Pronouns: she/âher or they/âthem.
I got interested in effective altruism back before it was called effective altruism, back before Giving What We Can had a website. Later on, I got involved in my university EA group and helped run it for a few years. Now Iâm trying to figure out where effective altruism can fit into my life these days and what it means to me.
Okay. I actually watched the TikTok. That shoulda been step 1 â I committed the cardinal sin of commenting without watching. (My previous comment was more responding to the screenshotted comments, based on my past experience with leftist discourse on TikTok and Twitter.)
The TikTok is 100% correct. The creatorâs points and arguments are absolutely correct. Every factual claim she makes is correct. The video is extremely reasonable, fair-minded, and even-handed. The creator is eloquent, perceptive, and clearly very intelligent. She comes across as earnest, sincere, kind, open-minded, and well-meaning. I really liked her brief discussion of Strangers Drowning. Just from this brief video, I already feel some fondness toward her. Based on this first impression, I like her.
If I still had a TikTok account, I would give video a like.
Her exegesis of Peter Singerâs parable of the drowning child is really, really good â quick, breezy, and straight to the point, in a way that should be the envy of any explainer. The only part that was a question mark for me was her use of the term âextreme utilitariansâ. Itâs not exactly inaccurate, though, and it does get the point across, so, now that Iâm thinking about it, I guess itâs actually fine. Come to think of it, if I were trying to explain this idea casually to a friend or an acquaintance or a general audience, I might use a similar phrase like âhardcore utilitariansâ or something.
It isnât a technical term, but she is referring to the extreme personal sacrifice some people will go through for their moral views, or people who take moral views to more of an extreme than the typical person will (even probably the typical utilitarian or the typical moral philosopher).
Her suspicion of the emotional motivations of people in EA who have pivoted from what tends to be more boring, humble, and sometimes gruelling work in global poverty to high-paying, sexy, glamorous, luxurious, fun, exciting work in AI safety is incredibly perceptive and just a really great point. I have said (and others have said) similar things in the past, and even so, the way she said it was so clear and perceptive that I feel I now better understand the point I was trying to make because she said it (and thought it) better. So, kudos to her on that.
I would say your instinct should not be to treat this as a PR or marketing or media problem, or to want to leap into the fray to provide a âcounternarrativeâ. I would say this is actually just perceptive, substantive, eloquently expressed criticism or skepticism. I think the appropriate response is to take it a substantive argument or point.
There are many things people in EA could do if they wanted to do more to establish the credibility of AI safety for a wider audience or for mainstream society. Doing vastly more academic publishing on the topic is one idea. People are right not to take seriously ideas only written on blogs, forums, Twitter, or in books that donât go through any more rigour or academic review than the previous three mediums. Science and academia provide a blueprint for how to establish mainstream credibility of obscure technical ideas.
Iâm sure there are other good ideas out there too. For example, why not get more curious about why AI safety critics, skeptics, and dissenters disagree? Why not figure out their arguments, engage deeply, and respond to them? This could be in informal mediums and not through academic publishing. I think it would be a meaningful step toward persuasion. Itâs kind of embarrassing for AI safety that itâs fairly easy for critics and skeptics to lob up plausible-sounding objections to the AI safety thesis/âworldview and there isnât really a convincing (to me, and to many others) response. Why not do the intellectual work, first, and focus on the PR/âmarketing later?
Something that would go a long way for me, personally, toward establishing at least a bit more good faith and credibility would be if AI safety advocates were willing to burn bad arguments that donât make sense. For instance, if an AI safety advocate were willing to concede the fundamental, glaring flaws in AI 2027 or Situational Awareness, I would personally be willing to listen to them more carefully and take them more seriously. On the other hand, if someone canât acknowledge that this is an atrocious, ridiculous graph, then I sort of feel like I can safely ignore what they say, since overall they havenât demonstrated to me a level of seriousness, credibility, or reasonableness that I would feel is needed if itâs going to be worthwhile for me to engage with their ideas.
Right now, whatever the best arguments in AI safety are, it feels like theyâre all lumped in with the worst arguments, and itâs hard for me not to judge it all based on the worst arguments. I imagine this will be a recurring problem if AI safety tries to gain more mainstream, widespread acceptance. If like 10% of people in EA were constantly talking about how great homeopathy is and is and how itâs curing all their ailments, and how foolish the medical and scientific establishment is for saying itâs just a placebo, would you be as willing to take EA arguments about pandemic risk seriously? Or would you just figure that this community doesnât know what itâs talking about? Thatâs the situation for me with AI safety, and Iâm sure others feel the same way, or would if they encountered AI safety ideas from an initial position of reasonable skepticism.
Those are just my first 2-3 ideas. Other people could probably brainstorm others. Overall, I think the intellectual work is lacking. More marketing/âPR work would either fail or deserve to fail (even if it succeeded), in my view, because the intellectual foundation isnât there yet.
Is this a response to what Gregory Lewis said? I donât think I understand.
Maybe this is subtle/âcomplicated⌠Are the examples youâre citing the actual consensus views of experts? Or are they examples of governments and institutions like the World Health Organization (WHO) misunderstanding what the expert conensus and/âor misrepresenting the expert consensus to the public?
This excerpt from the Nature article you cited makes it sound like the latter:
The change brings the WHOâs messaging in line with what a chorus of aerosol and public-health experts have been trying to get it to say since the earliest days of the outbreak. Many decry the agencyâs slowness in stating â unambiguously â that SARS-CoV-2 is airborne. Interviews conducted by Nature with dozens of specialists on disease transmission suggest that the WHOâs reluctance to accept and communicate evidence for airborne transmission was based on a series of problematic assumptions about how respiratory viruses spread.
Did random members of the EA community â as bright and eager as they might be â with no prior education, training, or experience with relevant fields like public health, epidemiology, virology, and medicine outsmart the majority of relevant experts on this question (airborne vs. not) or any others, not through sheer luck or chance, but by actually doing better research? This is a big claim, and if it is to be believed, it needs strong evidentiary support.
In this Nature article, there is an allegation that the WHO wasnât sufficiently epistemically modest or deferential to the appropriate class of experts:
Other criticisms are that the WHO relies on a narrow band of experts, many of whom havenât studied airborne transmission, and that it eschews a precautionary approach that could have protected countless people in the early stages of the pandemic.
And there is an allegation around communications, rather than around the science itself:
Having shifted its position incrementally over the past two years, the WHO also failed to adequately communicate its changing position, they say. As a result, it didnât emphasize early enough and clearly enough the importance of ventilation and indoor masking, key measures that can prevent airborne spread of the virus.
So, letâs say thereâs another pandemic. Which is the better strategy?
Strategy A: Read forum posts and blog posts by people in the EA community doing original research and opining on epidemiology, virology, and public health who have never so much cracked open a relevant textbook.
Strategy B: Survey sources of expert opinion, including publications like Nature, open letters written on behalf of expert communities, statements by academic and scientific organizations and so on, to determine if a particular institution like the WHO is accurately communicating the majority view of experts, or if theyâre a weird outlier adhering to a minority view, or just communicating the science badly.
I would say the Nature article is support for Strategy B and not at all support for Strategy A.
You could even interpret it as evidence against Strategy A. If you believe the criticism in Nature is right, even experts in an adjacent field or subfield, who have prestigious credentials like advising the WHO, can get things catastrophically wrong by being insufficiently epistemically modest and not deferring enough to the experts who know the most about a subject, and who have done the most research on it. If this is true, then that should make you even more skeptical about how reliable the research and recommendations will be from a non-expert blogger with no relevant education who only started learning about viruses and pandemics for the first time a few weeks ago.
What is described in the Nature piece sound like incredibly subtle mistakes (if we can for sure call them mistakes at this point). Lewisâ critique of the EA community is that it was making incredibly obvious, elementary mistakes. So, why think the EA community can outperform experts on avoiding subtle mistakes if it canât even avoid the obvious mistakes?
One of the recent examples of hubris I saw on the EA Forum was someone asserting that they (or the EA community at large) could resolve, within the next few months/âyears, the fundamental uncertainty around the philosophical assumptions that go into cost-effectiveness estimates comparing shrimp welfare and human welfare. Out of the topics I know well, the philosophy of consciousness might be #1, or at least near the top. I donât know how to convey the level of hubris that comment betrays.
It would be akin to saying that a few people in EA, with no training in physics, could figure out, in a few months or years, the correct theory of quantum gravity and reconcile general relativity and quantum mechanics. Or that a few people in EA, with no training in biology or medicine, would be able to cure cancer within a few months or years. Or that, with no background in finance, business, or economics, that theyâd be able to launch an investment fund that consistently, sustainably achieves more alpha than the worldâs top-performing investment funds every year. Or that, with no background in engineering or science, theyâd be able to beat NASA and SpaceX in sending humans to Mars.
In other words, this is a level of hubris thatâs unfathomable, and just not a serious or credible way to look at the world or your own abilities, in the absence of strong, clear evidence that you possess even average abilities relative to the relevant expert class.
I donât know the first thing about epidemiology, virology, public health, or medicine. So, I canât independently evaluate how appropriate or correct it is/âwas for Gregory Lewis to be so aggravated by the EA communityâs initial response to covid-19 that he considered distancing himself from the movement. I can believe that Lewis might be correct because a) he has the credentials, b) the way heâs describing it is how it essentially always turns out when non-experts think they can outsmart experts in a scientific or medical field without first becoming experts themselves, and c) in areas where I do know enough to independently evaluate the plausibility of assertions made by people in the EA community on the object level, I feel as infuriated and incredulous as Lewis described feeling in that 80,000 Hours interview.
I see these sort of wildly overconfident claims about being able to breezily outsmart experts on difficult scientific, philosophical, or technical problems as moderately, but not dramatically, more credible than the people talking about UFOs or ESP or whatever. (Which apparently is not that rare.)
I see a general rhetorical or discursive strategy employed across many people with fringe views, be they around pseudoscience, fake medicine, or conspiracy theories. First, identify some scandal or blunder or internecine conflict within some scientific expert community. Second, say, âAha! Theyâre not so smart, after all!â Third, use this as support for whatever half-cocked pet theory you came up with. This is obviously a logically invalid argument, as in, obviously the conclusion does not logically follow from the premises. The standard for scientific experts should not be perfection; the standard for amateurs, dilettantes, and non-expert iconoclasts should be showing they can objectively do better than the average expert â not on a single coin flip, but on an objective, unbiased measure of overall performance.
There is a long history in the LessWrong community of opposition to institutional science, with the typical amount of intellectual failure that usually comes with opposition to institutional science. There is a long history of hyperconfidently scorning expert consensus and being dead wrong. Obviously, there is significant overlap between the LessWrong community and the EA community, and significant influence by the former on the latter. What I fear is that this anti-scientific attitude and undisciplined iconoclasm has become a mainstream, everyday part of the EA community, in a way that was not true, or at least not nearly as true, in my experience, in the early-to-mid-2010s.
The obvious rejoinder is: if you really can objectively outperform experts in any field you care to try your hand at for a few weeks, go make billions of dollars right now, or do any other sort of objectively impressive thing that would provide evidence for the idea that you have the abilities you think you do. Surely, within a few months or years of effort, you would have something to show for it. LessWrong has been around for a long time, EA has been around for a long time. Thereâs been plenty of time. Whatâs the excuse for why people havenât done this yet?
And, based on base rates, what would you say is more likely: people being misunderstood iconoclastic self-taught geniuses who are on the cusp of greatness or people just being overly confident based on a lack of experience and a lack of understanding of the problem space?
I donât think any of these are personality traits. These are ideas or strategies that people can discuss and decide whether theyâre wise or unwise. You could, conceivably, have a discussion about one or more of these, become convinced that the way youâve been doing things is unwise, and then change your behaviour subsequently. I wouldnât call that âchanging your personalityâ. I donât see why these would be stable traits, as opposed to things that people can change by thinking about it and deciding to act differently.
I think there might be serious problems with the ideas or strategies that you described, if those were the ideas or strategies at play in EA. But my feeling is you gave a bit of a watered-down, euphemistic retelling of the ideas and strategies than what I tend to see people in EA actually act on, or what they tend to say they believe.
For instance, on covid-19, it seems like some people in EA still think (as evidenced by the comments on this post) that they actually repeatedly outsmarted the expert/âscientific communities on the relevant public health questions â not just by chance or luck, in a âbroken clock is right twice a dayâ or âcalling a coin flipâ way, but by general superior rationality/âepistemology â rather than following a much more epistemically modest, cautious rationale of we âmight be able to contribute something meaningful, and doing so is both low-effort and very good if it works, so worth the shotâ.
I donât buy that thinking this way is a stable personality trait that is beyond your power to change as opposed to something that you can be talked out of.
It seems weird to call any of these things personality traits. Is being an act consequentialist as opposed to a rule consequentialist a personality trait? Obviously not, right? It seems equally obvious to me that what weâre talking about here are not personality traits. It seems equally weird to me to call them personality traits as it would be to call subscribing to rule consequentialism a personality trait.
That looks like an interesting project, but Iâll just state the obvious: late 2021 August 29, 2020 was far too late to call covid early. (The horse is out of the barn, across the street, and eating the neighbourâs oats.)
Also, interesting projects like this by bright, nerdy people arenât meaningful evidence for the underlying thesis that âLessWrong called covid earlyâ is invoked to support, namely, that Eliezer Yudkowskyâs Sequences or the rest of the LessWrong âcanonâ or LessWrongâs overall philosophy or epistemology or culture produces superior rationality in people. If you compared the LessWrong community against some demographically similar cohort like, I donât know, undergraduate students in computer science at UC Berkeley, I imagine you would find all kinds of interesting projects created by the comparison cohort.
If LessWrong is the âinterventionâ and the LessWrong community is the âexperimental groupâ, then we also need a âcontrol groupâ. And we need to look out for confounding variables. For example, if we were to compare LessWrong against the average U.S. population, I would worry there might be differences that could be explained just by education. But if you take some cohort of bright, nerdy, educated people who have never read the Sequences and have never heard of LessWrong, I imagine you would see the same sort of things, like this project, that you see in the LessWrong community.
Itâs worth noting that the most organized, concerted effort of the LessWrong community to teach rationality, the Center for Applied Rationality (CFAR), turned out to be a complete disaster and, worst of all, CFAR also ran a summer camp for kids, meaning that it may have harmed/âdone wrong by children in a similar way as it harmed/âdid wrong by adults.
I think Holden Karnofsky nailed it way back in 2012 when he wrote this:
The Sequences (which I have read the vast majority of) do not seem to me to be a demonstration or evidence of general rationality. They are about rationality; I find them very enjoyable to read; and there is very little they say that I disagree with (or would have disagreed with before I read them). However, they do not seem to demonstrate rationality on the part of the writer, any more than a series of enjoyable, not-obviously-inaccurate essays on the qualities of a good basketball player would demonstrate basketball prowess. I sometimes get the impression that fans of the Sequences are willing to ascribe superior rationality to the writer simply because the content seems smart and insightful to them, without making a critical effort to determine the extent to which the content is novel, actionable and important.
This point is especially correct and important:
I endorse Eliezer Yudkowskyâs statement, âBe careful ⌠any time you find yourself defining the [rationalist] as someone other than the agent who is currently smiling from on top of a giant heap of utility.â To me, the best evidence of superior general rationality (or of insight into it) would be objectively impressive achievements (successful commercial ventures, highly prestigious awards, clear innovations, etc.) and/âor accumulation of wealth and power. As mentioned above, SI [Singularity Institute, now MIRI] staff/âsupporters/âadvocates do not seem particularly impressive on these fronts, at least not as much as I would expect for people who have the sort of insight into rationality that makes it sensible for them to train others in it. I am open to other evidence that SI staff/âsupporters/âadvocates have superior general rationality, but I have not seen it.
And this identification of a problem with overconfidence:
Insufficient self-skepticism given how strong its claims are and how little support its claims have won. Rather than endorsing âOthers have not accepted our arguments, so we will sharpen and/âor reexamine our arguments,â SI seems often to endorse something more like âOthers have not accepted their arguments because they have inferior general rationality,â a stance less likely to lead to improvement on SIâs part.
Plus ça change! How pitiful is our enforced return to those things that were set down in writing many, many years ago.
That seems like a perfectly reasonable, fair challenge to put to GiveWell. Thatâs the right question for people to ask! My impression is that GiveWell, starting early on and continuing today, has acted with humility and put in the grinding hard work to build credibility over time.
I donât think GiveWell would have been a meaningfully useful project if a few people just spent a bit of their spare time over a few weeks to produce the research and recommendations. (Yet that seems sufficient in some cases, such as covid-19, for people in EA to decide to overrule expert opinion.)
It could have been different if there were already a whole field or expert community doing GiveWell-style cost-effectiveness evaluations for global health charities. Part of what GiveWell did was identify a gap in the âmarketâ (so to speak) and fill it. They werenât just replicating the effort of experts.
[Edited on Dec. 16 at 8:50 PM Eastern to add: to clarify, I mean the job GiveWell did was more akin to science journalism or science communication than original scientific research. They were building off of expert consensus rather than challenging it.]
As I recall, GiveWell initially was a project the founders tried to do in their spare time, and then quickly realized was such a big task it would have to be a full-time job. I also hazily recall them doing a lot of work to get up to speed, and also that they had, early on, (and still have) a good process for taking corrections from people outside the organization.
I think as a non-expert waltzing into an established field, you deserve the skepticism and the challenges you will initially get. That is something for you to overcome, that you should welcome as a test. If that is too hard, then the project is too hard.
After all, this is not about status, esteem, ego, or pride, right? Itâs about doing good work, and about doing right by the aid recipients or the ultimate beneficiaries of the work. Itâs not about being right, itâs about getting it right.
Based on my observations and interactions, EA had much more epistemic modesty and much less of a messiah complex in the early-to-mid-2010s, although I saw a genuinely scary and disturbing sign of a messiah complex from a LEAN employee/âvolunteer as early as 2016, who mused on a Skype call about the possibility of EA solving the worldâs problems in priority sequence. (That person, incidentally, also explicitly encouraged me and my fellow university EA group organizer in the Skype meeting to emotionally manipulate students into becoming dedicated effective altruists in a way that I took to be plainly unethical and repugnant. So, overall, a demented conversation.)
The message and tone in the early-to-mid-2010s was more along the lines of: âwe have these ideas about how our obligation to give to charity and about charity cost-effectiveness that might sound radical and counterintuitive, but we want to have a careful, reasonable conversation about it and see if we can convince people weâre on the right trackâ. Whereas by now, in the mid-2020s, the message and tone feels more like: âthe EA community has superior rationality to 99.9% of people on Earth, including experts and academics in fields we just started thinking about 2 weeks ago, and itâs up to us to save the world â no, the lightcone!â. I can see how the latter would be narratively and emotionally compelling to some people, but itâs also extremely off-putting to many other people (like me, perhaps also to Gregory Lewis and other people he knows with backgrounds in public health/âmedicine/âepidemiology/âvirology/âetc., although I donât want to speak for him or the people he knows).
Two years ago, I thought these sort of ideas were way more fringe among the far left than I do now. I could just have terrible luck, but I encountered these sort of ideas way, way, way more than I ever expected I would. And it wasnât just once or twice or with people all in the same social circle. It was at least nine different unconnected individuals or unconnected social circles/âsocial contexts/âcommunities where someone expressed support for at least one of these ideas. Since itâs happened so many times, itâs hard for me to write it off.
In the conversations Iâve had with friends I still have now and donât endorse any of these extreme opinions, theyâve told me their experiences are similar to mine. So, still anecdotal, but still hard to just write off as just my bad luck.
I would find it comforting to see polling that found these to be truly fringe positions within the far left, so if anyone knows of any, please share it.
None of the nine examples Iâm thinking of were algorithmic social media feeds (some were people I knew in real life, some were local people in my community posting online, some were small and semi-private online communities). However, algorithmic social media feeds tend to amplify extreme views. So, if you step into that arena, even if a minority of minority believes something (e.g. 10-20% of the far left which is 5% of the U.S. population, so 0.5-1% of Americans overall), it might get disproportionate attention (e.g. it might look like 10% of the overall American population believes it).
Overall, this is just a warning to anyone who wants to get into the fray of these sort of TikTok/âTwitter short-form algorithmic social media debates with the far left that it might be disconcerting and crazymaking. And a concern that this format/âmedium, in general, may just not be a productive way of changing peopleâs minds about anything or having serious conversations.
Huh? I think everything mentioned in this post (either by me or by Gregory Lewis) are behaviours that people can consciously choose to engage in or not. I donât think any of them are personality traits.
What do you think is an example of a personality trait mentioned in this post?
The number Iâve seen people throw out a few times to estimate the number of people who identify with the effective altruism movement is 10,000, although I donât know where that comes from. In one survey/âpoll I read (I think it was Pew or Gallup), 5% of Americans identify as being on the far left. 5% of the American population is 17 million.
If the American far left is going to change ideologically or culturally, it probably wonât be because of anything the effective altruism movement does. Itâs just too big in comparison. I think thereâs a sense in which youâve just gotta resign yourself to the idea that many people on the far left will dislike effective altruism, insofar as they know anything about it, indefinitely into the future.
I think you have some interesting thoughts about messaging and outreach. For people who are concerned with paternalism or neocolonialism, or who are distrustful of charities, GiveDirectly is a great option. So, promoting GiveDirectly to people with these concerns seems like a good idea. I wonder also if explaining charities that do simple things like the Against Malaria Foundation giving bednets might be appealing to people, too. I feel like thatâs so simple, itâs hard to imagine it somehow being secretly evil.
Iâm personally fairly worn out and discouraged from trying, over many years, to talk to far leftist friends, acquaintances, and members of various communities (online and local). Despite voting for a social democratic party and having many strongly socially progressive and economically progressive/âsocial democratic views, Iâve often had a hard time finding common ground with many people on the far left, to the extent that Iâve ended relationships with friends and acquaintances and left certain communities. Some of the views I hold that I was in several cases not able to find common ground on:
-Governments should be democratic rather than authoritarian
-It is morally unacceptable to commit terrorist attacks against civilians, or to murder your political enemies, and certainly not something to celebrate or glorify
-Joseph Stalin and Mao Zedong were brutal dictators and not praiseworthy or figures to celebrate in any way
I find this very discouraging and depressing, and sad, and infuriating, and scary, and disturbing. I donât know what to do about it. I have no energy left for this kind of engagement, so Iâm not the right person to ask. I guess Iâm just trying to warn you about some of the sort of stuff you might encounter and find yourself having to argue with if you do go down this road of engaging with the far left.
Overall, I find that getting into politics or topical âdiscourseâ on TikTok or Twitter pretty much just sucks up time, attention, energy, and emotional stamina without spitting anything back out (like a black hole). Thereâs just an infinite amount of time-wasting and aggravation that can happen. And what good ever comes of it?
I wonder if thereâs meaningfully such a thing as trying to make better TikTok videos or better tweets or if thatâs like trying to make better cigarettes. I mean, in a sense, yes, you can obviously make better ones. There are lots of people who just do comedy videos on TikTok that I used to enjoy, and Hank Green does some good educational videos I see on YouTube Shorts. But I wonder if going in with the explicit intention of fighting discourse with discourse is going to get anywhere. (I commented on Bellaâs quick take with my thoughts on this as well.)
(Please donât interpret this as dismissive, I donât mean it that way, but I thought about this comic.)
The Ezra Klein Show (one of my favourite podcasts) just released an episode with GiveWell CEO Elie Hassenfeld!
I was specifically responding to your assertion that no one should be able to confidently say X. There are world-class experts like Ilya Sutskever and Demis Hassabis who do confidently say X, and theyâre even on the bullish, optimistic end of the spectrum in terms of AI capabilities forecasts/âAGI forecasts, such that theyâre some of the public figures in AI that people cite when they want to make an argument for near-term AGI. I was only directly responding to that narrow point.
It doesnât really have anything to do with different specific definitions of AGI. Iâm not sure if Sutskever and Hassabis even define AGI the same way, for example. Itâs just what both of them have said about what it will take to get to AGI, which is what you specifically said no one should be able to confidently say X.
On your more general argument that itâs obvious AGI or something enough to AGI is obviously going to be developed soon, or has already been developed, well, no, I donât agree with that general argument. To try to quickly boil down the main cruxes of my counterargument, AI isnât that useful for anything and there are a lot of thorny research problems people have already been banging their heads against for years that we need to make progress on to make AI more useful.
But I was just trying to respond to your narrow point about no one being able to confidently say X. I wasnât trying to open up a general debate about near-term AGI (let alone about regulating the generative AI systems that currently exist). However, if youâre eager, I would be happy to have that debate in the comments of another post (e.g. any of the ones Iâve written on the topic, such as the two I just linked to).
Woah, this is brutal.
Context for everybody: Gregory Lewis is a biorisk researcher with a background in medicine and public health. He describes himself as âheavily involved in Effective Altruismâ. (Heâs not a stranger here: his EA Forum account was created in 2014 and he has 21 posts and 6000 karma.)
The 80,000 Hours Podcast interview was recorded in mid-April 2020. Lewis starts off with a compliment:
If we were to give a fair accounting of all EA has done in and around this pandemic, I think this would overall end up reasonably strongly to its credit. For a few reasons. The first is that a lot of EAs I know were, excuse the term, comfortably ahead of the curve compared to most other people, especially most non-experts in recognizing this at the time: that emerging infectious disease could be a major threat to peopleâs health worldwide. And insofar as their responses to this were typically either going above and beyond in terms of being good citizens or trying to raise the alarm, these seem like all prosocial, good citizen things which reflect well on the community as a whole.
He also pays a compliment to a few people in the EA community who have brainstormed interesting ideas about how to respond to the pandemic and who (as of April 2020) were working on some interesting projects. But he continues (my emphasis added):
But unfortunately Iâve got more to say.
So, putting things politely, a lot of the EA discussion, activity, whatever you want to call it, has been shrouded in this miasma of obnoxious stupidity, and itâs been sufficiently aggravating for someone like me. I sort of want to consider whether I can start calling myself EA adjacent rather than EA, or find some way of distancing myself from the community as a whole. Now the thing I want to stress before I go on to explain why I feel this way is that unfortunately Iâm not alone in having these sorts of reactions.
⌠But at least I have a few people who talk to me now, who, similar to me, have relevant knowledge, background and skills. And also, similar to me, have found this community so infuriating they need to take a break from their social media or want to rage quit the community as a whole. ⌠So I think thereâs just a pattern whereby discussion around this has been very repulsive to people who know a lot about the subject is, I think, a course for grave concern.
That EAâs approval rating seems to fall dramatically with increasing knowledge is not the pattern you typically take as a good sign from the outside view.
Lewis elaborates (my emphasis added again):
And this general sense of just playing very fast and loose is pretty frustrating. I have experienced a few times of someone recommending X, then I go into the literature, find itâs not a very good idea, then I briefly comment going, âHey, this thing here, that seems to be mostly ignoredâ, then I get some pretty facile reply and I give up and go home. And thatâs happened to other people as well. So I guess given all these things, it seems like bits of the EA response were somewhat less than optimal.
And I think for ways it could have been improved were mostly in the modesty direction. So, for example, I think several EAs have independently discovered for themselves things like right censoring or imperfect ascertainment or other bits of epidemiology which inform how you, for example, assess the case fatality ratio. And thatâs great, but all of that was in most textbooks and maybe itâd have saved time had those been consulted first rather than doing something else instead.
More on this consulting textbooks:
But typically for most fields of human endeavor, we have a reasonably good way which is probably reasonably efficient in terms of picking up the relevant level of knowledge and expertise. Now, itâs less efficient if you just target it, if you know in advance what you want to know ahead. But unfortunately, this area tends to be one where itâs a background tacit knowledge thing. Itâs hard to, as it were, rapier-like just stab all the things, in particular, facts you need. And if you miss some then it can be a bit tricky in terms of having good ideas thereafter.
Whatâs worse than inefficiency:
The other problems are people often just having some fairly bad takes on lots of things. And itâs not always bad in terms of getting the wrong answer. I think some of the interventions do seem pretty ill-advised and could be known to be ill-advised if one had maybe done oneâs homework slightly better. These are complicated topics generally: something you thought about for 30 minutes and wrote a Medium post about may not actually be really hitting the cutting edge.
An example of a bad take:
So I think President Trump at the moment is suggesting that, as it were, the cure is worse than the disease with respect to suppression. ⌠But suppose weâre clairvoyant and we see in two yearsâ time, we actually see that was right. ⌠I think very few people would be willing to, well, maybe a few people listening to this podcast can give Trump a lot of credit for calling it well. Because they would probably say, âWell yeah, maybe that was the right decision but he chose it for the wrong reasons or the wrong epistemic qualitiesâ. And I sort of feel like a similar thing sort of often applies here.
So, for example, a lot of EAs are very happy to castigate the UK government when it was more going for mitigation rather than suppression, but for reasons why, just didnât seem to indicate they really attended to any of the relevant issues which you want to be wrestling with. And see that they got it right, but they got it right in the way that stopped clocks are right if you look at them at the right time of day. I think itâs more like an adverse rather than a positive indicator. So thatâs the second thing.
On bad epistemic norms:
And the third thing is when you donât have much knowledge of your, perhaps, limitations and youâre willing to confidently pronounce on various things. This is, I think, somewhat annoying for people like me who maybe know slightly more as Iâm probably expressing from the last five minutes of ranting at you. But moreover, it doesnât necessarily set a good model for the rest of the EA community either. Because things I thought we were about were things like, itâs really important to think things through very carefully before doing things. A lot of your actions can have unforeseen consequences. You should really carefully weigh things up and try and make sure you understand all the relevant information before making a recommendation or making a decision.
And it still feels weâre not really doing that as much as we should be. And I was sort of hoping that EA, in an environment where thereâs a lot of misinformation, lots of outrage on various social media outlets, thereâs also castigation of various figures, I was hoping EA could strike a different tone from all of this and be more measured, more careful and just more better I guess, roughly speaking.
More on EA criticism of the UK government:
Well, I think this is twofold. So one is, if you look at SAGE, which is the Scientific Advisory Group for Emergencies, who released what they had two weeks ago in terms of advice that they were giving the government, which is well worth a read. And my reading of it was essentially they were essentially weeks ahead of EA discourse in terms of all the considerations they should be weighing up. So obviously being worse than the expert group tasked to manage this is not a huge rap in terms of, âWell youâre doing worse than the leading experts in the country.â Thatâs fair enough. But theyâre still overconfident in like, âOh, donât you guys realize that people might die if hospital services get overwhelmed, therefore your policy is wrong.â It seems like just a very facile way of looking at it.
But maybe the thing is first like, not having a very good view. The second would be being way too overconfident that you actually knew the right answer and they didnât. So much that youâre willing to offer a diagnosis, for example, âMaybe the Chief Medical Officer doesnât understand how case ascertainment works or somethingâ. And itâs like this guy was a professor of public health in a past life. I think he probably has got that memo by now. And so on and so forth.
On cloth masks:
I think also the sort of ideas which Iâve seen thrown around are at least pretty dicey. So one, in particular, is the use of cloth masks; we should all be making cloth masks and wearing them.
And Iâm not sure thatâs false. I know the received view in EA land is that medical masks are pretty good for the general population which Iâll just about lean in favor of, although all of these things are uncertain. But cloth masks seem particularly risky insofar as if people arenât sterilizing them regularly which you expect they wonât: a common thing about the public that you care about is actual use rather than perfect use. And you have this moist cloth pad which you repeatedly contaminate and apply to your face which may in fact increase your risk and may in fact even increase the risk of transmission. Itâs mostly based on contact rather than based on direct droplet spreads. And now itâs not like lots of people were touting this. But lots on Twitter were saying this. They cite all the things. They seem not to highlight the RCT which cluster analyzed healthcare workers to medical masks, control, and cloth masks, and found cloth masks did worse than the control.Then you would point out, per protocol, that most people in the controlled arm were using medical masks anyway or many of them were, so itâs hard to tell whether cloth masks were bad or medical masks were good. But itâs enough to cause concern. People who write the reviews on this are also similarly circumspect and I think theyâve actually read the literature where I think most of the EAs confidently pronouncing itâs a good idea generally havenât. So thereâs this general risk of having risky policy proposals which you could derisk, in expectation, by a lot, by carefully, as it were, checking the tape.
More on cloth masks:
And I still think if youâre going to do this, or youâre going to make your recommendations based on expectation, you should be checking very carefully to make sure your expectation is as accurate as it could be, especially if thereâs like a credible risk of causing harm and thatâs hard to do for anyone, for anything. I mean cf. the history of GiveWell, for example, amongst all its careful evaluation. And weâre sort of at the other end of the scale here. And I think that could be improved. If it was someone like, âOh, I did my assessment review of mask use and hereâs my interpretation. I talked to these authors about these things or whatever elseâ, then Iâd be more inclined to be happy. But where thereâs dozens of ideas being pinged around⌠Many of them are at least dubious, if not downright worrying, then Iâm not sure Iâm seeing really EA live out its values and be a beacon of light in the darkness of irrationality.
Lewisâ concrete recommendations for EA:
The direction I would be keen for EAs to go in is essentially paying closer attention to available evidence such as it is. And there are some things out there which can often be looked at or looked up, or existing knowledge one can get better acquainted with to help inform what you think might be good or bad ideas. And I think, also, maybe thereâs a possibility that places like 80K could have a comparative advantage in terms of elicitation or distillation of this in a fast moving environment, but maybe itâs better done by, as it were, relaying on what people who do this all day long, and who have a relevant background are saying about this.
So yeah, maybe Marc Lipsitch wants to come on the 80K podcast, maybe someone like Adam Kucharski would like to come on. Or like Rosalind Eggo or other people like this. Maybe theyâd welcome a chance of being able to set the record straight given like two hours to talk about their thing rather than like a 15 minute media segment. And it seems like that might be a better way of generally improving the epistemic waterline of EA discussions, rather than lots of people pandemic blogging, roughly speaking, and a very rapid, high turnaround. By necessity, thereâs like limited time to gather relevant facts and information.
More on EA setting a bad example:
...one of the things Iâm worried about, itâs like a lot of people are going to look at COVID-19, start want get involved in GCBRs. And sort of all these people are cautious, circumspect, lotâs of discretion and stuff like that. I donât think 80Ks activity on this has really modeled a lot of that to them. Rob [Wiblin], in particular, but not alone. So having a pile of that does not fill me with great amounts of joy or anticipation but rather some degree of worry.
I think that does actually apply even in first order terms to the COVID-19 pandemic, where I can imagine a slightly more circumspect or cautious version of 80K, or 80K staff or whatever, would have perhaps had maybe less activity on COVID, but maybe slightly higher quality activity on COVID and that mightâve been better.
On epistemic caution:
I mean people like me are very hesitant to talk very much on COVID for fear of being wrong or making mistakes. And I think that fear should be more widespread and maybe more severe for folks who donât have the relevant background whoâre trying to navigate the issue as well.
Lewis twice mentions an EA Forum post he wrote about epistemic modesty, which sounds like it would be a relevant read, here.
Itâs quite a strange and interesting story, but I donât think it supports the case that LessWrong actually called covid earlier than others. Letâs get into the context a little bit.
First off, Dominic Cummings doesnât appear to be a credible person on covid-19, and seems to hold strange, fringe views. For example, in November 2024 he posted a long, conspiratorial tweet which included the following:
The Fauci network should be rolled up & retired en masse with some JAILED.
And their media supportersâi.e most of the old mediaâdriven out of business.
Incidentally, Cummings also had a scandal in the UK around allegations that he inappropriately violated the covid-19 lockdown and subsequently wasnât honest about it (possibly lied about it). This also makes me a bit suspicious about his reliability.
This situation with Dominic Cummings reminds me a bit about how Donald Trumpâs staffers in the White House have talked about how itâs nearly impossible to get him to read their briefings, but heâs obsessed with watching Fox News. Unfortunately, the information a politician pays attention to and acts on is not necessarily the best information, or the source that conveyed that information first.
As mentioned in the post above, there were already mainstream experts like the CDC giving public warnings before the February 27, 2020 blog post that was republished on LessWrong on February 28. Is it possible Dominic Cummings was, for whatever reason, ignoring warnings from experts while, oddly, listening to them from bloggers? Is Cummingsâ narrative, in general, reliable?
I decided to take a look at the timeline of the UK governmentâs response to covid in March 2020. Thereâs an article from the BBC published on March 14, 2020, headlined, âCoronavirus: Some scientists say UK virus strategy is ârisking livesââ. Hereâs how the BBC article begins:
More than 200 scientists have written to the government urging them to introduce tougher measures to tackle the spread of Covid-19.
In an open letter, the 229 specialists in disciplines ranging from mathematics to geneticsâthough no leading experts in the science of the spread of diseasesâsay the UKâs current approach will put the NHS under additional stress and ârisk many more lives than necessaryâ.
The signatories also criticised comments made by Sir Patrick Vallance, the governmentâs chief scientific adviser, about managing the spread of the infection to make the population immune.
The Department of Health said Sir Patrickâs comments had been misinterpreted.
The scientistsâall from UK universitiesâalso questioned the governmentâs view that people would become fed up with restrictions if they were imposed too soon.
The open letter says:
By putting in place social distancing measures now, the growth can be slowed down dramatically, and thousands of lives can be spared. We consider the social distancing measures taken as of today as insufficient, and we believe that additional and more restrictive measures should be taken immediately, as it is already happening in other countries across the world.
The BBC article also mentions another open letter, then signed by 200 behavioural scientists (eventually, signed by 680), challenging the governmentâs rationale for not instituting a lockdown yet. That letter opened for signatures on March 13, 2020 and closed for signatures on March 16, 2020.
First, note that this open letter calling for social distancing measures was published 16 days after the February 28, 2020 post on LessWrong and 17 days after the February 27, 2020 blog post it was republishing. If the UK government changed its thinking on or approach to covid-19 in the last few days of February or the first few days of March based on Dominic Cummings reading the blog posts he mentioned in that tweet, why was this open letter still necessary on March 14? What exactly is Cummings saying the bloggers convinced him to do, and when exactly did he do it?
Another quote from the March 14, 2020 BBC article:
Meanwhile the governmentâs scientific advisory group for emergencies (Sage) advised that measures to protect vulnerable peopleâincluding household isolationââwill need to be instituted soonâ.
On March 16, 2020, the UK government advised the public to avoid non-essential social contact. On March 23, 2020, the government announced a nationwide lockdown that officially took effect on March 26. Is it possible the UK governmentâs response was more influenced by mainstream experts than by bloggers?
Following up a bit on this, @parconley. The second post in Zviâs covid-19 series is from 6pm Eastern on March 13, 2020. Letâs remember where this is in the timeline. From my quick take above:
On March 8, 2020, Italy put a quarter of its population under lockdown, then put the whole country on lockdown on March 10. On March 11, the World Health Organization declared covid-19 a global pandemic. (The same day, the NBA suspended the season and Tom Hanks publicly disclosed he had covid.) On March 12, Ohio closed its schools statewide. The U.S. declared a national emergency on March 13. The same day, 15 more U.S. states closed their schools. Also on the same day, Canadaâs Parliament shut down because of the pandemic.
Zviâs post from March 13, 2020 at 6pm is about all the school closures that happened that day. (The U.S. state of emergency was declared that morning.) It doesnât make any specific claims or predictions about the spread of the novel coronavirus, or anything else that could be assessed in terms of its prescience. It mostly focuses on the topic of the social functions that schools play (particularly in the United States and in the state of New York specifically) other than teaching children, such as providing free meals and supervision.
This is too late into the timeline to count as calling the pandemic early, and the post doesnât make any predictions anyway.
The third post from Zvi is on March 17, 2020 and itâs mostly a personal blog. There are a few relevant bits. For one, Zvi admits he was surprised at how bad the pandemic was at that point:
Regret I didnât sell everything and go short, not because I had some crazy belief in efficient markets, but because I didnât expect it to be this bad and I told myself a few years ago I was going to not be a trader anymore and just buy and hold.
He argues New York City is not locking down soon enough and San Francisco is not locking down completely enough. About San Francisco, one thing he says is:
Local responses much better. Still inadequate. San Francisco on strangely incomplete lock-down. Going on walks considered fine for some reason, very strange.
I donât know how sound this was given what experts knew at the time. It might have been the right call. I donât know. I will just say that, in retrospect, it seems like going outside was one of the things we originally thought wasnât fine that we later thought was actually fine after all.
The next post after that isnât until April 1, 2020. Itâs about the viral load of covid-19 infections and the question of how much viral load matters. By this point, weâre getting into questions about the unfolding of the ongoing pandemic, rather than questions about predicting the pandemic in advance. You could potentially go and assess that prediction track record separately, but thatâs beyond the scope of my quick take, which was to assess whether LessWrong called covid early.
Overall, Zviâs posts, at least the ones included in this series, are not evidence for Zvi or LessWrong calling covid early. The posts start too late and donât make any predictions. Zvi saying âI didnât expect it to be this badâ is actually evidence against Zvi calling covid early. So, I think we can close the book on this one.
Still open to hearing other things people might think of as evidence that the LessWrong community called covid early.
I genuinely donât know how to answer these polls. I find it much easier to think about a shorter timeframe like the next 20 years â although even just that is hard enough â rather than try to predict the future over a timespan of 275+ years.
I find it much easier to say that the creation of AGI (specifically as I define it here, since some people even call o3 âAGIâ) is extremely unlikely by 2035 (i.e., much less than a 0.01% or 1 in 10,000 chance), let alone the Singularity.
(âCrazyâ seems hazy, to the point that it probably needs to be decomposed into multiple different questions to make it a true forecast â although I can respect just asking people for a vague vibe just as a casual exercise, even though it wonât resolve unambiguously in retrospect.)
My problem with trying to put a median year on AGI is that I have absolutely no idea how to do that. If science and technology continue, indefinitely, to make progress in the sort of way they have for the last 100-300 years, then it seems inevitable humans will eventually invent AGI. Maybe thereâs a chance itâs unattainable for reasons most academics and researchers interested in the subject donât currently anticipate.
For instance, one estimate is that to rival the computation of a single human brain, a computer would need to consume somewhere between 300 times and 300 billion times as much electricity as the entire United States does currently. If that estimate is accurate, and if building AGI requires that much computation and that much energy, then, at the very least, that makes AGI far less attainable than even some relatively pessimistic and cautious academics and researchers might have guessed. Imagine the amount of scientific and technological progress required to produce that much energy, or to perform that much computation commensurately more energy efficiently.
Letâs assume, for the sake of argument, computation and energy are not issues, and itâs just about solving the research problems. I just went on random.org and randomly generated a number between 1 and 275, to represent the range of years asked in this polling question. The result I got was 133 years. 133 years from now is 2158. So, can I do better than that? Can I guess a median year thatâs more likely to accurate, or more likely to be closer, at least, than a random number generator? Do I have a better methodology than using random.org? Why should I think so? This is a fundamental question, and it underlies this whole polling exercise, as well of most if not all forecasting related to AGI. For instance, is there any scientific evidence or historical evidence that anyone has ever been able to predict when scientific research problems would be solved, or when fundamentally new technologies would be developed, with any sort of accuracy at all? If so, whereâs the evidence? Letâs cite it to motivate these exercises. If not, why should we think weâre in a different situation now where we are better able to tell how the future will unfold?
The mental picture I have of the long-term future when I think about forecasting when the fundamental science and technology problems pre-requisite to building AGI will be solved is of a thick fog, where I can see clearly only a little distance in front of me, can see foggily a little bit further, and then after that everything descends into completely opaque gray-white mist. Is 2158 the median year? I tried random.org again. I got 58, which would be 2083. Which year is more likely to be the median, 2083 or 2158? Are they equally likely to be the median? I have no idea how to answer these questions. For all I know, they might be fundamentally impossible to answer. The physicist David Deutsch makes the argument (e.g., in this video at 6:25) that we canât predict the content of scientific knowledge we donât yet know, since predicting the content would be equivalent to knowing it now, and we donât know yet it. This makes sense to me.
We donât yet know what the correct theory of intelligence is. We donât know the content of that theory. The theory that human-like intelligence is just current-generation deep neural networks scaled up 1,000x times would imply a close median year for AGI. Other theories of intelligence would imply something else. If the specific micro-architecture of the whole human brain is whatâs required for human-like intelligence (or general intelligence), then that implies AGI is probably quite far away, since we donât yet know that micro-architecture and donât yet have the tools in neuroscience to find it out. Even if we did know, reconstructing it in a simulation would pose its own set of scientific and technological challenges. Since we donât know what the correct theory of intelligence is, we donât know how hard it will be to build an intelligence like our own using computers, and therefore we canât predict when it will happen.
My personal view that AGI is extremely unlikely (much less than 0.01% likely) before the end of 2035 comes from my beliefs that 1) human-like intelligence is definitely not current-gen deep neural networks scaled up 1,000x, 2) the correct theory of intelligence is not something nearly so simple or easy (e.g., if AGI could have been solved by symbolic AI, it probably would have been a long time ago), and 3) itâs extremely unlikely that all the necessary scientific discoveries and technological breakthroughs required to solve everything from fundamental theory to practical implementation will be solved within the next ~9 years. Scientists, philosophers, and AI researchers have been trying to understand the fundamental nature of intelligence for a long time. The foundational research for deep learning goes back around 40 years, and it built on research thatâs even older than that. Today, if you listen to ambitious AI researchers like Yann LeCun, Richard Sutton, François Chollet, and Jeff Hawkins, they are each confident in a research roadmap to AGI, but they are four completely different roadmaps based on completely different ideas. So, itâs not like the science and philosophy of intelligence is converging toward any particular theory or solution.
Thatâs a long, philosophical answer to this quick poll question, but I believe thatâs the crux of the whole matter.
Well, the evidence is there if youâre ever curious. You asked for it, and I gave it.
David Thorstad, who writes the Reflective Altruism blog, is a professional academic philosopher and, until recently, was a researcher at the Global Priorities Institute at Oxford. He was an editor of the recent Essays on Longtermism anthology published by Oxford University Press, which includes an essay co-authored by Will MacAskill, as well as essays by a few other people well-known in the effective altruism community and the LessWrong community. He has a number of published academic papers on rationality, epistemology, cognition, existential risk, and AI. Heâs also about as deeply familiar with the effective altruist community as itâs possible for someone to be, and also has a deep familiarity with the LessWrong community.
In my opinion, David Thorstad has a deeper understanding of the EA communityâs ideas and community dynamics than many people in the community do, and, given the overlap between the EA community and the LessWrong community, his understanding also extends to a significant degree to the LessWrong community as well. I think people in the EA community are accustomed to drive-by criticisms by people who have paid minimal attention to EA and its ideas, but David has spent years interfacing with the community and doing both academic research and blogging related to EA. So, what he writes are not drive-by criticisms and, indeed, apparently a number of people in EA listen to him, read his blog posts and academic papers, and take him seriously. All this to say, his work isnât something that can be dismissed out of hand. His work is the kind of scrutiny or critical appraisal that people in EA have been saying they want for years. Here it is, so folks better at least give it a chance.
To me, âugly or difficult topics should be discussedâ is an inaccurate euphemism. I donât think the LessWrong community is particularly capable of or competent at discussing ugly or difficult topics. I think they shy away from the ugly and difficult parts, and generally donât have the stomach or emotional stamina to sit through the discomfort. What instead is happening in the LessWrong community is people are credulously accepting ugly, wrong, evil, and stupid ideas in some part due to an inability to handle the discomfort of scrutinizing them and in large part due to just an ideological trainwreck of a community that believes ridiculous stuff all the time (like the many examples I gave above) and typically has atrocious epistemic practices (e.g. people just guess stuff or believe stuff based on a hunch without Googling it; the community is extremely insular and fiercely polices the insider/âoutsider boundary â landing on the right side of that boundary is sometimes what even determines whether people keep their job, their friends, their current housing, or their current community).
I spun this quick take out as a full post here. When I submitted the full post, there was no/âalmost no engagement on this quick take. In the future, Iâll try to make sure to publish things only as a quick take or only as a full post, but not both. This was a fluke under unusual circumstances.
Feel free to continue commenting here, cross-post comments from here onto the full post, make new comments on the post, or do whatever you want. Thanks to everyone who engaged and left interesting comments.
Help me make sure Iâm understanding this right. Youâre at position #4 from left to right, so this means 2029 according to your list. So, this means you think thereâs a 50% chance of a combination of the âcrazyâ scenarios happening by 2029, right?
Unfortunately, the EA Forum polls software makes it hard to ask certain kinds of questions. Your prediction is listed as â70% 2026â, but thatâs just an artifact of the poll software.
To make it clear to readers what people are actually predicting, and to make sure people giving predictions understand the system properly, you might want to add instructions for people to say something like â50% chance the Year of Crazy happens by 2029â at the top of their comments. That would at least save readers the trouble of cross-referencing the list for every single prediction.
I tried to do a poll on peopleâs AI bubble predictions and I ran into a similar issue with the poll software displaying the results confusingly.
Sometimes for social change, having the older generation die off or otherwise lose power is useful. Thereâs not much our hypothetical activist could do to accelerate that. One might think, for instance, that a significant decline in religiosity and/âor the influence of religious entities is a necessary reagent in this model. While one could in theory put money into attempting to reduce the influence of religion in 1900s public life, I think there would be good reasons not to pursue this approach. Rather, I think it could make more sense for the activist to let the broader cultural and demographic changes to do some of the hard work for them.
I donât agree with this causal model/âexplanatory theory.
This is some kind of at least partly deterministic theory about culture that says culture is steered by forces that canât be steered by human creativity, agency, knowledge, or effort. I donât agree with that view. I think culture is changed by what people decide to do.
Thatâs not an accounting trick in my bookâthere are clear redistributive effects here. If I spend my money on basic science to promote hologram technology, the significant majority of the future benefits of my work are likely going to flow to future for-profit hologram companies, future middle-class+ people in developed countries, and so on. Those arenât the benefits I care about, and Big Hologram isnât likely to pay it forward by mailing a bunch of holograms to disadvantaged children (in your terminology, they are going to free-ride off my past efforts).
That depends on two things:
If I fund research, then no one else in the future will subsidize the technology and provide it for free.
If I donât fund research, somebody else will.
I guess it could theoretically be true that both assumptions are correct, and maybe we can imagine a scenario where you would have good reasons to believe both of these things, but in practice, in reality, I think itâs rare that we ever really know things like that. So, while itâs possible to imagine scenarios where the upfront money will definitely be supplied by someone else and the down-the-line money definitely wonât, what does this tell us about whether this is a good idea in practice?
The hologram example is making the point: if the pool of dollars required to produce an outcome is a certain amount, the overall cost-effectiveness of producing that outcome doesnât change regardless of which dollars are yours or not. I think your point is: your marginal cost-effectiveness could be much higher or lower depending on whatâs going to happen if you do nothing. Which is true, I just donât think we can actually know whatâs going to happen if you do nothing, and the best version of this still seems to be guesswork or hunches.
It also seems like an oddly binary choice of the sort that doesnât really exist in real life. If you have significant philanthropic money, can you really not affect what others do? Letâs flip it: if another philanthropist said they would subsidize holograms down the line, that would affect what you would do. So, why not think you have the same power?
What seems to be emerging here is an overall theme of: âthe future will happen the way itâs going to happen regardless of what we do about itâ vs. âwe have the agency to change how events play out starting right nowâ. I definitely believe the latter, I definitely disbelieve the former. We have agency. And, on the other hand, we canât predict the future.
Who was it who recently quoted someone, maybe the physicist David Deutsch or the psychologist Steven Pinker, saying something like: how terrible would it be if we could predict the future? Because that would mean we had no agency.
The first post listed there is from March 2, 2020, so thatâs relatively late in the timeline weâre considering, no? Thatâs 3 days later than the February 28 post I discussed above as the first/âbest candidate for a truly urgent early warning about covid-19 on LessWrong. (2020 was a leap year, so there was a February 29.)
That first post from March 2 also seems fairly simple and not particularly different from the February 28 post (which it cites).
Fair enough, but it seems more like a cool, fun coding project in the realm of science communication, rather than a prediction or some sort of original scientific research or analysis that generated new insights.
The infectious disease doctor interviewed for the Smithsonian Magazine article about microCovid said that microCovid is a user-friendly, clearly explained version of tools that already existed within the medical profession. So, thatâs great, thatâs useful, but itâs not a prediction or an original insight. Itâs just good science communication and good coding.
The article also mentions two other similar risk calculators designed for use by the public. So, it isnât even unique for what it is.
When people say that LessWrong called covid early or was right about covid, what they mean is that LessWrong made correct predictions or had correct opinions (not by luck or chance, but by superior rationality) that other people didnât make or didnât have. And they say this in the context of providing reasons why the LessWrong communityâs views or predictions on other topics should be trusted or taken seriously.
microCovid, as nice a thing as it may be, does not support either of those ideas.
I think when you look at the LessWrong communityâs track record on covid-19, there is just no evidence to support this flattering story that the community tells about itself.