Project lead of LessWrong 2.0, often helping the EA Forum with various issues with the forum. If something is broken on the site, it's a good chance it's my fault (Sorry!).
I would actually be really interested in talking to someone like Baumeister at an event, or ideally someone a bit more careful. I do think I would be somewhat unhappy to see them given just a talk with Q&A, with no natural place to provide pushback and followup discussion, but if someone were to organize an event with Baumeister debating some EA with opinions on scientific methodology, I would love to attend that.
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I cannot find any section of this article that sounds like this hypothesis, so I am pretty confident the answer is that no, that is not what the article says. The article responds relatively directly to this:
Of course, being a prolific producer of premium prioritisation posts doesn’t mean we should give someone a free pass for behaving immorally. For all that EAs are consequentialists, I don’t think we should ignore wrongdoing ‘for the greater good’. We can, I hope, defend the good without giving carte blanche to the bad, even when both exist within the same person.
Not particularly hard. My guess is half an hour of work or so, maybe another half hour to really make sure that there are no UI bugs.
Yep, seems like that's the wrong link. Here is the fixed link: https://app.effectivealtruism.org/funds/far-future
Just to be clear, I don't think even most neoreactionaries would classify as white nationalists? Though maybe now we are arguing over the definition of white nationalism, which is definitely a vague term and could be interpreted many ways. I was thinking about it from the perspective of racism, though I can imagine a much broader definition that includes something more like "advocating for nations based on values historically associated with whiteness", which would obviously include neoreaction, but would also presumably be a much more tenable position in discourse. So for now I am going to assume you mean something much more straightforwardly based on racial superiority, which also appears to be the Wikipedia definition.
I've debated with a number of neoreactionaries, and I've never seen them bring up much stuff about racial superiority. Usually just arguing against democracy and in favor of centralized control and various arguments derived from that, though I also don't have a ton of datapoints. There is definitely a focus on the superiority of western culture in their writing and rhetoric, much of which is flawed and I am deeply opposed to many of the things I've seen at least some neoreactionaries propose, but my sense is that I wouldn't characterize the philosophy fundamentally as white nationalist in the racist sense of the term. Though of course the few neoreactionaries that I have debated are probably selected in various ways that reduces the likelihood of having extreme opinions on these dimensions (though they are also the ones that are most likely to engage with EA, so I do think the sample should carry substantial weight).
Of course, some neoreactionaries are also going to be white nationalists, and being a neoreactionary will probably correlate with white nationalism at least a bit, but my guess is that at least the people adjacent to EA and Rationality that I've seen engage with that philosophy haven't been very focused on white nationalism, and I've frequently seen them actively argue against it.
Describing members of Leverage as "white nationalists" strikes me as pretty extreme, to the level of dishonesty, and is not even backed up by the comment that was linked. I thought Buck's initial comment was also pretty bad, and he did indeed correct his comment, which is a correction that I appreciate, and I feel like any comment that links to it should obviously also take into account the correction.
I have interfaced a lot with people at Leverage, and while I have many issues with the organization, saying that many white nationalists congregate there, and have congregated in the past, just strikes me as really unlikely.
Buck's comment also says at the bottom:
Edited to add (Oct 08 2019): I wrote "which makes me think that it's likely that Leverage at least for a while had a whole lot of really racist employees." I think this was mistaken and I'm confused by why I wrote it. I endorse the claim "I think it's plausible Leverage had like five really racist employees". I feel pretty bad about this mistake and apologize to anyone harmed by it.
I also want us to separate "really racist" from "white nationalist" which are just really not the same term, and which appear to me to be conflated via the link above.
I also have other issues with the rest of the comment (namely being constantly worried about communists or nazis hiding everywhere, and generally bringing up nazi comparisons in these discussions, tends to reliably derail things and make it harder to discuss these things well, since there are few conversational moves as mindkilling as accusing the other side to be nazis or communists. It's not that there are never nazis or communists, but if you want to have a good conversation, it's better to avoid nazi or communist comparisons until you really have no other choice, or you can really really commit to handling the topic in an open-minded way.)
To me, the graph with a summary of all trends only seems to have very few that at first glance look a bit like s-curves. But I agree one would need to go beyond eyeballing to know for sure.
Yeah, that was the one I was looking at. From very rough eye-balling, it looks like a lot of them have slopes that level off, but obviously super hard to tell just from eye-balling. I might try to find the data and actually check.
Note: Actually looking at the graphs in Farmer & Lafond (2016), many of these do sure seem pretty S-curve shaped. As do many of the diagrams in Nagy et al. (2013). I would have to run some real regressions to look at it, but in particular the ones in Farmer & Lafond seem pretty compatible with the basic s-curve model.
Overlapping S-curves are also hard to measure because obviously there are feedback effects between different industries (see my self-similarity comment above). Many of the advances in those fields are driven by exogenous factors, like their inputs getting cheaper, with no substantial improvements in their internal methodologies. One of my models of technological progress (I obviously also share the model of straightforward exponential growth and assign it substantial probability) is that you have nested and overlapping S-curves, which makes it hard to just look at cost/unit output of any individual field.
For analyzing that hypothesis it seems more useful to hold inputs constant and then look at how cost/unit develops, in order to build a model of that isolated chunk of the system (and then obviously also look at the interaction between industries and systems to get a sense of how they interact). But that's also much harder to do, given that our data is already really messy and noisy.
I mean something much more basic. If you have more parameters then you need to have uncertainty about every parameter. So you can't just look at how well the best "3 exponentials" hypothesis fits the data, you need to adjust for the fact that this particular "3 exponentials" model has lower prior probability. That is, even if you thought "3 exponentials" was a priori equally likely to a model with fewer parameters, every particular instance of 3 exponentials needs to be less probable than every particular model with fewer parameters.
Thanks, this was a useful clarification. I agree with this as stated. And I indeed assign substantially more probability to a statement of the form "there were some s-curve like shifts in humanity's past that made a big difference" than to any specific "these three specific s-curve like shifts are what got us to where we are today".
As far as I can tell this is how basically all industries (and scientific domains) work---people learn by doing and talk to each other and they get continuously better, mostly by using and then improving on technologies inherited from other people.It's not clear to me whether you are drawing a distinction between modern economic activity and historical cultural accumulation, or whether you feel like you need to see a zoomed-in version of this story for modern economic activity as well, or whether this is a more subtle point about continuous technological progress vs continuous changes in the rate of tech progress, or something else.
As far as I can tell this is how basically all industries (and scientific domains) work---people learn by doing and talk to each other and they get continuously better, mostly by using and then improving on technologies inherited from other people.
It's not clear to me whether you are drawing a distinction between modern economic activity and historical cultural accumulation, or whether you feel like you need to see a zoomed-in version of this story for modern economic activity as well, or whether this is a more subtle point about continuous technological progress vs continuous changes in the rate of tech progress, or something else.
Hmm, I don't know, I guess that's just not really how I would characterize most growth? My model is that most industries start with fast s-curve like growth, then plateau, then often decline. Sure, kind of continuously in the analytical sense, but with large positive and negative changes in the derivative of the growth.
And in my personal experience it's also less the case that I and the people I work with just get continuously better, it's more like we kind of flop around until we find something that gets us a lot of traction on something, and then we quickly get much better at the given task, and then we level off again. And it's pretty easy to get stuck in a rut somewhere and be much less effective than I was years ago, or for an organization to end up in a worse equilibrium and broadly get worse at coordinating, or produce much worse output than previously for other reasons.
Of course enough of those stories could itself give rise to a continuous growth story here, but there is a question here about where the self-similarity lies. Like, many s-curves can also give rise to one big s-curve. Just because I have many s-curve doesn't mean I get continuous hyperbolic growth. And so seeing lots of relative discontinuous s-curves at the small scale does feel like it's evidence that we also should expect the macro scale to be a relatively small number of discontinuous s-curves (or more precisely, s-curves whose peak is itself heavy-tail distributed, so that if you run a filter for the s-curves that explain most of the change, you end up with just a few that really mattered).