1. Made a big google doc of ALL the things I could do. Not just a or b but literally everything I could think of (10 page google doc of thoughts and brainstorming), shared it around a bunch.
    1. Asked other people what I could do
    2. Tried to think radically more ambitiously
    3. Listed skills I thought I had and then thought of jobs that would use those
  2. Applied to 80k advising
    1. Which caused me to write up my thoughts on lost of things and answer lots of questions
    2. And I had a nice chat, which ended up leading to the job I ended up taking
  3. Talked to, on the margin, probably too many people, but SO many people
    1.  exploring new spaces (institutional decision making, distillation, etc)
    2. Asking what they thought was needed in those spaces
  4. Talked to my friends about my job search, which led to more opportunities
  5. Asked "If I was going to work in x [AI Safety, biosecurity, etc] what would I do?" and set 5 minute timers to generate ideas. (Thank you to Michelle Hutchinson for this)
  6. Tried to ask a variety of questions on how I might approach this search
    1. What skills do I have that are helpful for the world?
    2. What skills will I want to have in 5-10 years?
    3. What might cause me to burn out? How can I mitigate that?
    4. What are my current bottlenecks? What's stopping me?
    5. What's missing in the space? What's the low hanging fruit?
    6. How can I be ambitious?
    7. What job will give the most mentorship / the manager I work best with?
  7. Was super honest in all work trials and interviews about my level of interest and skill and what other jobs I was applying for
    1. Had conversations about why this job over that one was more impactful
  8. Used work trials to try to assess my own interest in the work (this didn't work for me, I got excited about everything)
  9. Wrote another google doc when I had honed it down to three possibilities, shared it with my friends and family, got comments, thought hard.
  10. Made the call.
  11. So far, enjoying my job!

 

Some templates you could use to think more quantitatively about your job search:

  • Lorenzo's, which I also think does a good job encouraging thinking about worst/best/moonshot scenarios
  • Nuno's, which requires having the squiggle <> google sheets download
Comments5


Sorted by Click to highlight new comments since:

Great list!

Related to 1., I personally made a Weighted Factor Model with made-up numbers and found it helpful.

(I think most numbers are wrong, and many are very wrong, but they are my current best guesses)

That's awesome!  Could you make a template of that? I did something like this to decide where to go to college.

I'm not sure what the template would look like: different people would have different columns (e.g. personal fit, location, career capital) and the numbers are pretty random.

Were you thinking of something like this? Or something fancier with z-scores?

That first thing is great! Ok for me to put it in the post? I like the push to think about worst/best/moonshot scenarios, probably lots of people should do that more.

I would be honored!

Curated and popular this week
Paul Present
 ·  · 28m read
 · 
Note: I am not a malaria expert. This is my best-faith attempt at answering a question that was bothering me, but this field is a large and complex field, and I’ve almost certainly misunderstood something somewhere along the way. Summary While the world made incredible progress in reducing malaria cases from 2000 to 2015, the past 10 years have seen malaria cases stop declining and start rising. I investigated potential reasons behind this increase through reading the existing literature and looking at publicly available data, and I identified three key factors explaining the rise: 1. Population Growth: Africa's population has increased by approximately 75% since 2000. This alone explains most of the increase in absolute case numbers, while cases per capita have remained relatively flat since 2015. 2. Stagnant Funding: After rapid growth starting in 2000, funding for malaria prevention plateaued around 2010. 3. Insecticide Resistance: Mosquitoes have become increasingly resistant to the insecticides used in bednets over the past 20 years. This has made older models of bednets less effective, although they still have some effect. Newer models of bednets developed in response to insecticide resistance are more effective but still not widely deployed.  I very crudely estimate that without any of these factors, there would be 55% fewer malaria cases in the world than what we see today. I think all three of these factors are roughly equally important in explaining the difference.  Alternative explanations like removal of PFAS, climate change, or invasive mosquito species don't appear to be major contributors.  Overall this investigation made me more convinced that bednets are an effective global health intervention.  Introduction In 2015, malaria rates were down, and EAs were celebrating. Giving What We Can posted this incredible gif showing the decrease in malaria cases across Africa since 2000: Giving What We Can said that > The reduction in malaria has be
LewisBollard
 ·  · 8m read
 · 
> How the dismal science can help us end the dismal treatment of farm animals By Martin Gould ---------------------------------------- Note: This post was crossposted from the Open Philanthropy Farm Animal Welfare Research Newsletter by the Forum team, with the author's permission. The author may not see or respond to comments on this post. ---------------------------------------- This year we’ll be sharing a few notes from my colleagues on their areas of expertise. The first is from Martin. I’ll be back next month. - Lewis In 2024, Denmark announced plans to introduce the world’s first carbon tax on cow, sheep, and pig farming. Climate advocates celebrated, but animal advocates should be much more cautious. When Denmark’s Aarhus municipality tested a similar tax in 2022, beef purchases dropped by 40% while demand for chicken and pork increased. Beef is the most emissions-intensive meat, so carbon taxes hit it hardest — and Denmark’s policies don’t even cover chicken or fish. When the price of beef rises, consumers mostly shift to other meats like chicken. And replacing beef with chicken means more animals suffer in worse conditions — about 190 chickens are needed to match the meat from one cow, and chickens are raised in much worse conditions. It may be possible to design carbon taxes which avoid this outcome; a recent paper argues that a broad carbon tax would reduce all meat production (although it omits impacts on egg or dairy production). But with cows ten times more emissions-intensive than chicken per kilogram of meat, other governments may follow Denmark’s lead — focusing taxes on the highest emitters while ignoring the welfare implications. Beef is easily the most emissions-intensive meat, but also requires the fewest animals for a given amount. The graph shows climate emissions per tonne of meat on the right-hand side, and the number of animals needed to produce a kilogram of meat on the left. The fish “lives lost” number varies significantly by