A parent I know reports (some details anonymized):
Recently we bought my 3-year-old daughter a "behavior chart," in which she can earn stickers for achievements like not throwing tantrums, eating fruits and vegetables, and going to sleep on time. We successfully impressed on her that a major goal each day was to earn as many stickers as possible.
This morning, though, I found her just plastering her entire behavior chart with stickers. She genuinely seemed to think I'd be proud of how many stickers she now had.
The Effective Altruism movement has now entered this extremely cute stage of cognitive development. EA is more than three years old, but institutions age differently than individuals.
What is a confidence game?
In 2009, investment manager and con artist Bernie Madoff pled guilty to running a massive fraud, with $50 billion in fake return on investment, having outright embezzled around $18 billion out of the $36 billion investors put into the fund. Only a couple of years earlier, when my grandfather was still alive, I remember him telling me about how Madoff was a genius, getting his investors a consistent high return, and about how he wished he could be in on it, but Madoff wasn't accepting additional investors.
What Madoff was running was a classic Ponzi scheme. Investors gave him money, and he told them that he'd gotten them an exceptionally high return on investment, when in fact he had not. But because he promised to be able to do it again, his investors mostly reinvested their money, and more people were excited about getting in on the deal. There was more than enough money to cover the few people who wanted to take money out of this amazing opportunity.
Ponzi schemes, pyramid schemes, and speculative bubbles are all situations in investors' expected profits are paid out from the money paid in by new investors, instead of any independently profitable venture. Ponzi schemes are centrally managed – the person running the scheme represents it to investors as legitimate, and takes responsibility for finding new investors and paying off old ones. In pyramid schemes such as multi-level-marketing and chain letters, each generation of investor recruits new investors and profits from them. In speculative bubbles, there is no formal structure propping up the scheme, only a common, mutually reinforcing set of expectations among speculators driving up the price of something that was already for sale.
The general situation in which someone sets themself up as the repository of others' confidence, and uses this as leverage to acquire increasing investment, can be called a confidence game.
Some of the most iconic Ponzi schemes blew up quickly because they promised wildly unrealistic growth rates. This had three undesirable effects for the people running the schemes. First, it attracted too much attention – too many people wanted into the scheme too quickly, so they rapidly exhausted sources of new capital. Second, because their rates of return were implausibly high, they made themselves targets for scrutiny. Third, the extremely high rates of return themselves caused their promises to quickly outpace what they could plausibly return to even a small share of their investor victims.
Madoff was careful to avoid all these problems, which is why his scheme lasted for nearly half a century. He only promised plausibly high returns (around 10% annually) for a successful hedge fund, especially if it was illegally engaged in insider trading, rather than the sort of implausibly high returns typical of more blatant Ponzi schemes. (Charles Ponzi promised to double investors' money in 90 days.) Madoff showed reluctance to accept new clients, like any other fund manager who doesn't want to get too big for their trading strategy.
He didn't plaster stickers all over his behavior chart – he put a reasonable number of stickers on it. He played a long game.
Not all confidence games are inherently bad. For instance, the US national pension system, Social Security, operates as a kind of Ponzi scheme, it is not obviously unsustainable, and many people continue to be glad that it exists. Nominally, when people pay Social Security taxes, the money is invested in the social security trust fund, which holds interest-bearing financial assets that will be used to pay out benefits in their old age. In this respect it looks like an ordinary pension fund.
However, the financial assets are US Treasury bonds. There is no independently profitable venture. The Federal Government of the United States of America is quite literally writing an IOU to itself, and then spending the money on current expenditures, including paying out current Social Security benefits.
The Federal Government, of course, can write as large an IOU to itself as it wants. It could make all tax revenues part of the Social Security program. It could issue new Treasury bonds and gift them to Social Security. None of this would increase its ability to pay out Social Security benefits. It would be an empty exercise in putting stickers on its own chart.
If the Federal government loses the ability to collect enough taxes to pay out social security benefits, there is no additional capacity to pay represented by US Treasury bonds. What we have is an implied promise to pay out future benefits, backed by the expectation that the government will be able to collect taxes in the future, including Social Security taxes.
There's nothing necessarily wrong with this, except that the mechanism by which Social Security is funded is obscured by financial engineering. However, this misdirection should raise at least some doubts as to the underlying sustainability or desirability of the commitment. In fact, this scheme was adopted specifically to give people the impression that they had some sort of property rights over their social Security Pension, in order to make the program politically difficult to eliminate. Once people have "bought in" to a program, they will be reluctant to treat their prior contributions as sunk costs, and willing to invest additional resources to salvage their investment, in ways that may make them increasingly reliant on it.
Not all confidence games are intrinsically bad, but dubious programs benefit the most from being set up as confidence games. More generally, bad programs are the ones that benefit the most from being allowed to fiddle with their own accounting. As Daniel Davies writes, in The D-Squared Digest One Minute MBA - Avoiding Projects Pursued By Morons 101:
Good ideas do not need lots of lies told about them in order to gain public acceptance. I was first made aware of this during an accounting class. We were discussing the subject of accounting for stock options at technology companies. […] One side (mainly technology companies and their lobbyists) held that stock option grants should not be treated as an expense on public policy grounds; treating them as an expense would discourage companies from granting them, and stock options were a vital compensation tool that incentivised performance, rewarded dynamism and innovation and created vast amounts of value for America and the world. The other side (mainly people like Warren Buffet) held that stock options looked awfully like a massive blag carried out my management at the expense of shareholders, and that the proper place to record such blags was the P&L account.
Our lecturer, in summing up the debate, made the not unreasonable point that if stock options really were a fantastic tool which unleashed the creative power in every employee, everyone would want to expense as many of them as possible, the better to boast about how innovative, empowered and fantastic they were. Since the tech companies' point of view appeared to be that if they were ever forced to account honestly for their option grants, they would quickly stop making them, this offered decent prima facie evidence that they weren't, really, all that fantastic.
However, I want to generalize the concept of confidence games from the domain of financial currency, to the domain of social credit more generally (of which money is a particular form that our society commonly uses), and in particular I want to talk about confidence games in the currency of credit for achievement.
If I were applying for a very important job with great responsibilities, such as President of the United States, CEO of a top corporation, or head or board member of a major AI research institution, I could be expected to have some relevant prior experience. For instance, I might have had some success managing a similar, smaller institution, or serving the same institution in a lesser capacity. More generally, when I make a bid for control over something, I am implicitly claiming that I have enough social credit – enough of a track record – that I can be expected to do good things with that control.
In general, if someone has done a lot, we should expect to see an iceberg pattern where a small easily-visible part suggests a lot of solid but harder-to-verify substance under the surface. One might be tempted to make a habit of imputing a much larger iceberg from the combination of a small floaty bit, and promises. But, a small easily-visible part with claims of a lot of harder-to-see substance is easy to mimic without actually doing the work. As Davies continues:
The Vital Importance of Audit. Emphasised over and over again. Brealey and Myers has a section on this, in which they remind callow students that like backing-up one's computer files, this is a lesson that everyone seems to have to learn the hard way. Basically, it's been shown time and again and again; companies which do not audit completed projects in order to see how accurate the original projections were, tend to get exactly the forecasts and projects that they deserve. Companies which have a culture where there are no consequences for making dishonest forecasts, get the projects they deserve. Companies which allocate blank cheques to management teams with a proven record of failure and mendacity, get what they deserve.
If you can independently put stickers on your own chart, then your chart is no longer reliably tracking something externally verified. If forecasts are not checked and tracked, or forecasters are not consequently held accountable for their forecasts, then there is no reason to believe that assessments of future, ongoing, or past programs are accurate. Adopting a wait-and-see attitude, insisting on audits for actual results (not just predictions) before investing more, will definitely slow down funding for good programs. But without it, most of your funding will go to worthless ones.
Open Philanthropy, OpenAI, and closed validation loops
The Open Philanthropy Project recently announced a $30 million grant to the $1 billion nonprofit AI research organization OpenAI. This is the largest single grant it has ever made. The main point of the grant is to buy influence over OpenAI’s future priorities; Holden Karnofsky, Executive Director of the Open Philanthropy Project, is getting a seat on OpenAI’s board as part of the deal. This marks the second major shift in focus for the Open Philanthropy Project.
The first shift (back when it was just called GiveWell) was from trying to find the best already-existing programs to fund (“passive funding”) to envisioning new programs and working with grantees to make them reality (“active funding”). The new shift is from funding specific programs at all, to trying to take control of programs without any specific plan.
To justify the passive funding stage, all you have to believe is that you can know better than other donors, among existing charities. For active funding, you have to believe that you’re smart enough to evaluate potential programs, just like a charity founder might, and pick ones that will outperform. But buying control implies that you think you’re so much better, that even before you’ve evaluated any programs, if someone’s doing something big, you ought to have a say.
When GiveWell moved from a passive to an active funding strategy, it was relying on the moral credit it had earned for its extensive and well-regarded charity evaluations. The thing that was particularly exciting about GiveWell was that they focused on outcomes and efficiency. They didn't just focus on the size or intensity of the problem a charity was addressing. They didn't just look at financial details like overhead ratios. They asked the question a consequentialist cares about: for a given expenditure of money, how much will this charity be able to improve outcomes?
However, when GiveWell tracks its impact, it does not track objective outcomes at all. It tracks inputs: attention received (in the form of visits to its website) and money moved on the basis of its recommendations. In other words, its estimate of its own impact is based on the level of trust people have placed in it.
So, as GiveWell built out the Open Philanthropy Project, its story was: We promised to do something great. As a result, we were entrusted with a fair amount of attention and money. Therefore, we should be given more responsibility. We represented our behavior as praiseworthy, and as a result people put stickers on our chart. For this reason, we should be advanced stickers against future days of praiseworthy behavior.
Then, as the Open Philanthropy Project explored active funding in more areas, its estimate of its own effectiveness grew. After all, it was funding more speculative, hard-to-measure programs, but a multi-billion-dollar donor, which was largely relying on the Open Philanthropy Project's opinions to assess efficacy (including its own efficacy), continued to trust it.
What is missing here is any objective track record of benefits. What this looks like to me, is a long sort of confidence game – or, using less morally loaded language, a venture with structural reliance on increasing amounts of leverage – in the currency of moral credit.
Version 0: GiveWell and passive funding
First, there was GiveWell. GiveWell’s purpose was to find and vet evidence-backed charities. However, it recognized that charities know their own business best. It wasn’t trying to do better than the charities; it was trying to do better than the typical charity donor, by being more discerning.
GiveWell’s thinking from this phase is exemplified by co-founder Elie Hassenfeld’s Six tips for giving like a pro:
When you give, give cash – no strings attached. You’re just a part-time donor, but the charity you’re supporting does this full-time and staff there probably know a lot more about how to do their job than you do. If you’ve found a charity that you feel is excellent – not just acceptable – then it makes sense to trust the charity to make good decisions about how to spend your money.
GiveWell similarly tried to avoid distorting charities’ behavior. Its job was only to evaluate, not to interfere. To perceive, not to act. To find the best, and buy more of the same.
How did GiveWell assess its effectiveness in this stage? When GiveWell evaluates charities, it estimates their cost-effectiveness in advance. It assesses the program the charity is running, through experimental evidence of the form of randomized controlled trials. GiveWell also audits the charity to make sure they’re actually running the program, and figure out how much it costs as implemented. This is an excellent, evidence-based way to generate a prediction of how much good will be done by moving money to the charity.
As far as I can tell, these predictions are untested.
One of GiveWell’s early top charities was VillageReach, which helped Mozambique with TB immunization logistics. GiveWell estimated that VillageReach could save a life for $1,000. But this charity is no longer recommended. The public page says:
VillageReach (www.villagereach.org) was our top-rated organization for 2009, 2010 and much of 2011 and it has received over $2 million due to GiveWell's recommendation. In late 2011, we removed VillageReach from our top-rated list because we felt its project had limited room for more funding. As of November 2012, we believe that that this project may have room for more funding, but we still prefer our current highest-rated charities above it.
GiveWell reanalyzed the data it based its recommendations on, but hasn’t published an after-the-fact retrospective of long-run results. I asked GiveWell about this by email. The response was that such an assessment was not prioritized because GiveWell had found implementation problems in VillageReach's scale-up work as well as reasons to doubt its original conclusion about the impact of the pilot program. It's unclear to me whether this has caused GiveWell to evaluate charities differently in the future.
I don't think someone looking at GiveWell's page on VillageReach would be likely to reach the conclusion that GiveWell now believes its original recommendation was likely erroneous. GiveWell's impact page continues to count money moved to VillageReach without any mention of the retracted recommendation. If we assume that the point of tracking money moved is to track the benefit of moving money from worse to better uses, then repudiated programs ought to be counted against the total, as costs, rather than towards it.
GiveWell has recommended the Against Malaria Foundation for the last several years as a top charity. AMF distributes long-lasting insecticide-treated bed nets to prevent mosquitos from transmitting malaria to humans. Its evaluation of AMF does not mention any direct evidence, positive or negative, about what happened to malaria rates in the areas where AMF operated. (There is a discussion of the evidence that the bed nets were in fact delivered and used.) In the supplementary information page, however, we are told:
Previously, AMF expected to collect data on malaria case rates from the regions in which it funded LLIN distributions: […] In 2016, AMF shared malaria case rate data […] but we have not prioritized analyzing it closely. AMF believes that this data is not high quality enough to reliably indicate actual trends in malaria case rates, so we do not believe that the fact that AMF collects malaria case rate data is a consideration in AMF’s favor, and do not plan to continue to track AMF's progress in collecting malaria case rate data.
The data was noisy, so they simply stopped checking whether AMF’s bed net distributions do anything about malaria.
If we want to know the size of the improvement made by GiveWell in the developing world, we have their predictions about cost-effectiveness, an audit trail verifying that work was performed, and their direct measurement of how much money people gave because they trusted GiveWell. The predictions on the final target – improved outcomes – have not been tested.
GiveWell is actually doing unusually well as far as major funders go. It sticks to describing things it's actually responsible for. By contrast, the Gates Foundation, in a report to Warren Buffet claiming to describe its impact, simply described overall improvement in the developing world, a very small rhetorical step from claiming credit for 100% of the improvement. GiveWell at least sticks to facts about GiveWell's own effects, and this is to its credit. But, it focuses on costs it has been able to impose, not benefits it has been able to create.
The Centre for Effective Altruism's William MacAskill made a related point back in 2012, though he talked about the lack of any sort of formal outside validation or audit, rather than focusing on empirical validation of outcomes:
As far as I know, GiveWell haven't commissioned a thorough external evaluation of their recommendations. […] This surprises me. Whereas businesses have a natural feedback mechanism, namely profit or loss, research often doesn't, hence the need for peer-review within academia. This concern, when it comes to charity-evaluation, is even greater. If GiveWell's analysis and recommendations had major flaws, or were systematically biased in some way, it would be challenging for outsiders to work this out without a thorough independent evaluation. Fortunately, GiveWell has the resources to, for example, employ two top development economists to each do an independent review of their recommendations and the supporting research. This would make their recommendations more robust at a reasonable cost.
GiveWell's page on self-evaluation says that it discontinued external reviews in August 2013. This page links to an explanation of the decision, which concludes:
We continue to believe that it is important to ensure that our work is subjected to in-depth scrutiny. However, at this time, the scrutiny we’re naturally receiving – combined with the high costs and limited capacity for formal external evaluation – make us inclined to postpone major effort on external evaluation for the time being.
- >If someone volunteered to do (or facilitate) formal external evaluation, we’d welcome this and would be happy to prominently post or link to criticism.
- We do intend eventually to re-institute formal external evaluation.
Four years later, assessing the credibility of this assurance is left as an exercise for the reader.
Version 1: GiveWell Labs and active funding
Then there was GiveWell Labs, later called the Open Philanthropy Project. It looked into more potential philanthropic causes, where the evidence base might not be as cut-and-dried as that for the GiveWell top charities. One thing they learned was that in many areas, there simply weren’t shovel-ready programs ready for funding – a funder has to play a more active role. This shift was described by GiveWell co-founder Holden Karnofsky in his 2013 blog post, Challenges of passive funding:
By “passive funding,” I mean a dynamic in which the funder’s role is to review others’ proposals/ideas/arguments and pick which to fund, and by “active funding,” I mean a dynamic in which the funder’s role is to participate in – or lead – the development of a strategy, and find partners to “implement” it. Active funders, in other words, are participating at some level in “management” of partner organizations, whereas passive funders are merely choosing between plans that other nonprofits have already come up with.
My instinct is generally to try the most “passive” approach that’s feasible. Broadly speaking, it seems that a good partner organization will generally know their field and environment better than we do and therefore be best positioned to design strategy; in addition, I’d expect a project to go better when its implementer has fully bought into the plan as opposed to carrying out what the funder wants. However, (a) this philosophy seems to contrast heavily with how most existing major funders operate; (b) I’ve seen multiple reasons to believe the “active” approach may have more relative merits than we had originally anticipated. […]
- In the nonprofit world of today, it seems to us that funder interests are major drivers of which ideas that get proposed and fleshed out, and therefore, as a funder, it’s important to express interests rather than trying to be fully “passive.”
- While we still wish to err on the side of being as “passive” as possible, we are recognizing the importance of clearly articulating our values/strategy, and also recognizing that an area can be underfunded even if we can’t easily find shovel-ready funding opportunities in it.
GiveWell earned some credibility from its novel, evidence-based outcome-oriented approach to charity evaluation. But this credibility was already – and still is – a sort of loan. We have GiveWell's predictions or promises of cost effectiveness in terms of outcomes, and we have figures for money moved, from which we can infer how much we were promised in improved outcomes. As far as I know, no one's gone back and checked whether those promises turned out to be true.
In the meantime, GiveWell then leveraged this credibility by extending its methods into more speculative domains, where less was checkable, and donors had to put more trust in the subjective judgment of GiveWell analysts. This was called GiveWell Labs. At the time, this sort of compounded leverage may have been sensible, but it's important to track whether a debt has been paid off or merely rolled over.
Version 2: The Open Philanthropy Project and control-seeking
Finally, the Open Philanthropy made its largest-ever single grant to purchase its founder a seat on a major organization’s board. This represents a transition from mere active funding to overtly purchasing influence:
The Open Philanthropy Project awarded a grant of $30 million ($10 million per year for 3 years) in general support to OpenAI. This grant initiates a partnership between the Open Philanthropy Project and OpenAI, in which Holden Karnofsky (Open Philanthropy’s Executive Director, “Holden” throughout this page) will join OpenAI’s Board of Directors and, jointly with one other Board member, oversee OpenAI’s safety and governance work.
We expect the primary benefits of this grant to stem from our partnership with OpenAI, rather than simply from contributing funding toward OpenAI’s work. While we would also expect general support for OpenAI to be likely beneficial on its own, the case for this grant hinges on the benefits we anticipate from our partnership, particularly the opportunity to help play a role in OpenAI’s approach to safety and governance issues.
Clearly the value proposition is not increasing available funds for OpenAI, if OpenAI’s founders’ billion-dollar commitment to it is real:
Sam, Greg, Elon, Reid Hoffman, Jessica Livingston, Peter Thiel, Amazon Web Services (AWS), Infosys, and YC Research are donating to support OpenAI. In total, these funders have committed $1 billion, although we expect to only spend a tiny fraction of this in the next few years.
The Open Philanthropy Project is neither using this money to fund programs that have a track record of working, nor to fund a specific program that it has prior reason to expect will do good. Rather, it is buying control, in the hope that Holden will be able to persuade OpenAI not to destroy the world, because he knows better than OpenAI’s founders.
How does the Open Philanthropy Project know that Holden knows better? Well, it’s done some active funding of programs it expects to work out. It expects those programs to work out because they were approved by a process similar to the one used by GiveWell to find charities that it expects to save lives.
If you want to acquire control over something, that implies that you think you can manage it more sensibly than whoever is in control already. Thus, buying control is a claim to have superior judgment - not just over others funding things (the original GiveWell pitch), but over those being funded.
In a footnote to the very post announcing the grant, the Open Philanthropy Project notes that it has historically tried to avoid acquiring leverage over organizations it supports, precisely because it’s not sure it knows better:
For now, we note that providing a high proportion of an organization’s funding may cause it to be dependent on us and accountable primarily to us. This may mean that we come to be seen as more responsible for its actions than we want to be; it can also mean we have to choose between providing bad and possibly distortive guidance/feedback (unbalanced by other stakeholders’ guidance/feedback) and leaving the organization with essentially no accountability.
This seems to describe two main problems introduced by becoming a dominant funder:
- People might accurately attribute causal responsibility for some of the organization's conduct to the Open Philanthropy Project.
- The Open Philanthropy Project might influence the organization to behave differently than it otherwise would.
The first seems obviously silly. I've been trying to correct the imbalance where Open Phil is criticized mainly when it makes grants, by criticizing it for holding onto too much money.
The second really is a cost as well as a benefit, and the Open Philanthropy Project has been absolutely correct to recognize this. This is the sort of thing GiveWell has consistently gotten right since the beginning and it deserves credit for making this principle clear and – until now – living up to it.
But discomfort with being dominant funders seems inconsistent with buying a board seat to influence OpenAI. If the Open Philanthropy Project thinks that Holden’s judgment is good enough that he should be in control, why only here? If he thinks that other Open Philanthropy Project AI safety grantees have good judgment but OpenAI doesn’t, why not give them similar amounts of money free of strings to spend at their discretion and see what happens? Why not buy people like Eliezer Yudkowsky, Nick Bostrom, or Stuart Russell a seat on OpenAI’s board?
On the other hand, the Open Philanthropy Project is right on the merits here with respect to safe superintelligence development. Openness makes sense for weak AI, but if you’re building true strong AI you want to make sure you’re cooperating with all the other teams in a single closed effort. I agree with the Open Philanthropy Project’s assessment of the relevant risks. But it's not clear to me how often joining the bad guys to prevent their worst excesses is a good strategy, and it seems like it has to often be a mistake. Still, I’m mindful of heroes like John Rabe, Chiune Sugihara, and Oscar Schindler. And if I think someone has a good idea for improving things, it makes sense to reallocate control from people who have worse ideas, even if there's some potential better allocation.
On the other hand, is Holden Karnofsky the right person to do this? The case is mixed.
He listens to and engages with the arguments from principled advocates for AI safety research, such as Nick Bostrom, Eliezer Yudkowsky, and Stuart Russell. This is a point in his favor. But, I can think of other people who engage with such arguments. For instance, OpenAI founder Elon Musk has publicly praised Bostrom’s book Superintelligence, and founder Sam Altman has written two blog posts summarizing concerns about AI safety reasonably cogently. Altman even asked Luke Muehlhauser, former executive director of MIRI, for feedback pre-publication. He's met with Nick Bostrom. That suggests a substantial level of direct engagement with the field, although Holden has engaged for a longer time, more extensively, and more directly.
Another point in Holden’s favor, from my perspective, is that under his leadership, the Open Philanthropy Project has funded the most serious-seeming programs for both weak and strong AI safety research. But Musk also managed to (indirectly) fund AI safety research at MIRI and by Nick Bostrom personally, via his $10 million FLI grant.
The Open Philanthropy Project also says that it expects to learn a lot about AI research from this, which will help it make better decisions on AI risk in the future and influence the field in the right way. This is reasonable as far as it goes. But remember that the case for positioning the Open Philanthropy Project to do this relies on the assumption that the Open Philanthropy Project will improve matters by becoming a central influencer in this field. This move is consistent with reaching that goal, but it is not independent evidence that the goal is the right one.
Overall, there are good narrow reasons to think that this is a potential improvement over the prior situation around OpenAI – but only a small and ill-defined improvement, at considerable attentional cost, and with the offsetting potential harm of increasing OpenAI's perceived legitimacy as a long-run AI safety organization.
And it’s worrying that Open Philanthropy Project’s largest grant – not just for AI risk, but ever (aside from GiveWell Top Charity funding) – is being made to an organization at which Holden’s housemate and future brother-in-law is a leading researcher. The nepotism argument is not my central objection. If I otherwise thought the grant were obviously a good idea, it wouldn’t worry me, because it’s natural for people with shared values and outlooks to become close nonprofessionally as well. But in the absence of a clear compelling specific case for the grant, it’s worrying.
Altogether, I'm not saying this is an unreasonable shift, considered in isolation. I’m not even sure this is a bad thing for the Open Philanthropy Project to be doing – insiders may have information that I don’t, and that is difficult to communicate to outsiders. But as outsiders, there comes a point when someone’s maxed out their moral credit, and we should wait for results before actively trying to entrust the Open Philanthropy Project and its staff with more responsibility.
EA Funds and self-recommendation
The Centre for Effective Altruism is actively trying to entrust the Open Philanthropy Project and its staff with more responsibility.
The concerns of CEA’s CEO William MacAskill about GiveWell have, as far as I can tell, never been addressed, and the underlying issues have only become more acute. But CEA is now working to put more money under the control of Open Philanthropy Project staff, through its new EA Funds product – a way for supporters to delegate giving decisions to expert EA “fund managers” by giving to one of four funds: Global Health and Development, Animal Welfare, Long-Term Future, and Effective Altruism Community.
The Effective Altruism movement began by saying that because very poor people exist, we should reallocate money from ordinary people in the developed world to the global poor. Now the pitch is in effect that because very poor people exist, we should reallocate money from ordinary people in the developed world to the extremely wealthy. This is a strange and surprising place to end up, and it’s worth retracing our steps. Again, I find it easiest to think of three stages:
- Money can go much farther in the developing world. Here, we’ve found some examples for you. As a result, you can do a huge amount of good by giving away a large share of your income, so you ought to.
- We’ve found ways for you to do a huge amount of good by giving away a large share of your income for developing-world interventions, so you ought to trust our recommendations. You ought to give a large share of your income to these weird things our friends are doing that are even better, or join our friends.
- We’ve found ways for you to do a huge amount of good by funding weird things our friends are doing, so you ought to trust the people we trust. You ought to give a large share of your income to a multi-billion-dollar foundation that funds such things.
Stage 1: The direct pitch
At first, Giving What We Can (the organization that eventually became CEA) had a simple, easy to understand pitch:
Giving What We Can is the brainchild of Toby Ord, a philosopher at Balliol College, Oxford. Inspired by the ideas of ethicists Peter Singer and Thomas Pogge, Toby decided in 2009 to commit a large proportion of his income to charities that effectively alleviate poverty in the developing world.
Discovering that many of his friends and colleagues were interested in making a similar pledge, Toby worked with fellow Oxford philosopher Will MacAskill to create an international organization of people who would donate a significant proportion of their income to cost-effective charities.
Giving What We Can launched in November 2009, attracting significant media attention. Within a year, 64 people had joined the society, their pledged donations amounting to $21 million. Initially run on a volunteer basis, Giving What We Can took on full-time staff in the summer of 2012.
In effect, its argument was: "Look, you can do huge amounts of good by giving to people in the developing world. Here are some examples of charities that do that. It seems like a great idea to give 10% of our income to those charities."
GWWC was a simple product, with a clear, limited scope. Its founders believed that people, including them, ought to do a thing – so they argued directly for that thing, using the arguments that had persuaded them. If it wasn't for you, it was easy to figure that out; but a surprisingly large number of people were persuaded by a simple, direct statement of the argument, took the pledge, and gave a lot of money to charities helping the world's poorest.
Stage 2: Rhetoric and belief diverge
Then, GWWC staff were persuaded you could do even more good with your money in areas other than developing-world charity, such as existential risk mitigation. Encouraging donations and work in these areas became part of the broader Effective Altruism movement, and GWWC's umbrella organization was named the Centre for Effective Altruism. So far, so good.
But this left Effective Altruism in an awkward position; while leadership often personally believe the most effective way to do good is far-future stuff or similarly weird-sounding things, many people who can see the merits of the developing-world charity argument reject the argument that because the vast majority of people live in the far future, even a very small improvement in humanity’s long-run prospects outweighs huge improvements on the global poverty front. They also often reject similar scope-sensitive arguments for things like animal charities.
Giving What We Can's page on what we can achieve still focuses on global poverty, because developing-world charity is easier to explain persuasively. However, EA leadership tends to privately focus on things like AI risk. Two years ago many attendees at the EA Global conference in the San Francisco Bay Area were surprised that the conference focused so heavily on AI risk, rather than the global poverty interventions they’d expected.
Stage 3: Effective altruism is self-recommending
Shortly before the launch of the EA Funds I was told in informal conversations that they were a response to demand. Giving What We Can pledge-takers and other EA donors had told CEA that they trusted it to GWWC pledge-taker demand. CEA was responding by creating a product for the people who wanted it.
This seemed pretty reasonable to me, and on the whole good. If someone wants to trust you with their money, and you think you can do something good with it, you might as well take it, because they’re estimating your skill above theirs. But not everyone agrees, and as the Madoff case demonstrates, "people are begging me to take their money" is not a definitive argument that you are doing anything real.
In practice, the funds are managed by Open Philanthropy Project staff:
We want to keep this idea as simple as possible to begin with, so we’ll have just four funds, with the following managers:
- Global Health and Development - Elie Hassenfeld
- Animal Welfare – Lewis Bollard
- Long-run future – Nick Beckstead
- Movement-building – Nick Beckstead
(Note that the meta-charity fund will be able to fund CEA; and note that Nick Beckstead is a Trustee of CEA. The long-run future fund and the meta-charity fund continue the work that Nick has been doing running the EA Giving Fund.)
It’s not a coincidence that all the fund managers work for GiveWell or Open Philanthropy. First, these are the organisations whose charity evaluation we respect the most. The worst-case scenario, where your donation just adds to the Open Philanthropy funding within a particular area, is therefore still a great outcome. Second, they have the best information available about what grants Open Philanthropy are planning to make, so have a good understanding of where the remaining funding gaps are, in case they feel they can use the money in the EA Fund to fill a gap that they feel is important, but isn’t currently addressed by Open Philanthropy.
In past years, Giving What We Can recommendations have largely overlapped with GiveWell’s top charities.
In the comments on the launch announcement on the EA Forum, several people (including me) pointed out that the Open Philanthropy Project seems to be having trouble giving away even the money it already has, so it seems odd to direct more money to Open Philanthropy Project decisionmakers. CEA’s senior marketing manager replied that the Funds were a minimum viable product to test the concept:
I don't think the long-term goal is that OpenPhil program officers are the only fund managers. Working with them was the best way to get an MVP version in place.
This also seemed okay to me, and I said so at the time.
[NOTE: I've edited the next paragraph to excise some unreliable information. Sorry for the error, and thanks to Rob Wiblin for pointing it out.]
After they were launched, though, I saw phrasings that were not so cautious at all, instead making claims that this was generally a better way to give. As of writing this, if someone on the effectivealtruism.org website clicks on "Donate Effectively" they will be led directly to a page promoting EA Funds. When I looked at Giving What We Can’s top charities page in early April, it recommended the EA Funds "as the highest impact option for donors."
This is not a response to demand, it is an attempt to create demand by using CEA's authority, telling people that the funds are better than what they're doing already. By contrast, GiveWell's Top Charities page simply says:
Our top charities are evidence-backed, thoroughly vetted, underfunded organizations.
This carefully avoids any overt claim that they're the highest-impact option available to donors. GiveWell avoids saying that because there's no way they could know it, so saying it wouldn't be truthful.
A marketing email might have just been dashed off quickly, and an exaggerated wording might just have been an oversight. But when I looked at Giving What We Can’s top charities page in early April, it recommended the EA Funds "as the highest impact option for donors."
The wording has since been qualified with “for most donors”, which is a good change. But the thing I’m worried about isn’t just the explicit exaggerated claims – it’s the underlying marketing mindset that made them seem like a good idea in the first place. EA seems to have switched from an endorsement of the best things outside itself, to an endorsement of itself. And it's concentrating decisionmaking power in the Open Philanthropy Project.
Effective altruism is overextended, but it doesn't have to be
There is a saying in finance, that was old even back when Keynes said it. If you owe the bank a million dollars, then you have a problem. If you owe the bank a billion dollars, then the bank has a problem.
In other words, if someone extends you a level of trust they could survive writing off, then they might call in that loan. As a result, they have leverage over you. But if they overextend, putting all their eggs in one basket, and you are that basket, then you have leverage over them; you're too big to fail. Letting you fail would be so disastrous for their interests that you can extract nearly arbitrary concessions from them, including further investment. For this reason, successful institutions often try to diversify their investments, and avoid overextending themselves. Regulators, for the same reason, try to prevent banks from becoming "too big to fail."
The Effective Altruism movement is concentrating decisionmaking power and trust as much as possible, in a way that's setting itself up to invest ever increasing amounts of confidence to keep the game going.
The alternative is to keep the scope of each organization narrow, overtly ask for trust for each venture separately, and make it clear what sorts of programs are being funded. For instance, Giving What We Can should go back to its initial focus of global poverty relief.
Like many EA leaders, I happen to believe that anything you can do to steer the far future in a better direction is much, much more consequential for the well-being of sentient creatures than any purely short-run improvement you can create now. So it might seem odd that I think Giving What We Can should stay focused on global poverty. But, I believe that the single most important thing we can do to improve the far future is hold onto our ability to accurately build shared models. If we use bait-and-switch tactics, we are actively eroding the most important type of capital we have – coordination capacity.
If you do not think giving 10% of one's income to global poverty charities is the right thing to do, then you can't in full integrity urge others to do it – so you should stop. You might still believe that GWWC ought to exist. You might still believe that it is a positive good to encourage people to give much of their income to help the global poor, if they wouldn't have been doing anything else especially effective with the money. If so, and you happen to find yourself in charge of an organization like Giving What We Can, the thing to do is write a letter to GWWC members telling them that you've changed your mind, and why, and offering to give away the brand to whoever seems best able to honestly maintain it.
If someone at the Centre for Effective Altruism fully believes in GWWC's original mission, then that might make the transition easier. If not, then one still has to tell the truth and do what's right.
And what of the EA Funds? The Long-Term Future Fund is run by Open Philanthropy Project Program Officer Nick Beckstead. If you think that it's a good thing to delegate giving decisions to Nick, then I would agree with you. Nick's a great guy! I'm always happy to see him when he shows up at house parties. He's smart, and he actively seeks out arguments against his current point of view. But the right thing to do, if you want to persuade people to delegate their giving decisions to Nick Beckstead, is to make a principled case for delegating giving decisions to Nick Beckstead. If the Centre for Effective Altruism did that, then Nick would almost certainly feel more free to allocate funds to the best things he knows about, not just the best things he suspects EA Funds donors would be able to understand and agree with.
If you can't directly persuade people, then maybe you're wrong. If the problem is inferential distance, then you've got some work to do bridging that gap.
There's nothing wrong with setting up a fund to make it easy. It's actually a really good idea. But there is something wrong with the multiple layers of vague indirection involved in the current marketing of the Far Future fund – using global poverty to sell the generic idea of doing the most good, then using CEA's identity as the organization in charge of doing the most good to persuade people to delegate their giving decisions to it, and then sending their money to some dude at the multi-billion-dollar foundation to give away at his personal discretion. The same argument applies to all four Funds.
Likewise, if you think that working directly on AI risk is the most important thing, then you should make arguments directly for working on AI risk. If you can't directly persuade people, then maybe you're wrong. If the problem is inferential distance, it might make sense to imitate the example of someone like Eliezer Yudkowsky, who used indirect methods to bridge the inferential gap by writing extensively on individual human rationality, and did not try to control others' actions in the meantime.
If Holden thinks he should be in charge of some AI safety research, then he should ask Good Ventures for funds to actually start an AI safety research organization. I'd be excited to see what he'd come up with if he had full control of and responsibility for such an organization. But I don't think anyone has a good plan to work directly on AI risk, and I don't have one either, which is why I'm not directly working on it or funding it. My plan for improving the far future is to build human coordination capacity.
(If, by contrast, Holden just thinks there needs to be coordination between different AI safety organizations, the obvious thing to do would be to work with FLI on that, e.g. by giving them enough money to throw their weight around as a funder. They organized the successful Puerto Rico conference, after all.)
Another thing that would be encouraging would be if at least one of the Funds were not administered entirely by an Open Philanthropy Project staffer, and ideally an expert who doesn't benefit from the halo of "being an EA." For instance, Chris Blattman is a development economist with experience designing programs that don't just use but generate evidence on what works. When people were arguing about whether sweatshops are good or bad for the global poor, he actually went and looked by performing a randomized controlled trial. He's leading two new initiatives with J-PAL and IPA, and expects that directors designing studies will also have to spend time fundraising. Having funding lined up seems like the sort of thing that would let them spend more time actually running programs. And more generally, he seems likely to know about funding opportunities the Open Philanthropy Project doesn't, simply because he's embedded in a slightly different part of the global health and development network.
Narrower projects that rely less on the EA brand and more on what they're actually doing, and more cooperation on equal terms with outsiders who seem to be doing something good already, would do a lot to help EA grow beyond putting stickers on its own behavior chart. I'd like to see EA grow up. I'd be excited to see what it might do.
- Good programs don't need to distort the story people tell about them, while bad programs do.
- Moral confidence games – treating past promises and trust as a track record to justify more trust – are an example of the kind of distortion mentioned in (1), that benefits bad programs more than good ones.
- The Open Philanthropy Project's Open AI grant represents a shift from evaluating other programs' effectiveness, to assuming its own effectiveness.
- EA Funds represents a shift from EA evaluating programs' effectiveness, to assuming EA's effectiveness.
- A shift from evaluating other programs' effectiveness, to assuming one's own effectiveness, is an example of the kind of "moral confidence game" mentioned in (2).
- EA ought to focus on scope-limited projects, so that it can directly make the case for those particular projects instead of relying on EA identity as a reason to support an EA organization.
- EA organizations ought to entrust more responsibility to outsiders who seem to be doing good things but don't overtly identify as EA, instead of trying to keep it all in the family.
(Originally posted at my personal blog and LessWrong. I've gotten some encouragement to cross-post this here, so I'm doing so.
Disclosure: I know many people involved at many of the organizations discussed, and I used to work for GiveWell. I have no current institutional affiliation to any of them. Everyone mentioned has always been nice to me and I have no personal complaints.)
Some feedback on your feedback (I've only quickly read your post once, so take it with a grain of salt):
You may still be right, though I would want some more balanced analysis.
(Disclosure, I read this post, thought it was very thorough, and encouraged Ben to post it here.)
Just to balance this, I actually liked the Ponzi scheme section. I think that making the claim 'aspects of EA have Ponzi-like elements and this is a problem' without carefully explaining what a Ponzi scheme is and without explaining that Ponzi-schemes don't necessarily require people with bad intentions would have potential to be much more inflammatory. As written, this piece struck me as fairly measured.
Also, since the claims are aimed at a potentially-flawed general approach/mindset rather than being specific to current actions, zeroing in too much might be net counterproductive in this case; there's some balance to strike here.
If someone thinks concentrated decisionmaking is better, they should be overtly making the case for concentrated decisionmaking. When I talk with EA leaders about this they generally do not try to sell me on concentrated decisionmaking, they just note that everyone seems eager to trust them so they may as well try to put that resource to good use. Often they say they'd be happy if alternatives emerged.
I enjoyed the SSC-style length and thought it helpful in fully explicating his arguments. :) It may be the case that an artificially-shortened version of the post would not be as listened-to. But perhaps a TL;DR could go at the top.
I found the analogy with confidence games thought-provoking, but it could have been a bit shorter.
1) I think you're missing one important way in which GiveWell and OpenPhil have demonstrated their credibility, which is by showing us many of the outputs of their decision-making processes and letting us judge their quality.
Having evidence that GiveWell's recommendations had a track record of high impact would give us an absolute recommendation: if you follow their advice, you can expect to do this well. Having evidence that they are good at making decisions (by whatever standard you subscribe to) gives you a relative recommendation: if you follow their advice, you can expect to do better than you would do yourself.
In this sense, GiveWell's confidence is not "loaned", it has been earned by continuing to provide evidence of (what the community thinks is) good decision making.
Of course, how well this works depends on how well we can recognize good decision-making. Only judging recommendations by whether they seem sensible to the community renders us vulnerable to groupthink, and untethers us from evidence. Good retrospectives on past recommendations would help us judge whether the decisions that are being made really are good, as well as being indicative of good tendencies within these organizations. So I think it would be great to do more of those (and, indeed, having the resources to run such retrospectives could be one of the advantages of having slightly more "centralised" institutions).
2) I do think that the pre-eminence of GiveWell and OpenPhil in the EA research space is a little unfortunate. Diversity of opinion is good, and in an ideal world I'd like to see several large institutions critiquing and evaluating each others' work. This is one of the reasons I was sad that GWWC stopped doing charity evaluation research. Even if they think that GiveWell simply does it better, having an independent set of opinions is quite valuable.
3) I don't quite see what now makes EA "self-recommending". Previously we said "give your money to these charities", now we say "give your money to this fund, and we'll give it to these charities". I don't see a significant difference there: in both cases we're claiming greater expertise than the donors, and asking them to defer to our judgement. It's just that one of them is more systematized.
What would be worrying is if we were advertising a fund as "the most effective way to donate" and then channeling all the money to EA orgs. That looks like a scam. But the EA Community fund is clearly separate from the others. If you donate to the Global Development fund, your money will be spent on Global Development.
4) It's good to keep us on our toes about how we sell things. It's always tempting to oversell, particularly with the recent increasing focus on outreach. But I think we can and should do better than that, so thanks for bringing this stuff up!
It also seems to me that the time to complain about this sort of process is while the results are still plausibly good. If we wait for things to be clearly bad, it'll be too late to recover the relevant social trust. This way involves some amount of complaining about bad governance used to good ends, but the better the ends, the more compatible they should be with good governance.
Yes, in case it wasn't clear, I think I agree with many of your concrete suggestions, but I think the current situation is not too bad.
On (1) I agree that GiveWell's done a huge public service by making many parts of decisionmaking process public, letting us track down what their sources are, etc. But making it really easy for an outsider to audit GiveWell's work, while an admirable behavior, does not imply that GiveWell has done a satisfactory audit of its own work. It seems to me like a lot of people are inferring the latter from the former, and I hope by now it's clear what reasons there are to be skeptical of this.
On (3), here's why I'm worried about increasing overt reliance on the argument from "believe me":
The difference between making a direct argument for X, and arguing for "trust me" and then doing X, is that in the direct case, you're making it easy for people to evaluate your assumptions about X and disagree with you on the object level. In the "trust me" case, you're making it about who you are rather than what is to be done. I can seriously consider someone's arguments without trusting them so much that I'd like to give them my money with no strings attached.
"Most effective way to donate" is vanishingly unlikely to be generically true for all donors, and the aggressive pitching of these funds turns the supposed test of whether there's underlying demand for EA Funds into a test of whether people believe CEA's assurances that EA Funds is the right way to give.
The point I was trying to make is that while GiveWell may not have acted "satisfactorily", they are still well ahead of many of us. I hadn't "inferred" that GiveWell had audited themselves thoroughly - it hadn't even occurred to me to ask, which is a sign of just how bad my own epistemics are. And I don't think I'm unusual in that respect. So GiveWell gets a lot of credit from me for doing "quite well" at their epistemics, even if they could do better (and it's good to hold them to a high standard!).
I think that making the final decision on where to donate yourself often offers only an illusion of control. If you're getting all your information from one source you might as well just be giving them your money. But it does at least keep more things out in the open, which is good.
Re-reading your post, I think I may have been misinterpreting you - am I right in thinking that you mainly object to the marketing of the EA Funds as the "default choice", rather than to their existence for people who want that kind of instrument? I agree that the marketing is perhaps over-selling at the moment.
Yep! I think it's fine for them to exist in principle, but the aggressive marketing of them is problematic. I've seen attempts to correct specific problems that are pointed out e.g. exaggerated claims, but there are so many things pointing in the same direction that it really seems like a mindset problem.
I tried to write more directly about the mindset problem here:
Do you think "trust me" arguments are inherently invalid, or that in this case sufficient evidence hasn't been presented?
I think sufficient evidence hasn't been presented, in large part because the argument has been tacit rather than overt.
This is an unfair gotcha. What would the point of this be? Of course the data is noisy. Not only is it noisy, it is irrelevant - if it was not, there would never be any need to have run randomized trials in the first place, you would simply dump the bed nets where convenient and check malaria rates. The whole point of randomized trials is realizing that correlational data is extremely weak and cannot give reliable causal inferences. (I can certainly imagine reasons why malaria rates might go up in regions that AMF does bed net distribution in, just as I can imagine reasons why death rates might be greater or increase over time in patients prescribed new drug X as compared to patients not prescribed X...) If they did the followups and malaria rates held stable or increased, you would not then believe that the bednets do not work; if it takes randomized trials to justify spending on bednets, it cannot then take only surveys to justify not spending on bed nets, as the causal question is identical. Since it does not affect any decisions, it is not important to measure. Or, if it did, what you ought to be criticizing Givewell & AMF for, as well as everyone else, is ever advocating & spending resources on highly unethical randomized trials, rather than criticizing them for not doing some followup surveys.
(A reasonable critique might be that they are not examining whether the intervention - which has been identified as causally effective and passing a cost-benefit - is being correctly delivered, the right people getting the nets, and using the nets. But as far as I know, they do track that...)
It's hard for me to believe that the effect of bednets is large enough to show an effect in RCTs, but not large enough to show up more often than not as a result of mass distribution of bednets. If absence of this evidence really isn't strong evidence of no effect, it should be possible to show it with specific numbers and not just handwaving about noise. And I'd expect that to be mentioned in the top-level summary on bed net interventions, not buried in a supplemental page.
You may find it hard to believe, but nevertheless, that is the fact: correlational results can easily be several times the true causal effect, in either direction. If you really want numbers, see, for example, the papers & meta-analyses I've compiled in https://www.gwern.net/Correlation on comparing correlations with the causal estimates from simultaneous or later conducted randomized experiments, which have plenty of numbers. Hence, it is easy for a causal effect to be swamped by any time trends or other correlates, and a followup correlation cannot and should not override credible causal results. This is why we need RCTs in the first place. Followups can do useful things like measure whether the implementation is being delivered, or can provide correlational data on things not covered by the original randomized experiments (like unconsidered side effects), but not retry the original case with double jeopardy.
This sort of framing leads to publication bias. We want double jeopardy! This isn't a criminal trial, where the coercive power of a massive state is being pitted against an individual's limited ability to defend themselves. This is an intervention people are spending loads of money on, and it's entirely appropriate to continue checking whether the intervention works as well as we thought.
As I understand the linked page, it's mostly about retroactive rather than prospective observational studies, and usually for individual rather than population-level interventions. A plan to initiate mass bednet distribution on a national scale is pretty substantially different from that, and doesn't suffer from the same kind of confounding.
Of course it's mathematically possible that the data is so noisy relative to the effect size of the supposedly most cost-effective global health intervention out there, that we shouldn't expect the impact of the intervention to show up. But, I haven't seen evidence that anyone at GiveWell actually did the relevant calculation to check whether this was the case for bednet distributions.
EA Global 2015 had one pannel on AI (in the morning, on day 2) and one talk tripplet on Global Poverty (in the afternoon, on day 2). Most of the content was not cause-specific.
People remember EA Global 2015 as having a lot of AI content because Elon Musk was on the AI pannel which made it loom very large in people's minds. So, while it's fair to say that more attention ended up on AI than on global poverty, it's not fair to say that the content focused more on AI than on global poverty
The featured event was the AI risk thing. My recollection is that there was nothing else scheduled at that time so everyone could go to it. That doesn't mean there wasn't lots of other content (there was), nor do I think centering AI risk was necessarily a bad thing, but I stand by my description.
We didn't offer any alternative events during Elon's panel because we (correctly) perceived that there wouldn't be demand for going to a different event and putting someone on stage with few people in the audience is not a good way to treat speakers.
We had to set up an overflow room for people that didn't make it into the main room during the Elon panel, and even the overflow room was standing room only.
I think this is worth pointing out because of the proceeding sentence:
The implication is that we aimed to bias the conference towards AI risk and against global poverty because of some private preference for AI risk as a cause area.
I think we can be fairly accused of aiming for Elon as an attendee and not some extremely well known global poverty person.
However, with the exception of Bill Gates (who we tried to get), I don't know of anyone in global poverty with anywhere close to the combination of a) general renown and b) reachability. So, I think trying to get Elon was probably the right call.
Given that Elon was attending, I don't see what reasonable options we had for more evenly distributing attention between plausible causes. Elon casts a big shadow.
 Some readers contacted me to let me know that they found this sentence confusing. To clarify, I do have personal views on which causes are higher impact than others, but the program design of EA Global was not an attempt to steer EA on the basis of those views.
Trying to square this circle, because I think these observations are pretty readily reconcilable. My second-hand vague recollections from speaking to people at the time are:
Any one of these in isolation would likely have been fine, but the combination left some people feeling various shades of surprised/bait-and-switched/concerned/isolated/unhappy. I think the combination is consistent with both what Ben said and what Kerry said.
Further, (2) and (3) aren't surprising if you think about the way San Francisco EAs are drawn differently to EAs globally; SF is by some margin the largest AI hub, so committed EAs who care a lot about AI disproportionately end up living and working there.
Note that EAG Oxford, organised by the same team in the same month with the same private opinions, didn't have the same issues, or at least it didn't to the best of my knowledge as a participant who cared very little for AI risk at the time. I can't speak to EAG Melbourne but I'd guess the same was true.
While (2) and (3) aren't really CEA's fault, there's a fair challenge as to whether CEA should have anticipated (2) and (3) given the geography, and therefore gone out of their way to avoid (1). I'm moderately sympathetic to this argument but it's very easy to make this kind of point with hindsight; I don't know whether anyone foresaw it. Of course, we can try to avoid the mistake going forward regardless, but then again I didn't hear or read anyone complaining about this at EAG 2016 in this way, so maybe we did?
I think 2016 EAG was more balanced. But I don't think the problem in 2015 was apparent lack of balance per se. It might have been difficult for the EAG organizers to sincerely match the conference programming to promotional EA messaging, since their true preferences were consistent with the extent to which things like AI risk were centered.
The problem is that to the extent to which EA works to maintain a smooth, homogeneous, uncontroversial, technocratic public image, it doesn't match the heterogeneous emphases, methods, and preferences of actual core EAs and EA organizations. This is necessarily going to require some amount of insincerity or disconnect between initial marketing and reality, and represents a substantial cost to that marketing strategy.
If this is basically saying 'we should take care to emphasize that EAs have wide-ranging disagreements of both values and fact that lead them to prioritise a range of different cause areas', then I strongly agree. In the same vein, I think we should emphasize that people who self-identify as 'EAs' represent a wide range of commitment levels.
One reason for this is that depending which university or city someone is in, which meetup they turn up to, and who exactly they talk to, they'll see wildly different distributions of commitment and similarly differing representation of various cause areas.
With that said, I'm not totally sure if that's the point you're making because my personal experience in London is that we've been going out of our way to make the above points for a while; what's an example of marketing which you think works to maintain a homogenous public image?
EffectiveAltruism.org's Introduction to Effective Altruism allocates most of its words to what's effectively an explanation of global poverty EA. A focus on empirical validation, explicit measurement and quantification, and power inequality between the developed and developing world. The Playpump example figures prominently. This would make no sense if I were trying to persuade someone to support animal charity EA or x-risk EA.
Other EA focus areas that imply very different methods are mentioned, but not in a way that makes it clear how EAs ended up there.
If you click "Donate Effectively," you end up on the EA Funds site, which presents the four Fund categories as generic products you might want to allocate a portfolio between. Two of the four products are in effect just letting Nick Beckstead do what he thinks is sensible with the money, which as I've said above is a good idea but a very large leap from the anti-Playpump pitch. "Trust friendly, sensible-seeming agents and empower them to do what they think is sensible" is a very, very different method than "check everything because it's easy to spend money on nice-sounding things of no value."
The GWWC site and Facebook page have a similar dynamic. I mentioned in this post that the page What We Can Achieve mainly references global poverty (though I've been advised that this is an old page pending an update). The GWWC Facebook page seems like it's mostly global poverty stuff, and some promotion of other CEA brands.
It's very plausible to me that in-person EA groups often don't have this problem because individuals don't feel a moral obligation to give the most generically effective pitch for EA, but instead just talk about what they personally care about and find interesting.
Thanks for digging up those examples.
I think 'many methods of doing good fail' has wide applications outside of Global Poverty, but I acknowledge the wider point you're making.
This is a problem I definitely worry about. There was a recent post by 80,000 hours (which annoyingly I now can't find) describing how their founders' approaches to doing good have evolved and updated over the years. Is that something you'd like to see more of?
This is a true dynamic, but to be specific about one of the examples I had in mind: A little before your post was written I was helping someone craft a general 'intro to EA' that they would give at a local event, and we both agreed to make the heterogeneous nature of the movement central to the mini speech without even discussing it. The discussion we had was more about 'which causes and which methods of doing good should we list given limited time', rather than 'which cause/method would provide the most generically effective pitch'.
We didn't want to do the latter for the reason I already gave; coming up with a great 5-minute poverty pitch is worthless-to-negative if the next person a newcomer talks to is entirely focused on AI, and with a diversity of cause areas represented among the 'core' EAs in the room that was a very real risk.
Yes! More clear descriptions of how people have changed their mind would be great. I think it's especially important to be able to identify which things we'd hoped would go well but didn't pan out - and then go back and make sure we're not still implicitly pitching that hope.
I found the post, was struggling before because it's actually part of their career guide rather than a blog post.
Thanks! On a first read, this seems pretty clear and much more like the sort of thing I'd hope to see in introductory material.
I just want to note that we have tried to make this case.
The fund page for the Long-Term Future and EA Community funds includes an extensive list of organizations Nick has funded in the past and of his online writings.
In addition, our original launch post contained the following section:
My guess is that you feel that we haven't made the case for delegating to Nick as strongly or as prominently as we ought to. If so, I'd love some more specific feedback on how we can improve.
I think that in a writeup for the two funds Nick is managing, CEA has done a fine job making it clear what's going on. The launch post here on the Forum was also very clear.
My worry is that this isn't at all what someone attracted by EA's public image would be expecting, since so much of the material is about experimental validation and audit.
I think that there's an opportunity here to figure out how to effectively pitch far-future stuff directly, instead of grafting it onto existing global-poverty messaging. There's a potential pitch centered around: "Future people are morally relevant, neglected, and extremely numerous. Saving the world isn't just a high-minded phrase - here are some specific ways you could steer the course of the future a lot." A lot of Nick Bostrom's early public writing is like this, and a lot of people were persuaded by this sort of thing to try to do something about x-risk. I think there's a lot of potential value in figuring out how to bring more of those sorts of people together, and - when there are promising things in that domain to fund - help them coordinate to fund those things.
In the meantime, it does make sense to offer a fund oriented around the far future, since many EAs do share those preferences. I'm one of them, and think that Nick's first grant was a promising one. It just seems off to me to aggressively market it as an obvious, natural thing for someone who's just been through the GWWC or CEA intro material to put money into. I suspect that many of them would have valid objections that are being rhetorically steamrollered, and a strategy of explicit persuasion has a better chance of actually encountering those objections, and maybe learning from them.
I recognize that I'm recommending a substantial strategy change, and it would be entirely appropriate for CEA to take a while to think about it.
Hey, Ben. Just wanted to note that I found this very helpful. Thank you.
I imagine this has been stressful for all sides, and I do very much appreciate you continuing to engage anyway! I'm looking forward to seeing what happens in the future.
I thought this was a really useful framework to look at the system-level. Thank you for posting this!
Quick points after just reading through it:
1) Your phrasing seems to convey too much certainty to me/flowed too much into a coherent story. I'm not sure if you did this too strongly bring across your points or because that's the confidence level you have in your arguments.
To me, it appears that you view Holden's position of influence at Open AI as something like a zero-sum alpha investment decision (where his amount of control replaces someone else's commensurate control). I don't see why Holden also couldn't have a supportive role where his feedback and different perspectives can help Open AI correct for aspects they've overlooked.
3) Overall principle I got from this: correct for model error through external data and outside views.
I agree this can be the case, and that in the optimistic scenario this is a large part of OpenAI's motivation.
Chris Blattman has put together some of his principles on giving and says he personally ranks GiveDirectly #1, but otherwise believes the "means and end to human well being is good government and political rights and freedoms" and therefore gives to Amnesty International, Human Rights Watch, the ACLU, the Southern Poverty Law Center, the Democratic National Committee, Planned Parenthood, the National Immigration Law Center, and the International Rescue Committee.
Some of those charities are developed-world charities and would likely be seen as ineffective by most EAs. However, he might not give to those charities if he was running an EA Fund (similar to how many GiveWell staff are donating to charities not recommended by GiveWell), or maybe multiple people could run the fund together.
One thing I like about Blattman's work is that he has done a lot of research on armed conflict and violence and how to prevent it (with high-quality RCTs). This area seems to be very neglected in EA:
EAs seem to focus on health most of the time (e.g. Charity Entrepreneurship almost exclusively evaluated health programs). There are lots of good reasons for focusing on health, and maybe the goal of EA is not to find all the best charities/programs but only some of them such that there's enough RFMF for the EA community as a whole. However, I'm skeptical and still think non-health approaches are very neglected in EA because:
1) There has been hardly any analysis of other program areas (e.g. so far I haven't seen any kind of back-of-the-envelope analysis focusing on peace and security, nor any kind of "fact post" on the EA forum, nor anything similar),
2) there might be a lot of additional funding available for such alternative approaches (by donors who tend to be more skeptical of GiveWell's health focus, or by donors whose funds are restricted in some way),
3) it would demonstrate to the outside world that EAs are really doing their homework instead of being easily satisfied with some easy-to-measure approaches, and this might accelerate EA movement growth and strengthen its impact and credibility in society at large (which could also increase total funding for top charities).
For these reasons, I would very much like someone like Chris Blattman to be involved with the EA Funds in some way (maybe not as a fund manager). Or some external review of GiveWell's work by someone like Blattman.
EDIT: Actually Open Phil wrote a bit about aid in fragile contexts: http://www.openphilanthropy.org/research/cause-reports/fragile-states
80K does briefly compare deaths from health-related causes to deaths from war, but I agree it would be nice to see a more detailed, nuanced analysis that took into account Blattman and others' arguments.
I left a similar comment in GiveWell's June 2017 open thread – let's see what they say:
This comment is confusing. The content is entirely common knowledge around here, it doesn't respond to any of the main claims of the post it responds to, and it's very long. Why did you post it?
Fyi, original comment was deleted and it now looks like you're criticizing a reasonable post, at least on mobile.
Thanks! Someone posted a multiple-page (on mobile) comment explaining Parfit's argument regarding extinction being much worse than 90% of people dying, amongst other things, that had basically no relevance to the OP.
If a mod wants to go ahead and clear all four comments here that'd be great.
I'm deeply sorry. I sometimes say something without catching context. Please understand I am a very newcomer on EA and this forum. I promise I will comment more carefully from now on.
Surely your comment would‘ve been very informative on its own.
Welcome to the forum! :-D
When I look at this on mobile I see: https://goo.gl/photos/uzum9yU8YWceuUSg6
This doesn't look confusing to me, but does it to you? Or do you see something else?
(If the layout makes it look like replies to deleted comments are replies to the post, that's a problem we should and can fix.)
i can see it clearly now, not sure if I was inattentive or something went wrong the first time I loaded the page.
if it happens again, I'd love a screenshot so I can debug
I also originally saw the reply attributed to a different comment on Mobile.