Or on the types of prioritization, their strengths, pitfalls, and how EA should balance them
The cause prioritization landscape in EA is changing. Prominent groups have shut down, others have been founded, and everyone is trying to figure out how to prepare for AI. This is the first in a series of posts examining the state of cause prioritization and proposing strategies for moving forward.
Executive Summary
* Performing prioritization work has been one of the main tasks, and arguably achievements, of EA.
* We highlight three types of prioritization: Cause Prioritization, Within-Cause (Intervention) Prioritization, and Cross-Cause (Intervention) Prioritization.
* We ask how much of EA prioritization work falls in each of these categories:
* Our estimates suggest that, for the organizations we investigated, the current split is 89% within-cause work, 2% cross-cause, and 9% cause prioritization.
* We then explore strengths and potential pitfalls of each level:
* Cause prioritization offers a big-picture view for identifying pressing problems but can fail to capture the practical nuances that often determine real-world success.
* Within-cause prioritization focuses on a narrower set of interventions with deeper more specialised analysis but risks missing higher-impact alternatives elsewhere.
* Cross-cause prioritization broadens the scope to find synergies and the potential for greater impact, yet demands complex assumptions and compromises on measurement.
* See the Summary Table below to view the considerations.
* We encourage reflection and future work on what the best ways of prioritizing are and how EA should allocate resources between the three types.
* With this in mind, we outline eight cruxes that sketch what factors could favor some types over others.
* We also suggest some potential next steps aimed at refining our approach to prioritization by exploring variance, value of information, tractability, and the
Very few of my peers are having kids. My husband and I are the youngest parents at our daycare. The next youngest parent is 3 years older than us, and his kid is a year younger than ours.
Most birth rate statistics I've seen group doctorates in with any professional degree other than a masters, so it's hard to tell what's going on outside anecdotal evidence. For example: https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-05-508.pdf
To be clear, I don't think people who don't want to have kids should have them, or that they're being "selfish" or whatever. But societies without children will literally die, so it's concerning that American society has such strong anti-natal sentiment. Especially if it's the part of American society with some of the smartest people who are more motivated by truth seeking than money.
Some of this seems to be inherent to a modern society (High birth rates in past society were because of high mortality rates, women being treated as baby factories, etc.), but in my own experience the reason the birth rate is so low is that people simply can't afford to have children.
In Japan and South Korea, the "salaryman culture" is such that employees are expected to devote their entire lives to their employers, to the extent of sleeping in the office at times. Needless to say, this makes it extremely difficult to have a relationship.
In short, wealth inequality and a society that's entirely focused on the generation of profit will both cause catastrophically low birth rates. I may be biased here, but then again it's exactly these situations that convinced me that our current economic system has outlived its usefulness.
One (probably awful) idea I've been playing around with is scaling up parenting.
Say, find some good people (maybe couples) who care about education and love raising kids, and fund them to raise a lot of kids with strong genetic potential.
There may be ways to raise them to be great people (e.g. this Future Perfect piece) and with devoted parenting it might be possible to raise them to be "expert do-gooders" (thinking of the Polgar sisters).
I had a great time at EAG! The organizers kicked ass, I'm sure it was a ton of work and I was really impressed by the entire thing. Here are some quick ideas on how to make upcoming EAGs even better: