Wei Dai's Quick takes

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

I wanted to share a small but important challenge I've encountered as a student engaging with Effective Altruism from a lower-income country (Nigeria), and invite thoughts or suggestions from the community. Recently, I tried to make a one-time donation to one of the EA-aligned charities listed on the Giving What We Can platform. However, I discovered that I could not donate an amount less than $5. While this might seem like a minor limit for many, for someone like me — a student without a steady income or job, $5 is a significant amount. To provide some context: According to Numbeo, the average monthly income of a Nigerian worker is around $130–$150, and students often rely on even less — sometimes just $20–$50 per month for all expenses. For many students here, having $5 "lying around" isn't common at all; it could represent a week's worth of meals or transportation. I personally want to make small, one-time donations whenever I can, rather than commit to a recurring pledge like the 10% Giving What We Can pledge, which isn't feasible for me right now. I also want to encourage members of my local EA group, who are in similar financial situations, to practice giving through small but meaningful donations. In light of this, I would like to: * Recommend that Giving What We Can (and similar platforms) consider allowing smaller minimum donation amounts to make giving more accessible to students and people in lower-income countries. * Suggest that more organizations be added to the platform, to give donors a wider range of causes they can support with their small contributions. Uncertainties: * Are there alternative platforms or methods that allow very small one-time donations to EA-aligned charities? * Is there a reason behind the $5 minimum that I'm unaware of, and could it be adjusted to be more inclusive? I strongly believe that cultivating a habit of giving, even with small amounts, helps build a long-term culture of altruism — and it would