Shirayuki3
new account for Shirayuki2
User ID: 4553
Shirayuki3
1mo 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
1mo 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
1mo 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
1mo 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
1mo 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
1mo 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
1mo 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
1mo 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.
Shirayuki3
1mo ago
This was more true perhaps 10-20 years ago, but nowadays the number of fuzoku (the Japanese sex industry) establishments that will actually bar foreigners are firmly a minority (at most they will require basic Japanese for safety reasons).
With the relative economic doldrums of Japan, the decline of interest in the sex industry amongst younger Japanese men, and the economic rises of China/Korea/Taiwan/the massive rise in Japanese tourism in general, there has been a fairly large re-orientation away from catering to native Japanese with declining purchasing power and interest in prostitution towards chasing affluent tourists with money to splash.
It's even becoming a minor wedge issue in Japanese politics that Japan is becoming a sex tourism destination, especially towards rich East Asian johns that are perceived, not really incorrectly, as a symbol of Japanese decline and national humiliation.
Shirayuki3
1mo ago
[Leading in AI] is a fundamental prerequisite to ensuring that democratic states can achieve favorable terms with authoritarian states.
Defending democracies that are under attack, such as Ukraine and (via cyber attacks) Taiwan, seems especially high priority, as does empowering democracies to use their intelligence services to disrupt and degrade autocracies from the inside.
This is pretty serious language to use when referring to the party that the Chinese people believe legitimately governs China.
If Anthropic's opening statement is literally "if we achieve a durable technological lead, we will use it to defeat the Chinese government", then naturally Anthropic trying to speak out of the other side of their mouth to blame China for not pausing will sound duplicitous and self-serving to a people brought up at the feet of the century of humiliation.
In my view, the fundamental mistake that was made and is continuing to be made by the American tech elite, and more broadly the Western neoliberal project, is holding the belief that we live in an age where ideology is no longer consequential, an era commanded solely by capital. Muslim asylum seekers will become Western liberals because we will make the Muslims rich, Russia will liberalise because Europe will make the Russians rich, China will liberalise because America will make the Chinese rich; in the real world, asylum seekers remain unassimilated, Russia invades Ukraine, and China has designs on Taiwan not because any of this makes any economic sense, but because of the might of the ideologies held by the ummah, Putinists and Chinese nationalists.
Similarly, a lot of tech elites have a post-ideology view that as long as the proles are tossed a wad of cash, they'll be allowed to do as they please; in essence, that Americans will become Western liberals because Silicon Valley will make Americans rich. In the real world, people care about things like "dignity" and "long-term benefit", and fundamentally, Americans do not believe that data-centres, and the goals of big tech and big AI, are aligned with their wellbeing and prosperity (frankly correctly, in many cases), and are not willing to be bought off by those they perceive as their enemies; complaining about object-level inaccuracies like water use or electricity is simply missing the broader point that there is no trust and no belief that data centres will benefit Americans.
It is informative, I think, to compare the attitudes of the median Chinese vs the median American on the topic of AI. While perhaps apprehensive of great changes unseen in a century, the median Chinese person believes that they are governed by those who work for the benefit of China, and that the power of technology and AI is and will be harnessed for the benefit of the people. Chinese model labs don't boast about how they're going to make everyone unemployed, or how they, and by proxy lab shareholders, are going to rule the world; Liang Wenfeng instead talks, very reasonably, about how his aim is to make a restrained profit, and how the benefits of AGI are going to accrue to society.
To be clear: I, myself, am pro data-centre, because my belief is that the best way to improve aggregate human wellbeing is unceasing development of the productive forces, and that this development is going to require building out compute to support AI and robotics. For others, it is easy to sneer at the idiocy of the proles, as @aqouta does, or believe that the outcome is overdetermined by economic forces, and that the proles will inevitably be swept aside, as @DaseindustriesLtd does.
I find these views to be somewhat shortsighted; a study of history shows clearly that people prioritize their ideological interests over their rational economic interests, and that when ideology and capital clash, ideology often comes out triumphant, at the expense of the interests of capital. Did it make economic sense for Venezuela to nationalise their oil fields and plunge the formerly richest Latin American country into poverty? Did it make economic sense for the finest across two generations of European men to die horribly across Verdun, Stalingrad and Normandy during the World Wars?
It's crucial to contextualize that all of this backlash is happening while the misery index (unemployment + inflation) is essentially completely unaffected by AI. If, or when, this begins to change, and the backlash against data centres, and more broadly against Silicon Valley and AI, continues to intensify, I think it is not unlikely that a truly bi-partisan, populist, degrowth ideology begins to consume American politics. One could imagine a scenario where the Dems take the White House in 2028, crush Musk and the broader American AI industry with the power of the state, and enforce a neo-luddite Fortress America defended by two oceans and the strategic nuclear triad.
Does this vision make any economic sense? Not at all.
Is this sustainable as a long term vision for America? Not at all; Americans never learned the lessons that the century of humiliation engraved into the Chinese psyche.
The trap is believing it matters at all whether such a vision makes economic sense. At a certain breaking point it no longer matters, the people will try and lash out however they can against those they believe to be their ideological enemies, and while a single drop of water has no power and holds no threat, no human technology is yet able to stop a tsunami. I think it is extraordinarily important, for all our sakes, that big tech and the frontier AI labs realise that they have lost the mandate of heaven instead of acting as if though they are no longer a part of society, and sincerely take steps to rectify this before it is forced upon them by the state and by the people, and we all become much worse off for it.
As a response to @Ioper and @Primaprimaprima as well:
If you define woke and DEI as "women having increased economic power relative to men" in such a way that it applies globally across East Asia and the global south then ok sure, but I don't think that's a particularly useful definition.
The decline of traditional publishing in favor of online entertainment is pretty clearly globalized; the phenomenon of men retreating to online and non-traditional reading (e.g the narou / qidian scenes, basically web serials for Japan/China) and of course video games and the myriad of digital pleasures, while only women continue to read traditionally published books, is a fully globalized phenomenon, not just contained to Anglo societies.
It seems fairly clear to me that this is a phenomenon driven by women gaining more economic power relative to men across the entire world, and revealed preferences given the general availability of internet and smartphones. If you want to call this woke or DEI then sure I guess, but I don't think saying that China or Pakistan is woke is a particularly useful definition.
Shirayuki3
2mo ago
You won't find something equivalent to Blood Meridian or Moby Dick published online
Most of Dickens' body of work was written as practically the equivalent of webserials for the Victorian era, as well as Anna Karenina and Brothers Karamazov. Even in the modern age I'd argue that lots of what's published online is better than what comes out of traditional publishing, and it's mostly status considerations as to why people denigrate works published online rather than anything to do with the format itself.
Shirayuki3
2mo ago
That is a very high barrier to entry
Yeah that's fair enough, I agree that booktok / romantasy slop is now aggressively marketed to women in a way that reading is no longer marketed to men.
Still, I'm not really convinced this is a problem per se; on an individual level there's plenty of avenues for men to read and write literature if they so desire, and on a societal level would we really be better off if the romantasy equivalent (Dungeon Crawler Carl?) was getting marketed aggressively to men?
I am convinced this is very much a supply issue, not a demand issue
IMO there's plenty of supply if you know where to look, frankly way more supply that any human could engage with in a thousand lifetimes, between the classics, modern web fiction, and non-traditional mediums (narrative indie games, graphic novels, visual novels etc). If the claim is more narrow that there's a supply issue within modern traditional publishing then I agree, but it seems like neither male producers nor male consumers as a whole are particularly interested in filling the gap, so it seems like a bit of a dead end. I'm not convinced that specifically lack of modern traditionally published books is why boys are reading less, when there's so much else available to read for those interested.
I would guess that at least half of those boys are "lost" because of an insufficient supply of books.
Those are some interesting stats, but I'm not convinced that less boys reading is causal to reduced male educational / professional success (although it does seem likely that there are other factors of modernity causal of both less reading and less success).
The era where every upper-middle class man received a traditional liberal arts education and was conversant in the classics is decades past; nowadays your doctor's favorite movie is the Avengers and your lawyer plays Fifa in the one hour free he has every week to unwind. The pressures behind competitive careers nowadays don't really align with developing literary taste; I've had much more interesting intellectual conversations with underemployed third-world internet anons compared to the vast majority of the magnet school strivers that I went to school with. I'm not convinced that more reading would lead to more men in elite positions at all.
Shirayuki3
2mo ago
Yes, a pause of frontier training while we sort out how we can do this safely seems our best move
Well, we've discussed this one before, but my position is still that wanting to pause frontier training is much like wanting to totally disarm every nuclear weapons state. Perhaps it's a noble goal to reduce x-risk in theory, but in practice no great power will ever allow themselves to be disarmed in such a manner and so it's impossible in practice to achieve such a goal. Additionally, the second-order effects of such a goal seem likely to be profoundly negative (the Cold War ex-nuclear weapons almost certainly would have lead to WW3, missing out on the potential economic and productivity gains of AI).
This is just a matter of closed labs being far ahead of open weights labs. If there was parity then open weights are categorically less safe as post training can sand off any alignment work done to prevent mass murder tasks.
I agree that open-weights models are less safe than closed-weight models of equivalent capability, but nobody, not even the Chinese labs themselves, believes that open weights are going to get ahead of closed weights in the short or medium term so this seems like a bit of a non-sequitur. I don't think you're really addressing the point I was trying to make in the original post, which is that it is closed-weights that is advancing the frontier, and thus it's much more likely that it is mistakes or malfeasance derived from closed-weight model access that is going to cause the feared harms.
we're all definitely going to die in this world
As soon as man comes to life, he is at once old enough to die.
Please don't waste time critiquing exactly that example, the AIs are going to be smarter than we are and will come up with any attack vector to cause human extinction that's possible if one is possible
If we accept this as a premise, that the wrong prompt is going to kill everyone, then honestly what are we even doing here? Treat your loved ones to something nice and enjoy your life, because even with maximum safety someone is certainly going to fuck up and eventuate human extinction.
Someone at a frontier lab will make a mistake during KYC and give access to the wrong actor, or they'll make a mistake while setting guardrails, or a government will fuck up containment when using the unrestricted model they'll demand, or there'll be a particularly fucked up RL training run (HuggingFace incident on steroids) and that's going to be that for the human race; open-weight models or safety-gated models need not apply at all.
For example, there's a bunch of hand-wringing around biorisk lately, but it's illustrative to look at the actual bioweapons attacks that have happened in modernity. The preponderance of the evidence points towards the 2001 Anthrax attacks having been done by a employee at Fort Detrick, who would have certainly have been given access to hypothetical bioweapon-GPT. The only "successful" bioweapons attack ever carried out by a private organisation was from Aum Shinrikyo, who had ludicrous amounts of money and significant institutional connections; how hard would have it been for them to get a subscription to bioweapon-Claude?
Based on history, it seems much more likely that if AI-assisted bioweapons really do ravage the earth, it's going to be either because an American closed-weight lab sold a bad actor access to an unrestricted subscription, or because some lab or government fucks up containment and releases some gain of function monstrosity into the wild. Even in the realm of cyber, OpenAi and Anthropic have already been responsible for many more "cyber attacks" than abliterated GLM / Kimi or whatever; I don't really think the fingers are really being pointed at the right places here.
I agree with Opt-out here. It's easy to point fingers at woke or DEI, but I think the cause is really just prosaic capitalism. Acknowledging I'm in a filter bubble, plenty of men in my orbit read; they just don't do it in a way that makes money for traditional industry.
They read Substacks, or they read Royalroad/web serials/fanfiction, or they "read" manga/indie narrative video games/visual novels, or they pirate all of their literature and the classics from Libgen and Anna's Archive. It's much easier than it's ever been to self-publish or release your work online without going via Big Publisher.
The difference is simply that female writers are disproportionately interested in the prestige of going via traditional Big Publisher, and female readers actually spend money with publishers and bookstores, driven by BookTok or whatever, and hence those industries move increasingly towards catering to the female userbases that actually make them money.
Trying to make men read in the same way that women like to read seems to me much like trying to make sports gambling appealing to women; perhaps in the interest of the industries trying to increase their profits, but honestly a waste of time for society at a whole to try and fit a square peg into a round hole.
Shirayuki3
2mo ago
I once had such an experience with a compassionate, highly intelligent friend of mine (mid 6 figures earner as an engineer, frequent donator to charity, would gladly give the shirt off his back to someone in need).
It started off with him posting some milquetoast meme in the groupchat supporting some ridiculous rent control policy, and me replying with another milquetoast meme referencing the economic problems with rent control. This kicked off an extremely long argument, debating the relative merits and demerits of rent control, which concluded with him admitting that the proposed policy would almost certainly raise housing prices in the long run.
At this point, as I see him continuing to type, I think I've convinced him to stop supporting the rent control policy; but instead he writes "even if you're right on a utilitarian level, I just can't morally support increasing the rent of people in need".
With this masterstroke, he's depicted himself as the empathetic deontologist chad and me as the cold-hearted utilitarian soyjak, and all I'm able to do is agree to disagree and slink away with my tail between my legs.
I think that fundamentally the vast majority of humans are wired to prefer policies and actions that have obvious, visible benefits, even if on aggregate, they're net negative in a way that's difficult to explain. It's really only EA's (extreme autists) that can bite the bullet and advocate for policy wonk solutions such as means-testing welfare or UAE-style guest worker visas, with aggregrate net-benefit but that look evil on the surface.
To be honest, I'm pretty blackpilled on the future of politics in the age of a low trust society permeated by internet and social media. It seems almost certain that politics are going to become Latinized, a pendulum between left wing socialist populism and right wing strongman populism.
But what is there to be done about it?
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.
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