Tom Ash was invited to write this post in the 'Where I'm giving and why' series as the Centre for Effective Altruism's Director of Operations; he's since moved to Charity Science, and runs the Effective Altruism Hub.

It’s difficult to pick between the top charities recommended by GiveWell and Giving What We Can, because neither group currently ranks their recommendations, and I certainly know less about the choice than their researchers do. However, it seems likely that one charity is (in expectation) better than the rest, and that the extra good done by my donating to it rather than the alternatives will be truly important - an extra life saved, or a huge difference to the recipients’ welfare. Just as the enormity of the good I could do moved me to pledge to donate 10% of my income, so it calls for putting real effort into picking the best charity - something I haven’t done enough in previous years.

This makes it a shame that GiveWell don’t pick out the charity that they think does most good, radically uncertain though this choice would be. However, it’s a choice that’s forced on their staff when they make their individual donations, and fortunately GiveWell have published where these go. A clear majority donate to GiveDirectly, and this carries great weight, as I trust GiveWell researchers’ ability to pick charities far more than I do my own. So GiveDirectly is a strong candidate. It has many qualities I value highly: straightforward counterfactual impact; an RCT demonstrating significant improvements in the lives of its beneficiaries; and a simple and clear model for doing good, without too many speculative or poorly-evidenced steps.

However, it has these qualities at the cost of doing slightly less good than some other candidates for my donations, at least on certain expected value calculations. I’m conscious of the weaknesses of these calculations, but in the case of the Against Malaria Foundation in particular they provide a persuasive case in favour of its doing more good than GiveDirectly. If they’re even roughly correct, I’d save several lives if I donated £5,000 to AMF this year. That’s an awe-inspiring ability to have, and seems better than sending that money to the poor households to which GiveDirectly would grant it, despite the enormous difference I know that would make.

So my current top choice would be AMF. As many readers will know, GiveWell recently ceased recommending it on the grounds that it currently lacks room for more funding, not having arranged enough bednet distributions to use up its substantial reserves. But this concern may be addressed within three or perhaps six months, as large distributions are currently being negotiated; Giving What We Can continues to recommend AMF for this very reason. Given this, I plan to give to AMF if it gains clear room for more funding over the next six months, and otherwise seriously consider donating to GiveDirectly.

This is a provisional choice, as I’m constantly learning and thinking about where my donations can do the most good. (For example, I’m open to the argument that I could help people more through indirect means; I’m currently talking to GiveWell about the possibility of donating to them, as this might ultimately cause larger donations to first-order charities than my own.)  I’d love to hear readers’ comments on my reasoning, as if there’s a better giving opportunity I’d very much want to know about it!

Comments5


Sorted by Click to highlight new comments since:

It's always hard to make such choices, especially in the face of so much uncertainty.

You wrote "If they’re even roughly correct, I’d save several lives if I donated £5,000 to AMF this year. That’s an awe-inspiring ability to have, and seems better than sending that money to the poor households to which GiveDirectly would grant it." I would just point out that bed nets have a good probability of "saving lives," but there's a difference between hypothetical probability and the actual benefits of the bed nets funded by your donation. It's entirely possible, for example, that you could fund thousands of bed nets every year for 5 or 10 years and never save a life: it depends on how many people would have contracted malaria without the nets you funded and out of that number how many of them would have died from the disease. There's a strong probability that you would save some lives, but it's far from certain. According to WHO there were 207 million cases of malaria in 2012, but only 627,000 people (mostly children) died of the disease. I prefer to think that my donations to AMF are sparing some people the misery of malaria, but I doubt I've personally saved any lives.

In contrast, with GiveDirectly you know that your donation is going to benefit the poorest households in some way. Many of those households put the money toward a metal roof, which provides long-term cash-flow benefits (and incidentally also helps reduce malaria risk, since mosquitoes can easily get through thatch roofs). Thatch roofs are expensive and time-consuming to maintain; only certain types of grasses are used for thatch and villagers in Kenya usually have to purchase thatch each year; it's not like they can just go out in the fields and gather it themselves. Many GiveDirectly recipients also buy cows, which also provide a source of income. And overall, there's more data on the benefits of direct cash handouts than there is on any other kind of development intervention.

That said, I'm still giving to AMF, not so much because I believe I'm saving lives but because AMF is such a strong role model for other charities to follow in terms of transparency and accountability.

"there's a difference between hypothetical probability and the actual benefits of the specific bed nets in the specific locations that are funded by your donation."

I don't think there really is, from a decision standpoint. According to previous statistics from Givewell, $2,500 is approximately what is needed to save a life via malaria nets (this figure is now outdated. Now it seems very different, but I think that Tom made the claim from when that was the case).

If this is true, than $5,000 would, on average, save 2 statistical lives.

Yes, it is possible that it wouldn't save anyone. But it's also possible it would save more than 2. Future unpredictable outcomes don't matter for decision making outside their probabilities at the time.

It's possible that any intervention wouldn't help anyone, even the GiveDirectly donations (though it is quite unlikely). That said, when making decisions it really seems like it's best to go on the best estimates, especially if benefits scale linearly (which they should do at this level of spending).

That said, I would definitely agree that the other benefits of giving to AMF are quite considerable and may be greater than the 'saving a life' part. 'Saving a life' in itself is a pretty poor metric for many reasons.

* I may be misunderstanding what you said, but to me it sounded as an argument of 'we can't make decisions on things we can't know for sure, because what if X happens?' This kind of argument is incredibly common and incredibly frustrating. Douglas Hubbard wrote a nice summary of this argument coming from who are supposed to be 'risk managers' in his book 'The Failure of Risk Management' here: http://www.amazon.com/Failure-Risk-Management-Why-Broken-ebook/dp/B0026LTMAU/ref=la_B001JSJHIS_1_2?s=books&ie=UTF8&qid=1390915736&sr=1-2

Oh, no, I'm definitely not making that argument. Most decisions have to be made in the face of some uncertainty (uncertainty is a key element of risk: without uncertainty there is no risk and thus no decision to make). I was arguing that we shouldn't jump to the comfortable conclusion that we've saved lives by giving to organisation X based on some statistical probability. And if you evaluate both of your charity choices with that caveat in mind, the differences might be less clear.

Effective altruism focuses on doing the most good with your donation, but there can be a disconnect between the most hypothetical good and the most actual good that gets done with your donation in the end. I don't think this should affect decision making, but I do think it should affect our confidence in how much good we may actually have done. Tom wrote in his post "If they’re even roughly correct, I’d save several lives if I donated £5,000 to AMF this year." I was just pointing out that it would be more accurate to say "I might save several lives" or "there's a strong statistical probability that I could save several lives" rather than "I would save several lives," because that sense of certainty seemed to play a role in his decision.

You're right, I didn't actually mean that I'd certainly save several lives, in the same way that I would if I funded 2 life-saving operations which wouldn't otherwise have happened. Instead I meant that I'd save several lives in expectation - i.e. that part of the expected value of my donation is the saving of those lives. I didn't spell that out to avoid being too verbose. (And you're right that this these lives saved are only part of the value of donations to AMF - as you say, they also spare large numbers of people the miseries of malaria, whether or not they would have died without bednets.)

I think we're all basically agreeing with each other here now. Language is indeed a difficult tool.

Curated and popular this week
 ·  · 5m read
 · 
This work has come out of my Undergraduate dissertation. I haven't shared or discussed these results much before putting this up.  Message me if you'd like the code :) Edit: 16th April. After helpful comments, especially from Geoffrey, I now believe this method only identifies shifts in the happiness scale (not stretches). Have edited to make this clearer. TLDR * Life satisfaction (LS) appears flat over time, despite massive economic growth — the “Easterlin Paradox.” * Some argue that happiness is rising, but we’re reporting it more conservatively — a phenomenon called rescaling. * I test rescaling using long-run German panel data, looking at whether the association between reported happiness and three “get-me-out-of-here” actions (divorce, job resignation, and hospitalisation) changes over time. * If people are getting happier (and rescaling is occuring) the probability of these actions should become less linked to reported LS — but they don’t. * I find little evidence of rescaling. We should probably take self-reported happiness scores at face value. 1. Background: The Happiness Paradox Humans today live longer, richer, and healthier lives in history — yet we seem no seem for it. Self-reported life satisfaction (LS), usually measured on a 0–10 scale, has remained remarkably flatover the last few decades, even in countries like Germany, the UK, China, and India that have experienced huge GDP growth. As Michael Plant has written, the empirical evidence for this is fairly strong. This is the Easterlin Paradox. It is a paradox, because at a point in time, income is strongly linked to happiness, as I've written on the forum before. This should feel uncomfortable for anyone who believes that economic progress should make lives better — including (me) and others in the EA/Progress Studies worlds. Assuming agree on the empirical facts (i.e., self-reported happiness isn't increasing), there are a few potential explanations: * Hedonic adaptation: as life gets
 ·  · 38m read
 · 
In recent months, the CEOs of leading AI companies have grown increasingly confident about rapid progress: * OpenAI's Sam Altman: Shifted from saying in November "the rate of progress continues" to declaring in January "we are now confident we know how to build AGI" * Anthropic's Dario Amodei: Stated in January "I'm more confident than I've ever been that we're close to powerful capabilities... in the next 2-3 years" * Google DeepMind's Demis Hassabis: Changed from "as soon as 10 years" in autumn to "probably three to five years away" by January. What explains the shift? Is it just hype? Or could we really have Artificial General Intelligence (AGI)[1] by 2028? In this article, I look at what's driven recent progress, estimate how far those drivers can continue, and explain why they're likely to continue for at least four more years. In particular, while in 2024 progress in LLM chatbots seemed to slow, a new approach started to work: teaching the models to reason using reinforcement learning. In just a year, this let them surpass human PhDs at answering difficult scientific reasoning questions, and achieve expert-level performance on one-hour coding tasks. We don't know how capable AGI will become, but extrapolating the recent rate of progress suggests that, by 2028, we could reach AI models with beyond-human reasoning abilities, expert-level knowledge in every domain, and that can autonomously complete multi-week projects, and progress would likely continue from there.  On this set of software engineering & computer use tasks, in 2020 AI was only able to do tasks that would typically take a human expert a couple of seconds. By 2024, that had risen to almost an hour. If the trend continues, by 2028 it'll reach several weeks.  No longer mere chatbots, these 'agent' models might soon satisfy many people's definitions of AGI — roughly, AI systems that match human performance at most knowledge work (see definition in footnote). This means that, while the compa
 ·  · 4m read
 · 
SUMMARY:  ALLFED is launching an emergency appeal on the EA Forum due to a serious funding shortfall. Without new support, ALLFED will be forced to cut half our budget in the coming months, drastically reducing our capacity to help build global food system resilience for catastrophic scenarios like nuclear winter, a severe pandemic, or infrastructure breakdown. ALLFED is seeking $800,000 over the course of 2025 to sustain its team, continue policy-relevant research, and move forward with pilot projects that could save lives in a catastrophe. As funding priorities shift toward AI safety, we believe resilient food solutions remain a highly cost-effective way to protect the future. If you’re able to support or share this appeal, please visit allfed.info/donate. Donate to ALLFED FULL ARTICLE: I (David Denkenberger) am writing alongside two of my team-mates, as ALLFED’s co-founder, to ask for your support. This is the first time in Alliance to Feed the Earth in Disaster’s (ALLFED’s) 8 year existence that we have reached out on the EA Forum with a direct funding appeal outside of Marginal Funding Week/our annual updates. I am doing so because ALLFED’s funding situation is serious, and because so much of ALLFED’s progress to date has been made possible through the support, feedback, and collaboration of the EA community.  Read our funding appeal At ALLFED, we are deeply grateful to all our supporters, including the Survival and Flourishing Fund, which has provided the majority of our funding for years. At the end of 2024, we learned we would be receiving far less support than expected due to a shift in SFF’s strategic priorities toward AI safety. Without additional funding, ALLFED will need to shrink. I believe the marginal cost effectiveness for improving the future and saving lives of resilience is competitive with AI Safety, even if timelines are short, because of potential AI-induced catastrophes. That is why we are asking people to donate to this emergency appeal