This is a special post for quick takes by Owen Cotton-Barratt. Only they can create top-level comments. Comments here also appear on the Quick Takes page and All Posts page.
Curated and popular this week
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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
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[Cross-posted from my Substack here]
If you spend time with people trying to change the world, you’ll come to an interesting conundrum: Various advocacy groups reference previous successful social movements as to why their chosen strategy is the most important one. Yet, these groups often follow wildly different strategies from each other to achieve social change. So, which one of them is right?
The answer is all of them and none of them.
This is because many people use research and historical movements to justify their pre-existing beliefs about how social change happens. Simply, you can find a case study to fit most plausible theories of how social change happens. For example, the groups might say:
* Repeated nonviolent disruption is the key to social change, citing the Freedom Riders from the civil rights Movement or Act Up! from the gay rights movement.
* Technological progress is what drives improvements in the human condition if you consider the development of the contraceptive pill funded by Katharine McCormick.
* Organising and base-building is how change happens, as inspired by Ella Baker, the NAACP or Cesar Chavez from the United Workers Movement.
* Insider advocacy is the real secret of social movements – look no further than how influential the Leadership Conference on Civil Rights was in passing the Civil Rights Acts of 1960 & 1964.
* Democratic participation is the backbone of social change – just look at how Ireland lifted a ban on abortion via a Citizen’s Assembly.
* And so on…
To paint this picture, we can see this in action below:
Source: Just Stop Oil which focuses on…civil resistance and disruption
Source: The Civic Power Fund which focuses on… local organising
What do we take away from all this? In my mind, a few key things:
1. Many different approaches have worked in changing the world so we should be humble and not assume we are doing The Most Important Thing
2. The case studies we focus on are likely confirmation bias, where
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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
It seems like "what can we actually do to make the future better (if we have a future)?" is a question that keeps on coming up for people in the debate week.
I've thought about some things related to this, and thought it might be worth pulling some of those threads together (with apologies for leaving it kind of abstract). Roughly speaking, I think that:
There are some other activities which might help make the future better without doing so much to increase the chance of having a future, e.g.:
However, these activities don't (to me) seem as high leverage for improving the future as the more mixed-purpose activities.
I think Leif Wenar's "Open Letter to Young EAs" has significant flaws, but also has a lot going for it, and I would seriously recommend people who want to think about the ideal shape of EA should read it.
I went through the letter making annotations about the bits I thought were good or bad. If you want to see my annotated version, you can do that here. If you want to be able to comment, let me know and I'll quite likely be happy to grant you permission (but didn't want to set it to "anyone with the link can comment" for fear of it getting overwhelmed).
As with ~all criticisms of EA, this open letter doesn't have any concrete description of what would be better than EA. Like just once, I would like to see a criticism say, "You shouldn't donate to GiveWell top charities, instead you should donate to X, and here is my cost-effectiveness analysis."
The only proposal I saw was (paraphrased) "EA should be about getting teenagers excited to be effectively altruistic." Ok, the movement-building arm of EA already does that. What is your proposal for what those teenagers should then actually do?
I mean it kind of has the proposal that they each need to work that out for themselves. (I think this is mistaken, and not the place I found the letter valuable.)
Most possible goals for AI systems are concerned with process as well as outcomes.
People talking about possible AI goals sometimes seem to assume something like "most goals are basically about outcomes, not how you get there". I'm not entirely sure where this idea comes from, and I think it's wrong. The space of goals which are allowed to be concerned with process is much higher-dimensional than the space of goals which are just about outcomes, so I'd expect that on most reasonable sense of "most" process can have a look-in.
What's the interaction with instrumental convergence? (I'm asking because vibe-wise it seems like instrumental convergence is associated with an assumption that goals won't be concerned with process.)
In general I strongly expect humans to try to instil goals that are concerned with process as well as outcomes. Even if that goes wrong, I mostly expect them to end up something which has incorrect preferences about process, not something that doesn't care about process.
How could you get to purely outcome-concerned goals? I basically think this should be expected just if someone makes a deliberate choice to aim for that (though that might be possible via self-modification; the set of goals that would choose to self-modify to be purely outcome-concerned may be significantly bigger than the set of purely outcome-concerned goals). Overall I think purely outcome-concerned goals (or almost purely outcome-concerned goals) are a concern, and worth further consideration, but I really don't think they should be treated as a default.
Just a prompt to say that if you've been kicking around an idea of possible relevance to the essay competition on the automation of wisdom and philosophy, now might be the moment to consider writing it up -- entries are due in three weeks.