I work at 80,000 Hours, managing the "one-on-one" team that has conversations with people about their social impact and career, and also the job board.
Yep, the recommended orgs list on the 80,000 Hours Job Board (and the job board itself) is certainly not aiming to be comprehensive.
Thanks for writing up this post. I'm excited to see more software engineers and other folks with tech backgrounds moving into impactful roles.
Part of my role involves leading the 80,000 Hours Job Board. In case it's helpful I wanted to mention that I don't think of all of the roles on the job board as being directly impactful. Several tech roles are listed there primarily for career capital reasons, such as roles working on AI capabilities and cybersecurity. I'm keen for people to take these "career capital" roles so that in the future they can contribute more directly to making the development of powerful AI systems go well.
Thanks for sharing this data. Would it be possible to share the wording of a sample question, e.g. for 1:1s, and how the scoring scale was introduced?
I really enjoyed this post. I personally feel as though I don't understand our users enough or have detailed enough models of how they are likely to react to our content, and so I appreciate write-ups like this.
FWIW, I found the Swapcard app to be a net improvement to my EAG experience. I found it easier to schedule meetings than my default approach of Google Sheets + Calendly links + emails. I wonder if part of it is that people seem more responsive on the app than via email? Not trying to detract from Rohin's experience. Just pipping up in case it's helpful. I also ran into a number of the issues that Rohin had, but just sighed and worked around them. Disclaimer: I work for 80,000 Hours, which is fiscally sponsored by CEA, which runs EA Global.
My wife and I are currently allocating 10% of my income to "giving later" , investing the funds 100% in stocks in the interim. We will likely make our regular donation to the donor lottery this year, which will come out of these funds. I would consider giving more to the donor lottery, but on first glance I am less excited about needing to put money into a DAF or equivalent if we win because it is less flexible than money in an investment account. If users have thoughts on the ideal vehicle to put "giving later" funds in, I would be interested to hear. I currently feel good about it being fairly flexible, such that it could be spend on things that are not charities or 501c3s. I am currently keeping it in a fairly standard investment account.
Hey Jia, I haven't done many online courses, but one that I did and enjoyed was the Coursera Deep Learning course with Andrew Ng. https://www.coursera.org/specializations/deep-learningI think if you will be working on multi-agent RL and haven't played around with deep learning models, you will likely find it helpful. You code up a python model that gets increasingly complicated until it does things like attempting to identify a cat (if I'm remembering it correctly). It's fairly 'hands on' but also somewhat accessible to people without a technical background. Friends of mine starting out at both CSET and OpenAI worked through it and found it helpful to get context as they moved into their new roles.
This post is extremely helpful, and I have referred to it multiple times as I plan my finances. Thanks again for putting it together.
The importance of this and related topics is premised on humanity's ability to achieve interstellar travel and settle other solar systems. Nick Beckstead did a shallow investigation into this question back in 2014, which didn't find any knockdown arguments against. Posting this here mainly as I haven't seen some of these arguments discussed in the wider community much.
[Spitballing] I'm wondering if Angry Birds has just not been attempted by a major labs with sufficient compute resources? If you trained an agent like Agent57 or MuZero on Angry Birds then I am curious as to whether the agent would outperform humans?