally bigger challenge. This takes longer than immediately going for the brass ring and succeeding on the first try, but I claim it is ultimately faster and has higher EV than repeated failures. I claim EA's emphasis on doing The Most Important Thing pushed people into premature ambition and everyone is poorer for it. Certainly I would have been better off hearing this 10 years ago  What size of challenge is the right size? I've thought about this a lot and don't have a great answer. You can see how things feel in your gut, or compare to past projects. My few rules: * stick to problems where failure will at least be informative. If you can't track reality well eno

USA has ~85k annual mowing injury ER visits: https://pubmed.ncbi.nlm.nih.gov/29395756/ ~44% of which are fractures and amputation: https://pubmed.ncbi.nlm.nih.gov/30067452/ Lawncare's also ~5% of USA pollution: https://www.bloomberg.com/opinion/articles/2021-05-21/lawn-mowers-are-the-next-electric-frontier https://www.epa.gov/sites/default/files/2015-09/documents/banks.pdf Autonomous mowing robots eliminate most of mowing's danger, pollution, labor cost/time, and noise

I often return to this bit of 80000 Hours' anonymous career advice, about how when you're great at your job, no one's advice is that useful. I like it a lot. It reminds me of Agnes Callard's observation about a young writer asking Margaret Atwood for advice and getting only the trite advice to "write every day":

At this point, we need an 80k page on "What to do after leaving Open AI" 1. Don't start another AI safety lab

EA hiring gets a lot of criticism. But I think there are aspects at which it does unusually well. One thing I like is that hiring and holding jobs feels way more collaborative between boss and employee. I'm much more likely to feel like a hiring manager wants to give me honest information and make the best decision, whether or not that's with them.Relative to the rest of the world they're much less likely to take investigating other options personally. Work trials and even trial tasks have a high time cost, and are disruptive to people with normal amounts of free time and work constraints (e.g. not having a boss who wants you to trial with other orgs because they personally care about you doing the best thing, whether or not it's with them). But trials are so much more informative than interviews, I can't imagine hiring for or accepting a long-term job without one.  Trials are most useful when you have the least information about someone, so I expect removing them to lead to more inner-ring dynamics and less hiring of unconnected people. EA also has an admirable norm of paying for trials, which no one does for interviews. 

Reflection on my time as a Visiting Fellow at Rethink Priorities this summer I was a Visiting Fellow at Rethink Priorities this summer. They’re hiring right now, and I have lots of thoughts on my time there, so I figured that I’d share some. I had some misconceptions coming in, and I think I would have benefited from a post like this, so I’m guessing other people might, too. Unfortunately, I don’t have time to write anything in depth for now, so a shortform will have to do. Fair warning: this shortform is quite personal and one-sided. In particular, when I tried to think of downsides to highlight to make this post fair, few came to mind, so the post is very upsides-heavy. (Linch’s recent post has a lot more on possible negatives about working at RP.) Another disclaimer: I changed in various ways during the summer, including in terms of my preferences and priorities. I think this is good, but there’s also a good chance of some bias (I’m happy with how working at RP went because working at RP transformed me into the kind of person who’s happy with that sort of work, etc.). (See additional disclaimer at the bottom.) First, some vague background on me, in case it’s relevant: * I finished my BA this May with a double major in mathematics and comparative literature. * I had done some undergraduate math research, had taught in a variety of contexts, and had worked at Canada/USA Mathcamp, but did not have a lot of proper non-Academia work experience. * I was introduced to EA in 2019. Working at RP was not what I had expected (it seems likely that my expectations were skewed). One example of this was how my supervisor (Linch) held me accountable. Accountability existed in such a way that helped me focus on goals (“milestones”) rather than making me feel guilty about falling behind. (Perhaps I had read too much about bad workplaces and poor incentive structures, but I was quite surprised and extremely happy about this fact.) This was a really helpful transition for m