richard_ngo's Quick takes

I think it would be helpful for you to mention and highlight your conflict-of-interest here.

I remember becoming much more positive about ads after starting work at Google. After I left, I slowly became more cynical about them again, and now I'm back down to ~2018 levels. 

EDIT: I don't think this comment should get more than say 10-20 karma. I think it was a quick suggestion/correction that Richard ended up following, not too insightful or useful.

I appreciate you drawing attention to the downside risks of public advocacy, and I broadly agree that they exist, but I also think the (admittedly) exaggerated framings here are doing a lot of work (basically just intuition pumping, for better or worse). The argument would be just as strong in the opposite direction if we swap the valence and optimism/pessimism of the passages: what if, in scenario one, the AI safety community continues making incremental progress on specific topics in interpretability and scalable oversight but achieves too little too slowly and fails to avert the risk of unforeseen emergent capabilities in large models driven by race dynamics, or even worse, accelerates those dynamics by drawing more talent to capabilities work? Whereas in scenario two, what if the AI safety movement becomes similar to the environmental movement by using public advocacy to build coalitions among diverse interest groups, becoming a major focus of national legislation and international cooperation, moving hundreds of billions of $ into clean tech research, etc.

Don't get me wrong — there's a place for intuition pumps like this, and I use them often. But I also think that both technical and advocacy approaches could be productive or counterproductive, and so it's best for us to cautiously approach both and evaluate the risks and merits of specific proposals on their own. In terms of the things you mention driving bad outcomes for advocacy, I'm not sure if I agree — feeling uncertain about paying for ChatGPT seems like a natural response for someone worried about OpenAI's use of capital, and I haven't seen evidence that Holly (in the post you link) is exaggerating any risks to whip up support. We could disagree about these things, but my main point is that actually getting into the details of those disagreements is probably more useful in service of avoiding the second scenario than just describing it in pessimistic terms.

This kind of reads as saying that 1 would be good because it's fun (it's also kind of your job, right?) and 2 would be bad because it's depressing. 

"hesitate to pay for ChatGPT because it feels like they're contributing to the problem"

Yep that's me right now and I would hardly call myself a Luddite (maybe I am tho?)

Can you explain why you frame this as an obviously bad thing to do? Refusing to help fund the most cutting edge AI company, which has been credited by multiple people with spurring on the AI race and attracting billions of dollars to AI capabilities seems not-unreasonable at the very least, even if that approach does happen to be wrong.

Sure there are decent arguments against not paying for chat GPT, like the LLM not being dangerous in and of itself, and the small amount of money we pay not making a significant difference, but it doesn't seem to be prima-facie-obviously-net-bad-luddite behavior, which is what you seem to paint it as in the post.

One exchange that makes me feel particularly worried about Scenario 2 is this one here, which focuses on the concern that there's:

No rigorous basis for that the use of mechanistic interpretability would "open up possibilities" to long-term safety.  And plenty of possibilities for corporate marketers – to chime in on mechint's hypothetical big breakthroughs. In practice, we may help AI labs again – accidentally – to safety-wash their AI products.

I would like to point to this as a central example of the type of thing I'm worried about in scenario 2: the sort of doom spiral where people end up actively opposed to the most productive lines of research we have, because they're conceiving of the problem as being arbitrarily hard. This feels very reminiscent of the environmentalists who oppose carbon capture or nuclear energy because it might make people feel better without solving the "real problem".

It looks like, on net, people disagree with my take in the original post. So I'd like to ask the people who disagree: do you have reasons to think that the sort of position I've quoted here won't become much more common as AI safety becomes much more activism-focused? Or do you think it would be good if it did?

history is full of cases where people dramatically underestimated the growth of scientific knowledge, and its ability to solve big problems.

There are 2 concurrent research programs, and if one program (capability) completes before the other one (alignment), we all die, but the capability program is an easier technical problem than the alignment program. Do you disagree with that framing? If not, then how does "research might proceed faster than we expect" give you hope rather than dread?

Also, I'm guessing you would oppose a worldwide ban starting today on all "experimental" AI research (i.e., all use of computing resources to run AIs) till the scholars of the world settle on how to keep an AI aligned through the transition to superintelligence. That's my guess, but please confirm. In your answer, please imagine that the ban is feasible and in fact can be effective ("leak-proof"?) enough to give the AI theorists all they time they need to settle on a plan even if that takes many decades. In other words, please indulge me this hypothetical question because I suspect it is a crux.

"Settled" here means that a majority of non-senile scholars / researchers who've worked full-time on the program for at least 15 years of their lives agree that it is safe for experiments to start as long as they adhere to a particular plan (which this majority agree on). Kinda like the way scholars have settled on the conclusion that anthropogenic emissions of carbon dioxide are causing the Earth to warm up.

I realize that there are safe experiments that would help the scholars of the world a lot in their theorizing about alignment, but I also expect that the scholars / theorist could probably settle on a safe effective plan without the benefit of experiments beyond the experiments that have been run up to now even though it might take them longer than it would with the benefit. Do you agree?

Interesting and insightful framing! I think the main concern I have is that your scenario 1 doesn't engage much with the idea of capability info hazards and the point that some of the people who nerd out about technical research lack moral seriousness or big-picture awareness to not always push ahead.

Re: Hacker culture

AI safety becomes the single community that's the most knowledgeable about cutting-edge ML systems. The smartest up-and-coming ML researchers find themselves constantly coming to AI safety spaces, because that's the place to go if you want to nerd out about the models. It feels like the early days of hacker culture.

I'd like to constructively push back on this: The research and open-source communities outside AI Safety that I'm embedded in are arguably just as, if not more hands-on, since their attitude towards deployment is usually more ... unrestricted. For context, I mess around with generative agents and learning agents.

I broadly agree that the AI Safety community is very smart people working on very challenging and impactful problems. I'm just skeptical that what you've described is particularly unique to AI Safety, and think that descriptiom would apply to many ML-related spaces. Then again, I could be extremely inexperienced and unaware of the knowledge gap between top AI Safety researchers and everyone else.

Re: Environmentalism

much more similar to the environmentalist movement. It has broader reach, but alienates a lot of the most competent people in the relevant fields. ML researchers who find themselves in AI safety spaces are told they're "worse than Hitler"

I was a climate activist organising FridaysForFuture (FFF) protests, and I don't recall this was ever the prevailing perception/attitude. Mainstream activist movements and scientists put up a united front, and they still mutually support each other today. Even if it was superficial, FFF always emphasised "listen to the science".

From a survey of FFF activists:

Our data show that activists overwhelmingly derive their goals from scientific knowledge and reject the idea that science could be used imprecisely just as an instrument to attain their goals.^[1]

I'm also fairly certain the environmentalist was a counterfactual net positive, with Will Macaskill himself commenting on the role of climate advocacy in funding solar energy research and accelerating climate commitments in What We Owe The Future. However, I will admit that the anti-nuclear stance was exactly as dumb as you've implied, and it embarrasses me how many activists expressed it.

Re: Enemy of my Enemy

Personally, I draw a meaningful distinction between being anti-AI capabilities and pro-AI Safety. Both are strongly and openly concerned about rapid AI progress, but the two groups have very different motivations, proposed solutions and degree of epistemic rigour. Being anti-AI does not mean pro AI Safety, the former is a much larger umbrella movement of people expressing strong opinions on a disruptive, often misunderstood field.

1. ^{^}

   Frontiers | “Listen to the science!”—The role of scientific knowledge for the Fridays for Future movement (frontiersin.org)

I think that the 2-scenario model described here is very important, and should be a foundation for thinking about the future of AI safety.

However, I think that both scenarios will also be compromised to hell. The attack surface for the AI safety community will be massive in both scenarios, ludicrously massive in scenario #2, but nonetheless still nightmarishly large in scenario #1.

Assessment of both scenarios revolves around how inevitable you think slow takeoff is- I think that some aspects of slow takeoff, such as intelligence agencies, already started around 10 years ago and at this point just involve a lot of finger crossing and hoping for the best.

Just like environmentalists often block some of the most valuable work on fixing climate change (e.g. nuclear energy, geoengineering, land use reform)

Something else you may note here.  The reason environmentalists are wrong is they focus on the local issue and ignore the larger picture.  

Nuclear energy: they focus on the local risk of a meltdown or waste disposal, and ignore the carbon emitting power plants that must be there somewhere else for each nuclear plant they successfully block.  Carbon emissions are global, even the worst nuclear disaster is local.

Geoengineering: they simply won't engage on actually discussing the cost benefit ratios.  Their reasoning shuts down or they argue "we can't know the consequences" as an argument to do nothing.  This ignores the bigger picture that temperatures are rising and will continue to rise in all scenarios.

Land use reform : they focus on the local habitat loss to convert a house to apartments, or an empty lot to apartments, and ignore that laws of conservation of number of humans.  Each human who can't live in the apartment will live somewhere, and probably at lower density with more total environmental damage.

Demanding AI Pauses: This locally stops model training, if approved, in the USA and EU.  The places they can see if they bring out the signs in San Francisco.  It means that top AI lab employees will be laid off, bringing any "secret sauce" with them to work for foreign labs who are not restricted.  It also frees up wafer production for foreign labs to order compute on the same wafers.  If Nvidia is blocked from manufacturing H100s, it frees up a share in the market for a foreign chip vendor.

It has minimal, possibly zero effect on the development of AGI if you think wafer production is the rate limiting factor.

I understand the sentiment, but there's a lot here I disagree with. I'll discuss mainly one.

In the case of global health, I disagree that"thoughtful people trying very hard to address a serious problem still almost always dramatically underrate the scale of technological progress." 

This doesn't fit with the history of malaria and other infectious diseases where the opposite has happened, optimism about technological progress has often exceed reality. 

About 60 years ago humanity was positive about eradicating malaria with technological progress. We had used (non-political) swamp draining and DDT spraying to massively reduce the global burden of malaria, wiping it out from countries like the USA and India. If you had done a prediction market in 1970, many malaria experts would have predicted we would have eradicated malaria by now - including potentially with vaccines, in fact it was a vibrant topic of conversation at the time, with many in the 60s believing a malaria vaccine would be here before now.

Again in 1979 after smallpox was eradicated, if you asked global health people how many human diseases we would eradicate by 2023, I'm sure the answer would have been higher than zero - the current situation.

Many diseases have had disturbingly slow technological progress, despite decades passing and billions of dollars spent. Tuberculosis for example could be considered a better vaccine candidate than malaria, yet it took 100 years to get a vaccine which might be 50% effective at best. We still have no good point of care test for the disease.

There are also rational reasons that led us to believe that in this specific case, making a malaria vaccine would be extremely difficult or even impossible - not just because we were luddites who lacked optimism. Malaria vaccines are the first ever to be invented that works against a large parasite - all previous vaccines worked against bacteria and viruses, and this even while we have failed to invent reliable vaccinations for many diseases that should be far easier than malaria. In the specific case of malaria you might be correct, we may have underrated the scale of progress, but I don't think this can be generalised across the global health field, and certainly not "dramatically)

A couple of other notes

First, I don't think anyone has mentioned that vaccine trials have all been undertaken in the context of widespread mosquito net use. Their efficacy would be far far worse, and maybe even not over useful thresholds without the widespread net distributions which Effective Altruists have pushed so hard. Vaccine rollouts may have been partially made possible or sped up by fairly ubiquitous mosquito net use, rather than what you seem to suggest that progress may have been hampered by resources diverted away form vaccine development towards nets

I also think there are some misunderstandings about the fundamentals of malaria here as well. For example @John G. Halstead mentioned countries eradicating malaria through draining swamps, but this was only possible because they were at the edges of the malaria map, where cutting off malaria transmission is much easier. This isn't a magic bullet closer to the equator. Draining Sub-saharan African swamps would not wipe out malaria there (although it might improve the situation somewhat)

I don't think you need to be mournful in this case, because 

1. There's still a decent chance, even with 20/20 hindsight that this wasn't a failure on the EA front, given that mosquito nets may aid vaccine efficiency, and also see @Linch  and other's comments below. 
2. Even if we did get this bet wrong, and money would have been better spent on vaccine development in this case, it may be an outlier case, not because global health people generally underestimate technological progress.

Do you think that if GiveWell hadn't recommended bednets/effective altruists hadn't endorsed bednets it would have led to more investment in vaccine development/gene drives etc.? That doesn't seem intuitive to me.

To me GiveWell fit a particular demand, which was for charitable donations that would have reliably high marginal impact. Or maybe to be more precise, for charitable donations recommended by an entity that made a good faith effort without obvious mistakes to find the highest reliable marginal impact donation. Scientific research does not have that structure since the outcomes are unpredictable. 

I don't think it makes sense to think of EA as a monolith which both promoted bednets and is enthusiastic about engaging with the kind of reasoning you're advocating here. My oversimplified model of the situation is more like:

• Some EAs don't feel very persuaded by this kind of reasoning, and end up donating to global development stuff like bednets.
• Some EAs are moved by this kind of reasoning, and decide not to engage with global development because this kind of reasoning suggests higher impact alternatives. They don't really spend much time thinking about how to best address global development, because they're doing things they think are more important.

(I think the EAs in the latter category have their own failure modes and wouldn't obviously have gotten the malaria thing right (assuming you're right that a mistake was made) if they had really tried to get it right, tbc.)

I think I'd be more convinced if you backed your claim up with some numbers, even loose ones. Maybe I'm missing something, but imo there just aren't enough zeros for this to be a massive fuckup.

Fairly simple BOTEC:

• 2 billion people at significant risk of malaria (WHO says 3 billion "at risk" but I assume the first 2 billion is at significantly higher risk than the last billion).
  • note that Africa has ~95% of cases/deaths and a population of 1.2 billion; I assume you can get a large majority of the benefits if you ignore northern Africa too. 
• LLINs last 3 years.
• a bednet covers ~1.5 people (can't find a source so just a guess; note that the main protected population for bednets are mothers and their young children, who usually sleep in the same bed).
• Say LLINs cost ~$4.50 for simple math (AMF says $2, GiveWell says $5-6; I think it depends on how you do moral accounting)
• So it costs $2B/year to cover almost all vulnerable people with bednets at current margins.
  • and likely <1B/year if we are fine with just covering the most vulnerable 5/6 of Africa.
• At 5-10%/year cost of capital, this is equivalent to $20B-$40B to have bednets forever.
  • even less if it's more targeted.
• Given how much money has already went into malaria R&D, we're already at less than one OOM difference (This is assuming that future R&D costs and implementation costs are a rounding error, which seems very unlikely to me).
• Getting rid of malaria forever is a lot better than bednets forever, but given how effective bednets are, and noting that even gene drives and vaccines are unlikely to be a completely "clean" solution either, adding half an OOM sounds about right, maybe 1 OOM is the upper bound. 
• Meanwhile the diminishing marginal curve for R&D is likely to be a lot sharper than the diminishing marginal returns curve for bednets. 
  • I've never drawn out the curve so I don't know what it looks like but I can easily see >1 OOM difference here.
• So at least the view from 10,000 feet up doesn't give you an obvious win for research vs bednets; and on balance I think it tilts in the other direction locally on EV grounds, even if you don't adjust for benefits of certainty.
• This analysis lacks a bunch of fairly important considerations in both directions (eg economic growth pushes in favor of wanting "band-aid" solutions now because richer countries are better equipped to deal with their own systemic problems, climate change pushes in favor of eradication), which might be enough to flip the direction of the inequality, but very unlikely to flip it by >1 OOM. And I suspect ballpicking numbers or analysis like the above is the core reason why some of the more quant-y committed global health/poverty EAs aren't sold on the "obviously technological solutions are better than band-aid solutions" argument that SV people sometimes make unreflectively.

Global development EAs were very much looking into vaccines around 2015 and then and now it seemed that the malaria vaccine is just not crazy cost-effective, because you have to administer it more than once and it's not 100% effective - see

Public health impact and cost-effectiveness of the RTS,S/AS01 malaria vaccine: a systematic comparison of predictions from four mathematical models

Modelling the relative cost-effectiveness of the RTS,S/AS01 malaria vaccine compared to investment in vector control or chemoprophylaxis 

An article on why we didn't get a vaccine sooner: https://worksinprogress.co/issue/why-we-didnt-get-a-malaria-vaccine-sooner

This seems like significant evidence for the tractability of speeding things up. E.g. a single (unjustified) decision by the WHO in 2015 delayed the vaccine by almost a decade, four years of which were spent in fundraising. It seems very plausible that even 2015 EA could have sped things up by multiple years in expectation either lobbying against the original decision, or funding the follow-up trial.

Retracted my last comment, since as joshcmorrison pointed out, the vaccines aren't mRNA-based.

Still, "Total malaria R&D investment from 2007 to 2018 was over $7 billion, according to data from Policy Cures Research in the report. Of that total, about $1.8 billion went to vaccine R&D."

https://www.devex.com/news/just-over-600m-a-year-goes-to-malaria-r-d-can-covid-19-change-that-98708/amp

I'm sympathetic to this. I also think it is interesting to look at how countries that eradicated malaria did so, and it wasn't with bednets, it was through draining swamps etc. 

(fwiw, I don't think that criticism applies to EA work on climate change. Johannes Ackva is focused on policy change to encourage neglected low carbon technologies.)

The new malaria vaccines are mRNA vaccines, and mRNA vaccines were largely developed in response to COVID. I think billions were spent on mRNA R&D. That could have been too expensive for Open Phil, and they might not have been able to foresee the promise of mRNA in particular to invest so much specifically in it and not waste substantially on other vaccine R&D.

Open Phil has been funding R&D on malaria for some time, including gene drives, but not much on vaccines until recently. https://www.openphilanthropy.org/grants/?q=malaria&focus-area[]=scientific-research

EDIT: By the US government alone, $337 million was invested in mRNA R&D pre-pandemic over decades (and the authors found $5.9 billion in indirect grants), and after the pandemic started, "$2.2bn (7%) supported clinical trials, and $108m (<1%) supported manufacturing plus basic and translational science" https://www.bmj.com/content/380/bmj-2022-073747

Moderna also spent over a billion on R&D, and their focus is mRNA. (May be some or substantial overlap with US funding.) Pfizer and BioNTech also developed mRNA COVID vaccines together.

Another related thing that isn't discussed enough is the immense difficulty of actually doing good research, especially in a pre-paradigmatic field. I've personally struggled to transition from engineer mindset, where you're just trying to build a thing that works (and you'll know when it does), to scientist mindset, where you need to understand the complex ways in which many different variables affect your results.

This isn't to say that only geniuses make important advances, though - hard work and persistence go a long way. As a corollary, if you're in a field where hard work doesn't feel like work, then you have a huge advantage. And it's also good for building a healthy EA community if even people who don't manage to have a big impact are still excited about their careers. So that's why I personally place a fairly high emphasis on passion when giving career advice (unless I'm talking to someone with exceptional focus and determination).

I think the strongest high-level argument for Givewell charities vs. most developed-world charity is the 100x multiplier.

That's a strong reason to suspect the best opportunities to improve the lives of current humanity lie in the developing world, but not decisive, and so usually analyses have been done, particularly of 'fan-favourite' causes like the ones you mention. 

I'd also note that both the examples you gave are not what I would consider 'Mainstream charity'; both have prima facie plausible paths for high leverage (even if 100x feels a stretch), and if I had to guess right now my gut instinct is that both are in the top 25% for effectiveness. 'Mainstream charity' in my mind looks more like 'your local church', 'the arts', or 'your local homeless shelter'. Some quantified insight into what people in the UK actually give to here.

At any rate, climate-change has had a few of these analyses over the years, off the top of my head here's a recent one on the forum looking at the area in general, there's also an old and more specific analysis of Cool Earth by GWWC, which after running through a bunch of numbers concludes:

Even with the most generous assumptions possible, this is still at least one order of magnitude greater than the cost of saving a life through donations to highly effective health charities such as the Against Malaria Foundation (at $3,461).

As for other areas, Givewell, (in?)famously, used to recommend charities in US education, but stopped after deciding their estimated effectiveness didn't stack up to what they could achieve in the Global Health/Poverty space. 

I don't have anything to hand for the US Democratic party, but lots of people talked in various places about donations directed at helping the Clinton campaign in 2016 and then the Biden campaign in 2020, so I'd start there. 80k's thoughts on the value of a vote would be a starting point.

If the case hasn't been made

On a different note, I'm somewhere between bemused and disappointed that you could think this is a possibility, especially for causes which many EAs were very positively disposed to prior to their involvement with EA (and in the case of climate change, a large number remain so!). To be clear, I'm mostly disappointed in the movement's ability to propagate information forward and in the fact that such analysis has apparently become so rare that you might think such common questions have never been looked at. Also to be clear, it could well be that the cases made are wrong, and I'd be happy to see refutations, but suggesting they haven't been made is quite a bit stronger; suggests a wilful blind spot, and I'm reminded of this SSC post. 

It's plausible to me that there's something near-term we simply haven't done an analysis of, and should have done, and if we did it would look very strong, but if so I'd strongly expect to be in an area that does not naturally occur to EA's core demographic, rather than in areas and ideas that naturally occur to that group.

After chatting with Alex Gordon-Brown, I updated significantly towards his position, which I've attempted to summarise below. Many thanks to him for taking the time to talk; I've done my best to accurately represent the conversation, but there may be mistakes. All of the following are conditional on focusing on near-term, human-centric charities.

Three key things I changed my mind on:

1. I had mentally characterised EA as starting with Givewell-style reasoning, and then moving on to less quantifiable things. Whereas Alex (who was around at the time) pointed out that there were originally significant disagreements between EAs and Givewell, in particular with EAs arguing for less quantifiable approaches. EA and Givewell then ended up converging more over time, both as EAs found that it was surprisingly hard to beat Givewell charities even allowing for less rigorous analysis, and also as people at Givewell (e.g. the ones now running OpenPhil) became more convinced in less-quantifiable EA methodologies.
   1. Insofar as the wider world has the impression of EA as synonymous with Givewell-style reasoning, a lot of that comes from media reports focusing on it in ways we weren't responsible for.
   2. Alex claims that Doing Good Better, which also leans in this direction, wasn't fully representative of the beliefs of core EAs at the time it was published.
2. Alex says that OpenPhil has found Givewell charities surprisingly hard to beat, and that this (along with other EA knowledge and arguments, such as the 100x multiplier) is sufficient to make a "compelling case" for them.
   1. Alex acknowledges that not many people who recommend Givewell are doing so because of this evidence; in some sense, it's a "happy coincidence" that the thing people were already recommending has been vindicated. But he thinks that there are enough careful EAs who pay attention to OpenPhil's reports that, if their conclusions had been the opposite, I would have heard people publicly making this case.
3. Alex argues that I'm overly steelmanning the criticism that EA has received. EA spent a lot of time responding to criticisms that it's impossible to know that any charities are doing a lot of good (e.g. because of potential corruption, and so on), and criticisms that we should care more about people near us, and so on. Even when it came to "systemic change" critiques, these usually weren't principled critiques about the importance of systemic change in general, but rather just "you should focus on my personal cause", in particular highly politicised causes.

Alex also notes that the Givewell headline claim "We search for the charities that save or improve lives the most per dollar" is relatively new (here's an earlier version) and has already received criticism.

Things I haven't changed my mind about:

1. I still think that most individual EAs should be much more careful in recommending Givewell charities. OpenPhil's conclusions are based primarily off (in their words) "back-of-the-envelope calculations", the details of which we don't know. I think that, even if this is enough to satisfy people who trust OpenPhil's researchers and their methodologies, it's far less legible and rigorous than most people who hear about EA endorsement of Givewell  charities would expect. Indeed, they still conclude that (in expectation) their hits-based portfolio will moderately outperform Givewell.
2. OpenPhil's claims are personally not enough to satisfy me. I think by default I won't endorse Givewell charities. Instead I'll abstain from having an opinion on what the best near-term human-centric charities are, and push for something more longtermist like pandemic prevention as a "default" outreach cause area instead. But I also don't think it's unreasonable for other people to endorse Givewell charities under the EA name.
3. I still think that the 100x multiplier argument is (roughly) cancelled out by the multiplier going the other way, of wealthy countries having at least 100x more influence over the world. So, while it's still a good argument for trying to help the poorest people, it doesn't seem like a compelling argument for trying to help the poorest people via direct interventions in poor countries.

Overall lessons: I overestimated the extent to which my bubble was representative of EA, and also the extent to which I understood the history of EA accurately.

Alex and I finished by briefly discussing AI safety, where I'm quite concerned about a lack of justification for many of the claims EAs make. I'm hoping to address this more elsewhere.

Thank you for writing this post-- I have the same intuition as you about this being very misleading and found this thread really helpful.

Here's Rob Wiblin:

We have been taking on the enormous problem of ‘how to help others do the most good’ and had to start somewhere. The natural place for us, GiveWell and other research groups to ‘cut our teeth’ was by looking at the cause areas and approaches where the empirical evidence was strongest, such as the health improvement from anti-malarial bednets, or determining in which careers people could best ‘earn to give’.
Having learned from that research experience we are in a better position to evaluate approaches to systemic change, which are usually less transparent or experimental, and compare them to non-systemic options.

From my perspective at least, this seems like political spin. If advocacy for anti-malarial bednets was mainly intended as a way to "cut our teeth", rather than a set of literal claims about how to do the most good, then EA has been systematically misleading people for years.

Nor does it seem to me that we're actually in a significantly better position to evaluate approaches to systemic change now, except insofar as we've attracted more people. But if those people were attracted because of our misleading claims, then this is not a defence.

You may also be interested in this piece from Open Phil:

https://www.openphilanthropy.org/blog/givewells-top-charities-are-increasingly-hard-beat

See also: Effective Altruism is an Ideology not (just) a Question.

Not endorsed by me, personally. I wouldn't call someone "not EA-aligned" if they disagreed about all of the worldview claims you made, but really care about understanding if someone is genuinely trying to answer the Question.

Empirically, it seems like the world is not improved the most by people whose primary motivation is helping others, but rather by people whose primary motivation is achieving something amazing. If this is true, that's a strong argument against slave morality.

This is seems very wrong to me on a historical basis. When I think of the individuals who have done the most good for the world, I think of people who made medical advances like the smallpox vaccine, scientists who discovered new technologies like electricity, and social movements like abolitionism that defeated a great and widespread harm.  These people might want to "achieve something amazing", but they also have communitarian goals: to spread knowledge, help people or avert widespread suffering. 

Also, it's super weird to take the Nietzschean master and slave morality framework at face value. it does not seem to be an accurate representation of the morality systems of people today. 

Very interesting points. Here are a few other things to think about:
1. I think there are very few people whose primary motivation is helping others, so we shouldn't empirically expect them to be doing the most good because they represent a very small portion of the population. This is especially true if you think (which I do) that the vast majority of people who do good are 1) (consciously or unconsciously) signaling for social status or 2) not doing good very effectively (the people who are are a much smaller subgroup because doing non-effective good is easy). It would be very surprising, however, if those who try to do good effectively aren't doing much better than those who aren't, as individuals, on average, but it seems unlikely to me (though feel free to throw some stats that will change my mind!). 

2. I'm very skeptical that "the defensibility of morality as the pursuit of greatness depends on how sophisticated our cultural conceptions of greatness are." Could you give more reason for why you think this? 

3. I'm skeptical that 1) searching for equanimity is truly the best thing and 2) that we have good and tractable methods of achieving it. Perhaps people would be better off as being more Buddhist on the margin, but, to me, it seems like (thoughtfully!) getting the heavy positive tail end results and be really careful and thoughtful about negatives leads to a much better off society. 

Let me know what you think! 

“...whether there's some divergence between what's most valuable for them and what's most valuable for infrequent browsers.”

I’d strongly guess that this is the case. Maybe Community posts should be removed from Forum favorites?

I think that's a good point, though I've heard it discussed a fair amount. One way of thinking about it is that 'direct work' also has movement building benefits. This makes the ideal fraction of direct work in the portfolio higher than it first seems.

.