GiveDirectly
Article
GiveDirectly is a recurring organization in the Astral Codex Ten archive, appearing 11 times across 11 issues between February 09, 2022 and December 10, 2025. The archive places it in contexts such as “GiveDirectly is a charity that gives your money directly to poor people in Africa”; “GiveDirectly’s 2014 unconditional cash transfer trial”; “he gave the rest to the charity GiveDirectly”. It most often appears alongside effective altruism, GiveWell, US.
Metadata
- Category: Organizations
- Mention count: 11
- Issue count: 11
- First seen: February 09, 2022
- Last seen: December 10, 2025
Appears In
- So You Want To Run A Microgrants Program
- Your Book Review: The Anti-Politics Machine
- 23
- Apply For An ACX Grant (2024)
- Highlights From The Comments On Capitalism & Charity
- Contra Stone On EA
- Open Thread 359
- Open Thread 379
- Apply For An ACX Grant (2025)
- Links For September 2025
- Links For December 2025
Related Pages
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- effective altruism (5 shared issues)
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- GiveWell (5 shared issues)
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- US (5 shared issues)
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- ACX Grants (4 shared issues)
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- Twitter (4 shared issues)
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- Africa (3 shared issues)
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- Against Malaria Foundation (3 shared issues)
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- China (3 shared issues)
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- EA (3 shared issues)
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- ACX (2 shared issues)
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- ACX (2 shared issues)
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- Asterisk (2 shared issues)
External Links
Source Context
Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.
How can big foundations be short of good opportunities when the world is so full of problems? This remains kind of mysterious to me, but my best guess is that they set some high bar, donate to everything above the bar, and keep the rest of their money in the hopes that good charities that exceed the bar spring up later - or spend the money trying to create charities that will one day exceed the bar. Global health charities sometimes set a bar of “10x more effective than GiveDirectly”, where GiveDirectly is a charity that gives your money directly to poor people in Africa; other cause areas are harder to find a bar for but maybe you can sort of eyeball it. This model suggests you should only donate your finding-good-opportunities ability if you think there’s a chance you can clear the relevant bar, but there might be pretty high value of information in seeing whether this is true.
Inline links: sometimes set
A story that plausibly explains these numbers (either a potential mechanism for an effect, or an explanation of why the effect turned out to be null) If these stories are challenged, it is not because there is no actual evidence for them, but because an economist in the audience has thought of their own preferred theory. If the speaker can find some data point that contradicts the questioner’s idea, this is thought to “confirm” the original story. Since audience members (who often have little specific knowledge of the region) are unlikely to ask questions like “what if this village just has an incredibly complicated set of social conventions around cattle that prevents their sale even without market barriers in place?” or “do the region’s economic challenges have more to do with this very specific regulation in South African immigration law?”, plausible-sounding stories that explain one or two numerical data points tend to gain traction in the literature whether or not they have anything to do with reality. Mark McGovern famously noted this trend in a review of two of Paul Collier’s books, writing: “Much of the intellectual heavy lifting in these books is in fact done at the level of implication or commonsense guessing. And the common sense is surely not that of the inhabitants of the countries being dissected, but that of the highly educated elite located primarily in Western Europe and North America. In those passages where Collier does lay out the thinking behind his explanations, they are always coherent and plausible, but the chain of causal relations makes it evident how fragile these models typically are.” The World Bank report’s fundamental misdiagnosis of the challenges Lesotho faced formed the basis for a series of failed “development initiatives”, most notably the Thaba-Tseka Development Project, a joint venture funded by the Canadian International Development Agency, the World Bank, the Government of Lesotho, and the UK Overseas Development Ministry. The project focused on providing technical solutions to the “problems” the World Bank report had identified: better agricultural techniques, easier access to markets, and increased government capacity to provide public goods. Each piece faced serious problems in execution, largely because interventions shown to have the sorts of “positive effects” randomized experiments might demonstrate elsewhere in Africa were not necessarily well suited to Lesotho’s unforgiving, mountainous terrain. But even more seriously, the project was so enveloped in “development discourse” that nobody thought to question whether they were working on problems their “recipients” cared about, or merely the ones the “tools of development” were capable of solving. As Ferguson writes, “The promise that crop farming could be revolutionized through the application of a well-known package of technical inputs was so firmly written into the project’s design that it was difficult for those on the scene to challenge it, or even to confront it.” Perhaps the only thing that has changed since Ferguson wrote is that we have tools to better identify these failures: the development literature continues to be littered with failed trials and interventions based on unchecked assumptions. One of the most famous is the British Department for International Development’s 90 million pound Tuungane project, whose Congolese incarnation sought to rebuild village governing institutions that the country’s civil war had destroyed. One of the most convincing explanations of its failure is that it may not have been necessary to begin with: the implementers do not seem to have checked whether the institutions had actually been weakened by violence, and baseline reports indicated that residents were relatively satisfied with village governance before the project even started! More research is needed to clarify the situation -- research which might have been useful to carry out before spending a £90 million on a “fix”. Part of this, perhaps, comes from the usual overconfidence that other social scientists like to accuse economists of. But there are much bigger systemic problems at play. Development work tends to run on short timelines: grad students and postdocs need to publish quickly for their careers to advance, NGO funding runs on 5-ish year cycles, and charities (particularly in “high-risk” areas) face extremely high employee turnover rates. This simultaneously limits the accumulation of institutional knowledge, while incentivizing practitioners away from the time-intensive process of understanding a particular context in favor of “getting results quick.” Similarly, the recent introduction of experimental evidence to the development field is a wondrous thing, but the revolution has to continue: randomized experiments can tell us about the effect an intervention had somewhere, but even the best methods of applying this kind of evidence to a specific context remain somewhat arbitrary and subjective. As EA begins to fund more complex (but potentially more effective) interventions, a key step will be to get a more systematic handle on how to gather evidence about specific places-- countries, states, even villages -- and how to match the tools we have to people who might benefit from them. II. The Trouble with Technocrats “But even if the project was in some sense a ‘failure’ as an agricultural development project, it is indisputable that many of its ‘side effects’ had a powerful and far-reaching impact on the Thaba-Tseka region. [...] Indeed, it may be that in a place like Mashai, the most visible of all the project’s effects was the indirect one of increased Government military presence in the region” As the program continued to unfold, the development officials became more and more disillusioned -- not with their own choices, but with the people of Thaba-Tseka, who they perceived as petty, apathetic, and outright self-destructive. A project meant to provide firewood failed because locals kept breaking into the woodlots and uprooting the saplings. An experiment in pony-breeding fell apart when “unknown parties” drove the entire herd of ponies off of cliffs to their deaths. Why, Ferguson’s official contacts bemoaned, weren’t the people of Thaba-Tseka committed to their own “development”? Who could possibly be opposed to trees and horses? Perhaps, the practitioners theorized, the people of Thaba-Tseka were just lazy. Perhaps they “didn’t want to be better.” Perhaps they weren’t in their right mind or had made a mistake. Perhaps poverty makes a person do strange things. Or, as Ferguson points out, perhaps their anger had something to do with the fact that the best plots of land in the village had been forcibly confiscated to make room for wood and pony lots, without any sort of compensation. The central government was all too happy to help find land for the projects, which they took from political enemies and put in the control of party elites, especially when it could use a legitimate anti-poverty program as cover. In Ferguson’s words, the development project was functioning as an “anti-politics machine” the government could use to pretend political power moves were just “objective” solutions to technical problems. A local student’s term paper captured the general discontent: “In spite of the superb aim of helping the people to become self-reliant, the first thing the project did was to take their very good arable land. When the people protested about their fields being taken, the project promised them employment. [...] It employed them for two months, found them unfit for the work, and dismissed them. Without their fields and without employment they may turn up to be very self-reliant. It is rather hard to know.” Two things stand out to me from this story. First, the “development discourse” lens served to focus the practitioners’ attention on a handful of technical variables (quantity of wood, quality of pony), and kept them from thinking about any repercussions they hadn’t thought to measure. This is a serious problem, because “negative effects on things that aren’t your primary outcome” are pretty common in the development literature. High-paying medical NGOs can pull talent away from government jobs. Foreign aid can worsen ongoing conflicts. Unconditional cash transfers can hurt neighbors who didn’t receive the cash. And the literature we have is implicitly conditioned on “only examining the variables academics have thought to look at” -- surely our tools have rendered other effects completely invisible! Second, the project organizers somewhat naively ignored the political goals of the government they’d partnered with, and therefore the extent to which these goals were shaping the project. Lesotho’s recent political history had been tumultuous. The Basotho Nationalist Party (BNP), having gained power upon independence in 1965, refused to give up power after losing the 1970 elections to the Basotho Congress Party (BCP). Blaming the election results on “communists”, BNP Prime Minister Leabua Jonathan declared a state of emergency and began a campaign of terror, raiding the homes of opposition figures and funding paramilitary groups to intimidate, arrest, and potentially kill anyone who spoke up against BNP rule. This had significant effects in Thaba-Tseka, where “villages [...] were sharply divided over politics, but it was not a thing which was discussed openly” due to a fully justified fear of violence. The BNP, correctly sensing the presence of a substantial underground opposition, placed “development committees” in each village, which served primarily as local wings of the national party. These committees spied on potential supporters of the now-outlawed BCP and had deep connections to paramilitary “police” units. When the Thaba-Tseka Development Project started, its international backers partnered directly with the BNP leadership, reasoning that sustainable development and public goods provision could only happen through a government whose role they primarily viewed as bureaucratic. As a result, nearly every decision had to make its way through the village development committees, who used the project to pursue their own goals: jobs and project funds found their way primarily to BNP supporters, while the “necessary costs of development” always seemed to be paid by opposition figures. The funding coalition ended up paying for a number of projects that reinforced BNP power, from establishing a new “district capital” (which conveniently also served as a military base) to constructing new and better roads linking Thaba-Tseka to the district and national capitals (primarily helping the central government tax and police an opposition stronghold). Anything that could be remotely linked to “economic development” became part of the project as funders and practitioners failed to ask whether government power might have alternate, more concerning effects. As we saw earlier, the population being “served” saw this much more clearly than the “servants”, and started to rebel against a project whose “help” seemed to be aimed more at consolidating BNP control than meeting their own needs. When they ultimately resorted to killing ponies and uprooting trees, project officials infatuated with “development” were left with “no idea why people would do such a thing,” completely oblivious to the real and lasting harm their “purely technical decisions” had inflicted. Have any EA projects had this sort of unexpected political side effect? I think it’s genuinely hard to tell without further research, but the possibility is frightening. (There’s been a little bit of research on the quantitative side --Recent research has found, for instance, that GiveDirectly’s 2014 unconditional cash transfer trial increased community participation but did not change voting patterns, so at least in 2014 the Kenyan government wasn’t using the program to stay in power. Was this the right question to test? I am not sure, especially without a more qualitative survey to see if there are other avenues we should be worried about.) III. Takeaways for Effective Altruism So what do we do as effective altruists (hereafter “EAs”)? I see three key takeaways. The first is a clear need for more qualitative research. GiveWell makes some qualitative judgments about charities, but Ferguson’s work illustrates the need for qualitative evaluation of the interventions themselves to see if the underlying studies have captured all of the “right” variables. Randomized experiments are really good at testing hypotheses, but by their very nature they can’t tell you about variables you didn’t decide ahead of time to measure. Are there significant side effects (positive or negative) we’ve missed from massive malaria net distributions? I don’t know, but if so they are not likely to be discovered by a bunch of Americans and Europeans sitting in a room and trying to guess the best things to measure. Rather, they’re probably already known (or suspected) by the people experiencing them, and a first step to finding out is going and asking them. (A second step is finding the right people to ask them -- real expertise in qualitative research is a rare and valuable skill.) Of course, qualitative research is messy and sometimes the people you interview are wrong or have other agendas. So once we have an “on-the-ground” hypothesis or concern, there will often be good reason to use a randomized trial or quasi-experimental method to test it or try to understand how much of a concern it might be! This sort of interdisciplinary approach is starting to gain traction in academia, but it has yet to be seriously applied in the EA sphere. There’s another angle to this: Ferguson’s most incisive insights arise not from studying the people being “served”, but by studying the development practitioners themselves. Other social scientists have continued this trend, from McGovern’s An Anthropologist Among the Mandarins and Robinson’s How Different Social Scientists Think to Marchais, Bazuzi, and Lameke’s The Data is Gold, and We Are The Gold-Diggers and Omar Bah’s webcomic Mzungus in Development and Governments. Each new paper illuminates the research process in new ways, and provides tools both to do better research and to identify potential weaknesses in the pre-existing literature. I think one of the highest impact investments an Effective Altruist fund could make right now would be to hire a handful of trained anthropologists (or other outside experts in qualitative research / ethnography) to hang out in places like GiveWell or the Machine Intelligence Research Institute for a few years and really study how effective altruism works as a system. How are decisions being made, and how is evidence being used to make them? What does “EA discourse” help make visible and which problems and concerns does it hide from our view? How do the positionalities of typical EA researchers affect their views of what’s important or what’s plausible? I have my guesses, and I’m sure you have yours. But I had my guesses about development economics, too, and I missed nearly everything Ferguson (and the authors mentioned two paragraphs up) uncovered. What more are we missing? The second is an emphasis on local context. As funding gaps for “low hanging fruit” like malaria disappear, EA is going to have to focus on more complicated interventions, which are likely to be fairly context-specific -- after all, why should an agriculture program that works in the flattest parts of the Sahel be expected to work the same way in the Maloti Mountains? Ferguson notes about several of the Thaba-Tseka project’s failed arms: “Tanzania may be very different from Lesotho on the ground, but, from the point of view of a development agency’s head office, both may be simply ‘the Africa desk’. In the Thaba-Tseka case, at least, the original project planners knew little about Lesotho’s specific history, politics, and sociology; they were experts on ‘livestock development in Africa,’ and drew largely on experience in East Africa.” For any sort of context-specific intervention to work, an intimate knowledge of the specific history, needs, and geography of individual villages and regions is necessary. The development world has slowly made steps in this direction, but it’s not clear to me that the EA community has a clear way of acquiring, accessing, or working with this information. I don’t think there’s a magic bullet to solve this problem, but in the long run any solution will probably need to involve a) on-the-ground, qualitative research and b) real representation in the EA network from areas EA organizations are interested in working. The development industry has a shameful history of infantilizing and ignoring the opinions of “locals”, and I think the conversations I’m starting to see in EA about diversity and representation of different parts of the Global South need to continue if we’re going to get enough serious knowledge of local contexts to effectively direct funding. The third is a continued need to take politics seriously. This is one of the most challenging issues in charitable giving: when is it okay to work with a government doing terrible things to deliver humanitarian aid? To what extent does an NGO feeding the hungry lend its legitimacy to or cover for an authoritarian regime’s misdeeds? I don’t have anything close to a full answer (and I don’t think anyone does), but Ferguson’s work exposes a possibility I hadn’t thought of before, in which “technical” and “apolitical” projects can expand the power of the state in unforeseen and potentially dangerous ways. After writing The Anti-Politics Machine, Ferguson largely gave up on the idea of charitable or state-based aid. (Understandably, I think, given that he spent most of a decade watching its most horrific side effects first-hand). It’s ironic, then, that I think his book’s practical value is greatest to those of us who still hold onto hope in its possibilities. May we have ears to hear the voices telling us where our work has fallen short, and eyes to see what it could become. Footnotes Ferguson pg. 55
Consistent with his oft-stated belief that the rich should be taxed at 70%, Medlock only kept 30% of the $1 million - along with paying the existing taxes, he gave the rest to the charity GiveDirectly.
There are already lots of good charities that help people directly at scale, for example Against Malaria Foundation (which distributes malaria-preventing bed nets) and GiveDirectly (which gives money directly to very poor people in Africa). I think these are hard to beat.
The Effective Altruist Forum now has a post on Economic Growth - Donation Suggestions And Ideas, listing suspected top charities for helping countries develop. These include ACX Grants winner Growth Teams, the Charter Cities Institute, GiveDirectly, and Overseas Development Institute.
Inline links: Economic Growth - Donation Suggestions And Ideas, Growth Teams, Charter Cities Institute, GiveDirectly, Overseas Development Institute
The charitable version of capitalism is GiveDirectly. It's just like buying things for yourself but the first person to spend the money is someone else.
For those of you who don’t know, GiveDirectly is a charity that gives your money directly to poor people in developing countries, and then they can spent it on whatever they want. They’re doing some cool stuff!
Inline links: GiveDirectly
Try spotting existential risk prevention on here. I don’t think Stone can claim that an EA version of this chart wouldn’t look phenomenally different. But then what’s left of his argument? III. Effective altruists devote absolutely enormous amounts of mental energy and research costs to program assessment, measurement of effectiveness. Those studies yield usually-conflicting results with variable effect sizes across time horizons and model specifications, and tons of different programs end up with overlapping effect estimates. That is to say, the areas where EAist style program evaluations are most compelling are areas where we don’t need them: it’s been obvious for a long time how to reduce malaria deaths, program evaluations on that front have been encouraging and marginally useful, but not gamechanging. On the other hand, in more contestable areas, EAist style program evaluations don’t really yield much clarity. It’s very rare that a program evaluation gets published finding vastly larger benefits than you’d guess from simple back-of-the-envelope guesswork, and the smaller estimates are usually because a specific intervention had first-order failure or long-run tapering, not because “actually tuberculosis isn’t that bad” or something like that. Those kinds of precise program-delivery studies are actually not an EAist specialty, but more IPA’s specialty. My second critique, then is this: there is no evidence that the toolkit and philosophical approach EAists so loudly proclaim as morally superior actually yields any clarity, or that their involvement in global efforts is net-positive vs. similar-scale donations given through near-peer organizations. The IPA mentioned here is Innovations For Poverty Action, a group that studies how to fight poverty. They’re great and do great work. But IPA doesn’t recommend top charities or direct donations. Go to their website, try to find their recommended charities. Unless I’m missing something, there are none. GiveWell does have recommended charities - including ones that they decided to recommend based on IPA’s work - and moves ~$250 million per year to them. If IPA existed, but not GiveWell, the average donor wouldn’t know where to donate, and ~$250 million per year would fail to go to charities that IPA likes. I think from the perspective of people who actually work within this ecosystem, Stone’s concern is like saying “Farms have already solved the making-food problem, so why do we need grocery stores?” (also, effective altruism funds IPA) I’m focusing on IPA here because Stone brought them up, but I think EA does more than this. I don’t think there’s an IPA for figuring out whether asteroid deflection is more cost-effective than biosecurity, whether cow welfare is more effective than chicken welfare, or figuring out which AI safety institute to donate to. I think this is because IPA is working on a really specific problem (which kinds of poverty-related interventions work) and EA is working on a different problem (what charities should vaguely utilitarian-minded people donate to?) These are closely related questions but they’re not the same question - which is why, for example, IPA does (great) research into consumer protection, something EA doesn’t consider comparatively high-impact. And I’m still focusing on donation to charity, again because it’s what Stone brought up, but EA does other things - like incubating charities, or building networks that affect policy. IV. Let’s skip farm animal welfare for a second and look at the next few: Global Aid, “Effective Altruism,” potential AI risks, biosecurity, and global catastrophic risk. These are all definitely disproportionate areas of EAist interest. If you google these topics, you will find a wildly disproportionate number of people who are EAist, or have sex at EAist orgies, or are the friends of people who have sex at EAist orgies. These really are some of the unique social features of EAism. And they largely amount to subsidizing white collar worker wages. I’m sorry but there’s no other way to slice it: these are all jobs largely aimed at giving money to researchers, PhD-holders, university-adjacent-persons, think tanks, etc. That may be fine stuff, but the whole pitch of effective altruism is that it’s supposed to bypass a lot of the conventional nonprofit bureaucracy and its parasitism and just give money to effective charities. But as EAism as matured into a truly unique social movement, it is creating its own bureaucracy of researchers, think tanks, bureaucrats… the very things it critiqued. Suppose an EA organization funded a cancer researcher to study some new drug, and that new drug was a perfect universal cure for cancer. Would Stone reject this donation as somehow impure, because it went to a cancer researcher (a white-collar PhD holder)? EA gives hundreds of millions of dollars directly to malaria treatments that go to the poorest people in the world. It’s also one the main funders of GiveDirectly, a charity that has given money ($750 million so far) directly to the poorest people in the world. But in addition to giving out bednets directly, it sometimes funds malaria vaccines. In addition to giving to poor Africans, it also funds the people who do the studies to see whether giving to poor Africans works. Some of those are white-collar workers. EA has never been about critiquing the existence of researchers and think tanks. In fact, this is part of the story of EA’s founding. In 2007, the only charity evaluators accessible by normal people rated charities entirely on how much overhead they had - whether the money went to white-collar people or to sympathetic poor recipients. EAs weren’t the first to point out that this was a very weak way of evaluating charities. But they were the first to make the argument at scale and bring it into the public consciousness, and GiveWell (and to some degree the greater EA movement) were founded on the principle of “what if there was a charity evaluator that did better than just calculate overhead?” In accordance with this history, if you look on Giving What We Can’s List Of Misconceptions About Effective Altruism, their #1 Misconception about about charity evaluation is that “looking at a charity’s overhead costs is key to evaluating its effectiveness”. This is another part of my argument that EA is more than just IPA++. For years, the state of the art for charity evaluators was “grade them by how much overhead they had”. IPA and all the great people working on evidence-based charity at the time didn’t solve that problem - people either used CharityNavigator or did their own research. GiveWell did solve that problem, and that success sparked a broader movement to come up with a philosophy of charity that could solve more problems. Many individuals have always had good philosophies of charity, but I think EA was a step change in doing it at scale and trying to build useful tools / a community around it. V. You could of course say AI risk is a super big issue. I’m open to that! But surely the solution to AI risk is to invest in some drone-delivered bombs and geospatial data on computing centers! The idea that the primary solution here is going to be blog posts, white papers, podcasts, and even lobbying is just insane. If you are serious about ruinous AI risk, you cannot possibly tell me that the strategy pursued here is optimal vs. say waiting until a time when workers have all gone home and blowing up a bunch of data centers and corporate offices. In particular terrorism as a strategy may be efficient since explosives are rather cheap. To be clear I do not support a strategy of terrorism!!!! But I am questioning why AI-riskers don’t. Logically, they should. I think if you have to write in bold with four exclamation points at the end that you’re not explicitly advocating terrorism, you should step back and think about your assumptions further. So: Should people who worry about global warming bomb coal plants? Should people who worry that Trump is going to destroy American democracy bomb the Republican National Convention? Should people who worry about fertility collapse and underpopulation bomb abortion clinics? EAs aren’t the only group who think there are deeply important causes. But for some reason people who can think about other problems in Near Mode go crazy when they start thinking about EA. (Eliezer Yudkowsky has sometimes been accused of wanting to bomb data centers, but he supports international regulations backed by military force - his model is things like Israel bombing Iraq’s nuclear program in the context of global norms limiting nuclear proliferation - not lone wolves. As far as I know, all EAs are united against this kind of thing.) There are three reasons not to bomb coal plants/data centers/etc. The first is that bombing things is morally wrong. I take this one pretty seriously. The second is that terrorism doesn’t work. Imagine that someone actually tried to bomb a data center. First of all, I don’t have statistics but I assume 99% of terrorists get caught at the “your collaborator is an undercover fed” stage. Another 99% get eliminated at the “blown up by poor bomb hygiene and/or a spam text message” stage. And okay, 1/10,000 will destroy a datacenter, and then what? Google tells me there are 10,978 data centers in the world. After one successful attack, the other 10,977 will get better security. Probably many of these are in China or some other country that’s not trivial for an American to import high explosives into. The third is that - did I say terrorism didn’t work? I mean it massively massively backfires. Hamas tried terrorism, they frankly did a much better job than we would, and now 52% of the buildings in their entire country have been turned to rubble. Osama bin Laden tried terrorism, also did an impressive job, and the US took over the whole country that had supported him, then took over an unrelated country that seemed like the kinds of guys who might support him, then spent ten years hunting him down and killing him and everyone he had ever associated with. One f@#king time, a handful of EAs tried promoting their agenda by committing some crimes which were much less bad than terrorism. Along with all the direct suffering they caused, they destroyed EA’s reputation and political influence, drove thousands of people away from the movement, and everything they did remains a giant pit of shame that we’re still in the process of trying to climb our way out of. Not to bang the same drum again and again, but this is why EA needs to be a coherent philosophy and not just IPA++. You need some kind of theory of what kinds of activism are acceptable and effective, or else people will come up with morally repugnant and incredibly idiotic plans that will definitely backfire and destroy everything you thought you were fighting for. EA hasn’t always been the best at avoiding this failure mode, but at least we manage to outdo our critics. VI. Stone moves on to animal welfare: It’s important to grasp that [caring about animals] is, in evolutionary terms, an error in our programming. The mechanisms involved are entirely about intra-human dynamics (or, some argue, may also be about recognizing the signs of vulnerable prey animals or enabling better hunting). Yes humans have had domestic animals for quite a long time, but our sympathetic responses are far older than that. We developed accidental sympathies for animals and then we made friends with dogs, not vice versa. Again, this is part of why I think it’s useful to have people who think about philosophy, and not just people who do RCTs. People having kids of their own instead of donating to sperm banks is in some sense an “error” in our evolutionary program. The program just wanted us to reproduce; instead we got a bunch of weird proxy goals like “actually loving kids for their own sake”. Art is another error - I assume we were evolutionarily programmed to care about beauty because, I don’t know, flowers indicate good hunting grounds or something, not because evolution wanted us to paint beautiful pictures. Anyone who cares about a future they will never experience, or about people on far off continents who they’ll never meet, is in some sense succumbing to “errors” in their evolutionary programming. Stone describes the original mechanisms as “about intra-human dynamics”, but this is cope - they’re about intra-tribal dynamics. Plenty of cultures have been completely happy to enslave, kill, and murder people outside their tribes, and nothing in their evolutionary mechanism has told them not to. Does Stone think this, too, is an error? At some point you’ve got to go beyond evolutionary programming and decide what kind of person you want to be. I want to be the kind of person who cares about my family, about beauty, about people on other continents, and - yes - about animal suffering. This is the reflective equilibrium I’ve landed in after considering all the drives and desires within me, filtering it through my ability to use Reason, and imagining having to justify myself to whatever God may or may not exist. Stone suggests EAs don’t have answers to a lot of the basic questions around this. I can recommend him various posts like Axiology, Morality, Law, the super-old Consequentialism FAQ, and The Gift We Give To Tomorrow, but I think they’ll only address about half of his questions. The other half of the answers have to come from intuition, common sense, and moral conservatism. This isn’t embarrassing. Logicians have discovered many fine and helpful logical principles, but can’t 100% answer the problem of skepticism - you can fill in some of the internal links in the chain, but the beginning and end stay shrouded in mystery. This doesn’t mean you can ignore the logical principles we do know. It just means that life is a combination of formally-reasonable and not-formally-reasonable bits. You should follow the formal reason where you have it, and not freak out and collapse into Cartesian doubt where you don’t. This is how I think of morality too. Again, I really think it’s important to have a philosophy and not just a big pile of RCTs. Our critics make this point better than I ever could. They start with “all this stuff is just common sense, who needs philosophy, the RCTs basically interpret themselves”, then, in the same essay, digress into: If I wanted to do this stuff, I would try terrorism.
GiveDirectly is a charity that gives money directly to poor families in Africa. GiveWell thinks they’re within an order of magnitude of the most effective charities in the world. You can learn more and donate here.
Inline links: here
2: GiveDirectly (a charity that gives money directly to poor people in developing countries) is hiring a "fundraising-focused research senior manager". Remote work, $108K in the US and slightly less in other countries. See here for details.
Inline links: GiveDirectly, here
There are already lots of good charities that help people directly at scale, for example Against Malaria Foundation (which distributes malaria-preventing bed nets) and GiveDirectly (which gives money directly to very poor people in Africa). These are hard to beat.
Inline links: Against Malaria Foundation, GiveDirectly
I tried to see if AI could do this, and it did something that technically met the requirements but had zero artistic merit - using a lot of words like “nowhere” and “outside” in one, then separating them out to “no where” and “out side” in the other. I didn’t invest much energy in creating a clever prompt telling it not to do that, so feel free to report if you get better success. 52: New study claims consultants are actually good, at least for profits: "We find positive effects on labor productivity of 3.6% over five years, driven by modest employment reductions alongside stable or growing revenue" 53: A Polish team tries to test Peter Turchin’s equations for predicting political unrest on recent Polish history, has to make some changes but claims mostly positive results. 54: New big multi-author Substack, The Argument, trying to be a sort of center-left version of the model pioneered by The Free Press and other high-production-value ideological Substack properties. Excited to see Kelsey Piper is involved, and she starts off strong with a post on the latest round of First World basic income studies, which find few positive effects. This is surprising, because recipients didn’t waste the money on alcohol or gambling or anything - they paid down debt and got useful goods. Still, it didn’t even affect things that should have been obvious, like stress level. It’s not even clear that amounts of money large enough to help with rent made homeless people more likely to get houses! Matt Bruenig criticizes the article, accusing Kelsey’s studies of being downstream of Perry Preschool style dreams that exactly the right welfare program will have massively compounding effects that cut poverty out at the root and turn everyone into elite human capital; he thinks giving people money won’t do this, but it will increase equality and give the poor better lives. I assume he’s not a strong hereditarian, but his argument makes even more sense from that perspective, and I’ve certainly criticized dumb outcome measures like infant brain waves which we have only tenuous reasons to think are related to anything we care about. But Kelsey reasonably responds that the outcome measures she’s talking about include stress level and life satisfaction. To defuse this critique, Bruenig either has to argue that our construct “life satisfaction” doesn’t really measure whether someone’s life is satisfactory, or else claim that giving poor people satisfactory lives isn’t really what we’re going for - which I think would require more explanation on his part. There’s some further (impressively acrimonious) debate on X, but I don’t see anything that addresses my core concern. GiveDirectly, a charity involved in basic income experiments, has a presponse here; they say that some studies are positive, and that the ones that aren’t might have tried too little cash to matter, or been confounded by COVID making everything worse. They also point out that basic income is harder to study than traditional programs like giving people housing, because if you’re giving housing you can measure housing-related outcomes directly and have a pretty good chance of getting enough statistical power to find them, but since everyone spends cash on different things, the positive effects might be scattered across many different outcomes (and therefore too small to reach significance on each). Everyone involved in this debate wants to emphasize that the poor results are for First World studies only, and that studies continue to show large benefits to giving cash in the developing world. 55: Related: I was less impressed by The Argument’s first foray into housing policy, which follows an all-too-familiar pattern: Some people say they don’t like noise and disorder and try to make rules against it in their apartments.
Inline links: New study claims consultants are actually good, tries to test Peter Turchin’s equations for predicting political unrest on recent Polish history, The Argument, a post on the latest round of First World basic income studies, criticizes the article, infant brain waves, debate on X, has a presponse here, first foray into housing policy
51: Some of the debate about basic income has focused on scale; if some people get a UBI and others don’t, this might cause the recipients positive effects (relative wealth/status increases) or negative effects (envy) that you wouldn’t see in a broader program. Basic income charity GiveDirectly has an ambitious plan to investigate this by giving UBI on a community-wide scale to increasingly sized units:
Inline links: has an ambitious plan to investigate this
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