Quick takes

As a university organizer at a very STEM focused state school, I suspect that students getting liberal arts degrees are more easily convinced to pursue a career in direct work. If this is the case, it could be because direct work compares more favorably with the other career options of those with liberal arts degrees, or because the clearer career outcomes of STEM majors create more path dependence and friction when they consider switching careers. This is potentially another thing to keep in mind when trying to compare the successes of EA uni groups.

Dwarkesh (of the famed podcast) recently posted a call for new guest scouts. Given how influential his podcast is likely to be in shaping discourse around transformative AI (among other important things), this seems worth flagging and applying for (at least, for students or early career researchers in bio, AI, history, econ, math, physics, AI that have a few extra hours a week). The role is remote, pays ~$100/hour, and expects ~5–10 hours/week. He’s looking for people who are deeply plugged into a field (e.g. grad students, postdocs, or practitioners) with high taste. Beyond scouting guests, the role also involves helping assemble curricula so he can rapidly get up to speed before interviews. More details are in the blog post; link to apply (due Jan 23 at 11:59pm PST).

Question: Should I serve on the board of a non-EA charity?  I have an opportunity through work to help guide a charity doing work on children's education and entertainment in the UK and US. It has an endowment in the tens of millions of pounds.  Has anyone else had experience serving on the board or guiding committee of a non-EA charity? Did you feel like you were able to have a positive influence? Do you have any advice?

Incidentally, ‘flipping non-EA jobs into EA jobs’ and ‘creating EA jobs’ both seem much more impactful than ‘taking EA jobs’. That could be e.g. taking an academic position that otherwise wouldn’t have been doing much and using it to do awesome research / outreach that others can build on, or starting an EA-aligned org with funding from non-EA sources, like VCs. (excerpt from https://lydianottingham.substack.com/p/a-rapid-response-to-celeste-re-e2g) 

I try to maintain this public doc of AI safety cheap tests and resources, although it's due a deep overhaul.    Suggestions and feedback welcome!

Let’s create example trial tasks to strengthen EA hiring? EA orgs use trial tasks quite a lot in hiring, which is great since candidates can demonstrate their skills, which is what truly matters regardless of their background. However, outside of EA, trial tasks are often quite different, and for the average candidate, it usually takes several rejections before they learn how to show their best in that setting. It would be great if we had example trial tasks for different roles (research, operations, etc.) so that people could practice before applying to real jobs. This way, strong candidates would not get lost in the hiring process simply due to inexperience with trial tasks.

I'd like to get feedback on the writing style of this post. I want to try to write up bi-monthly updates but don't enjoy sinking time into writing. I've never really stuck with blogging despite it being valuable for sharing what I'm working on as I'm a bit of a perfectionist. I end up spending hours combing over the posts I make. I'd like my posts to only take 30 minutes, so my current ideas are to write quickly and post as is, or to have an AI edit out my mistakes. Which of the two do you prefer? Do you have any suggestions on ways to make quick blog posts without potentially attaching poor communication or AI slop to myself? My original post. My prompt. Claude's edit of my post: ------ My Two-Month Deep Dive into AI Safety: From Imposter Syndrome to Clarity How ARBOx and ARENA helped me navigate a career transition into AI Safety—and what I learned about myself along the way Two months ago, I committed to spending my summer diving headfirst into AI Safety. As someone with a background in Swift development and traditional software engineering, the world of Transformers, Linear algebra, and AI alignment research felt like an entirely different universe. Here's what happened when I threw myself into ARBOx and ARENA—the good, the challenging, and the surprisingly clarifying moments that helped shape my career transition. Week 1-3: ARBOx in Oxford - Swimming in the Deep End ARBOx accepted me for their intensive program: one week of prerequisites, followed by two weeks of in-person training in Oxford. The reality check was swift. During pair programming sessions, I was often the weaker partner. While my colleagues brought post-grad experience with deep learning or career backgrounds in ML, I was frantically trying to remember basic PyTorch syntax. My years of Swift development, unit testing, and design patterns suddenly felt irrelevant when staring at Jupyter notebooks full of tensor operations. However, being the "slower" partner was actually incredibly v

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