NB: The following post will be entirely human-generated, with no LLM involvement – except for the cover image rendered by Gemini. It will also be brief.
I am (still, perpetually) learning French, and I use Anki to help me. I recommend it for standard and non-standard flashcard uses. Recently, I asked ChatGPT to generate a CSV with phrases for the front and back of the cards, for example:
Front: I will be able to visit France next year.
Back: Je pourrai visiter la France l’année prochaine. (futur simple)
I found the pack useful, but a few days later (today), I asked for more than first-person perspectives, as well as additional tenses. I entered this prompt, which is what triggered this blog entry:
‘You’ rendered this for me. Might you generate a similar file that I can use to import to Anki that includes versions other than first-person singular? Future tenses would be helpful as well.
Notice the ‘you‘ in scare quotes – inverted commas.
It’s no secret that I am partial to the episodic selves of Galen Strawson in contrast with diachronic selves, which is to say that I don;t believe that the you or the I or yesterday – or even a second ago – is intrinsically the same person. I’ve explained this elsewhere, so I’ll leave it here.
As much as I feel this way, I don’t feel put off referring to myself as myself or I – me, myself, and I – or to you as you, but I am more consciously uncomfortable with addressing an LLM as you, as demonstrated.
I know full well that each prompt and response is to a different instance of the LLM – a different episode. Unless the LLM accesses an earlier conversation in memory – and I use this term loosely here, too – it would not retain context, and the absence of you-ness would be painfully obvious.
I don;t believe that the self of people is functionally any different. Obviously, humans are carbon-based rather than silicon-based, and storage and retrieval operate differently beyond the substrates, but the mechanism is metaphorically similar.
Does anyone else feel dis-ease in addressing an LLM in the second person? Or is it just me – or me?
The question is reasonable, although belief may already be doing more work than I would permit it under cross-examination. My writing is generally diagnostic rather than doctrinal. I am more interested in identifying the architectural assumptions beneath a dispute than in selecting a furnished room within it. Where philosophy offers a contest between established positions, I often suspect that the arena itself has been badly designed.
Still, repeated diagnoses eventually disclose a pattern. Certain commitments recur: suspicion of substance, resistance to metaphysical inflation, distrust of linguistic confidence, rejection of moral realism, scepticism toward persistent personal identity, and an insistence that mediation does not entail fabrication.
What follows is therefore neither a creed nor a completed system. It is a provisional map of where I presently stand.
The labels are intended as coordinates, not allegiances. Where no established term quite fits, I have used my own. This is partly unavoidable and partly evidence for the very linguistic difficulty I spend so much time diagnosing.
This content, including video and podcast summary, are of a longer Substack article on my philosophical positions with descriptions.
I love language, and I study it. I also use LLMs. I am not anti-AI, but neither am I prescriptively pro-AI. I just happen to find them useful.
Audio: NotebookLM summary podcast of this topic.
I also, however, find them to have quirks. I won’t regurgitate the supposed over-representation of delve — or em dashes, or lists of three, and so on. These are each, at once, true and hardly egregious – especially given that we were all schooled on the same English that now sits in their training data.
What I want to focus on is the cadence. I watched this video, and the historical information is interesting – in fact, much of the material on the channel is. A few shorts were recommended to me, I discovered more, I subscribed, as one does. But listen to the talk track.
Video: The Most Mispronounced Words in English and the History Behind Them – Airlearn Language Show
Whilst I may be mistaken, it sounds like an LLM-produced script. Perhaps the joke is on me, and the presenter herself is an AI avatar. It also sounds as though a de-LLM process was applied afterwards to obfuscate the patterns – whether by a human or by another model running some humaniser GPT.
Of course, there are other explanations. Perhaps the writer simply happens to write this way, and the LLMs merely encroach on it. Without a writing history, one can’t know for certain. And – I know this is true of me – exposure, dare I say overexposure, shapes how one writes.
I run almost everything I write through AI and ask for suggestions – and you needn’t even ask; it volunteers anyway. When the output looks better, I adopt it: a word, a phrasing, a more concise rendering, a supporting sentence or a setup. After a while, my writing has been nudged in that direction. I already used delve; now I am merely conscious of it. I used to use em dashes – look at my pre–2020 posts – and switched to en dashes purely to avoid the witch-hunt. In each case, the LLM Age has done something to my style.
So, back to the video. If you are familiar with long-form LLM output, you will notice how she supports her ideas and how she builds her asides – with a very particular pattern. I am not judging: as I say, I use these tools extensively. I only want to point out an observation.
BONUS: I don’t pronounce Wednesday as /wenz.day/. I pronounce it closer to /wedñz-day/, the tilde is rather on the /d/ or the space the /d/ occupies, but I placed the mark on the /n/ instead because there is no tilde-d glyph, and I wanted to represent a nasality the more typical pronunciation doesn’t have – but that I add.
From here on, I asked Claude to analyse my post (above) along with the video script. Pay special attention to its own cadence, which comports with the video.
Here, then, is the observation.
Watch how a point is made to land. The move is nearly always the same: state the naïve reading, snatch it away, and hand back the corrected version as a tidy little binary. It’s not random. There’s a reason.It wasn’t design. It accumulated.English spelling isn’t bad design. It’s no design at all. The shape does the work an argument would otherwise have to do. Negate, reverse, reveal – and the reveal feels like insight precisely because something was first taken away. It is the cheapest available route to the sensation of having been told something.
Notice, too, the reassurance travelling alongside it. There’s a reason. There’s always a reason. The promise of an explanation, delivered before the explanation arrives, so that you settle in and stop wondering whether one is coming. And where genuine argument would be laborious, the list stands in for it: Old English, Norse, Norman, French, Latin, scholarship, Dutch typesetters, the great vowel shift. Abundance, read as authority. Say enough true things in a row and the row itself begins to feel like a proof.
Then the asides. Almost every one is the same manoeuvre – the proper noun that renames itself the instant it appears. Woden, the chief god of the Anglo-Saxon pantheon.Latin, the prestige language of learning.A Quechua word from the Andes.Frigg being Odin’s wife. Nothing is permitted to sit unglossed for even a clause. This is what maximal legibility looks like once it hardens into reflex: a horror of the unexplained referent, a compulsion to footnote in real time. The second variety is the personality wink – and English being English, it kept both – character applied topically, like a balm.
And, so that you are never left to feel anything unsupervised, your reactions are narrated back to you in advance: if that feels insane to you, good, because it is. The response, pre-issued, so you may be spared the labour of having it. The whole is held together by a governing metaphor with a landing – fossil, photograph, museum – reactivated at the close (every mispronounced word is a crime scene) and finished with a note of absolution: you haven’t been mispronouncing English because you’re careless. It is very nearly a form one could fill in.
None of which proves a human didn’t write it.
And that is the part worth sitting with. Suppose no model ever touched this script. Suppose the writer arrived at the cadence honestly, by the same route I did – by reading enough of the stuff that the rhythm simply seeped in. Then the pattern is no longer evidence of authorship at all. It is evidence of a house style, and the house is one we have all quietly moved into. The tell no longer tells you a machine was here. It tells you the machine’s prosody has become the water.
I find that rather more unsettling than a mere ghost-writer would be. A ghost-writer you can dismiss. A cadence you have caught, like an accent, off the sheer ambient volume of the thing – that you carry home. And the video is, with some poetry, about exactly this: silent letters as fossils, sounds that mouths stopped making but that spellings preserved, layer upon historical layer that nobody ever cleaned up. The irony is that the script is laying down a fresh one as it speaks. Somewhere in the prose of the next decade there will be a stratum you can date almost to the year – ah, yes, written just after the models arrived – and it will be made of precisely these moves.
I switched to en dashes to dodge the witch-hunt. But the dash was never the point. You can strip every em dash from a sentence and leave the skeleton wholly intact, because the skeleton was never punctuation. It was the not-this-but-that, the aside that footnotes itself, the pile that mistakes its own length for weight. A humaniser can launder the vocabulary. It cannot, so far, launder the architecture. Which is how one reads a script scrubbed clean of every obvious tell and still hears, quite distinctly, the thing it was scrubbed to hide.
I am not judging. I write this way too, now – rather more than I would like. I only wanted to point it out. While I can still tell that I’m doing it.
I’ve been working for days on a new short story that investigates time. I’ve already published The Box in English, but this new piece looks at a different aspect of time, one I suspect may work better in French because the grammar gives me more useful pressure points than English.
The working title is Les Années Vécues, which translates literally as The Years Lived. For now, that’s only a working title. Oddly enough, the purpose of this post is not really to describe the story, though I may do some of that. It is more about the tools, the process, and the strange route by which the idea arrived.
The story began as a conversation between me, Claude, and ChatGPT about human innovation and creativity. A colleague had recommended How Language Began. I bought it and read the first few chapters. For the record, it’s interesting.
Early on, the author discusses genetics and evolution, citing human inventions along the way, particularly those associated with Homo erectus. Because I tend to question narratives of progress, and especially grand claims around Innovation and Creativity, I fell into some LLM-assisted chit-chat. From there, the conversation drifted into time travel in fiction. We discussed tropes from Back to the Future to Outlander. Somewhere in that mess, I noticed a missing perspective I felt I could capitalise on.
For the record, again, I have not been especially successful at writing short stories. They tend to grow beyond my intent, usually into novelettes or novellas. My first novel, written as Ridley Park, began as a short story. That story is now ostensibly chapter five of Hemo Sapiens. It can stand on its own, but it plays better in context. It is still my favourite chapter, if I had to choose one. So I’ll see where this new one goes, if anywhere. Nowhere is always an option. The blank page remains admirably non-committal.
After hours of brainstorming with the LLMs, arbitrarily switching from French to English and back again, I had a plot outline with beats and flavour, tropes and intentions, subversions and misdirects. I had captured dialogue exchanges, worked through worldbuilding constraints, and fleshed out several plot points. Then I asked ChatGPT to build me a tracking document to serve as a punch list.
I’ve done this a few times before, but with the advancement of the tools, the output was surprisingly robust, arguably overkill, which isn’t always a vice.
The spreadsheet contains 9 tabs:
Lists
Dashboard
Punchlist
Beat Map
Continuity Rules
Motifs & Plants
Evidence Ledger
Open Questions
Sources
Lists
The Lists tab is mostly internal to the spreadsheet. It controls status values, priorities, categories, and related dropdowns. I would not have made it this elaborate manually, but I’m not offended by competence when it arrives uninvited.
I wouldn’t have been so elaborate, but it’s nice nonetheless.
The Dashboard
The Dashboard is also a bit of overkill, but useful overkill. In its inaugural state, it gives a quick view of task status, priorities, and next actions. Its intent should be clear from the screenshot.
Punchlist
The Punchlist is essentially an actionable to-do list with status markers. I think I can safely share this without giving too much away. It lets me manage the story as a set of unresolved craft problems rather than as a vague cloud of ‘I should really get back to that’.
Beat map
The Beat Map contains representative story beats, with notes that capture narrative purpose, confidence level, and risk-management annotations. This is where structure can be managed without cluttering the prose draft itself.
Continuity Rules
The Continuity Rules tab captures worldbuilding constraints and adjacent considerations. It is probably oversharing at this stage, but I’ll take the risk. These rules matter because speculative fiction can collapse quickly when the premise starts leaking.
Motifs & Plants
The Motifs & Plants tab tracks recurring touchpoints, images, phrases, and planted details. Some of these may be premature, but having them outside the draft helps me avoid forcing them into the prose too early.
Evidence Ledger
The Evidence Ledger tracks what counts as evidence inside the story world, who can interpret it, and how it may be misread. This is another continuity check, but also a thematic one.
Open Questions
The Open Questions tab is exactly what it sounds like: unresolved choices, structural uncertainties, and decisions I do not yet want to freeze into place. Sometimes the most useful document is the one that refuses to pretend everything has been solved.
Sources
The Sources tab lists the chat history and documents from which the rest of the content was derived.
The Rest
This is only a partial listing, and I am not finished ideating. I have not yet begun the prose.
I do not always plot my stories. More often than not, I take something closer to a stream-of-consciousness approach. But for one thing, my consciousness does not stream in French. So there’s that.
What impressed me most was the organisational layer the LLM produced. The spreadsheet is now hosted on Google Drive as a Sheet, accessible to both me and the LLMs, so it can be updated as the discussions and decisions continue.
I’m looking forward to wrapping up the ideation phase and beginning, and ideally completing, the prose. That last part remains the traditional nuisance.
Am I the only one who can’t resist a massive eyeroll – and, let’s be honest: jaw-drop – what you hear transhumanism couched as evolution? To me, it incites a similar reaction to hearing people witter on about machine consciousness, but I’ll sideline that topic.
My objection is linguistic: transhumanism often borrows the prestige of evolution to describe what is more precisely technological mediation. The fact that a device is worn, implanted, or integrated into a body does not by itself move it from tool-use into biological descent. The offspring still inherits the organism, not the upgrade. Technology is not heritable.
Audio: NotebookLM summary podcast of this topic.
Consider rhinoplasty. Rhinoplasty changes the presented phenotype, not the inherited genotype. The child inherits the developmental instructions, not the parent’s post-surgical edit. Likewise, a neural implant, prosthetic limb, exoskeleton, gene-unrelated enhancement, or titanium jaw of techno-vanity may alter the lived organism, but it does not thereby alter the reproductive line. This is the category error: Acquired modification is mistaken for inherited transformation.
So, transhumanism often confuses the edited encounter-profile of an organism with the evolutionary alteration of the organismic lineage. The rhinoplasty case is good because it shows the absurdity without needing much apparatus. No one sane thinks a nose job rewrites the germline. Yet when the modification is sufficiently glamorous, especially when welded to futurist rhetoric and venture-capital incense, people suddenly start talking as if augmentation equals evolution.
A prosthesis is to evolution what rhinoplasty is to heredity: a modification of presentation, function, or encounter, not a transformation of descent. The confusion arises when the altered individual is mistaken for an altered lineage.
The question isn’t: Can transhumanism be defended under some broader theory of evolution, cultural inheritance, niche construction, or techno-biological co-development? Sure, it can.
But my claim is narrower: The term evolution is being made to do illicit rhetorical work when acquired, engineered, prosthetic, or embedded modifications are spoken of as though they were equivalent to heritable biological transformation.
The problem is that we are sliding from tool-use to augmentation to enhancement to transformation to evolution. This move isn’t illegal, but it should attract your attention.
At each step, something plausible is smuggled into something grander. By the end, an implanted device or technical prosthesis has been rhetorically promoted into ‘the next stage of human evolution’, when what has actually happened is that an organism’s encounter-capacities have been modified by artefactual mediation.
In the end, I’m not claiming that transhumanist practices can’t affect selection environments, social organisation, embodiment, or cultural transmission. What I am claiming is that calling such practices evolution without specifying the relevant register is a linguistic inflation. It trades on the authority of biological evolution while often describing technological mediation, individual augmentation, or cultural change.
In my book, more accurate terms might be augmentation, prosthesis, mediation, tool evolution, cultural inheritance, or niche modification, but these re so glamorous or click-baity. I might as well wear a hat and call myself post-human.
I chatted up ChatGPT, so I am adding this response:
Exactly. The carried / worn / embedded distinction is mostly a boundary fetish, the sort of thing humans adore because skin looks like an ontological border and apparently everyone remains impressed by packaging.
An axe, spectacles, a pacemaker, a cochlear implant, a smartphone, and a neural implant all sit on the same broad continuum: external mediation of capacity. Some are held. Some are worn. Some are surgically installed. But unless the alteration becomes heritable, it is not biological evolution in the strict sense. It is phenotypic augmentation, affordance expansion, or environmental coupling.
The useful distinction is threefold:
Biological evolution Heritable variation changes across generations. The organism-line changes.
Cultural / technological evolution Tools, techniques, designs, institutions, and practices vary, are selected, retained, modified, and transmitted. Axe technology evolves. Writing evolves. Surgery evolves. The appalling human habit of calling every interface “intuitive” also evolves, though downward.
Individual augmentation A particular body-system gains capacities through artefacts. This may change what the organism can do, but it does not by itself alter the inherited biological line.
Your axe example is clean because it exposes the smuggling. The axe helped alter human selection environments. It extended reach, force, food access, defence, craft, and perhaps social organisation. That may feed into gene-culture co-evolution over long scales. But the axe itself is not an evolved human trait. It is a technological mediator that participates in the evolutionary ecology.
The same holds for transhumanist implants. A retinal implant may alter one person’s perceptual affordance field. A brain-computer interface may alter one person’s control loop. A prosthetic limb may alter one person’s mobility. But unless such modifications become transmissible across generations, biologically or through some stable reproductive architecture, calling them “evolution” is loose metaphor masquerading as profundity. Very on-brand for techno-utopianism: rename engineering as destiny and hope the grant reviewers are sleepy.
From your MEOW angle, the better formulation is:
The relevant transformation is not evolutionary but mediational. Tools, prostheses, implants, and interfaces reconfigure encounter-events by altering the affordance structure through which an organism meets constraint. Whether the device is carried in the hand, worn on the face, implanted beneath the skin, or networked through the environment is secondary. The organism-world relation changes; the inherited organism does not necessarily change.
That also lets you avoid an overcorrection. Transhumanist enhancement is not irrelevant. It may be historically enormous. But its primary register is encounter, not inheritance; mediation, not mutation; technical lineage, not biological descent.
So the blunt line is:
Transhumanism mistakes the evolution of tools for the evolution of the tool-user.
Not always, not necessarily, but often enough that the slogan deserves being dragged into the alley and relieved of its metaphysical wallet.
This is not a philosophical post. Well, it’s about my personal philosophy of using LLMs and AI agents in my writing and publication workflow, which is a different thing. I’ll structure it as I might have done a music project back in the day, because that framing still makes more sense to me than anything the tech industry has come up with.
Audio: NotebookLM summary podcast of this topic.NotebookLM Infographic on this topic.
Preproduction
Not all projects make it into production. Others were never intended to. But they all begin with at least a kernel of an idea — and some arrive fully formed, as if sprung from the head of Zeus, already wearing armour and looking for a fight.
Pre-ideating
What the hell is pre-ideating? I just made it up for this use case because that’s how I roll.
As I understand it, some people need help thinking of topics. This is not my problem. My problem is managing ideas rather than generating them. I have a backlog that will outlast me, so I don’t use this step. But it exists, and it’s probably the most widely discussed AI use case in creative circles: you prompt the model to suggest themes, genres, or concepts. Give me five ideas for a mystery novel. Or, if you’re feeling ambitious: Give me five ideas for a research paper in quantum physics. The model obliges. Whether what comes back constitutes an idea in any philosophically interesting sense is a question I’ll save for another day.
Ideating
This is where I usually enter the process, and the ideation takes shape in one or several different ways. The most common is simply a discussion – a sustained back-and-forth. A recent example: I was reading Judith Butler’s Gender Trouble and found myself with clarifying questions at every turn. Not because Butler is unclear, but because the implications kept ramifying in directions I wanted to follow. That extended dialogue – with ChatGPT in this instance – eventually became the philosophical core of Two Kings, currently stalled in Production.
Butler’s argument about incest taboos as foundational to broader regimes of sex and gender regulation gave me a narrative frame. The conversation helped me see what I actually thought about it, which is the more important thing. The LLM didn’t give me the idea. It gave me a sounding board patient enough to entertain the idea at two in the morning – it was actually two in the afternoon, but who’s looking?
Research
Another obvious use case, and one I use regularly. Continuing the Butler example: I asked about several feminist theorists she references, wanting to understand the lineage I was stepping into. But here’s a cleaner illustration. Writing as Ridley Park, I produced a novella, Sustenance, set in Iowa. I’ve visited Iowa several times, but I needed local flora and fauna for descriptive texture in certain scenes, so I asked
In the old days, I’d have gone to Google, Wikipedia, or I’d track down an Encyclopædia Britannica. The process is faster now, and the results are generally better for this kind of lateral, contextual research. For anything where accuracy is genuinely load-bearing, I verify. That’s not a criticism of the tool; it’s just basic epistemic hygiene.
Confirmation
Sometimes I have an idea and want to know whether someone’s already done it because I have no interest in reinventing wheels, and even less in reinventing them badly.
So I ask: Has anyone written X? What are the most significant treatments of Y? What typically comes back is a list of a dozen or more analogous sources. I review them and decide: does my idea still have independent purchase, or am I just writing a worse version of something that already exists? Sometimes I sharpen the idea in response. Sometimes I incorporate what I find, either to build on it or to identify where the existing literature is misframed, assumes too much, or has quietly imported the wrong ontological grammar. This last move is something of a professional tic.
Production
Drafting
I don’t use LLMs for full drafts. This is an obvious use case for those who do, particularly if the goal is volume – especially for the person who has already prompted for which genre currently has high demand and low representation on Amazon, and is now logically committed to producing it. That’s a coherent workflow – just not mine.
Edits and Revision
This I use often, and it’s probably where I get the most consistent value. After writing a passage or section, I feed it to one or more models with context already established — thesis statement, abstract, outline, supporting documents. What comes back varies: typographical errors, odd phrasings, unintentional repetitions (and, occasionally, new ones the model has helpfully introduced), suggested rewrites, observations about framing. I don’t treat any of this as instruction. I treat it as a second read from a reader who has no ego investment in agreeing with me – and yet obviously does. The important distinction is input versus output. I’m not asking it to write. I’m asking it to respond to what I’ve written.
Continuity
Are there gaps? Dropped threads? Promises made in chapter two that chapter seven has forgotten entirely? This is a genuinely useful mechanical check – the kind of thing that’s easy to miss when you’ve been inside a manuscript long enough to stop reading what’s actually there.
Flow
Do the scenes and chapters move well? Does the transition from one section to another feel like a logical step or an unannounced lurch? Useful, with the caveat that models have aesthetic preferences that don’t always align with mine, and I treat their flow suggestions accordingly.
Pacing
Is the pacing appropriate — both for the genre and for the particular piece? These are separate questions. A thriller has genre conventions around pace; a particular thriller might have reasons to subvert them. The model can flag where the pacing drifts; the judgement call about whether that’s a problem remains mine.
Postproduction
Formatting and Layout
I use AI for ideas about how to present content on the page: chapter opens, font choices, sizes, running headers, folios. This is design at the level of convention and taste rather than technical execution. I find it useful as a first pass — it surfaces options I might not have considered, which I then either adopt, adapt, or discard.
Cover Ideas
Thematic cover concepts, whether or not I ultimately outsource the art and creative work. I find this a productive way to articulate what the book is doing before I have to explain it to someone else.
How To
I use InDesign, Illustrator, and Photoshop with competence but not expertise. For specific technical tasks – how do I do this thing in InDesign — I ask. I also still use Google, YouTube, and the occasional book. These are not competing resources; they’re complementary ones, and which I reach for depends on what kind of answer I need.
Support and Maintenance
Marketing and Placement
Target markets, genre positioning, how to frame the work for audiences who didn’t watch it being assembled. This is a legitimate use case and one I engage with, even if marketing remains a word I say with a slight internal wince.
I also use platforms like ElevenLabs for audio, NotebookLM for podcast summaries and infographics, and Nano Banana or Midjourney for images.
Keywords and Descriptions
Adjacent to marketing but more administrative in character, the metadata layer that determines whether the work is findable by the people who would want it. Less interesting to think about than almost anything else in the process, and therefore an excellent candidate for AI assistance.
None of the above replaces the work. That’s the point. The writing is still the writing.
For most of human history, written Latin looked something like THISISASENTENCEABOUTPHILOSOPHYORWARYOUCHOOSE, and readers were simply expected to get on with it. And of course, in ALL CAPS. This was not considered a problem. The Romans were not known for their sensitivity to the needs of others.
The Romans did, briefly, experiment with the interpunct – a modest dot deployed between words, giving the reader something like THIS·IS·A·SENTENCE·ABOUT·PHILOSOPHY·OR·WAR·YOU·CHOOSE – before apparently deciding this was excessive hand-holding and abandoning it entirely. Punctuation’s first appearance in Western prose was thus also its first act of self-destruction. A precedent, as we shall see, that held.
Audio: NotebookLM summary podcast of this topic.
Relief came, eventually, from the most unlikely of sources: monks. Specifically, Irish and Anglo-Saxon monks in the 7th and 8th centuries, who were copying Latin texts they couldn’t actually read fluently, and who introduced spaces between words as a personal coping mechanism. Civilisation has strange bedfellows.
The comma, the full stop, and their assorted relatives arrived with the printing press – Aldus Manutius and the Venetian humanists essentially standardising the breath-marks of prose into something reproducible at scale. Punctuation became, in this period, the bureaucratisation of rhythm. A noble project. Mildly tyrannical in execution.
The em dash, meanwhile, had an entirely respectable career throughout the 18th and 19th centuries — a mark of genuine syntactic energy, used to interrupt, to pivot, to hold two thoughts in productive tension — before being left largely to the eccentric and the emphatic.
Then came the large language models. Within approximately eighteen months, the em dash was resurrected from the dead to become the default unit of thought, issuing them faster than Oprah Christmas giveaways. Every clause got one. Sometimes a sentence received two, bracketing a thought that required neither a bracket nor a thought. The em dash ceased to mean interruption and began to mean I am text generated at scale. Readers noticed. Then they mocked it. Then, following the immutable logic of cultural exhaustion, they stopped using it entirely. The em dash is now extinct — which is a shame, really.
The LinkedIn consensus has spoken: if you used AI in the writing process, you are not the author. The position is stated with the confidence of someone who has never hired a ghostwriter, employed a research assistant, submitted to a heavy editor, or considered that the Gettysburg Address was almost certainly not written by Lincoln.
Image: I couldn’t not share this Midjourney 8.1 image. It may not have understood the assignment.
Audio: NotebookLM summary podcast of this topic.
Authorship has never been a production relation. It has always been an attribution relation — an institutionally stabilised answer to the question of which name the practice elects to put on the cover. These are not the same thing, and conflating them is the error from which every subsequent confusion proceeds.
The ghostwriter has existed as long as commercial publishing. The political speechwriter is so normalised that nobody considers it worth remarking. The celebrity memoir, the corporate thought-leadership piece, the attributed editorial — these are not edge cases or embarrassing exceptions. They are the normal operation of every writing-adjacent industry that has ever existed. The name on the cover has never reliably indicated the hands on the keyboard, and the industry has never seriously pretended otherwise. It has simply preferred not to discuss it at dinner.
AI changes the tool. It does not change the structure. The person who prompts, selects, curates, revises, and publishes is doing what commissioners of ghostwriters have always done. What has changed is that AI makes the mediation visible in a way that polite convention previously concealed. Visibility triggers the purity reflex. What presents itself as a defence of authentic authorship is a defence of a particular fiction — the Romantic author as solitary originating consciousness — that the industry never consistently believed and certainly never consistently practised.
The purity position also fails on its own terms before it gets started. Consider the spectrum of AI-assisted writing: a full draft submitted for light polish; a human argument substantially revised by AI; collaborative ideation followed by AI drafting; a kernel of an idea handed over for full execution. These are genuinely different in terms of human contribution. The zealot position requires a threshold somewhere on this spectrum below which authorship lapses. It never specifies where. More fatally, it has no means of verification. There is no external method of determining where on the spectrum any given piece of writing falls. The detector tools are probabilistic noise that disproportionately penalise competent prose. Any audit mechanism sophisticated enough to catch first-order evasion immediately generates a second-order workaround. The regress terminates only at continuous surveillance of the writing process — panoptical authorship as the logical endpoint of the position taken seriously.
NotebookLM Infographic on this topic.
Then there is the recursion problem, which the zealot never addresses because it is fatal. The stochastic parrot charge against AI — that it merely recombines absorbed linguistic patterns without genuine origination — describes with considerable accuracy what human cognition also does. The writer’s training data is the Dickens read at ten, the billboard absorbed on a commute, the argument overheard on public transit, the half-remembered essay that shaped a position without ever being consciously cited. The causal chain of any human idea disappears into an unauditable cognitive history. Genuine origination in the sense the purity position requires has never existed. The Romantic author was always a retrospective confabulation. Barthes said so in 1967. The industry nodded politely and continued invoicing.
What the zealot is defending is not authorship. It is a particular grammar of authorship — one that selects compositional origin as the threshold criterion, applies it selectively and unverifiably, and uses the resulting suspicion as a status boundary. It is guild behaviour dressed as principle, which is understandable as a response to a genuine economic threat but should not be mistaken for a philosophical position.
Authorship is the position a culture elects to stabilise after the work has already been produced through far messier means. It has always been thus. AI did not break the fiction. It just made the fiction harder to keep a straight face about.
The Rest of the Story
I’ve written about this before. I am not an AI apologist, but I am peeved by anti-LLM zealots, who clearly haven’t thought through their arguments.
I finished reading A.J. Ayer’s Language, Truth, and Logic, the part about Bertrand Russell’s claim about ‘The author of Waverley was Scotch‘. My brain latched onto authorship, and my emotional response was WTF? I have other problems with Russell and Ayer on this, but that’s a matter for another day.
To make my point, this page up to the ellipsis is the output of Claude after an extended dialogue with it and ChatGPT after I read Ayers, and something didn’t sit quite right. I am not ashamed to use LLMs in my authoring workflow and am not ashamed to mention it, as here. Almost all of these thoughts are mine. I’ve simply asked Claude to organise the output. It’s good enough to output as-is, and any edits would be trivial, so I won’t bother. I probably could have made the edits in as much time as it took to type this, but I’ve got nothing to hide. I’m just a human with access to technology circa 2026.
I’m an active AI user. It’s no secret. My top uses are research and enquiry, but it is instrumental in my review and revision process.
Audio: NotebookLM summary podcast of this topic.
I am trying to wrap up my latest manuscript. I’m about 5 revisions through, so I felt I was finally in a position to check for cracks and missing elements, as well as the strength of my overall position and approach. It’s not a good idea to simply prompt, ‘What do you think about this?’
I’d tried prompts as simple as, ‘Act as a referee and be adversarial against this piece’ or ‘I got this from somewhere, and I want a critique’. These approaches shield you from AI’s programmed sycophantic tendencies. But they aren’t enough. You still need to create guidelines and guardrails, which include orientating the AI; otherwise, they will likely go off the reservation.
This is the actual prompt I last employed to various LLMs:
The attached is a complete development draft of Architecture of Willing, a philosophical monograph arguing that the vocabulary of will, intent, motive, choice, decision, and related terms operates through a two-stage grammatical mechanism – compression of action-patterns into portable nouns, followed by inversion of those nouns into apparent upstream authors of the very patterns from which they were abstracted. The book calls this mechanism authoring displacement and uses it to argue that retributive desert cannot be stably grounded in the vocabulary on which it depends.
The book is deliberately diagnostic rather than prescriptive. It does not propose a replacement psychology, a reformed legal code, or a new theory of agency. It refuses to settle the traditional free-will debate on either side. These refusals are intentional and are argued for within the text.
What I am asking for is a critical engagement from a position of maximum philosophical resistance. Specifically:
The book rests on a claim about what retributive practice requires – namely, a stable inward authoring source capable of making suffering genuinely owed rather than merely institutionally imposed. If that characterisation of retributivism’s requirements is wrong, or if it applies only to unsophisticated versions while leaving the strongest contemporary defences untouched, the central argument is significantly weakened. I would like to know whether that is the case, and if so, where exactly the book’s account of retributivism’s commitments fails to engage its best defenders.
More broadly: the book is a diagnosis of grammar. The question I want pressed is whether a grammatical diagnosis can do the normative work the book needs it to do – whether there is a gap between ‘this noun cannot stably support the load placed on it’ and ‘therefore practices depending on this noun are normatively unjustified’. If there is such a gap, what would close it, and does the book close it?
Please do not soften objections in the direction of ‘this is a good book with some gaps’. If the argument is unsound, say so and say where. If it is sound against some targets but not others, identify the targets it misses. The manuscript has already received generous assessments; what it needs now is the strongest case against it.
Of course, this prompt is specific to me and my project, but one may feel free to use it as a model for similar purposes.
Among the gaps returned were arguments I had not been aware of. In fact, in a couple of places, I had already cited authors, but the AI returned additional books or essays by the same people. In other cases, it offered material by authors I hadn’t considered. Obviously, I am interested in creating solid, watertight arguments, so this only helps my case.
For this project, my LLMs of choice have been Claude, ChatGPT, Gemini, Grok, and Kimi K2. I used Perplexity, Mistral, DeepSeek, and Z.ai GLM in earlier iterations.
Peer review
Another application is to take the critique output from one LLM into another with a prompt to evaluate the critique. My modus operandi here is to pick a ‘master’ LLM – typically in a Claude or ChatGPT project context – and treat it as my primary partner; the others are virtual subcontractors. This means that I can get a half-dozen or more reactions in minutes, which are then digested by the, let’s say, project manager, for assessment and a proposed action plan, typically in the form of a punch list. I recommend this approach as well.
NotebookLM Infographic on this topic.
Closing shot
When I was in grad school, this part of the project would have taken months. As it is, I’ve been working on this project since COVID-19, but it’s been an on-and-off affair, accumulating research information and documentation all the while. The manuscript will be better off, and my position honed sharper over this expanse of time, so the delay was beneficial.
Would more time also be beneficial? Probably, but one needs to stop somewhere, and I’m likely facing diminishing marginal returns. If I go the way of Wittgenstein, I’ll reverse track and recant everything. And so it goes…
So glad I took time out to watch a short exchange between Rick Beato and Justin Hawkins on whether music is becoming content rather than art. The question is framed in musical terms, but it hardly stops there. The same corrosion is visible in writing, visual art, criticism, and now, with grim inevitability, in AI-mediated production more broadly. The disease is not confined to music. Music merely makes the symptoms easier to hear.
For music, my aversion to pop music goes back to my youth. I was a kid when the Beatles practically invented pop music, but they left it to grow and continued exploring. Sadly, as solo artists, they mainly – not always – failed and rested on their laurels in pop. It’s not that their version or any pop music is inherently unlistenable. Surely, it’s not, if only by the aspiration of the pop moniker, but it has no depth, no soul, as it were. Some make this argument for Organic food. In essence, it involves an appeal to nature fallacy.
Audio: Slightly off, but not bad, NotebookLM summary podcast of this topic.
My own aversion to much pop music begins there. It is not that pop is necessarily bad, nor even that it is always shallow. That would be too crude and too easy. The problem is that pop often presents itself less as an artistic act than as a consumption object engineered for immediate uptake: catchy, frictionless, emotionally legible, and just disposable enough to make room for the next one. It is built to circulate.
That, for me, is the difference between content and art. Art may be accessible, even popular, but it retains some residue that exceeds its delivery mechanism. It resists total reduction to utility. Content, by contrast, is made to be processed. It is optimised not for depth but for throughput. Its highest ambition is not transformation, but engagement.
This is why the question matters beyond music. Writing, too, now lives under the same pressure. One is increasingly expected to produce not essays, arguments, or works, but units of output: posts, threads, reactions, takes, summaries, explainers, and other forms of polished verbal debris. The point is no longer to say something worth dwelling on, but to remain visible within the churn.
The issue, then, is not simply whether one should consume AI-generated material. That framing is too pious and too easy. The more interesting question is what the consumer thinks they are consuming. If a reader, listener, or viewer wants only speed, familiarity, and surface competence, then AI content is not a scandal at all. It is the logical endpoint of a culture that has already demoted art into a deliverable.
This is where the fuss over labelling enters. Is it a principled demand for honesty, or merely a theatrical gesture by people who still want the aura of art whilst consuming content on industrial terms? Some of it is clearly protectionism. Some of it is virtue signalling. But not all of it is empty. The insistence on labelling betrays an intuition, however muddled, that authorship still matters, and that not all artefacts are equivalent merely because they occupy the same screen-space.
The deeper question is whether we still want art at all, or whether we merely want the aesthetic styling of art attached to things optimised for convenience. Once a culture learns to prefer seamless output over resistance, recognisability over risk, and quantity over form, it should not act surprised when machines begin to serve it perfectly. They are only completing a trajectory already chosen.
So no, the issue is not AI alone. AI is only the latest mirror held up to a public that has spent years confusing availability with value and polish with depth. The real question is not whether machines can make content. Plainly, they can. The question is whether we still possess the appetite, patience, and seriousness required for art.
Image: Full image because the cover version is truncated. Generated by Gemini Nano Banana.
Philosophics 