I live for a high disagree-to-upvote ratio
huw
Karma: 2,135
So for your criteria:
Locals agree that it would be a good idea
Can be done using local resources and expertise
Not currently being done locally
Not something that local governments should be doing instead
A broad class of interventions that fit this bill are entrepreneurial interventions. The goal would be to build local capacity temporarily in order to prove out the intervention in the eyes of the government (who will want to see local demand and effectiveness), and then hand it over to them. These can be locally informed or have local adaptations (satisfying (1) and (2)), but wouldn’t necessarily be currently done because they’re new ideas.
it seems that would imply that locals would do it or ask their governments to do it
I think this isn’t true for these kinds of interventions. It’s easy to imagine large gaps between ‘I think this would be a good idea’ and ‘I have the resources, funding, and willingness to do this myself’ or ‘My government will do this’. Governments in particular move slowly and often want proof that an intervention works locally before implementing it themselves.
Just on the second point—I do think it would be consistent with EA values and broadly good for EAs to normatively value government partnerships more highly. Mulago also talk a lot about finding a ‘doer at scale’, and are very excited about government in this regard.
I wonder if there are ways of evaluating the economic impact of strengthening local institutions vs trying to implement alone.
(Obviously, in many contexts, this is easier said than done—but I also see lots of EA charities operate in countries with capable governments that don’t consider government as the default long-term doer.)
(FWIW, if you pledge today, your pledger number will be in the 10,200s, as a number of pledgers have rescinded their pledge—so no fun status benefits 😛)
You might be surprised to learn that CEAs of mental health interventions in the EA space (example) don’t count the value of preventing suicide and self-harm. But on a DALY basis, self-harm and suicide have roughly the same burden in total as depression as a whole, precisely because they’re so much worse (this is to say nothing of effects on income).
I think that mental health interventions, and especially direct suicide counselling, might be really underrated, simply because the research hasn’t been done in a lot of depth (that I’m aware of). Part of this is because it’s quite hard to accurately quantify the effects of interventions on long-term suicide rates (you need many years, and access to death records). However, there are a few good studies that I think might point to ways this could at least be estimated, and then we can agree on an appropriate evidence discount.
The theory of change gets quite convoluted. For example, people may report feeling suicidal or having suicidal thoughts, but this may have no real correlation with their attempts. Or we may find that people who report feeling less suicidal commit suicide less often, but it may not be true that reducing their feelings of suicidality actually has any effect on their long-term attempt rate.
Here’s a good paper looking at 84,000 people’s PHQ-9 scores and follow-ups with suicidality. Unfortunately, the evidence isn’t causal, but this study looks at suicide prevention RCTs and finds that, at least, depression interventions reduce ideation, but not suicidality. I’ll be doing a bit more research in this area because I think it’s quite promising!
A new study in The Lancet estimates that high USAID spending saved over 91 million lives in the past 21 years, and that the cuts will kill 14 million by 2030. They estimate high USAID spending reduced all-cause mortality by 15%, and by 32% in under 5s.
How are you thinking about trade as a deterrent? The typical defence here brings up TSMC—but IMHO should also bring up Foxconn, a gigantic employer in China—and that if the Chinese consumer economy collapses, this could cause enough headaches to make an attack unreasonable.
In this case, the two main courses of action would look like:
Use policy and lobbying within the US to reduce tariffs and chip controls (neglected on the margins, ex. chip controls, but probably not broadly)
Find other means of increasing consumer spending on foreign goods within China (seems not neglected as corporations have a direct incentive to pursue it)
I haven’t used it extensively for research tasks yet, but I do really worry about that. There is something I feel viscerally when I ‘get’ a paper that often requires a deep look into the mechanics of how a study was run (i.e. reading the whole thing), that’s just not going to come from a skim-read. There’s lots of nuance in the literature my intervention is based off of, that if I didn’t understand, would lead me to inappropriately embellish my results.
I think if I was using research tools, they’d save me a lot of time in the googling phase, but then I’d still skim papers for value, and hand-read the most important ones. Anecdotally, this seems to be what most full-time researchers do.
(I also find talking confidently about the details of papers impresses people I talk to, which can be valuable in and of itself)
How robust is your assumption about the value life events staying constant? If it were not true, then there may not be any rescaling to explain. Intuitively, if wellbeing saturates at the top end, having a really positive thing happen to me genuinely might not move the needle as much. In other words, if my life is already a 9, is it realistic to expect getting married will take me to a 10—a perfect life?
HLI have a good, but very preliminary, look at the linearity/compression of wellbeing here, and it seems like linearity/compression is actually very under-studied. This seems odd to me, considering that it would probably dramatically shift where you allocate resources if linearity was true vs if there were bigger gains to be made in the middle of the spectrum.
(Apologies if you have addressed this somewhere)
All of the headlines are trying to run with the narrative that this is due to Trump pressure, but I can’t see a clear mechanism for this. Does anyone have a good read on why he’s changed his mind? (Recent events feel like: Buffet moving his money to his kids’ foundations & retiring from BH, divorce)
I liked Bob Jacob’s essay Is Effective Altruism neocolonial?.
Aid dependency is a really interesting problem, where charities can become victims of their own success. I think we should be very thoughtful about counterfactual government funding—even when, due to natural government inefficiencies, it might be less cost-effective.
One place I think EAs can do a lot of good is in charity entrepreneurship. There are often good emerging ideas that need a strong evidence base before governments will adopt them, but a shortage of ambitious people willing to take these risks. At Kaya Guides, we see our role as pioneering a novel treatment method, and then working with governments to implement. Even if we don’t do this ourselves, our counterfactual impact will always have been to create an evidence base that encourages others to do so!
Thanks for the feedback! I’m not really smart enough to figure something like that out tbh, and by the point I’d seen that my realistic options were within an order of magnitude of each other (and both high-risk with high overlap) I was pretty satisfied that my decision was likely gonna hinge on something else.
Maybe your adjustment would take it outside that range but I think at the point of extreme success these charities would be selling impact at competitive rates (so funders would be getting marginal value out of them), and more than likely going to counterfactual funders (ex. government). Maybe this is truer in GHD and especially mental health than in animal welfare, which seems more concentrated. But yeah, at this point I was pretty satisfied that Kaya Guides had minimal risk of substantial funding displacement in a success scenario (I can’t be too specific about this in public), so I picked it.
(Maybe again—I’m just highlighting my specific scenario, there’s definitely an attempt to generalise here but I didn’t think too hard through it)
No, but I think that’s reasonable in most cases (although hard to figure out exactly how to allocate it).
I didn’t. It evidently works—as do cooperatives, which I was also excited to found—but I think the big worry is up the top end. It’s very hard to imagine a FAANG company structured this way. And some of the average-case calculations above are skewed upwards by a handful of top success stories.
I looked at a handful of mental health startups to inform my guesses on impact. I looked the most deeply into BetterHelp, but you can clearly see through their numbers that their prices have almost doubled in 5 years (and steadily, too, this wasn’t a COVID thing). From the research I did, my sense was that it wasn’t getting passed back onto their counsellors, nor fuelling an increase in growth spending. There’s no way it got twice as expensive to deliver therapy.
I think if we had to point to a single mechanism, once you run out of user growth—as BetterHelp have—your investors push you to find an equilibrium price. That price is necessarily going to be higher than the price that guarantees the broadest impact, and likely to be higher than the price for the most (breadth x depth) impact.
My best guess is regional pricing can act as a crude form of means-testing, but this probably comes with a perverse incentive to ignore the cheaper regions (as BetterHelp have—almost all of their users are in the U.S.).
(All of that goes out the window if you don’t go direct to consumers—I think deeper forms of healthtech might be quite value-aligned!)
what does these numbers represent?
How much money a CE charity might be able to raise on average. (This makes the assumption that deployed cash from a charity is roughly equivalent to donated cash from Founding to Give which is what the other numbers represent).
I actually made this exact decision, just in the opposite direction! Last year, I had a pending offer from AIM’s Founding to Give programme, and another to be CTO at Kaya Guides (my current role).
Odds & magnitude of success
For AIM incubatees, using historical data, I calculated that:
30% of CE incubatees received funding from a top funder (OP or GiveWell)
About 2⁄3 of funding for CE incubatees came from OP and GiveWell, so we can multiply by 3⁄2 to get the total funding amount they would’ve received
Based on real-world grant data from OP and GiveWell, the median AIM charity could expect to receive US$1.4M in lifetime funding, the mean could get US$20M, and the top handful (i.e. a GiveWell Top Charity) could get hundreds of millions
For FTG incubatees, I borrowed from AIM’s own BOTEC, but substituted more real-world data when I had it to model distributions. This models:
The rate of incubator (ex. YC) acceptance should be about 20–60%, given that ~40% of CE charities don’t languish.
The historical odds of a YC company getting a substantial exit is about 11–16%
AIM then model out company valuations and founder shares at exit.
The median YC startup might yield about US$2M donations at exit, and the mean about US$56M
The median YC healthtech startup might yield about US$2M at exit, and the mean about US$4M. (Much less of a long tail)
A healthtech startup might also have significant positive impact through its work, so I decided to model that in too. It increased the potential value by about 5× on average.
Mutliplying through, the summary statistics I came up with for each option (in value-equivalent US dollars):
CE incubatee
p5: ~$100k
Median: ~$500K
Mean: ~$6M
p95: ~$23M
FTG incubatee
p5: ~$0 (actually negative in the model, but intuitively, many startups fail, make no money, and have no positive impact)
Median: ~$2M
Mean: ~$56M
p95: ~$11B
FTG incubatee (healthtech)
p5: ~$6M
Median: ~$14M
Mean: ~$21M
p95: ~$64M
For Kaya Guides specifically, I also added a counterfactual impact factor that bumped it up a little bit, because I think we have an unusually unique opportunity to pioneer a new intervention globally.
Here’s the notebook I used to calculate all this. Maybe I should write this up as a full post someday.
Personal fit / corporate pressure
I spoke to a great deal of people, and one thing that came up repeatedly is that if you’re in the for-profit game to have a direct impact, you should probably forget about it. Opinions differ a lot here, but I’ve seen the inside of a handful of tech companies—and many more products from the outside—and I do generally believe that at the point you’re big enough to have a significant impact, it’s quite likely that your investors will pressure you to squeeze money out of it in a way that will likely ruin said impact. This is especially true if you’re relying on some of your impact coming from donated exit money, which will, in all likelihood, reduce your control over the company.
The rest of my decision here is personal, but I’m still not fully sold on Earning to Give. I tried it earlier in my career, and I found that the toll of not doing direct work was so mentally debilitating that I wasn’t able to effectively work that hard. I think that being a highly successful startup founder is probably really hard, and I’m evidently not constitutionally motivated enough to just make money.
Conclusion
Broadly, I would see the decision like this: I think founding a startup and founding a charity have highly transferrable skillsets, but require extremely different personalities and constitutions. For me, then, this narrowed the FTG paths I would be effective at to just healthtech, which had a much lower ceiling. Frankly, my model for healthtech wasn’t meaningfully larger than my model for Kaya Guides, and at this point, I just went with my gut feeling.
(I know this comment is a bit structurally messy but I hope it elucidates something of value and provides some harder numbers to Nick’s intuitions)
The plan for FTG is to get the founders into those programmes or to good seed funding, it’s trying to fill a different niche in the market which is value-aligned co-founder matching (harder than you think!)
Per Bloomberg, the Trump administration is considering restricting the equivalency determination for 501(c)3s as early as Tuesday. The equivalency determination allows for 501(c)3s to regrant money to foreign, non-tax-exempt organisations while maintaining tax-exempt status, so long as an attorney or tax practitioner claims the organisation is equivalent to a local tax-exempt one.
I’m not an expert on this, but it sounds really bad. I guess it remains to be seen if they go through with it.
Regardless, the administration is allegedly also preparing to directly strip environmental and political (i.e. groups he doesn’t like, not necessarily just any policy org) non-profits of their tax exempt status. In the past week, he’s also floated trying to rescind the tax exempt status of Harvard. From what I understand, such an Executive Order is illegal under U.S. law (to whatever extent that matters anymore), unless Trump instructs the State Department to designate them foreign terrorist organisations, at which point all their funds are frozen too.
These are dark times. Stay safe 🖤
For you or others reading this, I can really recommend protesting if you’re not already. I also doubt it passes the ITN test (although, I wouldn’t discount it!), but it does provide (a) a good outlet for your feelings and (b) a real sense that you’re not alone, that there are people out there who are gonna fight alongside you. I come back from protests feeling a mix of emotions, but depressed and disempowered is rarely one of them.
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The Global Fund and Gilead have announced that Lenacapavir, the new 6-month PrEP treatment for HIV, will be made available in 120 countries at no profit. Gilead originally agreed to license Lenacapavir, royalty-free, to local manufacturers, but have now also agreed to directly supply doses until those manufacturers reach capacity, likely for up to 2 million at-risk people. The Global Fund will direct resourcing and deliver doses.
Extremely good news, and a possible silver lining after potentially losing PEPFAR.