Shirayuki3
new account for Shirayuki2
User ID: 4553
Basically the whole overcapacity discourse is cope for Western fiscal irresponsibility and stagnant incumbents in threatened industries
I'm not sure why you're trying to shadowbox with a completely different set of arguments, instead of what I actually said. I fully agree with you on this point, and in fact quite admire Chinese industrial policy.
I'm simply making the point that mathematically it is not possible that America could meaningfully experience a productivity boom driven by exporting to global markets as you initially suggested. There is simply not enough money in global markets capable of absorbing a meaningful productivity increase in American goods. Any such increase in production would need to be absorbed by American consumers, which would then mechanically raise the consumption input of GDP, realistically by quite a bit, if you're proposing that Grok designed Optimus robots or Teslas etc are going to be mass produced and consumed.
Automating office work does not linearly lead to X times more office work done at the same compensation, maybe the workload can just expand to fill the capacity, real earnings are fixed, and net "productivity gain" is minor.
My median expectation is similar, in that that significant amounts of what AI can automate was already bullshit, and that application of AI to actual production will find itself limited in an Amdahlian sense by everything it cannot automate. My point is that if you expect rapid American production dominance diffused into the physical world driven by AI advantage, I don't see how you can expect minor net GDP and productivity growth at the same time. Mechanically this would bring up C, I and moderately NX in the GDP equation.
Shirayuki3
13d ago
The problem with the weak argument is that it is, well, weak. It demonstrates nothing
Well, the point is that framing is everything in public perception.
You can frame what happened as "OpenAI lost control of an emerging agent-civilization", or you can frame it as "OpenAI has horrible cybersecurity culture and trains using poorly designed RL environments", and OpenAI is clearly marketing to spin the narrative towards the first framing, whether or not you actually believe that line of thought.
Shirayuki3
13d ago
There is no such thing as "overcapacity"
Overcapacity in the sense that "Westerners complain about Chinese EVs being too cheap" is cope, but overcapacity in the sense that "the Chinese produce much more compared to what they can currently consume domestically" is just a matter of fact.
they earn and consume plenty for their GDP bracket and had a fast income share growth over the entire period of getting more competitive
That's an interesting Twitter thread, some things to consider there. Still, the sole claim I was making in my previous post is that if the American economy gained Chinese Characteristics and started heavily ramping up production, then that production would show up as business investment and either in domestic consumption statistics (more likely) or in net exports (less likely, numerically there's just nobody else that could consume that volume of production), and either way it'd be reflected in GDP statistics.
If you want a bullish forecast, Anthropic expects GDP growth up to 15% a year by 2030.
Yes, I personally think these types of predictions are ludicrous; I enjoyed Alex Imas's article on AI-enabled GDP that makes much more measured claims.
I was just curious where you sit on the spectrum of "imminent double-digit growth with no brakes", and "economic and social forces will curtail growth", given your very high level of bullishness on capabilities.
Wages stagnate, services revenues don't grow much, and yet there are more and better EVs, chips have higher density, Starship is debugged that much faster, domestic robots are everywhere, and the US begins to recapture global markets
By definition this scenario would lead to a massive increase in GDP growth, if your thesis is that growth in investment and exports spikes while growth in consumer spending and government spending is held roughly even.
I do think a more realistic scenario under your basic premises is that American consumer spending spikes, driven by consumer surplus and redistribution, even as wages stagnate and net exports rise moderately; there are simply no other markets in the world that would be able to absorb American production overcapacity, in the way that America allows the Chinese strategy of suppressing domestic consumption to function by absorbing Chinese overcapacity.
In either case, I don't see how GDP growth would be unable to capture these benefits. I think if this is the modal scenario you expect, you should be expecting fairly high GDP growth.
I think (?) you’re expressing several inter-related points with which I broadly agree
I think that's a good summary of my viewpoint.
I just don’t know what this means, concretely.
I worded that quite poorly; perhaps a better way to put it is that "the direction and magnitude of technological changes on human social structures can't be determined ipso facto".
Undetectable steroids would certainly change baseball, but do more or less people aim to go pro in baseball once it's widely known that you'll need to get onto steroids under the table to compete? Do audiences become more interested in the increased athleticism of the game, or do they lose interest because the game is now less about technical baseball prowess? Which types of baseball players ultimately end up better or worse off once these steroids are made available?
Questions like these are what mathematics and other professions are struggling with right now, but I think the answers to them can't really be determined by any way other than waiting and seeing what happens.
Shirayuki3
13d ago
stronger and more widely deployed American AI buys larger productivity gains, eating into their competitiveness
What would be your ballpark estimate for GDP growth for the United States in 2028?
For reference, GDP growth was 2.1% in 2025 and was 1.5% annualized in Q2 2026.
It cannot be that Anthropic and frontier developers are just chock full of these incredibly rare people and that this level of risk tolerance is also well-correlated with AI coding ability
Why not? AI researcher bonafides are extremely correlated with IQ and autism, being into LessWrong / AI Safety is also extremely correlated with IQ and autism, and of course if you're into LessWrong / AI Safety you're much more likely to work in AI.
There's very few people in the world in absolute terms that are world-leading AI researchers, that believe in uppercase AI Safety, and that believe in the "we have to build it before anyone else does" strategy, but Anthropic likely employs the supermajority of these people out of technical and ideological alignment.
Shirayuki3
13d ago
Well, the thing with the marketing arguments is that there's many ways to make those arguments, some more plausible than others.
Strong form: OpenAI intentionally induced their agents to compromise the internet for marketing purposes.
I agree that trying this would be very stupid and not particularly likely.
--
Semi-strong: OpenAI intentionally sandboxed their agents poorly to stochastically induce agent misbehaviour for marketing purposes.
This one I could see going either way. It does seem like there were some egregious oversights in the sandboxing setup, but whether these were intentional or real oversights is impossible to say.
--
Weak: OpenAI did not intend for misbehaviour to happen, but now that it has happened they're spinning it as hard as possible for marketing.
Personally, I think this one is pretty likely. I was very unimpressed by the METR report for instance, they basically just slopped together some agent review to hype up capabilities without actually auditing the root causes of why it all happened in the first place.
Shirayuki3
14d ago
even if we get rid of the hoop, it means nothing for the profession of basketball in and of itself
I think a slightly better analogy is that tomorrow there's a new rule that lowers the hoop in official basketball games to 8 or 9ft.
What are the first-order implications?
Height is less of an overwhelming advantage; many former basketball players quit the game out of disgust at the new rules, or because they're less competitive in short-hoop basketball, but other players formerly genetically barred from the apex of basketball become more competitive and perhaps there ends up being more basketballers overall.
Perhaps basketball becomes less popular because nobody wants to watch short-hoop basketball and basketballers suffer financially, or paradoxically it gets more popular because the game is less about the three-pointer meta and more about dunking again, and basketballers are more in demand than ever.
I don't think we really disagree that there are going to be large changes to how mathematics is practiced; the point is that technological changes cannot inherently alter anything in a system that is already artificially constructed by humans, and it is the impossible to predict societal changes arising as a result of technological progress that are what really going to affect mathematicians and basketballers.
Elite mountaineering, for example summiting Annapurna apparently has a 13.42% fatality rate.
Pre-modern infantry combat and modern battlefields if you're on the wrong side as a rebel or guerilla fighter would likely have a >10% casualty rate as well. We could also count things like suicide bombers and kamikaze pilots which would be obviously much much higher than 10%.
If we're counting lifetime rate, I believe free soloing and pre-modern childbirth would also exceed >10% lifetime as well.
I don't really disagree that 10% is very high, but I do also agree that many people have the demonstrated drive to risk 10% or even higher odds for causes they believe in.
Shirayuki3
14d ago
Yes, I find Solow's paradox very interesting in the context of the massive GDP growth that lots of "AGI-pilled" people predict, while nobody really knows why the internet ended up living up to to most expectations of transformation, but almost no expectations of productivity improvement.
Personally, I think some combination of "dark consumer surplus" (e.g I can read books online instead of buying them, which is great for me but shows up as less GDP) and "growth compared to counter-factual" (i.e growth would have been even worse due to economic headwinds, without the internet) is plausible, but it really is extraordinarily difficult to predict these sorts of things.
Yes, we can continue to build beautiful towers of abstraction into infinity for the rest of time; frankly, pure mathematics has already lost all pretense that it's trying to do anything economically useful.
Even if AI becomes strictly superior to humans at proving and disproving conjectures, as is the clear trajectory of the technology, it means nothing for the profession of mathematics in and of itself; the limiting factors are the interest of mathematicians in continuing to pursue mathematics under the new paradigm, and more broadly the interest of society in economically subsidizing their pursuits, which are both profoundly social and not technological questions.
It's over for translators
Everyone says this as a kind of self-reinforcing meme, but objectively it's not true.
For example, as just one example I'm familiar with, Japanese/Chinese book/game/show translation began booming in the last ten years and has been booming even harder in the last five years even with AI. Ten years it was extraordinarily difficult to find translations of Japanese/Chinese media outside of the most mainstream anime, while nowadays there is an enormous translation-industrial complex that employs many people I'm acquainted with, and that is dedicated to pumping out simultaneous localizations of even extremely niche media into English/Japanese/Chinese, because of massive consumer demand.
I'm certainly not saying translation is a growth field in the age of AI, and it's not something I'd advise anyone to get into in 2026, but the point is how these technologies diffuse into the economy and interact with demand is extraordinarily hard to predict and often times very counter-intuitive.
As another example, someone could have watched the DARPA Grand Challenge in 2004 and realized that self-driving trucks were a matter of time, but someone else could have started driving a truck in 2004 at the age of 18, have reached 40 in 2026 without meaningful threat from self-driving, and have had a good chance of making it into retirement as well, based on the current pace of self-driving rollout.
Shirayuki3
14d ago
I think this is somewhat bi-modal; there are certainly lots of people in bullshit jobs who use AI to bullshit harder and work less, but also plenty of AI-pilled SWE's and mathematicians are working much more and much harder as a result of AI.
This is kind of my point; for roles like administration or consulting where the output doesn't really matter, the raw capability of AI to replace those people isn't the operative term in terms of what happens to their employment or their role in the economy, and for many roles where AI is actually a substantial productivity enhancement, the effect of AI so far is mostly complimentary rather than rivalrous.
Shirayuki3
14d ago
Putting aside discussion of x-risk itself aside, it's pretty clearly a psyop as that tweet suggests; much bigger names in AI have been saying this kind of stuff for years and nobody cared, but now suddenly this random guy with no social media presence and the most milquetoast (for x-risk discussion standards) take gets 100 million views, quote tweets from everyone who's anyone in AI safety and a prepared media response?
Interesting political times ahead, especially with the midterms fast approaching.
The question I find most interesting with regards to AI right now is the discontinuity between benchmark capabilities progress and the utter lack of impact on pretty much everything in the real world.
Certainly most doubters of AI on a capabilities level have continually been proven wrong in terms of LLM's hitting a wall. On the other hand, the boosters have also been continually proven wrong in terms of the effects in the world. I think it's a reasonable generalization to make that conditional on LLM's being somewhere between at parity and superhuman at translation, writing most code and at being able to prove mathematical theorems, most boosters would have expected at least something to change in the real world, probably significantly more than what's actually happened.
I've written about translators a few times now, but they've been first on the chopping block for close to a decade, and yet have held on admirably with no particular impact on their employment at a macro level.
Count is doomposting artists below, when in practice the impact of AI art on artists looks much more complementary than rivalrous except at the margins; for most applications of AI art no artist would have been paid to produce it in any case, and commercial illustrators, fine artists and Patreon goonsloppers are all doing about as well as they were prior to the advent of diffusion models.
Software engineers got a lot of doom around the start of the year once LLM's got good at writing code, but by all indications software engineering employment is continuing to improve from 2022 lows, and the production quality and quantity of useful software is still highly bottlenecked on software engineers who actually know what they're doing.
They will no longer be meaningful for producing math, rather they will only be humans who understand it.
Now it is the turn of mathematicians to feel doomed; in that context, I find this sentence very interesting.
Is the purpose of the Great Work not for humans to understand mathematics? What does it even mean to "produce" mathematics?
First silicon came for arithmetic, then it came for symbolic manipulation, and now it's come for theorem proving, this will certainly change the roles of working mathematicians and perhaps destroy the egos of some of their number, but the purpose of pure mathematics was never to sit there churning out proofs in the first place.
In general, I think most people tend to conceptualize jobs as individual tasks, and when those tasks get automated, then it's over for those jobs; in practice, automation of tasks generally induces demand and opens up previously uneconomical or unknown tasks. Additionally, many, perhaps most jobs in modern economies do not really exist to hill-climb tasks in the first place, but rather for social reasons, political reasons, legal reasons, just to name three. The reason many commission artists make a living is not primarily for the fidelity of their art, and the reason mathematicians get paid is not for their skill at proving theorems of no economic value. If, or when, these jobs change, it really has very little to do with technological capabilities and a lot to do with the evolution of society, which is certainly driven by technology, but almost impossible to predict.
I am, of course, not implying that nothing will ever happen, and to the contrary expect many changes to reverberate throughout the world; rather I think that the boosters heralding mass unemployment or very rapid change in the world have not properly thought through why nothing of the sort has yet happened, what capabilities are yet missing before such things might be possible, and how such capabilities might be elicited from existing technology, as opposed to the almost tautological framing of RSI or AGI where all this is true by definition.
In some sense, it's not really that surprising though; the vast majority of people barely understand their own value and why they get paid what they do, let alone anyone else's value at their firm or in their profession, let alone the value of everyone else in the economy.
Shirayuki3
15d ago
I think it's kind of like cooking your own food; even if technically you could do it yourself and it's gotten much easier to do so in the last 70 years, a lot of the "luxury" of eating out is having someone else do it for you, and being able to eat something out of distribution from what you'd normally eat.
I find that vibe-coding games sounds interesting in theory, but in practice it appeals much more to "people who want to make games" than "people who want to play games"; playing your own game feels kind of boring once you've put your intellectual efforts into making it.
Shirayuki3
16d ago
Yes, I don't disagree that there will be a lot of churn and pain in the meantime.
I find it's practically a second part-time job to hold back the worst impulses of my non-technical coworkers, the junior developers and management to slop up tickets, documentation and the codebase, which has been somewhat taxing. Unfortunately, it'll probably get worse before it gets better.
Shirayuki3
16d ago
I'm not sure if I would even go that far
I think if you're skilled and disciplined with your LLM usage, it's pretty unquestionable that software engineering productivity has improved.
For example, I've really enjoyed using Ghostty, Dwarfstar and pi; each of these excellent software projects are written using LLM's with no slop in sight, but importantly these projects are also owned by mitchellh, antirez, and badlogic, who are three incredible programmers in their own right.
That being said, I basically agree with you that ironically, the natural-language programming interface is actually extremely difficult to use correctly, and many AI coding initiatives aren't going particularly well because it's so easy to default into slinging slop and hence productivity improvements are hard to find in many cases.
I'm optimistic that over time the industry will develop better norms and understand how LLM tooling should and should not be used, and we'll all be able to reap the benefits (a man can hope...).
Shirayuki3
16d ago
I'm also finding it quite hard to articulate, but I agree that there seems like there's something missing in terms of "volition" or "creativity".
Pretty much all white collar work above a junior level involves a lot of "deciding what should be done next", "convincing other people about what to do next" and "taking responsibility for what to do next"; at least for now LLM's can't really do any of this, even if LLM's are now very good at hill-climbing individual tasks that comprise jobs.
Shirayuki3
16d ago
Your anecdotes about translation are very interesting, I hope you keep updating us.
Sure, I'm happy you find it interesting. I just find translation as it relates to automation intriguing, because a) I have more knowledge about it than most other professions and b) it seems to have stubbornly resisted contraction; at least on paper most people would think translation as a profession has been going downhill for the last 25 years and yet they've been doing better than the average joe would expect (not to say doing phenomenally, but certainly making a reasonable middle class living).
I certainly wouldn't advise anyone to get into translation in 2026, but then again I wouldn't have advised anyone to get into translation in 2016, 2006 and probably not 1996 either. It's just very difficult to predict how these things pan out, and this is a single niche profession amongst the broader economy that's orders of magnitude more complex.
Simply put, I don't actually think much wealth is generated through software directly.
I generally agree that tech bros have a tendency how to overrate how important software is to the economy, but I do think a "software singularity" where software engineering got a massive uplift in productivity would be showing quantitative and qualitative signs at a macro level that don't appear to be appearing so far. That being said, in this case diffusion is still in progress, and probably we'll have a better idea in a few years of how useful it really is.
Where I expect things to start showing up big-time in GDP is when advancements in AI translate out into doing physical things
I definitely agree that if, or more realistically when, things like humanoid robotics become mainstream instead of just gimmicks there are going to be massive impacts on GDP.
I'm not as sure about this applying to things like toaster manufacturing though; I don't particularly have deep knowledge about this, but it was my impression that especially in East Asia, the manufacturing chain for consumer goods is already extremely automated. Perhaps it's a failure of vision, but I don't see how LLM's could really meaningfully increase manufacturing productivity in significant ways unless we're talking about AGI/ASI levels of robots autonomously developing the entire supply chain.
ai-assisted chip development and software engineering is a default option
I personally think the effects of current AI on software engineering productivity are somewhat overstated (at my fairly AI-pilled software firm there's been many "AI-assisted" design documents and RFC's of dubious value, lots of rewrites of internal platforms, test suites and frameworks that look productive but haven't really been that useful, and only somewhat modest improvement in terms of actual firm-wide user-legible value), but as a whole I would agree that software engineering productivity has been meaningfully enhanced via AI.
There doesn't yet seem to be meaningful impact on software engineering employment, or anything noticeable on a macro scale as a result of modern LLM coding, but I think I would agree it is too early to determine the wider effects of coding agents one way or another.
translation is basically solved
I think translation is an great example of what I mean by "if AI is so good, why is nothing happening"?
We've basically had "solved translation for dummies" since 2016 Google Translate NMT, in the sense that the output wasn't great, but someone with no knowledge could bumble through understanding the gist of a brochure or a manual, where previously it might have been literally impossible for them to understand the text without consulting another human. I remember quite a few people in language learning communities I was part of at the time were already getting blackpilled on the full automation of translation as an inevitability all the way back in 2016.
LLM's took that up one step further, since about early 2023 we've had "solved translation for normies" in the sense that LLM's could reliably provide semantically correct translations for pretty much any input/output language pair. Maybe it makes some minor mistakes or it sounds weird to the critical reader, but nothing that really matters in the vast majority of use-cases for the vast majority of people.
Most if not all my friends in 2016 would have agreed that the existence of these models would be the end of human translation, and yet in nearly four years there still has been no significant macro impact on translator employment, or really anything noticeable on a macro scale that might be noticeable if translation was truly "solved".
So then, why is this case? This topic came up when I was chatting with some translators the other day, but I wasn't really satisfied by the points that ended up being brought up.
Is AI translation too expensive? Perhaps plausible for the earliest LLM's, but certainly not any remotely recent model, at least when compared to the fully loaded salary of a first world translator.
Is AI translation not reliable enough? I thought this might be the case, but I was assured that this isn't really true for most translation jobs. It certainly matters to have a human liability shield for regulated medical, diplomatic, legal use cases etc, but most translators don't work in those niches, and for most translation work accuracy is not really that paramount - most people are happy with "good enough" and people who care about translation quality have always been a small minority.
Is diffusion simply incomplete and all the translators will be unemployed in X more months or years? Plausible, but I'm not convinced this can be the entire story either; at this point more than half the planet has tried ChatGPT or Gemini, and AI is top of mind in nearly all corporate boardrooms right now. Even if diffusion is slower than expected, I would think it reasonable that after nearly four years there should be some sort of real world impact.
Are there induced demand effects outweighing the supply increase? Certainly demand for Japanese<->English, Chinese<->English and Chinese<->Japanese translation (and likely lots of other language pairs) has exploded in the last 10-20 years; the expectation now is for games, media, writing to be rapidly localized across many different languages when you used to have to wait years for any kind of translation if at all.
This can't be the entire story though; if translation really was solved, it wouldn't matter how high demand was when AI would be meeting the vast majority of it. Perhaps it's possible that most translation is solved, but induced demand for the translation that is not solved means that most translators still have jobs?
I agree that logistics and tooling are significant bottlenecks for anything that needs to interface with the physical world, but I think it's a logical criticism to make that even solely in the worlds of bits and words there's really been very little happening in the world relative to the capabilities of LLM's.
In general I don't think I've seen a rigorous argument supporting the idea that "AI just needs X more months to develop Y capabilities and it'll have Z real world effect", when it seems that nobody really understands what capabilities are missing from the current models that are currently preventing them from having major real-world impact in the first place.
Shirayuki3
18d ago
Not something I have statistics for, but my intuition would probably be that there's more C/K speaking girls than the past driven by increased tourist demand and foreign immigration (to a lesser extent Korean, to a greater extent Chinese, the development of foreign enclaves in the major Japanese cities is another wedge issue in Japanese politics), but that C/K speaking girls would still be a tiny minority in absolute terms, as native Japanese women are still a proportional super-majority of the population, and very few Japanese women, especially the ones that end up in sex work, are going to have the ability to learn Chinese or Korean.
With all the renewed hype around Astra and AI mathematics, I have been feeling that I haven't really seen a response I'm satisfied with from the AI bulls (at least the imminent mass unemployment / AGI / singularity types) to the 80IQ skeptic question of "If AI is so good, why is nothing happening?".
FWIW, if I knew in 2020 that in a few years we would have AI models that can get a perfect score on the IMO for pennies and meaningfully contribute to research mathematics I have expected that we basically live in a sci-fi world as well; yet now we have these models for $20 a month, and literally nothing I'm aware of has happened on a macro level clearly attributable to AI, either quantitatively or qualitatively, apart from the distortion of the AI capex buildout. In fact, it's actually GLP-1's that are basically a complete miracle on a macro-economic and public health level, and where there actually are many macro statistics that are visibly affected by GLP-1's.
On some level there probably is anthropomorphization going on here where the natural human assumptions are that
- Only a human with 99.99% percentile intelligence could meaningfully contribute to frontier mathematics
- Humans with 99.99% percentile intelligence are extraordinarily economically valuable and powerful
- AI can contribute to frontier mathematics
- Therefore AI is extraordinarily economically valuable and powerful
when in fact the conclusion does not actually follow from the premises; it is possible that AI is extraordinarily economically valuable and powerful for other reasons, but this does not follow from being superhuman at mathematics.
Modern pure mathematics is, as we seem to be finding out, not particularly economically valuable in and of itself; mostly mathematicians are lionized for their intellect because a human with that level of intelligence could obviously do significant amounts of other economically valuable work, but this seems extremely non-obvious in the case of AI.
The "best" response I've seen is something along the lines of "actually AI is still heavily limited by spikiness right now but the exponential is going to keep going bro" which I suppose is honest as to current capabilities and not disprovable, but it does feel like a retreat away from "AI is already crazy good" as many people have been and are touting, and towards magical thinking; somewhere along the line the party line swapped from "AGI imminent" to "AI that creates AGI imminent".
My take-away certainly isn't that AI is a fugazi; obviously it's powerful technology and I'm still quite bullish in the mid-long term, but I've certainly been feeling myself getting anti-hyped with recent releases as a result of this growing discontinuity of any real-world effects.
I suppose this is this week's race discussion thread; could someone actually steelman the "white supremacy" takes, for lack of a better way to put it after a minute's thought, that seem all the rage on the Motte lately? For example, this post from last week's thread, and the OP.
I can quite well understand the theory of mind of people who complain about mass immigration, or even immigration in general.
I can also understand the theory of mind of the HBD realists and the scientific racists who go on about the Hajinal line or Ashkenazi selection pressures or whatever. If you're actually a WASP nativist or something then alright, at least you have something cohesive going on there.
Yet when people start going on about whiteness it just seems really silly to me. Just in the last hundred years Greeks, Italians, Slavs, Irishmen went from distinctly "other" to "white" to all but the most dedicated haters. Likely in another hundred years assimilated Hispanics, Indians and East Asians will probably be considered "white" for all intents and purposes.
If "white" is just a Schelling point for the things you actually care about (culture, immigration, governance, whatever) then complaining about some dudes wearing cowboy hats just makes you sound like a base racist that misses the point entirely.
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