Mediocre criticism can get plenty of upvotes as long as it's a culture fit.

If the author does a good job of pitching it to Less Wrongers, then the critical post can activate readers' it's virtuous to be open-minded mindset and turn their critical faculties towards the thing that the post is criticizing and away from the post itself. So instead of evaluating the post according to their ordinary standards of epistemics and quality, they instead try to find anything in it that seems good / insightful / overly neglected / provoking of new useful thoughts / on a promising track.

Seems like you're mushing together several loosely related things, including what we might call model-based motivation, explicit long-term planning, unified purpose, and precisely targeted goals.

Model-based motivation: being motivated to do something in a way that relies on your internal models of the world, not just on direct sensory rewards.

Explicit long-term planning: being aware of your goal, explicitly planning ways to achieve it, following those plans including over periods of months or years. 

Unified purpose: a person's motivations and actions in a domain fitting together coherently to work towards a single purpose, even across contexts. 

Precisely targeted goals: having the goal precisely match something that can be specified on other grounds besides what we can empirically observe that people aim for (like "inclusive genetic fitness" which is picked out by theory).

The godshatter post is mainly about the last two - people have a collection of fragmented motivations which helped towards the selected-for purpose in the contexts where we evolved. Your argument here is mainly about the first two.

I think that the first two are pretty common, and are found in human romantic/reproductive goals, e.g. long-term planning around having kids, or motivations to improve ones appearance in ways that you expect potential partners to find attractive. I think that the last two are pretty rare, including for status - most people have a collection of somewhat-status-related motivations (though perhaps a small fraction of people (sociopaths?) have status as a more unified goal), and I haven't seen anyone specify the "status" target well enough to even check if people's motivations aim at that precise target.

You seem to think that this post poses a single clear puzzle, of the sort that could have a single answer. 

I disagree. I think the post has clarity problems (especially in its definition of poverty in terms of "desperate scrabbling", which conflates a lack of at least one essential material resource with anything at all that a person might desperately care about) and kind of gestures at various questions related to poverty.

I haven't given that article a close read, but on a quick look through it I find it basically not at all compelling.

It looks like it's the genre of 'this part of reality is surprisingly detailed, therefore be paranoid/nihilistic/cynical about it'.

This genre of article is saying: there's this concept that you've been using, which you've been treating as a clean abstraction without really thinking much about where it can from, but if you look at where it comes from, there is a bunch of messy detail & judgments calls.

And that much, often, is true. But it's written with an air of suspicion, or with explicit claims that therefore it's all just a bunch of made-up nonsense. Which does not follow.

Numbers that involve judgment calls aren't in general fake/nonsense/bullshit. I regularly use subjective probabilities, Fermi estimates, etc., and I imagine that you do too.

If you want, you can have the takeaway from this sort of article: "that's right, I've been using this concept without really understanding the messy detail behind it. Do I care enough about this to want to understand where it comes from?"

If so, then you can go try to learn about it, using the processes that you usually use to learn about things. Try to find writing by economists explaining where inflation numbers and "real GDP" numbers come from, or some narrower question that you could dig into enough so that you have a . Have a conversation with Claude about it. Make a google doc where you think through what you would do if it was up to you to come up with number for "real GDP", or to do whatever tasks people do when they rely on "real GDP" numbers. Etc.

This post of yours looks like it's kinda trying to do some of that, although the things that you'd want to learn about might not fit into a lesswrong comment, and I don't know if you'll find anyone who is sufficiently well-informed about real GDP calculations and willing to spend the time to leave a detailed comment for you to get a good object-level answer here. And it reads like you've already maybe 70% bought in to the mood & the narratives of the post you've linked, which is not something that I'd recommend with this genre of post before you've tried to learn about it elsewhere. Maybe you can come back to this post afterwards and consider its reasoning after you have more grounding in the topic, but relying on this person's judgment & narratives about some topic just because he's the one who pointed out to you that it is surprisingly detailed seems like bad process.

To get a little more object-level: One thing that's missing from the article (and your takeaways from it) is that most of the judgment calls that the economists who come up with "real GDP" numbers make are at the process level, of what procedures to use to assign a number to real GDP for a country for a particular year, given the various complications. When trying to answer a question like "what was US GDP in 1946" they have limited degrees of freedom because they're mostly just relying on the processes that they've decided to apply to answering that sort of question for all countries & years. Which is pretty different from "BEA economists eye-balling a bunch of factors and coming up with a number that "seems right"", even if both involve judgment calls.

Did you have a different vision for how to get really good AI X-risk legislation passed?

I'd interpreted your post has already implicitly sharing something like orthonomal's view, since I took you to be arguing that we should prioritize getting a small number of legislators who really Get It.

It sounds like your view is that (say) a House with 5 legislators who are amazing on AI X-risk, 15 who seem like they're kinda pretty good, and 415 others is actively worse than one with 5 amazing legislators and 430 others?

I'm not sure why you think this. I'd think that most of the ways in which the pretty good legislators could be disappointing would make them more similar to the 415 others, or less influential, rather than actively worse. And often it would still be somewhat helpful to have them in Congress, e.g. they'd generally be more likely than random legislators to vote for a good AI bill that has a chance at becoming law.

One big way it could backfire to have a pretty-good-seeming legislator in the house is if they become a leading voice on AI while having misguided views on AI. But the concern about candidates who have a combination of prioritizing AI, being very competent, and having misguided views on AI feels different than just having extremely high standards for amazingness on AI X-risk.

The first is simple, unemployment. It's calculated in a way that is very favorable to the government^[1], because the government decides how it's calculated and generally wants to look like things are going well. Labor force participation, a statistic that more accurately captures the share of the productive population that is being squandered, has fallen precipitously from 2005 to around 2015, enjoyed a slight increase from 2015 to 2019, and then taken a nosedive afterwards, never recovering to its 2019 high. Since 2005, a full four percent of the population - one out of 25 people - have dropped out of the labor force. This is the sort of thing that affects everything, from the national psyche to the social fabric to, of course, our ability to use the country's human resources efficiently.

Prime age employment to population ratio is a better measure, and it does not show a decline since 2005.

The measure that you picked goes down if the population gets older and includes a larger share of retired people (which it has) or if more people age 16-24 are in school rather than working (which has also been happening).

Previous discussion

Rows 1677, 54048, 93530, and 141774 look anomalous - they should be guaranteed wins but are marked as losses. (3 of them pit 1 Laser Lance & 1 Rail Rifle vs. 2 Arachnoid Abominations.)