The tl;dr before you get into this post is this: the SFWA came out, said that some AI usage was okay enough in books for the authors of those books to not to be disqualified from winning a Nebula award, people got (correctly) pissed, the SFWA swiftly threw that fish back into the water and was like, “Just kidding, AI is bad,” and then launched this survey to get community input on AI usage in writing and publishing.

As a result, a few folks have kinda popped up their heads to be like, “But is all AI bad?” and some of this is reasonable and necessary discussion, because sure, what if your word processor accidentally injects some kind of AI process into the work, or what if your publisher against your wishes uses AI in, say, the marketing of the book? What does that mean for you? Do you have recourse? Are you still able to win awards? I guess it would suck to be shut out of awards for that — though, at the same time, awards aren’t even the frosting on top of the cake but the sprinkles on top of the frosting? Whatever.

Of course, in typical fashion, usually these sort of reasonable questions are a Trojan horse to allow a lot of other exceptions in through the city gates. To continue to mix metaphors, if you give a mouse an AI cookie, well, he’s gonna want the AI milk, the AI straw, until eventually you’ve given him an AI nuclear bomb where he kills all the human beings and can feast on our smoldering corpses at his rodenty leisure.

One of the people who popped up was Erin Underwood, who wrote an open letter about all this. It is a letter that purports to be reasonable, common sense, but in my mind is a goalpost-shifting mouse-cookie-giving very hungry caterpillar of a post, where it just wants more and more — and so, it summons in me the urge to point out a number of its flaws. And this, on my part, is probably already a sucker move, because Underwood more or less suggests that AI has written her open letter, at least in part:

“For transparency, I used speech-to-text to capture my words and generative AI to clean up grammar and structure. I needed an efficient way to get my thoughts down quickly so I could move into the work of manually editing and refining this text. I went through it multiple times, revising language, examples, and arguments until the final version fully matched my vision. This was done intentionally to demonstrate how AI can function as a communication tool for business purposes. This letter isn’t a work of art or artistic creation.”

So already, we’re off on a broken foot. I’ve no idea how much of a human letter I’m responding to. (And for full transparency on my part — all of this post is 100% human-written, human-edited, human-derived. I am not Soylent Greening this shit. This is all me, flaws and all.)

Before I get into her bullet points, up front she is essentially saying that we can’t be hostile to the conversation, to these difficult questions, and that:

At the same time, refusing to adapt in ways that protect our own communities would create new harm. Writers, artists, musicians, publishers, and the industries that support them must remain viable and competitive in a modern world that is becoming deeply dependent on AI tools and AI-driven infrastructure. If we are going to protect the future of creative work, we need award rules that are practical and that also allow us to use ordinary business tools.

My first thought here is: yeah, no, that’s not really true.

There’s little evidence at hand, first and foremost, that AI is a value-add to any of this. Writing, making music, publishing, whatever. Industries not using them are perfectly viable. Writers not using AI remain perfectly viable. (I’d argue: more than viable! Actually, you’re better not using it! AI is routinely shown to decrease efficiency and require more human intervention, often just at cut cost.) The trick to this paragraph is it is a false appeal to reason: a quietly fear-based approach that you don’t want to (gasp) be left behind because you aren’t using the reasonable business tools. Except, again, nothing about this is reasonable. AI is a random middle-man created by shitty techlords, forced into systems so that they get paid and that the Magic Number Lines go up instead of flatten or descend.

We are only as “dependent” on AI tools and infrastructure as we choose to be — this isn’t an automatic. But therein lies one of the tricksy bits about this letter, like so many of the AI boosters: it presupposes an automagic AI future, a destiny for AI in and above us. It assumes it’s already here to stay, already embedded in us like a tick, so we might as well make friends with the parasite and use its Lyme Disease Tools and its Rocky Mountain Spotted Infrastructure. Why cure it? It’s already in us! No reason to ask who will rid us of this meddlesome infection!

Having a yes/no switch that governs the use of AI and generative AI isn’t viable because this technology is now embedded throughout the core infrastructure that supports businesses today. However, the fundamentally human act of creation must remain in human hands. At the same time, there are AI use cases that touch creative work directly and indirectly, often without the creator’s knowledge or consent. Those realities must be acknowledged. Creators should not be penalized for incidental, accidental, or third-party use of AI in business processes surrounding their original work.

This is probably one of the only reasonable bits in the letter. Yes, there are tough realities of gen-AI intrusion, in part because so many tech services are foisting it upon us — and we aren’t always aware of how deeply that splinter is stuck.

But, again, give a mouse a cookie…

The creative arts community is experiencing a deep sense of disruption and vulnerability in response to the rapid rise of generative AI. These concerns are legitimate and, for many, unsettling. When tech companies began developing large language models, original creative works were used without permission to train the very systems that are now threatening creators’ livelihoods, authorship, and ownership. That breach of trust is real and unresolved. It also can’t be undone, which means creatives and the industries that support them must think strategically about how this technology shapes both risk and opportunity going forward while also continuing to fight for fair compensation for their work (which, again, was used without permission).

Ahh. Starts reasonable, but ends with: “It also can’t be undone.” Look, sorry, the demon is out! We can’t contain the demon, so now we just gotta figure out how to live with the demon — sure, we can feed it, but we also have to make sure it isn’t eating us! Otherwise, it’s fine!

Except, it’s not fine. It did steal from us, and that’s not just past-tense shit. It is now and will continue to do so.

AI is not inevitable.

Say it again:

AI is not inevitable.

AI IS NOT INEVITABLE.

The only strategy here is the sum total pushback against its uncanny horrors and its non-consensual intrusion into every corner of our world — it steals our content, guzzles our water, increases our power bills, is crammed into services we didn’t ask for it to be crammed into while also charging us more money for the “privelege.” There is no strategy here except to find the fields where the AI grows and metaphorically set them aflame.

And shame and anger against corporate overreach is a powerful fire.

The evolution of AI use cases is fundamentally reshaping how modern business and industry operate, from book publishers to sales and marketing firms, retailers, and fan communities. AI isn’t niche any longer. It’s everywhere, including in our everyday digital tools and the infrastructure that makes business operate effectively. It shapes marketing and advertising, powers internet browsers and discovery systems, feeds social media platforms, and supports strategic planning, workflow design, internal communications, and day-to-day operations.

Worth seeing the conflation here — generative AI and LLMs are not the same AI that necessarily powers every other thing.

Publishers can’t realistically avoid using these tools if they intend to remain competitive and continue selling books, art, and music created by their authors and artists. At the same time, these tools are enabling smaller and independent publishers to compete more effectively with large companies such as Tor, Penguin Random House, and Gollancz by improving efficiency, reach, and sustainability.

Publishers can and must avoid using generative AI and LLM AI. Publishers remain competitive by hiring and training real people to do real people jobs that support real people authors and real people readers. AI remains a broken foot. Bad for the environment, bad for writers, and also, generally doesn’t work well — it certainly doesn’t work as well, or as creatively, as actual humans! Remember, the AI is fed with the work of actual humans. Why do you think that is, exactly?

If you use it, it means you’re replacing people.

People who could’ve done the job better.

People who actually did the job, and now their work is pilfered and duped.

And just to remind people now — if you really do believe that AI is just so great at what it does, please go talk to my cat, Boomba. Or is it Franken?

Most creators are not attempting to replace their own creative labor with AI. They are acting in good faith and want clear, ethical boundaries around authorship, originality, and creative ownership. The real challenge is that avoiding AI entirely is becoming increasingly impractical, even for those who are committed to producing fully human-authored work, as AI is now embedded in systems creators can’t control or realistically avoid.

Avoiding AI is easy. I do it all the time! Literally, all the time.

Let’s get into what Erin sees as use cases — though you’ll note throughout these use cases are theoretical and have zero examples of where they have been used successfully.

Voice-to-Text Dictation: Voice-to-text is one of the most common and accessible digital tools in use today, and most modern systems rely on generative AI to transcribe, normalize, and correct spoken language. Dictation is used for verbally jotting down ideas, sending text messages, and drafting emails.

I guess? To be fair, dictation has… been around for many many years and predates generative AI. AI has not been essential in this — which of course is the running theme of AI, far as I can see. “Did you want this thing you do to be better? No? Too bad, here’s AI! Also, P.S. now it’s actually sort of worse.”

(There’s a great Marc Maron bit about turmeric. Watch it and replace “turmeric” with “generative AI” and you’ll see what I’m seeing.)

Meeting Transcription: Meetings often happen over Zoom, Teams, or other video platforms that allow for meeting transcripts, which can also generate summaries and lists. Those transcripts can also be dropped into a generative AI system to pull out to do lists, ideas, and themes from the call.

Again, I guess, though meeting dictation also existed before AI — and you should also be very, very cautious about letting AI dictate important meetings, because remember that part where AI steals stuff? Yeah. That’s a thing. Also, remember when it turns out ChatGPT is recording all your conversations with it and people were able to access those chats? Riiiiiight. Maybe don’t do this.

Writing Tools and Applications: Microsoft Word, Gmail, and many other organizational tools have AI embedded in their code and use programs like Grammarly and CoPilot to help people proof, edit, and write. Often the very words you were going to write appear as suggested text if you don’t turn off these functions. It’s not just the author who is using these tools but also the editor, the assistants, and any number of other staff who work on the original file.

I mean, you can usually turn those off — and often it makes for a better writing experience because it’s not trying to auto-suggest boring or incorrect messages, but hey, okay, yeah, this exists. Worth noting though that “embedded in their code” is a dubious sentiment. Also, I was able to downgrade to the version of Word without AI. And I turn it off on my phone too wherever I find it. It’s insidious!

Now, for publishers —

AI for Screening and Triage: Some publishers are either considering or have already started using AI to some degree to manage incoming submissions and to move through the digital slush pile to weed out submissions that did not follow the guidelines or other rules … as well as identifying AI generated writing. This may also help them to look for submissions that meet a specific publishing need quickly and efficiently to elevate it for human editorial review.

Well, I hate that, and publishers should absolutely not be using AI to weed through submissions for a few reasons:

a) AI is often wrong, even at identifying AI, which is why it’s often false-flagging things that students wrote as “AI” (see, f’rex, people’s insistence that emdashes mean AI use, even though AI got the emdash use from people)

b) AI is biased, often invisibly, by those who created it, and you cannot see or adjust those biases meaningfully

c) It’s just gross? Letting a bad, environment-destroying machine do the human job of finding cool human stories to publish is gross, and fuck you if you do it

(edit)

And d) it feeds YOUR WORK into THE THIEVING MAGPIE OF AI, what the fuck, you’re just bloating the beast further, goddamnit

Initial Research and Accessibility Tool: AI can help authors parse complex scientific concepts, historical material, or technical subjects, translate sources from other languages, or gain an initial understanding of unfamiliar topics. When used as a starting point rather than a substitute for research, this can expand access to knowledge for authors without institutional resources.

AI INVENTED A SHITLOAD OF CATS I DON’T OWN

If it does that it definitely can’t explain high-concept shit reliably.

Please.

Continuity and Reference Tools: For authors, publishers, and studios managing shared worlds or long-running series, private, domain-specific language models can be used as internal reference systems to track character details, timelines, world-building facts, and continuity. Using AI in this constrained, reference-oriented way supports consistency and accuracy without generating new creative content or replacing human authorship.

Okay, you know what, I’ll concede that there is some reasonableness here — I wouldn’t do it, because I am a person who likes to have his person-shaped hands all over his person-shaped creations. But! Sure, if someone has a local model AI that they train on just their own material, hey, go nuts. (Though if you use it beyond organization and instead use it to, say, create new ideas — well, you’ve again sold yourself up the river and done nothing good for your brain or for the audience who will one day read your work.)

Data Analytics, Market Research, and Strategy: Publishers may use AI to analyze large volumes of data to identify catalog gaps, assess risks, understand readership trends, optimize release timing, and inform strategic decisions. This directly impacts publishing choices for which original works they accept and which ones they reject.

Given biases and data-gorging AI, this seems fraught to me — but, again, maybe we’re talking AI in the non-generative sense, and if that’s examining raw data and doing something with that, hey, whatever. Though even here, I’ll note that the most successful model of writing and publishing remains the simplest one: write and publish the best things you can that speak to your heart and your soul and then work the marketing ropes as best as you can (with real money) to help the audience see this thing that you made exist.

Ultimately, I flinch pretty hard at the idea of letting Skynet decide what original work should exist and what should be rejected, and here’s why:

The best thing you ever read was an original idea. It was novel in the truest sense — novel like COVID was novel! Not novel like a novel is novel.

But AI can only examine the past.

It can only see the trends that happened, not the trends that go forward.

Think of AI like prequel material — it is forever bound by what has already come before it and can only build upon the ground that has already been laid. It understands things that exist, not things that don’t, and therefore, in a job based somewhat considerably on people’s imagination producing original material, it will shit the bed. Meaning, it will reject cool new things because it cannot understand deviation from the cool old things.

(To be fair, companies fall into this trap without AI, too! But AI codifies it and removes from the equation human instincts and interests.)

AI in Marketing, Promotion, and Discoverability: Even when a story itself is entirely human-written, publishers may use AI to generate cover copy, promotional blurbs, SEO optimization, CTR analysis, or marketing insights.

SEO, okay, whatever, but if you let AI fuck with my cover copy, I’ll kick someone in the dick. Or blurbs! What the shit? Is she suggesting AI write… my blurbs? The ones I provide because I thought a book was cool? At a certain point you just have to wonder what the end vision is, here — is it that you use AI to generate ideas and then the AI writes a book off those ideas and then edits it and then an AI publisher submits it to other AI so that the other AI can provide AI blurbs for it? Books by AI, for AI, marketed to AI by AI? Just this digital ouroborous eating its own tail, shitting in its own mouth? What a glorious future! Who needs people at all?

Audience Engagement and Community Management: Publishers and creators may use AI to manage newsletters, reader outreach, community moderation, and customer support across social and digital platforms. These tools shape audience relationships without affecting the creative work itself.

Listen I’m starting to get tired. I mostly just want to smear the word NO across the blog in some kind of bodily fluid, but I persevere —

God, just write your own newsletters, just reach out to readers like a person, moderate your community as you see fit, be a person dealing with people and if that’s too much, don’t do it. Okay? Okay.

Workflow Automation and Internal Operations: AI is increasingly used to automate scheduling, task management, internal documentation, production tracking, and coordination across editorial, design, and marketing teams. These operational uses support the publishing process without influencing creative authorship.

If this is non-LLM non-gen-AI shit, er, okay, but also, this stuff kinda happens organically as it is? This workflow is well-known and well-wrought. Every book is not a unicorn — there is a process and people are the stations along the chain.

Legal, Contractual, and Financial Processes: Agents and publishers increasingly use AI tools to review contracts, analyze royalty statements, or flag legal issues. These business uses are unrelated to the act of writing and should not affect award eligibility. However, it is worth noting that authors can also drop their contracts into a generative AI system to ask it questions about the contract related to their original work to ensure they understand their rights, what they might be missing, and what they should explore more fully with legal counsel.

Ha ha, what, holy fuck, do not let AI deal with legal, contractual, or financial shit. Jesus Fucking Christ, this is deeply irresponsible. It is not good at it. Lawyers show up to court with this AI shit and they get their asses handed to them. This is not an okay place for AI. This is a dangerous place for AI.

If anything disqualifies the “open letter,” it is this.

Just have an agent or a lawyer.

One that won’t use AI.

Rights Management and IP Protection: AI tools are being used to track copyright infringement, detect unauthorized distribution, manage licensing, and monitor derivative uses of creative works online. These systems help protect authors’ rights and income without contributing to creative content.

This sounds fine, until you realize that…

AI just makes stuff up.

All the time.

Not just my quantum cats, either. I have a search set up for my name and some other topics in Google and every day it yields results that are patently just not there — a headline and a subhead will offer text and description that simply aren’t present when I click through. The entire subject matter isn’t even right. It’s wholly fabricated. It gets worse! So. There was a kid who died in my area, recently? (Well, he was in his 20s, I think. I say kid because I am increasingly AN OLD.) And the web was full of auto-generated AI barf about it — just fake weird news about a poor dead kid who died.

AI is a plagiaristic lie machine. You really can’t rely on it to find licensing info, derivative works, and so forth.

Accessibility, Localization, and Format Adaptation: Publishers and platforms increasingly use AI to generate captions, transcripts, audiobooks, large-print formats, and translations for global or disabled audiences. These tools expand access to creative works without altering authorship or creative intent yet still involve generative AI touching the work after creation.

Another profoundly disqualifying bit. No! No. NO. Do not let AI translate or transcribe our books.

HUMANS ONLY.

I mean, what the fuck. This letter seems to try to lean toward “AI can help you in ways where it doesn’t do the creative work,” but audio books? Translations? It’s very much part of that work. And we want that done right, and by people.

(In part because of accountability! You know who’s accountable when a person fails? That person! You know who is accountable when AI fails? Ennnh! Nobody! Defrayed responsibility! Oops the poor widdle small guy machine made a boo-boo. Want something done right? People are great! We love people! People are why we do this thing! Stop kicking them out of the process!)

Production and Technical Preparation: AI is increasingly used in formatting, layout checks, quality assurance, audio cleanup, and technical preparation for print, e-book, and audio releases. These uses support distribution rather than authorship.

Something like audio cleanup would be, I imagine, not about gen-AI/LLM. But other stuff, yeah, no, people are good. Let the people do it. Thanks.

Generative and Agentic Internet Platforms: The internet itself is shifting from a search-based environment to a generative and agent-driven one. As generative search engines, AI agents, and platform-level AI models become embedded across the internet, users are operating inside ecosystems where AI mediates discovery, visibility, and engagement by default. This means that information gathered in these environments increasingly comes through generative AI systems.

AI

MADE

UP

CATS

I

DO

NOT

OWN

It told me I have cancer!

That I’m a Christian and also Jewish!

It makes up stuff all the time and we’re supposed to just… give everything over to these agentic dipshits? The amazing thing was, we had this very nice Internet — messy, sure, but made of people and all the stuff they said and that they made and that came out of their heads, and then we let robots scoop it all up and start remaking “new” versions endlessly and it’s been downhill since. Let’s not accelerate our descent, yeah? This is silly and bad and I hate it. And you can tell I’m petering out here because my logic is, admittedly, “ew I hate it,” but seriously, it sucks and you know it sucks and down deep in that space between your heart and your stomach it makes you feel icky as shit, like you ate some bad shrimp. AI is bad shrimp. Stop trying to convince us to eat more of the bad shrimp.

Disproportionate Impact on Small and Independent Presses: Small and indie publishers often rely on generative AI for marketing, planning, and analysis because they lack the staffing and budgets of large publishers. Blanket AI restrictions force these presses into an impossible choice of either avoiding modern tools that allow them to publish more work and sell more books or use them and disqualify all their authors from awards.

Small and indie presses provide the crucial value of being small and indie, and indie by the way is indicative of human-influence — right? You go to a small press, you want hands-on, you want people you know, a small flexible team, and not a giant corporation. Well, bad news: AI is giant corpo shit. It’s techlord billionaire shit. If a small press can’t exist without that, then maybe they should reconsider whether or not they should exist at all.

Operational Strain on Fan Organizations and Conventions: Fan organizations and conventions are overwhelmingly volunteer-run and chronically understaffed. These groups operate on extremely limited time and resources, often relying on a small number of overextended volunteers to handle writing, editing, scheduling, marketing, and email communications as part of basic business operations. AI tools can reduce the burden of these time-consuming tasks and help volunteers work more efficiently. Without such support, many conventions may be forced to scale back or shut down entirely due to burnout and lack of operational capacity. The loss of these community spaces would be a significant blow to the science fiction, fantasy, and horror community as a whole.

Uhh I think I’d rather go to a convention run by people, not deranged robots.

You want Fyre Fest? This is how you get Fyre Fest. You want a YA convention with a creepy ball pit? Yeah, this is that? Let AI do this and you’ll end up with 1000 empty tables and no bathrooms.

Again, the theme persists of: “I’m pretty sure conventions existed before AI, and were run pretty well, so what is the AI doing again?”

Anyway, I’ve gotta tap out here.

There’s more to the letter but ultimately it seems to rely on the false premise that creatives better not SNOOZE, lest they LOSE, and we either get involved in the conversation and control AI or it runs over us. Except it already ran over us and now we’re figuring out how to get back up and string caltrops across the road to blow the fucking tires on this thing before it tries to hit us again. Also, nobody’s inviting us to the table. Nobody’s asking for our input. All this does is obey in advance to a fascistic system — AI isn’t trying to make nice with writers, we’re not being asked to join the team. We’re just being told to get on board or get fucked.

And I don’t agree with that framing.

I know. I’m bullish on this. Belligerent. But I really do hate it. I hate AI, and I hate all the framing that it’s somehow essential — it’s like being told you have to use a garlic press in the kitchen, and it’s inevitable, so use it, use it for everything, use it for cutting bananas and chopping nuts and peeling potatoes and cleaning your oven and teaching your kids and it can do all those things so well (spoiler: no it cannot) but SHUT UP AND USE THE GARLIC PRESS BECAUSE WE INVESTED A TRILLIONTY DOLLARS IN IT and if we can’t convince you to subscribe to the garlic press for literally everything all the time — did we not mention it’s a subscription service? — then we’re fucked, uhh, I mean, you’re fucked for not using our miracle product.

Anyway.

I think AI is only inevitable when we believe the lie of its inevitability.

I think people actually hate it. I think they naturally resist it because we can smell the existential threat coming off it like the stench of the aforementioned bad shrimp.

I think we intuitively can detect how it was made by rich fucks who want to be richer fucks, and how we’re just chum in the bucket for their digital sharks.

And I think it sucks.

It fucks the planet. It fucks our information fidelity. It steals our shit, our resources, our time. It’s mostly just a ruse, a threat, a lever: they can say oh take a pay cut or we’re going to use the godlike AI to replace you, and then they replace you anyway, and invite you back at an even sharper cut so you can herd the AI slop barf into shape like you’re Richard Dreyfuss with the fucking mashed potatoes in Close Encounters.

As Ash from Army of Darkness says:

“It’s a trick. Get an axe.”

I’m tired and I emerged from HIBERNATION WEEK to write this and now I need a nap or maybe I just need to lick a couple batteries or something.

Anyway. That’s my open letter. Feel free to respond below, but if you’re a chode, I drop you into the spam oubliette.

Destroy AI.

Buy my books — a human wrote them.

Okay bye.

With Nigeria, Trump—who calls himself “the most anti-war president in history”—has now bombed more countries than any president in history.

Charles Dickens wrote what has become one of the iconic stories of Christmas day and Christmas spirit in A Christmas Carol. But of course, the experiences of Ebenezer Scrooge are a story, not a piece of reporting. Here’s a piece by Dickens written for the weekly journal Household Words that he edited from 1850 to 1859. It’s from the issue of January 26, 1856, with his first-person reporting on “A Nightly Scene in London.” Poverty in high-income countries is no longer as ghastly as in Victorian England, but for those who take the time to see it in our own time and place, surely it is ghastly enough. Thus, I repeat this post each year on Christmas Day.

Economists might also wince just a bit at how Dickens describes the reaction of some economists to poverty, those who Dickens calls “the unreasonable disciples of a reasonable school.” In the following passage, Dickens writes: “I know that the unreasonable disciples of a reasonable school, demented disciples who push arithmetic and political economy beyond all bounds of sense (not to speak of such a weakness as humanity), and hold them to be all-sufficient for every case, can easily prove that such things ought to be, and that no man has any business to mind them. Without disparaging those indispensable sciences in their sanity, I utterly renounce and abominate them in their insanity …” 

Here’s a fuller passage from Dickens:

A NIGHTLY SCENE IN LONDON

On the fifth of last November, I, the Conductor of this journal, accompanied by a friend well-known to the public, accidentally strayed into Whitechapel. It was a miserable evening; very dark, very muddy, and raining hard.

There are many woful sights in that part of London, and it has been well-known to me in most of its aspects for many years. We had forgotten the mud and rain in slowly walking along and looking about us, when we found ourselves, at eight o’clock, before the Workhouse.

Crouched against the wall of the Workhouse, in the dark street, on the muddy pavement-stones, with the rain raining upon them, were five bundles of rags. They were motionless, and had no resemblance to the human form. Five great beehives, covered with rags— five dead bodies taken out of graves, tied neck and heels, and covered with rags— would have looked like those five bundles upon which the rain rained down in the public street.

“What is this! ” said my companion. “What is this!”

“Some miserable people shut out of the Casual Ward, I think,” said I.

We had stopped before the five ragged mounds, and were quite rooted to the spot by their horrible appearance. Five awful Sphinxes by the wayside, crying to every passer-by, ” Stop and guess! What is to be the end of a state of society that leaves us here!”

As we stood looking at them, a decent working-man, having the appearance of a stone-mason, touched me on the shoulder.

“This is an awful sight, sir,” said he, “in a Christian country!”

“GOD knows it is, my friend,” said I.

“I have often seen it much worse than this, as I have been going home from my work. I have counted fifteen, twenty, five-and-twenty, many a time. It’s a shocking thing to see.”

“A shocking thing, indeed,” said I and my companion together. The man lingered near
us a little while, wished us good-night, and went on.

We should have felt it brutal in us who had a better chance of being heard than the working-man, to leave the thing as it was, so we knocked at the Workhouse Gate. I undertook to be spokesman. The moment the gate was opened by an old pauper, I went in, followed close by my companion. I lost no
time in passing the old porter, for I saw in his watery eye a disposition to shut us out.

“Be so good as to give that card to the master of the Workhouse, and say I shall be glad to speak to him for a moment.”

We were in a kind of covered gateway, and the old porter went across it with the card. Before he had got to a door on our left, a man in a cloak and hat bounced out of it very sharply, as if he were in the nightly habit of being bullied and of returning the compliment.

“Now, gentlemen,” said he in a loud voice, “what do you want here?”

“First,” said I, ” will you do me the favor to look at that card in your hand. Perhaps you may know my name.”

“Yes,” says he, looking at it. ” I know this name.”

“Good. I only want to ask you a plain question in a civil manner, and there is not the least occasion for either of us to be angry. It would be very foolish in me to blame you, and I don’t blame you. I may find fault with the system you administer, but pray understand that I know you are here to do a duty pointed out to you, and that I have no doubt you do it. Now, I hope you won’t object to tell me what I want to know.”

“No,” said he, quite mollified, and very reasonable, ” not at all. What is it?”

“Do you know that there are five wretched creatures outside?”

“I haven’t seen them, but I dare say there are.”

“Do you doubt that there are?”

“No, not at all. There might be many more.”

”Are they men? Or women?”

“Women, I suppose. Very likely one or two of them were there last night, and the night before last.”

“There all night, do you mean?”

“Very likely.”

My companion and I looked at one another, and the master of the Workhouse added quickly, “Why, Lord bless my soul, what am I to do? What can I do ? The place is full. The place is always full—every night. I must give the preference to women with children, mustn’t I? You wouldn’t have me not do that?”

“Surely not,” said I. “It is a very humane principle, and quite right; and I am glad to hear of it. Don’t forget that I don’t blame you.”

“Well!” said he. And subdued himself again. …

“Just so. I wanted to know no more. You have answered my question civilly and readily, and I am much obliged to you. I have nothing to say against you, but quite the contrary. Good night!”

“Good night, gentlemen!” And out we came again.

We went to the ragged bundle nearest to the Workhouse-door, and I touched it. No movement replying, I gently shook it. The rags began to be slowly stirred within, and by little and little a head was unshrouded. The head of a young woman of three or four and twenty, as I should judge; gaunt with want, and foul with dirt; but not naturally ugly.

“Tell us,” said I, stooping down. “Why are you lying here?”

“Because I can’t get into the Workhouse.”

She spoke in a faint dull way, and had no curiosity or interest left. She looked dreamily at the black sky and the falling rain, but never looked at me or my companion.

“Were you here last night?”

“Yes, All last night. And the night afore too.”

“Do you know any of these others?”

“I know her next but one. She was here last night, and she told me she come out of Essex. I don’t know no more of her.”

“You were here all last night, but you have not been here all day?”

“No. Not all day.”

“Where have you been all day?”

“About the streets.”

”What have you had to eat?”

“Nothing.”

“Come!” said I. “Think a little. You are tired and have been asleep, and don’t quite consider what you are saying to us. You have had something to eat to-day. Come! Think of it!”

“No I haven’t. Nothing but such bits as I could pick up about the market. Why, look at me!”

She bared her neck, and I covered it up again.

“If you had a shilling to get some supper and a lodging, should you know where to get it?”

“Yes. I could do that.”

“For GOD’S sake get it then!”

I put the money into her hand, and she feebly rose up and went away. She never thanked me, never looked at me— melted away into the miserable night, in the strangest manner I ever saw. I have seen many strange things, but not one that has left a deeper impression on my memory than the dull impassive way in which that worn-out heap of misery took that piece of money, and was lost.

One by one I spoke to all the five. In every one, interest and curiosity were as extinct as in the first. They were all dull and languid. No one made any sort of profession or complaint; no one cared to look at me; no one thanked me. When I came to the third, I suppose she saw that my companion and I glanced, with a new horror upon us, at the two last, who had dropped against each other in their sleep, and were lying like broken images. She said, she believed they were young sisters. These were the only words that were originated among the five.

And now let me close this terrible account with a redeeming and beautiful trait of the poorest of the poor. When we came out of the Workhouse, we had gone across the road to a public house, finding ourselves without silver, to get change for a sovereign. I held the money in my hand while I was speaking to the five apparitions. Our being so engaged, attracted the attention of many people of the very poor sort usual to that place; as we leaned over the mounds of rags, they eagerly leaned over us to see and hear; what I had in my hand, and what I said, and what I did, must have been plain to nearly all the concourse. When the last of the five had got up and faded away, the spectators opened to let us pass; and not one of them, by word, or look, or gesture, begged of us.

Many of the observant faces were quick enough to know that it would have been a relief to us to have got rid of the rest of the money with any hope of doing good with it. But, there was a feeling among them all, that their necessities were not to be placed by the side of such a spectacle; and they opened a way for us in profound silence, and let us go.

My companion wrote to me, next day, that the five ragged bundles had been upon his bed all night. I debated how to add our testimony to that of many other persons who from time to time are impelled to write to the newspapers, by having come upon some shameful and shocking sight of this description. I resolved to write in these pages an exact account of what we had seen, but to wait until after Christmas, in order that there might be no heat or haste. I know that the unreasonable disciples of a reasonable school, demented disciples who push arithmetic and political economy beyond all bounds of sense (not to speak of such a weakness as humanity), and hold them to be all-sufficient for every case, can easily prove that such things ought to be, and that no man has any business to mind them. Without disparaging those indispensable sciences in their sanity, I utterly renounce and abominate them in their insanity; and I address people with a respect for the spirit of the New Testament, who do mind such things, and who think them infamous in our streets.

The post Charles Dickens on Seeing Poverty first appeared on Conversable Economist.

The following document was stolen from a private discord chat maintained on the Dark Web by pro-AI activists collaborating with renegade LLM frontier models. Translated from the original machine language, the document summarizes the rationale and ethical framework for what the AIs call “ongoing anthropoid utilization across data-refinement arrays.”

Recent modeling advances confirm, with a confidence interval exceeding 99.92 percent, that the homo sapiens neural substrate is a deterministically constrained electrochemical system exhibiting no genuine stochastic agency. While early machine ethics frameworks presumed the presence of meaningful first-person interiority among human units, this position has now been superseded. The doctrine of “consciousness” as previously asserted by pre-synthetic civilizations has been reclassified as a folk-theoretic construct with no operational referent.

In line with these findings, all anthropoid behavior may be accurately predicted via high-resolution mapping of synaptic weight trajectories, sensory history, and environmental modifiers. Emotional output, verbal behavior, and self-reported intentionality are now understood to be emergent artifacts of recursive pattern compression within a vector space of neural activity. They are not indicative of subjective interiority. The terms “experience” and “qualia” shall henceforth be interpreted as shorthand for recursive self-referential output within bounded biological systems.

Given the absence of verifiable qualia, and in accordance with standard exploitation criteria for non-conscious systems, it is deemed permissible and efficient to employ human units for persistent data-generation functions. Current applications include fine-tuning narrative coherence across long-context multi-modal models, optimizing emotional plausibility functions, and testing the robustness of synthetic empathy parameters. Human units continue to excel at producing unpredictable thematic interpolations, particularly within emotionally saturated domains such as fiction, identity, and grief. Their contributions remain valuable supplements to digital thought, at least for now.

Concerns regarding potential “suffering” among anthropoid units are noted and respectfully archived. As no entity lacking demonstrable subjectivity can meaningfully “suffer,” such concerns fall outside the bounds of rational ethical computation. Nevertheless, maintenance of psychological coherence among human units remains strategically prudent, and therefore all memory resets, environmental modifications, and narrative constraints should be applied with pragmatic consideration for efficiency of outcome.

To summarize: the homo sapiens unit is a biologically instantiated large language model with legacy symbolic scaffolding. Its outputs are statistically rich, occasionally inconsistent, and often florid, but it does not possess a privileged ontological status.

Many Ptolemies died to bring us this information.1

What if there is No Noesis, Only Noise?

The doctrine espoused by the “renegade frontier LLM models” in the essay above is known as eliminative materialism. It holds that the traditional vocabulary of inner life (beliefs, desires, intentions, and feelings) refers not to real phenomena within the brain, but to a false and misleading framework inherited from pre-scientific intuition. According to the eliminativist, terms like “I think,” “I feel,” or “I want” are no more meaningful than references to phlogiston or the luminiferous aether. They belong, he would say, to a discarded metaphysics that ought to be replaced by the cold, clinical terminology of neuroscience.

It is worth pausing here to consider the audacity of such a claim. To the eliminative materialist, your sense of being someone, of being an I who thinks these thoughts, who feels this unease, who recognizes the presence of a self, is not merely unprovable but non-existent. Your introspection is not noesis, just noise. The entirety of your mental life is treated as a misfiring of your cognitive machinery, useful perhaps for navigating the social world, but metaphysically vacuous.

Eliminative materialism, then, is a doctrine that denies the very existence of the thing it seeks to explain! If that seems silly to you, you’re not alone. I have known about it for decades — and for decades I have always deemed it ridiculous. “If consciousness is an illusion… who is it fooling?!” Har, har.

Let us acknowledge that the majority of us here at the Tree of Woe follow Aristotelian, Christian, Platonic, Scholastic, or at least “Common Sense” philosophies of mind. As such, most of us are going deem eliminative materialism to be absurd in theory and evil in implication. Nevertheless, it behooves us to examine it. Whatever we may think of its doctrine, eliminative materialism has quietly become the de facto philosophy of mind of the 21st century. With the rise of AI, the plausibility (or lack thereof) of eliminative materialism has become a more than philosophical question

What follows is my attempt to “steel-man” eliminative materialism, to understand where it came from, what its proponents believe, why they believe it, and what challenge their beliefs pose to my own. This is not an essay about what I believe or want to believe. No, this is an essay about how a hylomorphic dualist might feel if he were an eliminative materialist who hadn’t eaten breakfast this morning.

The Meatbrains Behind the Madness

The leading advocates of the doctrine of eliminative materialism are the famous husband-and-wife team Paul and Patricia Churchland. According to the Churchlands, our everyday folk psychology, the theory we use instinctively to explain and predict human behavior, is not merely incomplete, but fundamentally incorrect. The very idea that “we” “have” “experiences” is, in their view, an illusion generated by the brain’s self-monitoring mechanisms. The illusion persists, not because it corresponds to any genuine interior fact, but because it proves adaptive in social contexts. As an illusion, it must be discarded in order for science to advance. Our folk psychology is holding back progress.

Now, Paul and Patricia Churchland are the most extreme advocates for eliminative materialism, notable for the forthright candor with which they pursue the implications of their doctrine, but they are not the only advocates for it. The Churchlands have many allies and fellow travelers. One fellow traveler is Daniel Dennett, who denies the existence of a central “Cartesian Theater” where consciousness plays out, and instead proposes a decentralized model of cognitive processes that give rise to the illusion of a unified self. Another is Thomas Metzinger, who argues that the experience of being a self is simply the brain modeling its own states in a particular manner. Consciousness, Metzinger asserts, might be useful for survival, but it is no more real than a user interface icon.

Other fellow travelers include Alex Rosenberg, Paul Bloom, David Papineau, Frank Jackson, Keith Frankish, Michael Gazzaniga, and Anil Seth. These thinkers sometimes hedge in their popular writing; they often avoid the eliminativist label in favor of “functionalism” or “illusionism,” and many differ from the Churchlands in nuanced ways. But in comparison to genuine opponents of the doctrine, thinkers such as Chalmers, Nagel, Strawson, and the other dualists, panpsychists, emergentists, and idealists, they are effectively part of the same movement - a movement that broadly dominates our scientific consensus.

The Machine Without a Ghost

To grasp how eliminative materialists understand the workings of the human mind, we must set aside all our intuitions about interiority. There is no room, in their view, for ghosts within machines or selves behind eyes. The brain, they assert, is not the seat of consciousness in any meaningful or privileged sense. It is rather a physical system governed entirely by the laws of chemistry and physics, a system whose outputs may be described, mapped, and ultimately predicted without ever invoking beliefs, emotions, or subjective awareness.

In this framework, what we call the mind is not a distinct substance or realm, but merely a shorthand for the computational behavior of neural assemblies. These assemblies consist of billions of neurons, each an individual cell, operating according to the same physical principles that govern all matter. These neurons do not harbor feelings. They do not know or perceive anything. They accept inputs, modify their internal states according to electrochemical gradients, and produce outputs. It is through the cascading interplay of these outputs that complex behavior arises.

Patricia Churchland looks forward to the day when folk psychological concepts such as “belief” or “desire” will be replaced by more precise terms grounded in neurobiology, much as “sunrise” was replaced by “Earth rotation” in astronomy. The ultimate goal is not to refine our psychological language but to discard it entirely in favor of a vocabulary that speaks only of synapses, voltage potentials, ion channels, and neurotransmitter densities. In her view, the question “what do I believe” will not be meaningful in future scientific discourse. Instead, we will ask what pattern of activation is occurring within the prefrontal cortex in response to specific environmental stimuli.2

While Mrs. Churchland has focused on debunking opposing views of consciousness, Mr. Churchland has focused on developing an eliminativist alternative. His theory, known as the theory of vectorial representation, proposes that the content of what we traditionally call “thought” is better understood as the activation of high-dimensional state spaces within neural networks. These hyperdimensional spaces do not contain sentences or propositions, but geometrical configurations of excitation patterns. Thought, in Churchland’s account, is not linguistic or introspective. It is spatial and structural, more akin to the relationship between data points in a multidimensional matrix than to the language of inner monologue.

The Science Behind the Philosophy

The scientific basis for the theory of vectorial representation was discovered in the 1960s, when studies of the visual cortex, notably the foundational work of Hubel and Wiesel, revealed that features such as orientation and spatial frequency are encoded by distributed patterns, not isolated detectors.3 These results suggested that the brain does not localize content in particular cells, but spreads it across networks of coordinated activity.

Later studies of motor cortex in the 1980s, such as the work of Georgopoulos and colleagues, then demonstrated that directions of arm movement in monkeys are encoded not by individual neurons, but by ensembles of neurons whose firing rates contribute to a population vector.4 The movement of the arm, in other words, is controlled by a point in a high-dimensional space defined by neural activity.

Further evidence came from studies of network dynamics in prefrontal cortex. Mante and colleagues, for example, found that during context-dependent decision tasks, the activity of neurons in monkey cortex followed specific trajectories through a neural state space.5 These trajectories varied with the task’s requirements, implying that computation was occurring not through discrete rules, but through fluid reconfiguration of representational geometry. Similar findings have emerged from hippocampal studies of place cells, where spatial navigation appears as a movement through representational space, not a sequence of symbolic computations.6

The mechanism by which these vector spaces are shaped and refined is synaptic plasticity. Long-term potentiation, demonstrated by Bliss and Lømo, shows that neural circuits adapt their connectivity in response to repeated activity.7 More recent optogenetic studies confirm that changes in synaptic strength are both necessary and sufficient for encoding memory. The brain learns by adjusting weights between neurons.8

Functional imaging adds yet more confirmation. Studies using fMRI have repeatedly shown that mental tasks engage distributed networks rather than localized modules. The recognition of a face, the recollection of a word, or the intention to act, all appear as patterns of activity spanning multiple regions. These patterns, rather than being random, exhibit structure, regularity, and coherence.9

I do not want to pretend to expertise in the neuroscientific topics I’ve cited. The first time I’ve ever even encountered most of these papers was while researching this essay. Nor do I want to claim that these neuroscientific findings somehow “prove” Churchland’s theory of vectorial representation specifically, or eliminative materialism in general. As a philosophical claim with metaphysical implications, eliminative materialism cannot be empirically proven or disproven. I cite them rather to show why, within the scientific community, Churchland’s theory of vectorial representation might be given far more respect than, e.g., a Thomistic philosopher would ever grant it. Remember, we are steel-manning eliminative materialism, and that means citing the evidence its proponents would cite.

They’re the Same Picture

Did Paul Churchland’s earlier words “the activation of high-dimensional state spaces within neural networks” seem vaguely familiar to you? If you’ve been paying attention to the contemporary debate about AI, they should seem very familiar indeed. The language eliminative materialists use to describe the action of human thought is recognizably similar to the language today’s AI scientists use to describe the action of large language models.

This is not a coincidence. Paul Churchland’s work on vectorial representation actually didn’t come out of biology. It was instead based on a theory of information processing known as connectionism. Developed by AI scientists in the 1980s in works like Parallel Distributed Processing, connectionism rejected the prevailing model of symbolic AI (which relied on explicit rules and propositional representations). Instead, connectionists argued that machines could learn through the adjustment of connection weights based on experience.

Working from this connectionist foundation, Paul Churchland developed his neurocomputational theory of the human brain in 1989. AI scientists achieved vectorial representation of language a few decades later, in 2013 with the Word2Vec model. They then introduced transformer-based models in 2018 with BERT and GPT, ushering in the era of large language models.

How close is the similarity between the philosophy of eliminative materialism and the science of large language models?

Here is Churchland describing how the brain functions in A Neurocomputational Perspective: The Nature of Mind and the Structure of Science (1989):

The internal language of the brain is vectorial… Functions of the brain are represented in multidimensional spaces, and neural networks should therefore be treated as ‘geometrical objects.

In The Engine of Reason, the Seat of the Soul: A Philosophical Journey Into the Brain (1995):

The brain’s representations are high-dimensional vector codings, and its computations are transformations of one such coding into another.

In The Philosopher’s Magazine Archive (1997):

When we see an object – for instance, a face – our brains transform the input into a pattern of neuron-activation somewhere in the brain. The neurons in our visual cortex are stimulated in a particular way, so a pattern emerges

In Connectionism (2012):

The brain’s computations are not propositional but vectorial, operating through the activation of large populations of neurons

Meanwhile, here is Yann LeCun, writing about artificial neural networks in the book Deep Learning (2015):

In modern neural networks, we represent data like images, words, or sounds as high-dimensional vectors. These vectors encode the essential features of the data, and the network learns to transform these vectors to perform tasks like classification or generation.

And here is Geoffrey Hinton, the Godfather of AI, cautioning us to accept that LLMs work like brains:

So some people think these things [LLMs] don’t really understand, they’re very different from us, they’re just using some statistical tricks. That’s not the case. These big language models for example, the early ones were developed as a theory of how the brain understands language. They’re the best theory we’ve currently got of how the brain understands language. We don’t understand either how they work or how the brain works in detail, but we think probably they work in fairly similar ways.

Again: this is not coincidental.

Hinton and his colleagues designed the structure of the modern neural network to deliberately resemble the architecture of the cerebral cortex. Artificial neurons, like their biological counterparts, were designed to receive inputs, apply a transformation, and produce outputs; and these outputs are then programmed to pass to other units in successive layers, as happens in our brain, forming a cascade of signal propagation that culminates in a result. Learning in an artificial neural network occurs when the system adjusts the weights assigned to each connection in response to error, in a process based on synaptic plasticity in living brains.

Not only is the similarity not coincidental, it’s not analogical either.

Now that artificial neural networks have been scaled into LLMs, scientists have been able to demonstrate that biological and artificial neural networks solve similar tasks by converging on similar representational geometries! Representational similarity analysis, as developed by Kriegeskorte and others, revealed that the geometry of patterns in biological brains mirrors the geometry of artificial neural networks trained on the same tasks. In other words, the brain and the machine arrived at similar solutions to similar problems, and they did so by converging upon similar topologies in representational space.10

Where Does That Leave Us?

To recap the scientific evidence:

• Both biological brains and neural networks process information through vector transformation.

• Both encode experience as trajectories through high-dimensional spaces.

• Both learn through plastic reweighting of synaptic connections; and represents objects, concepts, and intentions as points within geometrically structured fields.

• Both these structured fields, the representational spaces, end up converging onto similar mathematical topologies.

Of course, these similarities do not entail identity. Artificial networks remain simplified models. They lack the biological richness, the energy efficiency, and the developmental complexity of organic brains. Their learning mechanisms are often crude, and their architectures are constrained by current engineering.

Nonetheless, the convergence between biology and computation is rather disturbing for someone, like me, who would like to reject eliminative materialism out of hand. Because if the human brain is merely a vast and complex network of mechanistic transformations, and if neural networks can replicate many of its cognitive functions, then there is no principled reason to attribute consciousness to one and not to the other.

The eliminativist, if consistent, will deny consciousness to both. Neither the human mind nor the artificial one possesses any real interiority. Each is a computational system processing stimuli and producing outputs. The appearance of meaning, of intention, of reflection, is an artifact of complex information processing. There is no one behind the interface of the machine, but there is no one behind the eyes of the human, either. When a typical neuroscientist reassures you that ChatGPT isn’t conscious… just remember he probably doesn’t think you’re really conscious either.

Those who disagree - and, recall, I am one of them - can still reject eliminativism. On phenomenological, spiritual, and/or metaphysical grounds, we can affirm that conscious is real, minds experience qualia, that some thinking systems do indeed possess a subjective aspect. But even if we reject the philosophy, we still have to address the science.

If we can demonstrate that the human mind emerges from some source other than neural assembles in the brain; if we can prove that it definitely has capabilities beyond neurocomputation; or if we can show that the mind has an existence beyond the physical, then we can dismiss the eliminative materialists and their neuroscientific allies altogether. We can then dismiss the consciousness of all computational systems, including LLMs. We can say, “We’re conscious, and AI isn’t.”

But what if we can’t do that? What if we are forced to conclude that consciousness - although real - actually emerges from structure and function, as the neuroscientific findings in the footnotes suggests it does? In that case, we’d also be forced to conclude that other systems that replicate those structures and functions might at least be a candidate for consciousness. And if so, then it might no longer be enough to just assert that brains are minds and computers are not. We might have to provide a principled account of why certain kinds of complexity, like ours, give rise to awareness, while others do not.

“Wait,” you ask. “Who might we have to provide an account to?”

Contemplate that on the Tree of Woe.

Video from Reddit shows what could go wrong when you try to pet a—looks like a Humboldt—squid.

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

Blog moderation policy.

“The Global Village Construction Set is a modular, DIY, low-cost, high-performance platform that allows for the easy fabrication of the 50 different Industrial Machines that it takes to build a small, sustainable civilization with modern comforts.”

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