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mlsbt
Karma: 122
The problem of artificial suffering
This type of piece is what the Criticism contest was designed for, and I hope it gets a lot of attention and discussion. EA should have the courage of its convictions; global poverty and AI alignment aren’t going to be solved by a friend group, let alone the same friend group.
I think the wording of your options is a bit misleading. It’s valuable to publish your criticism of any topic that’s taking up non-trivial EA resources, regardless of its true worth as a topic—otherwise we might be wasting bednets money. The important question is whether or not infinite ethics fits this category (I’m unsure, but my best guess is no right now and maybe yes in a few years). Whether or not something is a “serious problem” or “deserves criticism”, at least for me, seems to point to a substantively different claim. More like, “I agree/disagree with the people who think infinite ethics is a valuable research field”. That’s not the relevant question.
I’m using ‘friend group’ as something like a relatively small community with tight social ties and large and diverse set of semi-reliable identifiers.
EA attracts people who want to do large amounts of good. Weighted by engagement, the EA community is made up of people for whom this initial interest in EA was reinforced socially or financially, often both. Many EAs believe that AI alignment is an extremely difficult technical problem, on the scale of questions motivating major research programs in math and physics. My claim is that such a problem won’t be directly solved by this relatively tiny subset of technically-inclined do-gooders, nice people who like meet-ups and have suspiciously convergent interests outside of AI stuff.
EA is a friend group, algebraic geometers are not. Importantly, even if you don’t believe alignment is that difficult, we’d still solve it more quickly without tacking on this whole social framework. It worries me that alignment research isn’t catching on in mainstream academia (like climate change did); this seems to indicate that some factor in the post above (like groupthink) is preventing EAs from either constructing a widely compelling argument for AI safety, or making it compelling for outsiders who aren’t into the whole EA thing.
Basically we shouldn’t tie causes unnecessarily to the EA community—which is a great community—unless we have a really good reason.
This is a great post and the most passionate defense I’ve seen of something like ‘improving institutional decision-making’, but broader, being an underrated cause area. I’m sympathetic to your ideas on the importance of good leadership, and the lack of it (and of low-trust, low-coordination environments more generally) as a plausible root cause behind many of the problems EAs care about most. However, I don’t think this post has the evidence to support your key conclusions, beyond the general intuition that leadership is important.
Some of your thoughts:
If you want to have maximum impact you typically want to focus on leadership and governance. Most solvable problems in the world are really leadership and governance problems at their core.
If you want that impact to be lasting, you should focus on building organizations, institutions, or ecosystems that endure over time.
If you are trying to positively impact any group or initiative, leadership is most often your point of maximum leverage.
Corruption is Mexico’s one fundamental problem.
Note the last point isn’t a key conclusion, but is illustrative of the lack of evidence in this post. Is corruption Mexico’s fundamental problem? The IADB report pretty convincingly argues that societal trust is vital to economic development, and is your best piece of evidence. But it doesn’t argue that trust is the most (or most fundamental) factor, especially outside of Latin America, as opposed to things like effective institutions or more basic economic factors. And note that it indicates that Mexico has the second-highest level of trust in Latin America. Trust isn’t lack of corruption isn’t leadership/governance; they’re all related, but it leaves me confused as to what specifically you’re arguing for.
The rest of your points are huge claims, but other than the IADB report your evidence seems to be the blog post about Haiti and DR’s divergence, and your list of real-world examples. The post about Haiti is suggestive, but is a fundamentally limited example as the history of one small, idiosyncratic country. It discusses the corruption of the Duvaliers, but also a host of other factors, and furthermore argues that the divergence began decades before François came to power. So corruption vs trust isn’t the slam-dunk takeaway that it would need to be to even start thinking about generalizing from Haiti to the world.
Your list of places where ecosystem-building “actually [is] already working” is DARPA, a building at MIT, a math team, and a bunch of clubs. Regarding evidence of their cost-effective impact relative to the current EA paradigm, I’ll give you the first three, which are your “building ecosystems on a limited budget” category. But again, this doesn’t get us far beyond the general intuition that everyone already agrees with, that good leadership is good.
It’s true that the best interventions can often only be identified with hindsight, but that’s less applicable to meta-level criticisms of EA like yours. There are a lot of wonderful-sounding ideas like ecosystem-building out there, that hit all the right intuitions and are hard to explicitly argue against. But should EA make this pivot? That question needs more evidence than what’s in this post.
I think it’s usually okay for an issue-based analysis of the medium-term future to disregard relatively unlikely (though still relevant!) AI / x-risk scenarios. By relatively unlikely, I just mean significantly less likely than business-as-usual, within the particular time frame we’re thinking about. As you said, If the world becomes unrecognizably different in this time frame, factory farming probably stops being a major issue and this analysis is less important. But if it doesn’t, or in the potentially very long time before it does, we won’t gain very much strategic clarity about decreasing farmed animal suffering by approaching it with a longtermist lens. There’s a lot of suffering that probably won’t affect the long-run future but is still worth thinking about effectively. In other words, I don’t think longtermism helps us think about how to be animal advocates today.
By the most recent World Bank and FAO data, as well as the 2017 FAO data you link to, Greece isn’t close to being the largest producer of fish in the EU nor the 15th largest producer in the world. Correct me if I’m wrong, I think the correct claim is that Greece farms the greatest number of fish in the EU. Fish production statistics are generally by total weight rather than fish number, and I see how the latter is more relevant to welfare concerns. However I think your phrasing is a bit misleading, as Greece has a very unique fish industry for the EU. It farms a huge amount of low-weight fish and has a relatively small wild-catch industry. For most (all?) other European countries, total national fish catch (by weight and number) is still dominated by fishing fleet capture rather than aquaculture. I’d be curious to know how your model weights welfare impacts on humane slaughter method adoption vs improving living conditions on farms. If the latter is a bigger deal, I see how Greece can be a high-leverage country to start with, especially considering the growing proportion of aquaculture in fish production worldwide.
Yea, WBE risk seems relatively neglected, maybe because of the really high expectations for AI research in this community. The only article I know talking about it is this paper by Anders Sandberg from FHI. He makes the interesting point that similar incentives that allow animal testing in today’s world could easily lead to WBE suffering. In terms of preventing suffering his main takeaway is:
Principle of assuming the most (PAM): Assume that any emulated system could have the same mental properties as the original system and treat it correspondingly.
The other best practices he mentions, like perfectly blocking pain receptors, would be helpful but only become a real solution with a better theory of suffering.
That’s a good point, at my level thinking about the details of lifetime impact between two good paths might be almost completely intractable. I don’t remember where I first saw that specific idea, it seems like a pretty natural endpoint to the whole EA mindset. And I’ll check out that book, it’s been recommended to me before.
I didn’t call for a ton more analysis, I pointed that the post largely relies on vibes. There’s a difference.
That Wired article is fantastic. I see this threshold of 5 microns all over the place and it turns out to be completely false and based on a historical accident. It’s crazy how once a couple authorities define the official knowledge (in this case, the first few scientists and public health bodies to look at Ward’s paper), it can last for generations with zero critical engagement and cause maybe thousands of deaths.
I’m confused about the distinction between fomite and droplet transmission. Is droplet transmission a term reserved for all non-inhalation respiratory pathogen transmission (like touching a droplet on a surface and then touching your face, or the droplet landing on your mouth), so it includes some forms of fomite transmission? I’m seeing conflicting sources and a lot that mention the >5 μm rule so don’t seem too trustworthy.
Great post. #9 is interesting because the inverse might also be true, making your idea even stronger: maybe a great thing you can do for the short term is to make the long term go well. X-risk interventions naturally overlap with maintaining societal stability, because 1) a rational global order founded in peace and mutual understanding, which relatively speaking we have today more than ever before, reduces the probability of global catastrophes; and less convincingly 2) a catastrophe that nevertheless doesn’t kill everyone would indefinitely set the remaining population back at square one for all neartermist cause areas. Maintaining the global stability we’ve enjoyed since the World Wars is a necessary precondition for the coterminous vast improvements in global health and poverty, and it seems like a great bulk of X-risk work boils down to that. Your #2 is also relevant.
Great post! Quick note: clicking on the carets takes me to that same section rather than the longer intervention descriptions under ‘List of prioritized interventions’.
I think most people would choose S because brain modification is weird and scary. This an intuition that’s irrelevant to the purpose of the hypothetical but is strong enough to make the whole scenario less helpful. I’m very confident that ~0/100 people would choose D, which is what you’re arguing for! Furthermore, if you added a weaker M that changed your emotions so that you simply care much more about random strangers than you currently do, I think many (if not most) people—especially among EAs—would choose that. Doubly so for idealized versions of themselves, the people they want to be making the choice. So again, you are arguing for quite strange intuitions, and I think the brain modification scenario reinforces rather than undermines that claim.
To your second point, we’re lucky that EA cause areas are not prisoner’s dilemmas! Everyday acts of altruism aren’t prisoner’s dilemmas either. By arguing that most people’s imagined inhabitants of utopia ‘shut up and multiply’ rather than divide, I’m just saying that these utopians care *a lot* about strangers, and therefore that caring about strangers is something that regular people hold dear as an important human value, even though they often fail at it. Introducing the dynamics of an adversarial game to this broad truth is a disanalogy.
“Shut Up and Divide” boils down to “actually, you maybe shouldn’t care about individual strangers, because that’s more logically consistent (unless you multiply, in which case it’s equally consistent)”. But caring is a higher and more human virtue than being consistent, especially since there are two options here: be consistent and care about individual strangers, or just be consistent. You only get symmetry if the adoption of ‘can now ethically ignore suffering of strangers’ as a moral principle is considered a win for the divide side. That’s the argument that would really shake the foundations of EA.
Why should we derive our values from our native emotional responses to seeing individual suffering, and not from the equally human paucity of response at seeing large portions of humanity suffer in aggregate? Or should we just keep our scope insensitivity, like our boredom?
So actually we have three choices: divide, multiply, or be scope insensitive. In an ideal world populated by good and rational people, they’d probably still care relatively more about their families, but no one will be indifferent to the suffering of the far away. Loving and empathizing with strangers is widely agreed to be a vital and beautiful part of what makes us human, despite our imperfections. The fact that we have this particular cognitive bias of scope insensitivity may be fundamentally human in some sense, but it’s not really part of what makes us human. Nobody’s calling scope sensitive people sociopaths. Nobody’s personal idea of utopia elevates this principle of scope insensitivity to the level of ‘love others’.
Likewise, very few would prefer/imagine this idealized world as filled with ‘divide’ people rather than ‘multiply’ people. Because:
The weird thing is that both of these emotional self-modification strategies seem to have worked, at least to a great extent. Eliezer has devoted his life to improving the lot of humanity, and I’ve managed to pass up news and discussions about Amanda Knox without a second thought.
Most people’s imagined inhabitants of utopia fit the former profile much more closely. So I think that “Shut Up and Divide” only challenges the Drowning Child argument insofar as you have very strange ethical intuitions, not shared by many. To really attack this foundation you’d have to argue for why these common intuitions about good and bad are wrong, not just that they’re ripe for inconsistencies when held by normal humans (which every set of ethical principles is).
I agree that your (excellent) analysis shows that the welfare increase is dominated by lifting the bottom half of the income distribution. I agree that this welfare effect is what we want. Pritchett’s argument is linked to yours because he claims the only (and therefore best) way to cause this effect is national development. He writes: “all plausible, general, measures of the basics of human material wellbeing [including headcount poverty] will have a strong, non-linear, empirically sufficient and empirically necessary relationship to GDPPC.” (Here non-linear refers to a stronger elasticity of these wellbeing metrics at lower than higher levels of GDPPC).
Of course as you point out national development can’t really be the only thing that decreases poverty—redistribution would too. But every single data point we have of countries shows that the rich got rich through development, not redistribution. And every single data point we have of rich countries shows that the bottom half of their income distributions is doing very well, relative to LMICs. So yes, redistribution would cause great welfare gains for a bit, but it’s not going to turn a $5000 GDPPC nation to a $50000 one. And the welfare gains from that nation’s decreased poverty headcount are going to dwarf the redistribution-caused welfare gains, even given your adjustments. (This isn’t an argument against redistribution as EA cause area, which could still be great; it’s an argument that redistribution’s efficacy isn’t really a point against the greater importance of the search for growth).
Regarding the correlation/causation, I’d be more sympathetic to your point if it was a nice and average correlation. Pritchett: “The simple correlation between the actual $3.20/day or $5.50/day headcount poverty rate and headcount poverty as predicted using only the median of the country distribution is .994 and for $1.90 it is .991. These are about as high a correlation as real world data can produce.” It’s very implausible that this incredibly strong relationship would break with some new intervention that increases median consumption. Not a single policy in the history of the world that changed a country’s median consumption has broken it.
To your final point that the cost of increasing median consumption might be way too high (relative to redistribution) - first of all, as Hillebrandt/Halstead pointed out, evaluating that claim should be a much larger priority in EA than it is right now. But development economics seems to have worked in the past, with just the expenses associated with a normal academic field! I’m sorry but I’m going to quote Pritchett again:
There are a number of countries (e.g. China, India, Vietnam, Indonesia) that said (1) “Based on our reading of the existing evidence (including from economists) we are going to shift from policy stance X to policy stance Y in order to accelerate growth”, (2) these countries did in fact shift from policy stance X to Y and (3) the countries did in fact have a large (to massive) accelerations of growth relative to [business as usual] as measured by standard methods (Pritchett et al 2016).
One had to be particularly stubborn and clever to make the argument: “Politicians changed policies to promote growth based on evidence and then there was growth but (a) this was just dumb luck, the policy shift did not actually cause the shift in growth something else did or (b) (more subtly) the adopted policies did work but that was just dumb luck as there was not enough evidence the policies would work for this to count as a win for ‘evidence’ changing policy.
TL;DR: Increasing productivity still beats redistribution in the long-term given reasonable assumptions about costs.
I’m confused how this squares with Lant Pritchett’s observation that variation in headcount poverty rates across nations, regardless of where you set the poverty line, is completely accounted for by variation in the median of the distribution of consumption expenditures.
I think this is pretty strong evidence that Holden and Parfit are p-zombies :)
In my post I said there’s an apparent symmetry between M and D, so I’m not arguing for choosing D but instead that we are confused and should be uncertain.
You’re right, I misrepresented your point here. This doesn’t affect the broader idea that the apparent symmetry only exists if you have strange ethical intuitions, which are left undefended.
Also, historically, people imagined all kinds of different utopias, based on their religions or ideologies. So I’m not sure we can derive strong conclusions about human values based on these imaginations anyway.
I stand by my claim that ‘loving non-kin’ is a stable and fundamental human value, that over history almost all humans would include it (at least directionally) in their personal utopias, and that it only grows stronger upon reflection. Of course there’s variation, but when ~all of religion and literature has been saying one thing, you can look past the outliers.
Considering your own argument, I don’t see a reason to care how altruistic other people are (including people in imagined utopias), except as a means to an end. That is, if being more altruistic helps people avoid prisoners’ dilemmas and tragedy of the commons, or increases overall welfare in other ways, then I’m all for that, but ultimately my own altruism values people’s welfare, not their values, so if they were not very altruistic, but say there was a superintelligent AI in the utopia that made it so that they had the same quality of life, then why should I care either way? Why should or do others care, if they do? (If it’s just raw unexplained intuitions, then I’m not sure we should put much stock in them.)
I’m not explaining myself well. What I’m trying to say is that the symmetry between dividing and multiplying is superficial—both are consistent, but one also fulfills a deep human value (which I’m trying to argue for with the utopia example), whereas the other ethically ‘allows’ the circumvention of this value. I’m not saying that this value of loving strangers, or being altruistic in and of itself, is fundamental to the project of doing good—in that we agree.
This is a great post and I think this type of thinking is useful for someone who’s specifically debating between working at / founding a small EA organization (that doesn’t have high status outside EA) vs a non-EA organization (or like, Open Phil) early in their career. Ultimately I don’t think it’s that relevant (though still valuable for other reasons) when making career decisions outside this scope, because I don’t think that conflating the EA mission and community is valid. The EA mission is just to do the most good possible; whether or not the community that has sprung up around this mission is a useful vehicle for you as an individual to do the most good you can is a different and difficult question. If you believe that EA as a movement will grow significantly in wealth and ability to affect the world, you could rationally choose to align yourself with EA groups and organizations for career capital / status reasons (not considering first-order impact). However, it seems like the EA community greatly values externally successful people, for instance when hiring; there’s very little insider bias, or at least it’s easy to overcome. When considering next steps I think the mindset of “which option maximizes my lifetime impact” is more correct and useful, though harder to answer individually, than an indirect question like “which option is more aligned with the current EA community” or “which option is ranked higher by 80000 Hours” in almost all cases. I’m sorry if I misunderstood your post, I’m trying to sort out my own thoughts as well. Again, conflating the community and mission is still a useful approximation if you’re considering working for one of the smaller EA organizations, or in a ‘smaller’ role.