Stories such as Peter Singer's "drowning child" hypothetical frequently imply that there is a major funding gap for health interventions in poor countries, such that there is a moral imperative for people in rich-countries to give a large portion of their income to charity. There are simply not enough excess deaths for these claims to be plausible.

Much of this is a restatement of part of my series on GiveWell and the problem of partial funding, so if you read that carefully and in detail, this may not be new to you, but it's important enough to have its own concise post. This post has been edited after its initial publication for clarity and tone, including a major revision on 31 January 2020.

People still make the funding gap claim

In his 1997 essay The Drowning Child and the Expanding Circle, Peter Singer laid out the basic argument for a moral obligation to give much more than most to, for the good of poor foreigners:

To challenge my students to think about the ethics of what we owe to people in need, I ask them to imagine that their route to the university takes them past a shallow pond. One morning, I say to them, you notice a child has fallen in and appears to be drowning. To wade in and pull the child out would be easy but it will mean that you get your clothes wet and muddy, and by the time you go home and change you will have missed your first class.

I then ask the students: do you have any obligation to rescue the child? Unanimously, the students say they do. The importance of saving a child so far outweighs the cost of getting one’s clothes muddy and missing a class, that they refuse to consider it any kind of excuse for not saving the child. Does it make a difference, I ask, that there are other people walking past the pond who would equally be able to rescue the child but are not doing so? No, the students reply, the fact that others are not doing what they ought to do is no reason why I should not do what I ought to do.

Once we are all clear about our obligations to rescue the drowning child in front of us, I ask: would it make any difference if the child were far away, in another country perhaps, but similarly in danger of death, and equally within your means to save, at no great cost – and absolutely no danger – to yourself? Virtually all agree that distance and nationality make no moral difference to the situation. I then point out that we are all in that situation of the person passing the shallow pond: we can all save lives of people, both children and adults, who would otherwise die, and we can do so at a very small cost to us: the cost of a new CD, a shirt or a night out at a restaurant or concert, can mean the difference between life and death to more than one person somewhere in the world – and overseas aid agencies like Oxfam overcome the problem of acting at a distance.

Singer no longer consistently endorses cost-effectiveness estimates that are so low, but still endorses the basic argument. Nor is this limited to him. As of 2019, GiveWell claims that its top charities can avert a death for a few thousand dollars, and the Center for Effective Altruism claims that someone with a typical American income can save dozens of lives over their lifetime by donating 10% of their income to the Against Malaria Foundation, which points to GiveWell's analysis for support. (This despite GiveWell's long-standing disclaimer that you shouldn't take its expected value calculations literally). The 2014 Slate Star Codex post Infinite Debt describes the Giving What We Can pledge as effectively a negotiated compromise between the perceived moral imperative to give literally everything you can to alleviate Bottomless Pits of Suffering, and the understandable desire to still have some nice things.

How many excess deaths can developing-world interventions plausibly avert?

According to the 2017 Global Burden of Disease report, around 10 million people die per year, globally, of "Communicable, maternal, neonatal, and nutritional diseases.”* This is roughly the category that the low cost-per-life-saved interventions target. If we assume that all of this is treatable at current cost per life saved numbers - the most generous possible assumption for the claim that there's a funding gap - then at $5,000 per life saved (substantially higher than GiveWell's current estimates), that would cost about $50 billion annually to avert.

This is already well within the capacity of funds available to the Gates Foundation alone, and the Open Philanthropy Project / GiveWell is the main advisor of another multi-billion-dollar foundation, Good Ventures. The true number is almost certainly much smaller because many communicable, maternal, neonatal, and nutritional diseases do not admit of the kinds of cheap mass-administered cures that justify current cost-effectiveness numbers.

If there literally were a present, rather than a future, annual funding gap of $50 billion for interventions that can save a life for $5,000, then the Gates Foundation alone could wipe out all fatalities due to communicable diseases this year, a couple times over. And infections are the major target of current mass-market donor recommendations.

Even if we assume no long-run direct effects (no reduction in infection rates the next year, no flow-through effects, the people whose lives are saved just sit around not contributing to their communities), a large funding gap implies opportunities to demonstrate impact empirically with existing funds. Take the example of malaria alone (the target of the intervention specifically mentioned by CEA in its "dozens of lives" claim). The GBD report estimates 619,800 annual deaths - a reduction by half at $5k per life saved would only cost $1.55 billion per year, an annual outlay that the Gates Foundation alone could sustain nearly indefinitely, and Good Ventures could certainly maintain for a couple of years on its own.

GiveWell's estimated cost per life saved numbers include substantial adjustments for uncertainty. (The studies supporting the intervention might be flawed in some way, the effect might not transfer into new contexts, the implementation might be screwed up somehow...) This means that if the intervention works as believed, it's almost surely substantially cheaper to save a life than the current cost per life saved numbers imply.

GiveWell's stated reason for not bothering to monitor statistical data on outcomes (such as e.g. malaria incidence and mortality, in the case of AMF) is that the data are too noisy. But such a huge, sudden reduction in deaths from some particular class of causes ought to be very noticeable and easy to verify.

What does this mean?

At current cost per life saved numbers, an annual $50 billion funding gap, or even a $3.1 billion gap for malaria, would have to imply that it's operationally possible to eliminate deaths from malaria for one year in one country at comparatively low cost relative to the endowments of existing large already-active donors. Such an experiment would quickly reveal the true cost per life saved with much more precision, and the true number would almost certainly be much lower or much higher - a very valuable experiment if there's anything else worth doing with the money.

The case for such an experiment is even stronger for interventions like deworming, where GiveWell explicitly states that most of the expected value is in the 1-2% probability tail scenario where deworming is fantastically beneficial.

Even under the interpretation where there's funding gap outside existing large donors' ability to fill it indefinitely, if Good Ventures were to fund a decisive experiment empirically demonstrating a large effect from the GiveWell top charities, this ought to make a large difference in GiveWell's ability to move money to those charities in the future, and therefore ought to make filling the next year's funding gap much more appealing to other potential donors. (And if the intervention doesn't do what we thought, then potential donors are less motivated to step in - but that's good, because it doesn't work!)

The smaller a distribution is operationally possible, the smaller the implied funding gap. For instance, if deaths from malaria could only be reduced by 10% per year at $5,000 per life saved, and this would be too small an effect to show up clearly in the noisy data available, then that implies only a $310 million annual funding gap for malaria at $5,000 per life saved, which Good Ventures alone could fund nearly indefinitely (especially since excess deaths are declining). If deaths from all communicable, maternal, neonatal, and nutritional diseases could only be reduced by 10%, that implies only a $5 billion annual funding gap for the entire range of developing-world health interventions.

If the low cost-per-life-saved numbers are meaningful and accurate, then charities like the Gates Foundation and Good Ventures are hoarding money at the price of millions of preventable deaths. If the Gates Foundation and Good Ventures are behaving properly because they know better, then the opportunity to save additional lives cheaply has been greatly exaggerated. My former employer GiveWell in particular stands out, since it publishes such cost-per-life-saved numbers, and yet recommended to Good Ventures that it not fully fund GiveWell's top charities; they were worried that Good Ventures would be saving more than their "fair share" of lives.

In either case, a source that both cared about and believed these numbers, with the resources of Good Ventures, would be well advised to prioritize experiments that revealed information about the efficacy of its interventions, over trying to move more funds. We're not getting this information from such a source.

The process that promoted these claims to your attention is more like advertising than like science or business accounting. Basic epistemic self-defense requires us to interpret them as marketing copy designed to control your behavior, not unbiased estimates designed to improve the quality of your decisionmaking process.

We should be more skeptical, not less, of vague claims by the same parties to even more spectacular returns on investment for speculative, hard to evaluate interventions, especially ones that promise to do the opposite of what the argument justifying the intervention recommends.

If you give based on mass-marketed high-cost-effectiveness representations, you're buying mass-marketed high-cost-effectiveness representations, not lives saved. Doing a little good is better than buying a symbolic representation of a large amount of good. There's no substitute for developing and acting on your own models of the world.

Summary

• Effective Altruism claims that there is a large funding gap for cheap well-understood developing-world interventions.
• Even the most aggressive plausible construal of this claim implies an annual funding gap that could be covered completely for a few years by existing major institutional donors.
• If this is true, it implies opportunities for comparatively cheap experiments (relative to the endowments of major donors in the space) with extremely high information value.
• Such experiments have not happened either because they are impossible, or because the relevant institutional donors think they have better things to do with their money.
• Neither scenario suggests that small donors should try to fill this funding gap. If they trust big donors, they should just give to the big donors. If they don't, why should they believe a story clearly meant to extract money from them?

Note that as I pointed out in my original series on GiveWell, the Open Philanthropy Project, and Good Ventures, the "returns to scale" argument applies to GiveWell / Open Philanthropy Project / Good Ventures as well.

Insofar as there's a way to fix these problems as a low-info donor, there's already enough money. The underlying information problem is much higher-leverage; what's needed is to orient ourselves in the world well enough to take unconfused prosocial action.

One good thing to spend money on is taking care of yourself and your friends and the people around you and your community and trying specific concrete things that might have specific concrete benefits. If you want to make a leveraged investment in the future, focusing on giving people slack to try to fix the underlying systems problems that got us so confused in the first place.

UPDATE 7 July 2022: A friend pointed out that this comment does a good job summarizing a core point of this post:

How many lives do you think can be saved for between $5k and $10k? The smaller the number, the more "~$5k per life saved" looks like an impact certificate you're buying from Good Ventures at a price assessed by GiveWell, rather than a serious claim that for an extra $5k you can cause a life to be saved through the intervention you funded.

The larger the number, the more the marginal cost looks like the average costs for large numbers of lives saved (and therefore the "why don't they do an experiment at scale?" argument holds).

Claims that you can make the world different in well-specified ways through giving (e.g. more lives saved by the intervention you funded) imply the latter scenario, and substantively conflict with the former one.

Do you disagree with this model? If so, how?

* A previous version of this post erroneously read a decadal rate of decline as an annual rate of decline, which implied a stronger conclusion than is warranted. Thanks to Alexander Gordon-Brown to pointing out the error.