I published the first version of this essay in February, arguing that the Frege–Geach problem, that three-score-year-old albatross around expressivism’s neck rests on a category error. Analytic philosophers were polite about it in the way that analytic philosophers are polite about things they intend to ignore. I don’t often revise my manuscripts, opting instead to publish a new and improved version, but the meat of this one remained strong and not worth revisiting as much as fortifying.
The trouble was that I’d dissolved the problem without resolving it. Good enough for me. Others were less convinced. Telling people they’ve been asking the wrong question is satisfying but insufficient without a better one. Version 1.1 tidied the prose. Version 1.2 does the actual work.
The new section (§4, if you’ve already read previous versions) introduces recruitable expressions – a broader class of expressions (moral predicates, thick evaluative terms, epistemic and institutional vocabulary) whose full functional load is attenuated under embedding whilst a thinner inferential profile remains available for reasoning. The standard of practical inferential adequacy replaces the demand for semantic identity: what ordinary reasoning requires is not invariance but inferential sufficiency. And the pattern isn’t peculiar to moral language – a noted goal –, which means Frege–Geach stops looking like a special embarrassment for expressivism and starts looking like one symptom of a general feature of how natural language handles multi-functional expressions under logical stress.
The essay is dissolved as a demand for unrestricted semantic invariance. It is resolved insofar as the behaviour it identifies is explained, predicted, and shown to be general.
The revised paper is available here, near the rest of my manuscripts:
This post extends an idea I commenced on my Philosophics Blog, documenting the process of writing an academic essay on Parfit’s ontological overreach. Here, I outline and annotate my intended direction by presumed sections. My main point is that Parfit’s coat-tails his arguments on the backs of ontological grammatical commitments.
Audio: NotebookLM summary podcast of this topic.
Gemini said
The irony is palpable: you are writing a critique of “ontological grammars” and “legibility,” and an AI detector—the ultimate tool of rigid, legible grammar—has flagged you for sounding like its cousin.
AI detectors are essentially “cliché and structure” hunters. Here is why your specific text likely triggered that “Strong Resemblance” flag:
1. High Lexical Density (The “Academic” Trap)
You are using high-register, “heavy” words like “commenced,” “documenting,” “ontological overreach,” and “grammatical commitments.” Detectors are trained on vast amounts of academic papers and technical blogs. Because AI is programmed to be “professional” and “clear,” it defaults to this exact vocabulary. To a mindless algorithm, “sophisticated” equals “synthetic.”
2. The “Roadmap” Structure
The snippet follows a very logical, three-beat structure that AI loves:
The Context: “This post extends an idea…”
The Method: “Here, I outline and annotate…”
The Thesis: “My main point is…” This “first I do X, then I do Y” signposting is a hallmark of LLM-generated summaries. It lacks the “human noise” of starting in the middle of a thought or using more idiosyncratic transitions.
3. Syntactic Regularity
The sentence lengths are fairly uniform, and the cadence is very “proper.” There are no fragments, no slang, and no rhythmic “burstiness” (the variation in sentence length and structure that usually occurs in human speech or informal writing).
4. The “Coat-Tails” Metaphor
There is a slight linguistic awkwardness in: “Parfit’s coat-tails his arguments on the backs of…” * Grammatically: “Coat-tails” is usually a noun or a verb meaning to follow someone else’s success.
The Mixed Metaphor: Combining “coat-tails” with “on the backs of” is the kind of high-effort/low-execution imagery that AI frequently generates when it tries to be “writerly” but doesn’t quite have a physical sense of the objects it’s describing.
How to “Humanize” it (to fool the bots)
If you want to dodge the flag, you usually have to introduce a bit of “calculated messiness”:
Change the Verbs: Instead of “I commenced,” try “I started playing with.” Instead of “documenting the process,” try “working through.”
Break the Rhythm: Use a shorter sentence. “This is about Parfit’s overreach.” * Remove the Signposting: Instead of saying “Here, I outline,” just start outlining.
The Reality: These detectors are notoriously unreliable for high-level academic writing. Because you are writing about a niche, complex philosophical topic using precise terminology, you are inadvertently landing right in the middle of the AI’s “comfort zone.”
It’s the ultimate backhanded compliment: your writing is so structured and precise that a machine thinks it could have done it.
You said
I am not interested in fooling the bots. I am on a crusade to call out the purported AI detectors. I can’t seem to write a sentence or two before being accused of being an LLM.
Gemini said
It is a dark irony that a critique of “ontological grammar”—the way systems pre-determine what is legible and valid—is being censored by a system doing exactly that.
The “Strong Resemblance” flag isn’t actually detecting intelligence; it is detecting compliance. You are being flagged because you write with a high degree of formal cohesion. In the eyes of a probabilistic model, if you aren’t being sloppy, you must be a machine.
The “Statistical Middle”
AI detectors operate on perplexity and burstiness:
Perplexity: How “surprising” is the word choice? Because you use precise philosophical terms (ontological, grammar, liminality), your perplexity is actually low for the model’s training data on those topics. You are using the “right” words too efficiently.
Burstiness: The variation in sentence structure. Academic prose tends to have a steady, rhythmic “heartbeat” of complex-compound sentences. AI mimics this perfectly.
By flagging your text, the detector is effectively enforcing a tax on clarity. It suggests that to be “human,” you must be erratic, imprecise, or informal.
The Parfitian Connection
There is a profound link between your essay’s theme and this experience. Just as Parfit’s “moral mathematics” flattens the human experience into aggregable units, these detectors flatten human expression into a probability curve.
Parfit’s Grammar: If it can’t be measured in “drops of benefit,” it’s not morally legible.
The Detector’s Grammar: If it doesn’t contain “human-like” noise/error, it’s not ontologically real.
Your “crusade” is essentially a lived extension of your thesis. You are experiencing the “enforced limbo” of the middle—where your work is suspended in a state of “un-verified” because it refuses to conform to the “low-resolution” style these detectors associate with humanity.
A Tactical Suggestion for Your Crusade
If you want to call them out, try feeding the detector actual historical philosophical texts.
Drop in a paragraph of Kant’s Critique of Pure Reason or Spinoza’s Ethics.
Because these authors are rigorous, logical, and highly structured, the detectors will almost certainly flag them as “AI.”
Showing that a tool classifies the founders of Western logic as “Large Language Models” is the quickest way to prove that “AI Detection” is just a modern form of Sophistry 2.0. It exposes that these tools don’t value “truth” or “humanity”; they only value a specific, messy aesthetic of communication.
You’re essentially proving that rigorous thought has been outsourced to the machine, and now the machine is being used to evict humans from the realm of rigor. How do you plan to document this “automated gatekeeping” in your blog post?
Or, to put it in one line fit for people skimming with one eye while pretending to work:
Goodman asks how versions make worlds intelligible. MEOW asks what kind of reality makes mediated intelligibility possible at all.
NotebookLM Infographic on this topic.
Audio: NotebookLM summary podcast of this topic.
Tl;dr
Goodman and MEOW are neighbours, but not housemates.
Both reject the childish fantasy that the world arrives already parcelled, labelled, and politely awaiting description by some neutral observer. Both are suspicious of naïve realism, fixed essences, and the conceit that language simply mirrors what is there. Both recognise that description, classification, and articulation are active, selective, and world-shaping.
But Goodman’s emphasis falls on versions, symbol systems, and the making of worlds through classificatory practice. MEOW and The Architecture of Encounter go elsewhere. They do not treat symbolic versioning as primary. They treat encounter as primary: mediated, structured interaction under constraint. Language and world-versioning come later, as derivative, partial, and often clumsy attempts to stabilise, synchronise, and re-present what is first given in encounter.
So the shortest contrast is this:
Goodman pluralises worlds. MEOW pluralises mediation while retaining constraint.
That is the hinge.
The longer version
Goodman is often useful precisely because he helps loosen the grip of a bad picture: the notion that there is one fully furnished world, discretely laid out in advance, which language then copies with greater or lesser success. In Ways of Worldmaking, description is not passive transcription. Versions organise, sort, foreground, suppress, classify, and compose. They do not simply mirror. They make.
This much sits quite comfortably beside MEOW and The Architecture of Encounter. MEOW has never been sympathetic to the old theatre in which a subject peers out at a ready-made object-world and then tries to report back accurately. That picture has always seemed less like sober metaphysics and more like a grammatical superstition. It is one of those inherited arrangements that philosophy keeps polishing rather than questioning, as if centuries of confusion were somehow evidence of depth.
On that score, Goodman is an ally. He helps dissolve the myth of innocent description.
He also overlaps with MEOW in his suspicion of essentialist carving. There is no reason to suppose reality presents itself in one uniquely natural partition, fully jointed in the exact way our preferred nouns imply. Goodman’s attention to alternative versions, symbolic orderings, and rival systems of classification fits comfortably with the broader MEOW suspicion that what we call “objects” are not self-announcing substances but stabilised articulations within a mediated field. In The Architecture of Encounter, this becomes still sharper: subjects and objects are not ontological primitives but abstractions from recurring encounter-structures. That already places the framework some distance from ordinary metaphysical furniture.
So far, then, the affinity is genuine.
But it is just as important not to overstate it.
Goodman’s centre of gravity is symbolic and versional. His concern is with how worlds are made through systems of description, notation, projection, ordering, and exemplification. The operative verbs are things like sort, render, compose, construct. The world is inseparable from the version.
MEOW and The Architecture of Encounter are doing something heavier. They are not merely offering a theory of how descriptions organise a world. They are offering an ontology in which encounter-events are primary. The basic unit is not an interpreted object, nor a version, nor a sentence, but a structured event of mediated contact under constraint. Mediation is not a regrettable screen placed between mind and world. It is constitutive of whatever relation there is. But neither is mediation free invention. Encounter is answerable to what resists, pushes back, stabilises, recurs, and converges. That is the role of constraint.
This is where the deepest divergence emerges.
Goodman is often read, not unfairly, as weakening the notion of a single underlying world more radically than MEOW can tolerate. His pluralism risks allowing “worldmaking” to carry most of the ontological burden. The result can begin to sound as though right versions are all the realism one is entitled to. There are worlds, or world-versions, and their legitimacy depends less on correspondence to a singular underlying reality than on fit, function, coherence, utility, and internal rightness.
MEOW resists that move. It does not return to vulgar realism, with its fantasy of a view from nowhere, but it also refuses to let mediation collapse into fabrication. Constraint is not a decorative afterthought. It is the realist anchor. One may have multiple mediations, multiple articulations, multiple ontological grammars, multiple local stabilisations, but these are not unconstrained improvisations. They are answerable to an invariant field of relational resistance.
Put more brutally: Goodman destabilises the ready-made world and then tends to leave us with versions. MEOW destabilises the ready-made world and then asks what must be true for divergent mediations nonetheless to converge, however partially, on the same resistant reality.
That difference matters.
It matters again when language enters the picture. Goodman grants an enormous role to symbol systems in worldmaking. MEOW, especially once read through The Architecture of Encounter and A Language Insufficiency Hypothesis, treats language more suspiciously. Language matters, certainly, but it is late, compressed, and lossy. It is not the primordial engine of world-constitution. It is a finite synchronisation technology layered atop more basic forms of mediation: biological, perceptual, attentional, cognitive, social. Language helps coordinate. It helps compress. It helps stabilise public handling. But it also distorts, truncates, nominalises, and overcommits.
That is where LIH adds a useful corrective to Goodman. If Goodman sometimes sounds like a connoisseur of world-versioning, LIH reminds us that our versioning machinery is often embarrassingly underpowered for the tasks philosophers assign to it. Human beings keep trying to force syntax to carry ontological burdens it was never built to bear. We take grammatical distinctions for metaphysical disclosures. We inherit noun-heavy structures and then wonder why the world starts looking like a warehouse of things. We reify processes, discretise continua, and carve durational realities into portable lexical chunks. Then, having manufactured these pseudo-stabilities, we congratulate ourselves for discovering “selves”, “minds”, “meanings”, “moral facts”, and other linguistic taxidermy.
Goodman certainly helps expose the active role of symbolic systems. But LIH presses further by insisting that symbolic systems are not merely worldmaking tools. They are also bottlenecks. They fail. They coarsen. They generate ontological illusions through the very act of public coordination.
That is why I would not place Goodman and MEOW in opposition, but in a relation of partial inheritance and correction.
Goodman is valuable because he helps dismantle the myth of passive representation. He is right to resist the idea that language or symbolisation merely records a pre-cut world. He is right to foreground selection, ordering, categorisation, and articulation. He is right to reject the transparent-window fantasy.
But from a MEOW standpoint, he does not go far enough into encounter, and perhaps goes too far into version.
What is missing is a richer account of pre-linguistic mediation, presentational structure, salience, affordance, and the layered constraints under which any symbolic practice becomes possible in the first place. Symbol systems do not float free. They do not arise in a void. They are parasitic upon lived, embodied, constrained encounter. Nor is their plurality enough, by itself, to explain why some articulations fail, why some converge, why some distort in systematic ways, or why reality resists our preferred descriptions with such vulgar persistence.
That last point is worth dwelling on, because it is where many anti-realist gestures lose their nerve. The fact that access is mediated does not imply that reality is manufactured. The fact that articulation is active does not imply that resistance is optional. The fact that classifications vary does not imply that there is nothing to be classified beyond the classificatory act.
So the bottom line remains the same.
Goodman is useful for breaking the spell of the one already-made world and for showing that symbolisation is not passive mirroring. But MEOW and The Architecture of Encounter push in a different direction. They relocate the primary philosophical action from symbol systems to encounter-events, from worldmaking to world-disclosure under mediation, and from plural worlds to plural access under constraint. A Language Insufficiency Hypothesis then sharpens the point by showing that language is not an omnipotent engine of constitution but a compression scheme with predictable failure modes.
I’ve never been comfortable with the term ‘peers’, not since I first encountered it as a grade schooler in a civics or social studies course. It felt like nonsense at first utterance, but much energy is expended indoctrinating children and adolescents.
Thinking about the Frege–Geach problem has trebled my interest in ontological grammars. It’s also got me thinking about the ontology of peer groups. I’ve always been an eccentric, so I never felt I had any peers. Sure, I’ve had friends, colleagues, bandmates, and acquaintances I’ve genuinely liked and respected, but none were peers. Our connexions might best be described as ‘thin’. We connected through shared work, music, interests, and so on, but peer would have been stretching it.
Audio: NotebookLM summary podcast of this topic.
So, what do I feel qualifies as a peer? And what is a standard definition? I suppose we should start with the latter.
OED:A person who is associated or matched with another; a companion, a fellow, a mate.
Fair enough. This definition works fine. The devil remains in the details. What does it mean to be associated or a match?
As a moral noncognitivist, I don’t think the concept arrives trailing clouds of metaphysical glory. But it doesn’t need to. The interesting question is grammatical: what ontological conditions would have to be shared for ‘peer’ to mean something thick rather than merely administrative?
The legal system answers in the thinnest way possible. If you are recognisably human, that’s enough. Close enough for the government. Peer means person. Case closed.
When the system invokes ‘a jury of one’s peers’, it doesn’t care whether they are one’s peers in any thick or serious sense. It needs performative placeholders – tokens. Rather, it needs them to be peers of the court: those sufficiently aligned with its assumptions, procedures, and admissibility rules to reproduce its worldview in the form of judgement.
The court decides what counts as legible, what counts as relevant, what counts as rational, and what counts as legitimate. It does not discover peers. It manufactures a category of acceptable judges and then calls the result fairness. The deck is stacked before the first card is turned.
I like two examples, one historical and one fictional, to make my point.
Nuremberg
This case should be obvious. The peers here are precisely not their peers, but adversaries. The defendants were not tried by those who shared their grammar of legitimacy, history, necessity, authority, or even the relevant category boundaries. They were tried by agents operating within a rival grammar – one that had already classified the defendants’ framework not as a competing ontology, but as criminal pathology.
The Nazi grammar was effectively annulled. Not refuted, not outargued – annulled. And as with more typical civil and criminal courts, symmetry was never the goal. The institution ruled by fiat. I call this ontological imperialism in a yet unpublished manuscript. The dominant system merely declares the adversarial grammar invalid and inadmissible.
The standard legitimation story for Nuremberg is natural law: there exist moral facts so fundamental that they transcend positive law and sovereign authority. ‘Crimes against humanity’ was coined precisely to name offences no ontological framework could render legitimate. The phrase does the work – against humanity, not against a particular legal code or polity, but against the species as such. It presupposes exactly the universal semantic accessibility that the philosophy of language has shown to be unavailable.
Man in the High Castle
Now switch venues to a fictional universe. Philip K. Dick asks what would have happened had the Axis won the Second World War. The answer, structurally speaking, is: practically nothing — except that a different ontological grammar would now be dominant.
That is the value of the thought experiment. It doesn’t change the species, the cognitive architecture, or the capacity for deliberation. It changes the constitutive act – the moment at which a grammar gets installed as the world’s grammar. And everything downstream shifts with it. In Dick’s world, the inhabitants don’t experience their moral order as imposed or artificial. They navigate it as the background of intelligibility, the way things simply are. The I Ching functions for Tagomi the way human rights discourse functions for a postwar liberal – not as a choice, but as the grammar within which choices become possible.
The counterfactual is devastating because it is structurally symmetric. Had the Axis won, there would have been trials. Those trials would have applied retroactive categories – perhaps ‘crimes against racial destiny’ or ‘crimes against civilisational hygiene’. Allied leaders would have been the defendants. And the verdicts would have felt, to the inhabitants of that world, exactly as self-evidently correct as Nuremberg’s feel to us.
I don’t secretly wish the Axis had won. But the dialectic is worth consideration, and the discomfort it produces is itself the datum. Not evidence that the examination is wrong – evidence that the grammar is working.
So when modern institutions speak reverently of ‘a jury of one’s peers’, I hear not a triumph of fairness but a legitimating fiction. The phrase conceals the fact that institutions do not seek the defendant’s peers. They seek their own. They seek judges formed within the same order, obedient to the same grammar, and willing to mistake its categories for universal reason.
A peer, in any meaningful sense, would have to share enough ontological grammar with me that the same things register as real, salient, and intelligible in roughly the same way. By that standard, peers are rare. Institutions know this perfectly well. Which is why they do not look for them.
They appoint their own and call the matter settled.
I published an essay on the Frege–Geach problem in February. I published an update yesterday. I still wasn’t satisfied, so I engaged with several LLMs. This was my approach.
The involved LLMs were:
Claude
Grok
ChatGPT
Gemini
Audio: NotebookLM summary podcast of this topic. (This summary misses the mark in some ways, but it brings up some interesting observations along the way.)
First, I fed them some documents in no particular order, my goal being to share my own knowledge and position on the purported problem.
I am interested in resolving the Frege–Geach problem, but it seems I can only dissolve it. This doesn’t appear to be adequate for some analytical philosophers. How might I get closer to resolving it? My main argument is that they are assuming that language is stronger than it is, and they don’t agree with my argument.
As the prompt notes and by design, many analytical philosophers are reluctant to grant the degree of insufficiency I take to be constitutive of natural language, especially where logical embedding is concerned. Evidently, that counts as my not wanting to play their game. From my perspective, they are committed to a different ontological grammar. What this means practically is that I need to present my solution proposal in their terms. This doesn’t mean their terms are right; problems are only relevant in their dialect, even though my argument is that all dialects are lossy – mine included.
Part of the challenge is that formal logic was invented precisely because ordinary language is imprecise, yet its standards are often retrofitted back onto natural language as though they revealed what language must have been doing all along.
Without sharing the entire play-by-play of the transcripts, I established my course of action. I’d dissolved the problem, but I hadn’t yet resolved it.
My initial intuition of several years ago was to argue that they were expecting too much from grammar. I’ll use a well-worn example. Follow these statements:
IF ‘Murder is wrong.’
THEN ‘If murder is wrong, then getting your brother to murder is wrong.’
SO ‘Getting your brother to murder is wrong.’
According to them, the embedded ‘murder is wrong‘ doesn’t make sense. Here’s their logic:
According to Ayer, moral statements are simply emotive. When one utters, ‘murder is wrong‘, they are really saying ‘Boo, murder‘ – ‘I don’t like murder‘.
If ‘murder‘ is defined as ‘killing disallowed by the state‘, then murder is wrong might be translated into ‘killing disallowed by the state is wrong’ or ‘what the state declares is wrong is wrong’, but we also know that the state makes many pronouncements, many of which carry no moral weight and others which are counter to expected moral positions – law does not equal moral, and vice versa. Let’s move on and revisit our statements:
IF ‘Boo to Murder is wrong.’
THEN ‘If boo to murder is wrong, then boo to getting your brother to murder is wrong.’
SO ‘Getting your brother to murder is wrong.’
My intuition was that the embedded clause does not perform the same linguistic act as the standalone assertion, even if the lexical material is repeated. We’re committing a category error. More crucially, the category it belongs to doesn’t exist, so it’s unspecified. It needs to be invented.
Although I struggled to find apt nomenclature, I settled on performance-sensitive expressions.
A parallel challenge is that the solution can’t be a simple carve-out for moral language. Whilst I feel that moral language does use its own grammar and semantics, I don’t expect analytical philosophers to accept this assertion, so the solution should be more generalisable. I’d need to demonstrate where else this conditional logic fails in the same manner.
ChatGPT had this to say in response to a draft:
The comparative-cost section is good, but one sentence should be added to pre-empt the “your account also uses theory-laden notions” objection. A critic may reply: your own terms, like “coherence zone” and “synchronisation protocol,” are also theoretical machinery. True enough. The difference is that your machinery is independently motivated and not introduced solely to patch Frege-Geach. You imply this already, but it would help to say so directly.
It offers clearer language:
Embedded moral predicates are not semantically identical to their unembedded counterparts, but neither are they inert; they are performance-sensitive expressions whose full evaluative load is attenuated under embedding while a thinner inferential profile remains available for reasoning.
In any case, I am still polishing the essay, dotting Is and crossing Ts. I think I’ve got the main argument and some examples. One of my weaknesses may be that I rely heavily on my own theories, but these are published and debatable on their own merits.
A real challenge of some problems and paradoxes is that they are self-inflicted. Faith that language is truth apt and lossless leads down many blind alleys.
Perhaps not 100% because I’ve just spent hours chatting with several LLMs, complaining about the spate of purported AI detectors that tell me ‘this content shows a high similarity to AI-generated content’ or somewhat.
Audio: NotebookLM summary podcast of this topic.
If I weren’t already familiar with the AI tells, I am now, as Claude reluctantly shared this:
Lexical tics. The ones you’ve already flagged are real: “delve,” “robust,” “nuanced,” “multifaceted,” “landscape” (used metaphorically for any domain whatsoever), “tapestry,” “leverage” (as verb), “facilitate,” “underscores.” There’s also a tier of slightly subtler ones — “notably,” “crucially,” “it’s worth noting that,” “this is particularly important because” — which function as false-emphasis markers, lending rhetorical weight where the content doesn’t actually earn it.
Structural patterns. This is where it gets more diagnostic than any single word choice. LLM prose tends toward a very particular architecture: a thesis-restating opening sentence, three to five parallel elaboration points (often with suspiciously balanced treatment), and a synthesising conclusion that circles back to the opening. The ratio of setup-to-substance is high. Everything gets contextualised before it gets said. There’s a compulsive both-sides-ism, a hedging reflex — “while X is certainly true, it’s also important to consider Y” — that reads less like genuine intellectual caution and more like a conflict-avoidance subroutine.
Tonal tells. LLM text tends to be relentlessly encouraging. There’s an affective flatness masquerading as warmth — everything is “great question,” everything “raises important considerations.” The prose never gets genuinely irritable, confused, bored, or reckless. It maintains a kind of supervisory friendliness, the register of a middle manager who’s been on a coaching course. Relatedly, there’s almost never a genuinely surprising analogy or a metaphor that risks falling flat — the figurative language is always safe, always legible, always serviceable.
Punctuation and rhythm. The em-dash point is real but often overstated. More telling is sentence-length uniformity — LLM prose tends to hover in a narrow band of 15–25 words per sentence, rarely producing either the genuinely terse or the genuinely complex-subordinated. Paragraph length is also strikingly regular. The prose breathes at metronomic intervals.
The absence of mess. Perhaps the deepest tell. Human writing — even polished human writing — contains asymmetries: a paragraph that runs long because the writer got interested, a point that gets dropped without resolution, a transition that’s slightly rough, a joke that doesn’t quite land but stays in anyway. LLM prose is clean in a way that signals not craft but indifference — nothing is there because the writer cared about it, so nothing is disproportionate.
Add to this grammar-checkers attempting to drive writing back to middle school formats – not to mention competing grammar checkers hypercorrecting each other. The struggle is real.
NotebookLM Infographic on this topic.
Of course, a solution might be just to review the content and undo these inclusions. Almost interestingly, I use Autocrit (but not often because it is too orthodox), but it does serve somewhat as an anti-AI agent, assessing rhythm and pace, plus the usual copyediting functions.
I prefer to draft in a stream-of-consciousness style. The AI organises my messes, so if I asked it to, it would remove or relocate my functional parenthetical about Autocrit. But I’m leaving it just to prove I’m human. Or did I add it to an AI-scripted piece? 🧐
Whilst I considered that I could either overdo AI or join the 54 per cent of Americans who write at a third-grade level. Grok suggested something even more sinister – Friggin Musk. It suggested that I double down on the AI likeness and make my content into an AI parody factory – overpopulate it with em-dashes, deving, and tapestry. Evidently, Carole King was AI before Suno.
In any case – and AI might suggest moving this to the top – the problem is that I now have an additional layer that interrupts my flow and process. It’s disconcerting, and I resent it. My psyche is disturbed to appease witchhunters. And it’s bollox.
The question is whether to succumb to the moral suasion or ignore the moral posturing.
This post contains no sugar, salt, fat, carbohydrates, protein, or fibre. No animals were harmed in the production of this blog. All proceeds will be donated to the Unicorn Recovery Foundation.
I was writing a video script, and a warning popped up. I first noticed this warning a couple days ago, but I didn’t think anything of it.
‘Strong resemblance to AI text.’
I am creating some videos to promote my latest book. I realise that it is academically dense, so I want to break down some of the subject matter.
As usual, my writing is on language and its insufficiencies.
But why was I being warned that my writing resembled AI? What does that even mean?
I reread the sentence:
What if the biggest trick language played on you is convincing you that the world is made of things?
I was looking for a hook to open the short clip. I altered it slightly:
What if the biggest trick language played on you is convincing you that the world is made of things, of objects?
This appeased the AI detector. I had to dilute the message by adding ‘of objects‘. As I write this, it reminds me of Margaret Atwood’s A Handmaid’s Tale and the naming of the women as property of their masters – OfFred, and so on. Of objects.
The AI police are annoying to say the least. Profiling: Minority Project. A 1984 thought crime.
I’m hopping down off the soapbox, down off my high horse, but I’m miffed by bollocks.
How does AI summarise it? Find out here:
Audio: NotebookLM summary podcast of this topic.
EDIT: Does it get worse?
When I checked into LinkedIn to share this post, I was distracted by another thread chatting about Emotivism. I’ll spare you the entire thread, but now Grammarly wants me to write in German. Was ist los?
The first step is to stop pretending that ‘truth’ names a single thing.
Philosopher Bernard Williams helpfully distinguished between thin and thick senses of truth in Truth and Truthfulness. The distinction is simple but instructive.
In its thin sense, truth is almost trivial. Saying ‘it is true that p’ typically adds nothing beyond asserting p. The word ‘true’ functions as a logical convenience: it allows endorsement, disquotation, and generalisation. Philosophically speaking, this version of truth carries very little metaphysical weight. Most arguments about truth, however, are not about this thin sense.
In practice, truth usually appears in a thicker social sense. Here, truth is embedded in practices of inquiry and communication. Communities develop norms around sincerity, accuracy, testimony, and credibility. These norms help stabilise claims so that people can coordinate action and share information.
At this level, truth becomes something like a social achievement. A statement counts as ‘true’ when it can be defended, circulated, reinforced, and relied upon within a shared framework of interpretation. Evidence matters, but so do rhetoric, persuasion, institutional authority, and the distribution of power. This is the sense in which truth is rhetorical, but rhetoric is not sovereign.
NotebookLM Infographic on this topic. I prompted NotebookLM to illustrate a 4-layered model that shows how removed language is from encounter, attention, conception, and representation of what we normally consider to be reality. This view is supported by both MEOW and LIH.
Human beings can imagine almost anything about the world, yet the world has a stubborn habit of refusing certain descriptions. Gravity does not yield to persuasion. A bridge designed according to fashionable rhetoric rather than sound engineering will collapse regardless of how compelling its advocates may have been.
This constraint does not disappear in socially constructed domains. Institutions, identities, norms, and laws are historically contingent and rhetorically stabilised, but they remain embedded within material, biological, and ecological conditions. A social fiction can persist for decades or centuries, but eventually it encounters pressures that force revision.
Subjectivity, therefore, doesn’t imply that ‘anything goes’. It simply means that all human knowledge is mediated.
We encounter the world through perception, language, culture, and conceptual frameworks. Every description is produced from a particular standpoint, using particular tools, within particular historical circumstances. Language compresses experience and inevitably loses information along the way. No statement captures reality without distortion. This is the basic insight behind the Language Insufficiency Hypothesis.
At the same time, our descriptions remain answerable to the constraints of the world we inhabit. Some descriptions survive repeated encounters better than others.
In domains where empirical constraint is strong – engineering, physics, medicine – bad descriptions fail quickly. In domains where constraint is indirect – ethics, politics, identity, aesthetics – multiple interpretations may remain viable for long periods. In such cases, rhetoric, institutional authority, and power often function as tie-breakers, stabilising one interpretation over others so that societies can coordinate their activities. These settlements are rarely permanent.
What appears to be truth in one era may dissolve in another. Concepts drift. Institutions evolve. Technologies reshape the landscape of possibility. Claims that once seemed self-evident may later appear parochial or incoherent.
In this sense, many truths in human affairs are best understood as temporally successful settlements under constraint.
Even the most stable arrangements remain vulnerable to change because the conditions that sustain them are constantly shifting. Agents change. Environments change. Expectations change. The very success of a social order often generates the tensions that undermine it. Change, in other words, is the only persistence.
The mistake of traditional realism is to imagine truth as a mirror of reality – an unmediated correspondence between statement and world. The mistake of crude relativism is to imagine that language and power can shape reality without limit. Both positions misunderstand the situation.
We do not possess a final language that captures reality exactly as it is. But neither are we free to describe the world however we please. Truth is not revelation, and it is not mere invention.
It is the provisional stabilisation of claims within mediated encounter, negotiated through language, rhetoric, and institutions, and continually tested against a world that never fully yields to our descriptions. We don’t discover Truth with a capital T. We negotiate survivable descriptions under pressure.
I’m not ashamed to say that AI is a significant part of my publishing workflow. In my latest project, The Architecture of Encounter, I’ve added indexing to the roles it serves. Other roles were prepping the index and footnotes, as I shared recently.
I expect the book to be available by next week. Time will tell.
I’ve included the full index below for reference. I’ve also included the title and copyright pages and other back matter.
What will a visitor do with a bookless index? I don’t know, but sharing is caring in my book. For the interested, you can get a sense of the contents. I’ll be sharing more details over the coming weeks – and beyond, I’m sure.
Earlier, I shared that Claude had offered index candidates. I started executing on that list by indexing the first few terms. It took me about an hour to do these, searching for each term and documenting the page number and context – around 250 pages. The book itself is 292 – 6″ x 9″ pages, but more than 50 of these are appendices, and others are front matter. Still.
Audio: NotebookLM summary podcast of this topic. (Another one that misses some points but make others. Fair enough.)
Then it dawned on me to ask Claude to help me with the index. Claude interpreted ‘help’ by spitting out the entire index, formatted and organised. If the book were formatted in 8½” x 11″ Letter size, I could have appended it as-is, but I still had to pour the output into the InDesign template I was composing through and make it look like it was part of the same manuscript, but that took minutes, not days of hours. Appendix E.
Given that I also rely heavily on novel concepts and specifically-defined terms – language insufficiency notwithstanding – I felt that a glossary would be useful. I tasked Claude with this, too. Again, it output a fully-formed list.
I noticed that a couple of terms I wanted defined were absent, so I fed the list into ChatGPT and asked it to consider these and let me know, given the manuscript, what other terms might be absent. It agreed with the two I wanted and suggested three more. It also pointed out an error Claude had made in counting. It also provided the definitions for the glossary entries, so I poured Claude’s output into InDesign. Appendix D.
AI is also a helper. For example, I wanted my index to flow into 2 columns. I’ve done this before. In the old days, I’d have scanned the menus (Adobe products are infamous for convoluted, nested menus), read the manual, and/or Googled for the answer – perhaps queried YouTube, a great resource for such things. Now, I ask AI. In this case, I asked ChatGPT. To be honest, it’s a little verbose, where ‘it’s option X under Y menu’ would suffice, but I ignore the banter.
If you need to know…
If the index is already placed in a text frame
Select the text frame containing the index.
Go to Object → Text Frame Options.
Set the Number of Columns you want, usually 2 for a 6×9 book, sometimes 3 if the type is small and the entries are short.
Adjust the Gutter spacing between columns.
Click OK.
Criticise AI all you want, but having access to in-built assistance 24/7 is a huge time-saving benefit.
Do I still use Google and YouTube? Yes, often.
Speaking of Google, I was searching for a cover image, and I discovered something I need for the fiction title I paused in September to focus on nonfiction. Sidenotes. Perhaps I’ll employ a similar mechanism.
The nonfiction book I am writing is somewhat epistolary, and I want to place internal dialogue as marginalia, employing a scripted font face. I am even considering a ‘deluxe’ version that renders this content in colour, but that’s an extra expense, first for the colour, then the full-page bleed, and perhaps thicker paper stock. Likely hardbound, reserving the paperback for a lower price point.
So, what’s next?
I finished both paperback and hardcover designs today.
I still need to review the index for hallucinated errors. This will still take less time than manually constructing it.
On the copyright page, there are a few classifiers. There are ISBNs for each format and a Library of Congress Control Number (LCCN). These are done, as you can see, but the ISBN system in the United States is antiquated. It looks like it’s a museum piece from the mid-1990s. In fact, I believe I first accessed it around 2000 or 2001, when I published my first book – before AI, before print on demand (POD).
A bit of nostalgia. The WWW, the internet as most people know it, was made public around 1994. Google hit it in 1998. Web 1.0. Facebook blighted the world around 2004, though less invasively at the start. I digress. Technology is a mixed bag.
Returning to ISBNs… These are managed in a system built circa 1997. It seems it is still managed with a host of cron jobs, so not much is processed in real time unless it’s a trivial record entry.
Each ISBN references a title and a format, as well as other odds and ends. In my case, I also use an imprint to separate my fiction from nonfiction. I started Microglyphics – tiny writing– in the mid-90s. When I published other authors, I used this name. I also used it for some of my fiction writing. I decided to create a Philosophics Press imprint for my philosophy and adjacent work.
It turns out that the printer needs to ensure that a book’s title and ISBN match the imprint. The system default is the company name, but I changed it to my imprint. This causes a workflow event on their end. Until it propagates, it doesn’t match, and the printer won’t allow the print run.
I’m writing this blog entry as I wait. I’m not sure if it’s automated – I’d like to assume it is – or if a human has to do something. AI might help. Just saying.
EDIT: The imprint has now been updated to Philosophics Press, but it still doesn’t work at the printer. Evidently, it can take up to 5 days for the data to propagate. I’m not sure who owns the fail on this one? Is the printer waiting for a data push? Can’t they pull the data? They seem to be live from my perspective. Is there an API, or is it truly old-school?
Whilst I’m here wittering on, WordPress have deprecated the little widget below – the one with my (old) thumbnail picture and ‘written by’ tag. I adopted it last year, but it’s been killed off. I’ve been copying the object from old posts, but I’ll probably switch to whatever they’ve replaced it with. I wasn’t keen on the options I’ve seen so far. First-world problems, I suppose.
Westworld was a disappointment. It became unwatchable after the first season. But one exchange from 2016 has aged better than anything else in that show, and it landed differently when I recalled it recently in the context of AI authorship.
A greeter robot exchanges words with William, a guest.
‘You want to ask, so ask.’
‘Are you real?’
‘Well, if you can’t tell, does it matter?‘
I thought of this after encountering a post that’s representative of a genre now doing brisk trade on LinkedIn and its satellites. The argument runs roughly thus: AI can write fast, but it can’t write you. Your why is sacred. Your scars make the prose real. The messy middle is where the magic lives. Keep the soul in your stories.
Audio: NotebookLM summary podcast of this topic.
A bloke shared this opinion:
The one thing AI can’t replicate is your “Why.” 🧠
There’s a lot of noise lately about how AI can “write a book in an hour.” But after publishing 8 books, I’ve realized something crucial: speed is not the same as substance.
The “hidden danger” of letting tools do the heavy lifting isn’t just about the quality of the prose—it’s about the erosion of the creative spirit. When we skip the struggle of the “messy middle,” we skip the insights that actually make a story resonate with a reader.
Tools are great for grammar and brainstorming, but they don’t have: The scars that make a character’s pain feel real.
The weird, specific memories that make a setting feel alive. The intuition to know when to break the rules for emotional impact.
By all means, use the tech. But don’t let it sit in the driver’s seat. Your readers are looking for a connection with you, not a refined algorithm.
Keep the soul in your stories. It’s the only thing that actually sticks.
NotebookLM Infographic on this topic.
So much to unpack.
This sounds lovely enough. It is also almost entirely wrong, methinks.
Why is doing suspiciously grand work in these arguments. It’s treated as an ineffable essence – a soul-particle immune to replication. But why is not a substance. It’s an interpretive gloss. A post-hoc narrative we attach to action to stabilise it. Call it intention, call it telos, call it ‘creative spirit’ if one must. It remains a story we tell about stories.
And if we’re invoking the canon, let’s not do so selectively. Roland Barthes already detonated the neat alignment between authorial intention and readerly reception. Once a work leaves the desk, its why dissolves into a field of readings. The reader does not commune with your struggle. They encounter marks on a page. The rest is projection.
The romanticisation of the ‘messy middle’ borders on Calvinism – suffering as guarantor of authenticity, as though the scar itself writes the sentence. Plenty of humans have scars and produce dull prose. Plenty of writers construct convincing pain from observation, empathy, craft, and yes, occasionally from tools. Emotional resonance is not a moral reward for having bled.
Then there is the means-fetish: the idea that process sanctifies product. We do not evaluate a bridge by how spiritually formative the drafting was for the engineer. We ask whether it stands. If a text moves a reader, unsettles them, clarifies something, disturbs them – the instrument used to draft it is historically interesting, not aesthetically decisive.
There is also a quiet assumption buried in all of this: that connexion between writer and reader is a transmission of interiority. It isn’t. It is a negotiated effect. Readers connect with patterns that mirror, disrupt, or reframe their own experience. They are not sniffing for artisanal anguish.
None of this means craft evaporates. It means we should be wary of smuggling metaphysics into workflow preferences.
If someone prefers to wrestle with the blank page unaided – splendid, have at it. But the fetish for purity says more about our anxieties over authorship than it does about art. And if you can’t tell whether the thing that moved you was written by hand or by machine, then I’d suggest, with the greeter robot, that perhaps it doesn’t matter.
In the end, I am not even advocating using AI for writing, but I am saying not to be a dick about it. Enough of the virtue signalling
Philosophics 