I’m a bit surprised that you didn’t discuss international climate finance in the neglectedness section. The OECD estimates that 21% of ~$79 billion of annual climate financing for developing countries goes to adaptation.
I’m not sure the economic losers point is a strong one. It seems to model economic opportunities in an area as fixed, such that someone gets pushed down a rung to worse opportunity when someone else (in this case, someone treated by deworming) enters at a higher rung. But elasticities are complex and the kings of economic opportunities available might also be changed by deworming.
I think it would be better to focus on productivity. And it seems likely that the productivity externalities of deworming, if indeed it makes treated individuals more productive, are negligible or slightly positive. I don’t see how it could make untreated individuals less productive, and therefore worse off.
You’re so productive! I’d love to read a blog post talking about how you manage multiple projects, structure your day, and organize your work.
I appreciate a lot of what’s in this post! I do think it’s the case that we as a community have only explored a fraction of the space of development initiatives. It’s really plausible to me that there are more impactful approaches or things to fund out there.
That said, I feel this swings too hard against the traditional EA approach of careful analysis and prioritization. After working in development I’m kind of allergic to calls to do things like “establish ecosystems that empower altruistic leaders at scale, and that allow those that build and those that analyze to collaborate to each other’s mutual benefit”. Many of these programs do exist. Only a few of them are impactful.
I did a quick Google search and found that something kind of like what you propose does actually exist. The Global Shapers Community has a hub in Port-Au-Prince, which “brings together exceptional Haitian youths whose mission is to shape the community to which they belong”. I found it useful as an example of what something like this would actually look like in practice. Anyone can glance over their website and form their own view on how promising they think it would be to give this organization (or something like it) $1M.
I don’t think this project, or other projects like what you discuss in the post, are un-analyzable by EA evaluators. I do think it’s likely that many of them just sound better in theory than in practice.
Yep, totally agree that this would be tricky! There’d be a lot of details to think through. I would note that Vivalt does run regressions where, e.g., the kind of organization implementing the program (government vs NGO) is included as a covariate, and the coefficient on sample size doesn’t change much (-0.011 vs −0.013 in the single linear regression; see table 7, p. 31).
On non-specific discount factors: one approach which I was interested in when doing a lot of this work was to use estimates we have of how much effect sizes shrink when more and/or larger studies are conducted.
For example, in this paper Eva Vivalt, using a sample of impact evaluations, regresses effect size on variables like number of studies and sample size. As one would expect, the larger the sample size, the smaller the estimated effect size. I always wondered if you could just use the regression coefficients she presents to estimate how much an effect size would be expected to shrink if one conducted a larger study.
I don’t think this strikes at exactly what you or HLI are trying to get at. But I do think it’s valuable to ponder how we might get at “principled” discount rates, given all we know about the validity problems these studies exhibit.
What a great post, thanks for this. Hope to see a response from GiveWell. I’m really impressed by the clarity of explanation and analysis here.
Some readers may not know that the effect of deworming has been controversial for many years. Seriously, check out this ‘anthology’ of critiques and responses from 2015 - and there’s been more written since! Tom Chivers also had a short explainer in UnHerd in 2020.
Hm, maybe. I still think there are diminishing returns—the first person I ask is more likely to provide that insight than the 10th.
Under your model, the questions I’d have are (1) whether one person’s insight is worth the time-cost to all 10 people, and (2) how do you know when to stop getting feedback, if each person you ask has a 10% chance of providing a critical insight?
For what it’s worth, Jeff Bezos dropped out of the physics major at Princeton because he felt he couldn’t compete with the top students in his class.
Death by feedback
It’s not unusual to see a small army of people thanked in the “Acknowledgements” section of a typical EA Forum post. But one should be careful not to get too much feedback. For one, the benefits of more feedback diminish quickly, while the community costs scale linearly. (You gain fewer additional insights from the fifth person who reads your draft than you do from the first, but it takes the fifth person just as long to read and comment.)
My biggest worry, though, is killing my own vision by trying to incorporate comments from too many other people. This is death by feedback. If you try to please everyone, you probably won’t please anyone.
There are lots of different ways one could write about a given topic. Imagine I’m writing an essay to convince EA Forum readers that the resplendent quetzal is really cool. There’s lots I could talk about: I could talk about its brilliant green plumage and long pretty tail; I could talk about how it’s the national animal of Guatemala, so beloved that the country’s currency is called the quetzal; or I could talk about its role in Mesoamerican mythology. Different people will have different ideas about which tack I should take. Some framings will be more effective than others. But any given framing can be killed by writing a scattered, unfocused, inconsistent essay that tries to talk about everything at once.
Sure, go ahead and get feedback from a few people to catch blunders and oversights. It’s pretty awesome that so many clever, busy people will read your Forum posts if you ask them to. But don’t Frankenstein your essay by stitching together different visions to address all concerns. It’s important to recognize that there’s not a single, ideal form a piece can approach if the author keeps gathering feedback. “Design by committee” is a perjorative phrase for a reason.
Thanks to absolutely nobody for giving feedback on this post.
Feel a bit sad reading this. I’m sorry you’ve felt alienated by EA and are unsure about how you fit in.
Re: your last sentence: you’re far from alone in feeling this way. I cannot recommend Luisa Rodriguez’s 80000 Hours article about imposter syndrome highly enough.
I don’t think super high intelligence, or Ivy league degrees, are a requirement for engaging with EA. But setting aside that question, I do think there are lots of ways to engage that aren’t, like, “do complicated AI alignment math”. Organizations need many people and skills other than researchers to run well. And I think there are many ways to express EA values outside of your career, e.g. by donating, voting for political candidates who focus on important issues, and leading by example in your personal life and relationships.
Thanks for the link. I want to emphasize that I think this is a very good paper. The intro especially is well worth reading for its description of the program and poverty trap model.
Here’s a relevant quote; the results aren’t much of an update as the absolute treatment effect in terms of per-capita consumption didn’t change between years 7 and 10.
Average household per capita consumption was $1.35 (2018 PPP) at baseline in the control group and $2.90 by year ten. [...] [The treatment group’s] per capita consumption is $0.60 per day (0.6 standard deviations) higher than the control group at both years seven and ten, and income is 0.3 standard deviations higher. This temporal pattern of growing effects followed by persistence is consistent with the alleviation of a poverty trap, what BRAC describes as the graduation of treated households. However, it is also consistent with there being persistent effects without actually getting out of a trap: the control households do become less poor over time, and the treatment households are still not very rich by the time the treatment effect stabilizes (although their average consumption is above the World Bank threshold for “moderate poverty”).
(p. 472, emphasis mine)
Note that the authors’ wording is more cautious and nuanced than the Vox article.
[Epistemic status: Writing quickly about a complicated literature—I think the direction of this critique is right but would love to discuss further in the comments!]
I know authors don’t choose their own headlines, but this one really is a ridiculous overstatement. We can’t crown something the “best” way to help extremely poor people after only comparing two interventions (graduation vs. cash). And even in a head-to-head comparison, the available evidence suggests that the characteristics and effects of graduation-style programs vary so much across contexts that we should be extremely cautious about generalizing from a study of one particular program in one particular place.
At the risk of further beating an already dead horse, I also think it’s worth re-contextualizing this article in the context of the growth vs. randomista debate (which, IMO, has not advanced much at all since Hauke and John’s post in Jan. 2020. Here again is Pritchett’s damning figure comparing the gains from a representative $1,000,000,000 investment in Graduation-type programs to the value of various national growth accelerations:
Overall I feel pretty disappointed at how un-quantitative the linked Vox article is. Sigal summarizes the results of the latest BRAC study as “study subjects enjoying higher income and consumption even a full decade later.” But this is just saying the program has AN effect. This is trivial. What matters is the size of the effect. Unfortunately, Sci-Hub hasn’t indexed the 2021 study the Vox article focuses on. But I’ve looked at the results of previous graduation studies and haven’t been blown away. Banerjee et al. (2016) report of BRAC that “seven years after the asset were first distributed, the monthly consumption of those assigned to treatment is 16 dollars–or 25%–higher [than those in the control group]”.
Of course, 16 extra dollars per month works out to $0.50 per day. I believe in diminishing returns to consumption such that an extra 50 cents per day is very meaningful if it boosts your consumption by 25%. But any claims that Graduation helps people “graduate from” or “escape” poverty assumes a low poverty line, such as the standard $1.25 per day. That is, the average very poor Graduation program participant remains very poor after participating in the program. I think it’s misleading to talk about them escaping poverty as Vox and Graduation proponents do: e.g. from the article “[BRAC] aims to “graduate” recipients out of extreme poverty.”
I’m impressed by the thoroughness of Sigal’s literature review here but still think it understates the extent to which these programs are controversial. In fact, I basically think we shouldn’t generalize at all from studies of one particular Graduation program. Some of these issues are discussed in what I think is a pretty good critical article, Kidd & Athias 2019, which I don’t see discussed in the Vox piece.
Thanks for this, Michael. It’s really valuable to have someone carefully digging into these results. After reading Stevenson and Wolfers I’d sort of dismissed the paradox. This updated me against that view and has me more worried again.
I think I have more credence on the possibility that people’s scales are shifting over time than you do. In particular, questions like the Cantril ladder asks people to think about a 10⁄10 as the “best possible life”. But with growth, it’s plausible to me that the best possible life is getting better over time. Perhaps people are interpreting that as best possible (attainable) life, rather than as the cosmically-absolute best possible life. And someone living the best possible (attainable) life in 2022 can go to space, travel the world, eat every kind of food, and access every possible entertaining movie and game ever made. None of these was possible in 1922, even for people living their best possible lives.
To account for this, people would have to be shifting their scales over time. Or, it is plausible to me that my 10⁄10 is different than my grandparents’, and in an objective sense my 10⁄10 is better than my grandparents’.
Yeah, I think this meme is both damaging and mistaken and I’m disappointed to see it crop up again here. There’s plenty of evidence against such a broad assertion.
The Precipice dedicates an entire chapter to climate change, and I have it on good authority that climate change is discussed seriously in another important, upcoming EA book
Climate change has been discussed many times on the 80,000 Hours podcast, including extensively by Will Macaskill here
EA Funds lists the Founders Pledge Climate Change Fund on their website, and that Fund has raised millions of dollars for effective climate orgs
EA analysis and funding has been instrumentable in supporting a dramatic scale-up of the Clean Air Task Force, one of the best climate organizations in the world
Thanks for this, I think it deepened my understanding of Tom’s model. It looks like a lot of work went into this post and I appreciate you taking the time to make your analysis so intelligible!
I think it’s possible there’s too much promotion on the EA Forum these days. There are lots of posts announcing new organizations, hiring rounds, events, or opportunities. These are useful but not that informative, and they take up space on the frontpage. I’d rather see more posts about research, cause prioritization, critiques and redteams, and analysis. Perhaps promotional posts should be collected into a megathread, the way we do with hiring.
In general it feels like the signal-to-noise ration on the frontpage is lower now than it was a year ago, though I could be wrong. One metric might be number of comments—right now, 5⁄12 posts I see on the frontpage have 0 comments, and 11⁄12 have 10 comments or fewer.
One thought I had while reading this was just: you run slower during a marathon, but marathons are still really hard.
Maybe this comment conflates working more than average with giving “everything … including their soul and weekends”?
It’s tricky because different people perhaps need to hear different things here. I’d like to have a culture where it’s possible for people to work normal hours in EA jobs. But I also know people who work more than average because they care deeply about their work and are ambitious, without seeming (to me at least) to be on the verge of crisis.
wars happen much more quickly now (I’m not sure why—maybe because planes are faster than walking?)
I think advances in strategy, automation, logistics, and transportation have a lot to do with this! And I do think there’s a general lesson there—everything has been speeding up, so we should generally expect collapses today to happen faster than they happened in the past.