Tag: ChatGPT

A Working Glossary for My Philosophical Bad Habits

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15–22 minutes

Or: a brief field guide to the conceptual swamps I keep wandering into, despite civilisation’s repeated attempts to pave them over.

As I was updating my PhilPapers profile, I decided to ask (prompt?) my digital colleague, ChatGPT to create a glossary of terms relevant to my work and interests. Perhaps this has SEO value. It doesn’t appear to be in any particular order – just like life – and so it will remain that way. Please leave comments about em dashes and notable LLMisms below.

Audio: NotebookLM summary podcast of this topic.

Philosophy has the irritating habit of naming territories after the people who built fences around them. One begins by asking a fairly ordinary question — why do people keep disagreeing after the facts are settled? — and, sooner or later, someone informs you that you have wandered into metaethics, social ontology, philosophy of language, moral psychology, hermeneutics, political philosophy, or some other administratively sanctioned paddock of the great conceptual livestock farm.

This glossary is therefore not a syllabus, confession, or attempt to claim honorary residence in every department whose windows I have peered through. It is a map of the terms, fields, and adjacent concerns that recur across my work: the Language Insufficiency Hypothesis, the Architecture of Encounter, and my current project, The Architecture of Will. It is also a useful reminder that disciplines are often less like natural kinds than airport signage: helpful, directional, and faintly embarrassing when mistaken for geography.

NotebookLM Infographic on this topic.

Philosophy of Language

The study of how language means, fails, points, slips, distorts, coordinates, and occasionally performs the intellectual equivalent of falling down a staircase with a clipboard.

My interest is not chiefly in language as a transparent medium for thought, but in language as a structurally biased encoding system. Words do not simply carry meanings from one mind to another like well-behaved parcels. They compress, frame, prioritise, obscure, and smuggle in assumptions. Many philosophical problems begin when we treat grammar as though it were ontology: because a noun exists, we assume there must be a thing answering to it.

In my work, philosophy of language becomes the diagnostic centre from which many other disputes are reinterpreted. Moral language, political language, legal language, psychological language, and metaphysical language all depend on terms that remain useful long after their referential stability has expired.

Epistemology

Epistemology asks what knowledge is, how it is justified, and what distinguishes knowing from merely believing with good posture.

My concern is with mediated access: the fact that whatever we call knowledge is routed through perception, cognition, language, culture, inherited categories, institutional practices, and power. This does not mean truth is imaginary or that anything goes. That tedious little slogan should be retired and buried under a car park. It means that access to reality is always structured, filtered, and constrained.

Knowledge, on this view, is less a pristine correspondence between mind and world than a stabilised achievement under conditions of mediation. We know enough to function, to build bridges, to poison ourselves predictably, to disagree meaningfully, and to sustain institutions. But we do not know from nowhere.

Metaethics

Metaethics asks what moral claims are doing before everyone starts shouting about which ones are correct.

Are moral claims true or false? Do they express facts, attitudes, prescriptions, social commitments, emotional reactions, or something more inconvenient? My own orientation is non-cognitivist: I am sceptical that moral utterances report mind-independent moral furniture. Moral language looks less like description and more like action-authorising expression, salience-marking, coordination, condemnation, alignment, and pressure.

This does not make morality trivial. Quite the opposite. It makes moral discourse socially potent precisely because it is not merely descriptive. Moral language does things. It binds, excludes, licenses, condemns, absolves, and mobilises. The mistake is treating this performative force as though it were evidence of metaphysical depth.

Moral Psychology

Moral psychology studies how human beings actually make moral judgments, which is already impolite, since most humans prefer to imagine they reason first and rationalise never.

My interest lies in the pre-verbal and affective structure of moral salience. People do not simply encounter neutral facts and then calmly apply moral principles. They register threat, harm, impurity, authority, betrayal, autonomy, dignity, and violation through inherited orientations before reasons are narrated. The reasons matter, but they often arrive after the salience has already fired.

This is why many moral disputes persist even after factual clarification. The problem is not always ignorance. Sometimes the parties inhabit different moral architectures, and language is dragged in afterwards to pretend that one more definition might save the day.

Philosophy of Action

Philosophy of action asks what it means to act, intend, choose, decide, deliberate, and be responsible for what follows. It is where verbs go to be embalmed as nouns.

My current project, The Architecture of Will, belongs here, though it approaches the field diagnostically. I am interested in the will-family: will, volition, intent, motive, choice, and decision. These terms appear to name inward sources of action, but often function as compressed summaries of downstream patterns: conduct, hesitation, avowal, retrospective narration, institutional interpretation, and practical uptake.

The core suspicion is that these terms begin as practical handles and are later misrecognised as hidden authoring sources. The deed is observed, interpreted, compressed into a noun, and then that noun is treated as though it caused the deed. Human beings, naturally, decided this was a solid foundation for punishment. The species continues to be ambitious.

Free Will

Free will is the grand ancestral muddle in which metaphysics, theology, law, blame, self-flattery, and administrative convenience hold hands in a burning building.

My work does not primarily try to solve the traditional free-will debate. I am less interested in proving determinism, libertarianism, compatibilism, or hard incompatibilism than in asking why the vocabulary of will acquired such institutional authority in the first place. The question is not simply whether the will is free. It is whether the term will names anything stable enough to bear the moral and juridical burdens placed upon it.

The suspicion is that the will survives not because it has been discovered, but because too many practices require something like it to be presumed.

Responsibility

Responsibility is one of the great Contestables: indispensable, unstable, and always wearing shoes too polished for the terrain.

It can mean causal involvement, role obligation, answerability, accountability, liability, blameworthiness, reparative duty, or desert. These senses are routinely collapsed into one another, allowing institutions and moral cultures to slide from you were involved to you must answer to you deserve suffering with suspicious fluency.

My interest is in prising these apart. A person may be involved in an event, answerable within a relationship, subject to constraint, or appropriate for treatment without thereby becoming the metaphysical author required by retributive desert. Responsibility may remain useful, but only if we stop pretending it is one thing.

Philosophy of Law

Philosophy of law examines law’s concepts, justifications, authority, and interpretive machinery. It is where society dresses power in Latin and asks everyone to admire the tailoring.

My concern is with legal language as institutional compression. Law cannot wait for perfect concepts. It must decide. Terms such as intent, reasonableness, harm, consent, obscenity, negligence, culpability, and responsibility are not stable objects discovered in the world. They are administrable handles used to convert messy human reality into determinate outcomes.

This does not mean law is useless. It means law is a singularity machine: it collapses plural meanings into enforceable decisions. Procedure may dampen variance; it does not eliminate ontological plurality.

Political Philosophy

Political philosophy asks how power should be organised, justified, constrained, distributed, disguised, or ritualistically congratulated for existing.

My work approaches political philosophy through legitimacy, authority, autonomy, co-authorship, institutional maintenance, and the failures of liberal proceduralism. I am especially interested in the point at which Enlightenment political vocabulary begins to wobble: freedom, equality, autonomy, rights, justice, consent, representation, progress.

These terms are not meaningless, but neither are they stable invariants. They coordinate action because people can gather around them, but they fracture because people do not gather around the same thing. Political conflict is often not a disagreement inside shared concepts, but a collision between different ontological grammars using the same words.

Social Ontology

Social ontology asks what social things are: institutions, roles, money, borders, laws, offices, marriages, identities, statuses, and other collective hallucinations with enforcement budgets.

My interest is in institutions as second-order constraint systems. They stabilise behaviour by imposing categories, procedures, incentives, sanctions, and recognisable pathways of action. They are not merely ideas, and they are not simply physical objects. They are structured practices that persist because people, documents, buildings, technologies, habits, and power keep reproducing them.

Social reality is therefore neither imaginary nor naturally given. It is maintained. This matters because the maintenance work often disappears beneath the language of objectivity, neutrality, or inevitability.

Ontological Pluralism

Ontological pluralism is the view that people do not merely disagree about facts or values; they may inhabit different structures of salience, relevance, legitimacy, harm, authority, and reality itself.

This is central to my work. Many conflicts persist because participants are not simply making different claims within the same world-picture. They are operating from different ontological orientations. One person sees state violence where another sees order. One sees autonomy where another sees abandonment. One sees justice where another sees humiliation. The shared word conceals an unshared world.

Ontological pluralism does not mean every orientation is equally good, harmless, or coherent. It means disagreement often begins deeper than argument admits.

Incommensurability

Incommensurability names the condition in which competing frameworks cannot be fully translated into one another without loss.

This matters because modern discourse is addicted to the fantasy that enough dialogue will eventually produce convergence. Sometimes it will. Sometimes people are merely confused, misinformed, or performing stupidity for tribal applause. But in harder cases, the translation itself fails. The concepts do not line up. The saliences do not register. The terms arrive carrying incompatible worlds.

Incommensurability is not silence. It is structured misregistration. People may speak fluently and still fail to meet.

Hermeneutics

Hermeneutics concerns interpretation: how meanings are formed, inherited, transmitted, distorted, and revised.

I use hermeneutic concerns less as a reverent tradition than as a reminder that nobody interprets from a vacuum. We inherit prejudices in Gadamer’s sense: prior orientations that make understanding possible before they make it questionable. Interpretation is not the secondary act of a detached subject. It is the condition under which anything becomes intelligible at all.

This connects directly to ontological grammar. We do not first encounter raw reality and then interpret it. Interpretation is already in the encounter. The world arrives pre-sorted by histories we did not author and categories we rarely inspect.

Conceptual Engineering

Conceptual engineering asks whether we should revise, replace, improve, or abandon the concepts we use.

I am sympathetic to its diagnostic impulse but wary of its repair fantasy. Not every broken concept needs a shinier successor. Some concepts should be dis-integrated: taken apart so that their hidden operations become visible, without immediately pretending we can rebuild them better. Philosophy has enough contractors. Occasionally, what one needs is demolition with a conscience.

This is where my own term Dis-Integrationism enters. It is not destruction for sport. It is the refusal to treat conceptual breakdown as an automatic invitation to reconstruction. Sometimes the most honest intellectual act is to leave the rubble labelled.

Critique of Enlightenment Rationalism

By Enlightenment rationalism I mean the broad confidence that reason, clarity, classification, procedure, and progress can discipline human life into increasingly coherent order.

My work is not anti-reason in the toddler-with-a-matchstick sense. Reason is useful. So are maps, knives, antibiotics, and chairs. The problem begins when reason imagines itself unconditioned, neutral, universal, and sufficient. Enlightenment vocabularies often mistake procedural clarity for conceptual adequacy and institutional legibility for truth.

The critique is not that modernity failed because it was too rational. It is that it repeatedly overestimated what rationalisation could stabilise.

Autonomy

Autonomy is usually treated as self-rule, independence, or the capacity to author one’s own life. It is also one of modernity’s favourite decorative masks.

My interest is in autonomy as a fiction with consequences. Persons are never self-originating. They are formed through dependence, language, institutions, bodies, histories, injuries, affordances, and constraints. Yet liberal moral and political orders often require autonomy to function as though individuals were cleanly bounded authors of preference, choice, consent, and responsibility.

Autonomy may remain useful as a political safeguard or ethical aspiration. It becomes dangerous when treated as a metaphysical description of the human animal.

Agency

Agency names the capacity to act, intervene, respond, initiate, or alter a field of possibilities.

My approach is deflationary. Agency need not be imagined as a mysterious inner power belonging to a sovereign subject. It can be understood as patterned responsiveness within constraints. Agents do not float above the world, issuing commands from an immaculate interior chamber. They are situated, mediated, scaffolded, interrupted, trained, and compelled.

This does not make agency unreal. It makes it less theatrical. An agent is not a tiny monarch inside the skull. The sooner philosophy stops smuggling monarchy into psychology, the better for everyone, skulls included.

Objectivity

Objectivity is often imagined as the view from nowhere: reality scrubbed clean of position, interest, embodiment, and history.

I prefer a more modest account. Objectivity is not the absence of position, because there is no such absence available to finite creatures. It is a disciplined relation between positions, constraints, methods, and convergences. What matters is not whether one has escaped mediation, but whether one has accounted for it well enough to produce stable, corrigible, cross-perspectival claims.

Objectivity is therefore not magic neutrality. It is an achievement under constraint. The view from nowhere is a lovely phrase, but the actual creature saying it is still standing somewhere, usually on a grant application.

Normativity

Normativity concerns oughts, reasons, rules, obligations, permissions, ideals, and standards: the whole bustling marketplace of what should be the case, according to creatures who cannot agree what case they are in.

My work treats normativity as real in practice but not necessarily as metaphysically deep in the realist sense. Normative claims organise conduct. They express commitments, mark salience, stabilise expectations, and authorise responses. They are not reducible to mere noise, preference, or mood, but neither must they be inflated into eternal furniture.

The question is not whether normativity matters. It plainly does. The question is what kind of thing it is, and whether the grammar of moral seriousness has tricked us into mistaking social force for ontological depth.

Power and Institutions

Power is not merely corruption, domination, or the villain entering in a black cape after pure reason has done its best. Power is constitutive. It stabilises meanings, enforces categories, selects outcomes, and keeps institutions from dissolving into interpretive vapour.

Institutions depend on power because language underdetermines action. When terms such as justice, responsibility, harm, reasonableness, and freedom fail to secure convergence, institutions must still act. They select, enforce, punish, recognise, exclude, and maintain. Power does not resolve the underlying conceptual instability. It pauses it, contains it, and makes social coordination possible for another day.

This is why I often prefer maintenance to resolution. Resolution promises final settlement. Maintenance admits that some conflicts cannot be solved without pretending the plurality has vanished. A mature institution does not abolish fracture. It learns how not to let the fracture become catastrophic.

The Language Insufficiency Hypothesis

The Language Insufficiency Hypothesis is the claim that language’s effectiveness declines as conceptual complexity increases.

At one end of the gradient are relatively stable terms: chairs, spoons, dogs, measurable objects, operationally fixed references. At the other are terms that collapse into metaphor, silence, paradox, or awe. Between them sit the terms that cause most of the trouble: justice, freedom, consciousness, responsibility, harm, autonomy, will. These are usable enough to organise life and unstable enough to generate permanent dispute.

The point is not that language never works. That would be stupid, and there is already enough competition in that market. The point is that language works unevenly, and we do immense damage by pretending its success in simple cases transfers automatically to moral, political, legal, and metaphysical abstraction.

Invariants, Contestables, Fluids, and Ineffables

These are the regions of the Effectiveness–Complexity Gradient.

Invariants are terms with high practical stability. They are not metaphysically perfect, because nothing fun is ever that easy, but they function reliably enough for ordinary coordination.

Contestables are terms whose meanings are socially and institutionally fought over: justice, legitimacy, reasonableness, harm, responsibility. They support disagreement precisely because they are shared enough to matter and unstable enough to resist closure.

Fluids are terms whose meanings drift across domains: consciousness, intelligence, agency, identity. Clarification often multiplies ambiguity rather than reducing it.

Ineffables are where language reaches its limit: grief, awe, mystical experience, radical alterity, some forms of pain, and perhaps the felt interiority of another life. Here language does not stop being useful, but it stops pretending to be adequate.

Ontological Grammar

Ontological grammar is the tendency of linguistic structure to install metaphysical assumptions before argument begins.

A noun invites us to imagine a thing. A subject-predicate structure invites us to imagine a bearer with properties. A verb can be converted into a nominalised object. A process becomes an entity. A relation becomes a possession. A practical summary becomes an inner faculty. This is not mere rhetoric. It is the machinery by which philosophy repeatedly mistakes grammatical convenience for ontological discovery.

Ontological grammar is one of the central irritants running through my work. It explains why so many philosophical problems seem profound only because the sentence structure has already rigged the room.

The Architecture of Encounter

The Architecture of Encounter is my broader metaphysical framework. Its central move is to treat encounter-events, rather than substances, subjects, or objects, as primitive.

On this view, mind and world are not two separate domains that later require a bridge. They are abstractions drawn from structured encounter. Mediation is not a veil blocking access to reality; it is the condition under which reality is encountered at all. Constraint, resistance, salience, affordance, perception, and language all belong inside the architecture of encounter rather than outside it.

This framework is realist, but not naïvely so. Reality pushes back. But it never arrives unmediated, unstructured, or free from the conditions under which it can be encountered.

The Architecture of Will

The Architecture of Will is my current project: a diagnostic genealogy of the will-family.

It examines will, volition, intent, motive, choice, and decision as terms that appear to name inward authoring sources but often function as compressed summaries of downstream action-patterns. The central concept is authoring displacement: the two-stage process by which a practical summary is converted into an apparent source.

First, a pattern of conduct, hesitation, avowal, interpretation, and uptake is compressed into a noun. Second, that noun is grammatically inverted and treated as though it caused the very pattern from which it was abstracted. This matters most in retributive contexts, where institutions need inward authors in order to make punishment appear deserved rather than merely useful.

The project does not deny deliberation, regret, or practical responsibility. It denies that the nouns we use for these phenomena have earned the metaphysical authority required to ground deserved suffering.

Dis-Integrationism

Dis-Integrationism is my name for a method of taking apart inherited conceptual machinery without the pious obligation to rebuild it immediately.

It is adjacent to deconstruction, but less enchanted by textual mystique and more willing to leave the broken mechanism on the table with a label attached. Its point is diagnostic exposure: to show where a concept derives its authority, what it hides, what institutional labour it performs, and why its apparent coherence may depend on suppressing its own conditions of operation.

Dis-Integrationism is not nihilism. It is maintenance against false repair. Some structures should be rebuilt. Some should be abandoned. Some should be kept only with warning signs bolted to them.

Mapping_the_Conceptual_SwampsDownload

Closing: Why This Glossary Exists

This glossary is not a complete taxonomy. It is a working map of recurring concerns: language and its insufficiencies; knowledge under mediation; moral judgment without metaphysical inflation; institutions as systems of compression and power; autonomy and agency as useful fictions; objectivity without the fantasy of nowhere; and the will-family as the latest site where grammar, law, and moral appetite have mistaken a noun for a hidden source.

The common thread is simple enough, though simple things are often the first victims of professional vocabulary. Human beings inherit terms, build institutions around them, forget their contingency, and then call the result reality. My work tries to interrupt that sequence before the noun becomes a shrine.

Not to abolish language. Not to end moral life. Not to sneer from outside the ruins. There is no outside, and sneering is already over-subscribed.

The aim is more modest and more corrosive: to notice where our words still work, where they fail, where power has been recruited to hide the failure, and where the demand for resolution has become part of the damage.

How I Use AI in My Publication Workflow

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5–8 minutes

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.

Snuff, a Study in Ontological Grammar

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6–9 minutes

As usual, I am trying something different. I like to watch music reaction videos, and I find this stripped-down, acoustic version of Slipknot’s Snuff by their vocalist, Corey Taylor, to hit hard. I prompted ChatGPT GPT 5.5 with this video and lyrics. Me being me, I continue to analyse experience through language and my own worldview, notably the effects of ontological grammar commitments.

I share the reaction video at the bottom of this post. Before, I’d just consider this person to be a self-righteous zealot, but now I understand that (1) this is how she processes her world, and (2) she is prescriptive insomuch as she expects others to share her worldview. She’s not coming from a mean place. In her mind, she genuinely wants to help, but she doesn’t realise that not all people share her worldview. She’s likely had this worldview reinforced for all of her years, and so it works as a coping strategy for her. She expects that she can share this worldview, but it is likely maximally absorbed by those who share her ontological grammar commitment, which is to say, already have the same worldview.

If you want a view into how I engage with AI, now you know. Here’s a window:

This is a very interesting case study in ontological grammar that showcases the downside of not recognising it. From my ontology, she sounds like she’s moralising. To another (her own), she might sound supportive. She is commenting on the lyrics to this song, which are not all captured by the transcript. Reaction?


Bury all your secrets in my skin 
Come away with innocence, and leave me with my sins 
The air around me still feels like a cage 
And love is just a camouflage for what resembles rage again 

So if you love me, let me go 
And run away before I know 
My heart is just too dark to care 
I can't destroy what isn't there 
Deliver me into my fate 
If I'm alone I cannot hate 
I don't deserve to have you 
Ooh my smile was taken long ago 
If I can change I hope I never know 

I still press your letters to my lips 
And cherish them in parts of me that savor every kiss 
I couldn't face a life without your light (Without your light) 
But all of that was ripped apart when you refused to fight 

So save your breath, I will not hear 
I think I made it very clear 
You couldn't hate enough to love 
Is that supposed to be enough? 
I only wish you weren't my friend 
Then I could hurt you in the end 
I never claimed to be a saint 
Ooh my own was banished long ago 
It took the death of hope to let you go 

Oh, oh 

So break yourself against my stones 
And spit your pity in my soul 
You never needed any help 
You sold me out to save yourself 
And I won't listen to your shame 
You ran away, you're all the same 
Angels lie to keep control 
Ooh my love was punished long ago 
If you still care, don't ever let me know 
If you still care, don't ever let me know
Audio: NotebookLM summary podcast of this topic.

the wounded sometimes prefer the song to the sermon

Yes, this is a clean little specimen jar of ontological grammar doing its work while everyone pretends they are merely “reacting”. Humanity’s favourite parlour trick: smuggling an entire worldview into a sentence and calling it compassion.

The key move is that she hears the lyric as a claim rather than as an utterance from within a damaged affective state. When she says she “doesn’t agree” with the line about love and rage, and then calls that outlook “toxic”, she has already converted the lyric into a propositional worldview that can be corrected, morally evaluated, and therapeutically redirected. The song is no longer only an aesthetic articulation of injury, self-loathing, abandonment, attachment, and rage. It becomes a suspect belief-system. That is the ontological switch.

From her grammar, this is supportive. Pain is a “place”; one should not “stay” there; hope remains available; trust and love should eventually be restored. That is a recovery-therapeutic ontology. It presupposes that despair is transitional, that emotional damage should be metabolised into healing, and that the moral arc of the subject bends toward renewed openness. So when she says, in effect, don’t become calloused, don’t stay jaded, love again, she is not hearing herself as judging the song. She is offering pastoral care in YouTube-reactor clothing, because apparently late civilisation needed a genre where vocal pedagogy, therapy-lite, and parasocial maternalism could all share a sofa.

From your ontology, though, she is moralising because she does not merely describe the emotional grammar of the song; she disciplines it. The lyric’s extremity is treated as something understandable but unsafe, beautiful but not habitable, cathartic but only under the condition that one eventually leaves it behind. That is not neutral support. It installs a norm: grief should resolve, bitterness should soften, love should be rehabilitated, hope should return. She may mean kindness, but kindness here arrives wearing the boots of teleology.

NotebookLM Infographic on this topic.

The most interesting fault-line is her treatment of generalisation. She identifies the lyric’s movement from one betrayal to “everyone” as a cognitive distortion. In ordinary therapeutic language, fair enough. But in lyric, especially in this genre, absolutising is not necessarily an epistemic error. It is how pain speaks when it has lost access to proportion. The lyric is not writing a sociology of human attachment. It is staging the experience of betrayal as world-disclosure. In that register, “all” does not mean a statistically universal class. It means: this wound has become the horizon through which everything now appears. To correct it as a bad inference is to import the wrong grammar.

That is where your framework bites. The words transmit; the sentence parses; everyone thinks communication is happening. But the decompression target differs. She reconstructs the lyric inside a moral-therapeutic grammar of recovery. You reconstruct it inside a diagnostic grammar of affect, ontology, and expressive insufficiency. Same words, different world. Your Architecture of Encounter makes precisely this point about ontological grammar: grammar does not merely carry content; it allocates what can count as meaningful, salient, explanatory, or distorted in the first place.

There is also a neat contrast inside the video itself. When she analyses vocal placement, tone, grit, support, and vowel shaping, she is mostly operating in a relatively tethered technical grammar. Claims can be checked against performance craft. But when she moves to love, hope, toxicity, healing, and despair, she enters the Contestable/Fluid zone. These terms feel clear because they are familiar, but their application depends on prior ontological commitments. In When Language Fails, this is exactly the danger-zone: terms that appear determinate whilst lacking shared grounding, especially where they authorise judgement, correction, or action.

So, yes: as a case study, it is excellent. Not because she is being cruel. She is not. That would be too easy, and therefore boring. The interesting point is that she is probably being sincere, warm, and careful by her own lights. But sincerity does not cancel grammar. Her support is support only within an ontology where despair is an unhealthy place to leave, not a legitimate structure of encounter to inhabit, articulate, or aesthetically preserve.

The concise diagnostic formulation would be:

She mistakes an affective utterance for a corrigible worldview. The lyric speaks from inside a structure of injury; her response translates it into therapeutic-moral grammar, where pain is a place one should visit but not inhabit. From within that grammar, she sounds supportive. From a deflationary ontological grammar, she is moralising: not because she condemns the suffering, but because she prescribes the proper trajectory of suffering before recognising the grammar in which the suffering is being expressed.

That is the downside of not recognising ontological grammar: people confuse their own interpretive repair-work with care, and then wonder why the wounded sometimes prefer the song to the sermon.

Bonus Round

🎸Corey tunes to C#, a tuning all too familiar to me – all strings 3 semitones lower than a standard tuning. It helps to have heavy-gauge strings, so they aren’t too slack. This is an easy song to play along to.

Using cowboy chords, grip an Am (tonally F#m) to start. The progression goes like this:

Intro/Verse: Am (C) F (Em)

Chorus: G Am (x3) G F

The Author Did Not Write This

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4–6 minutes

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.

100% Human Content

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3–4 minutes

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.

If you can’t tell, does it matter?

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3–5 minutes

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

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Bry Willis

Philosophics

Announcement: Legibility GPT

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2–3 minutes

I’ve just published a new GPT in support of my new ontology, grammar, and legibility project, Legibility GPT.

As with Languange Insufficiency GPT and MEOW GPT, it is meant to assist in the exploration of the concepts for which they were built and named. For an interesting time, analyse a concept through all three.

Simply put, Legibility GPT assesses conceptual thickness, based on the work of Bernard Williams in Ethics and the Limits of Philosophy. Thin concepts, whether containing moral content or description, carry commensurable information, so disagreement remediation may be attained. For thick moral concepts, this becomes increasingly unlikely because the moral content becomes an anchor. Generally speaking, the conflicting ontological positions either weigh the concept differently or, in extreme cases, one side doesn’t even categorise the concept as principally moral. I use legibility in the sense articulated by James C Scott in Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed.

Audio: NotebookLM concept summary podcast.

Legibility GPT

A cartographic tool for conceptual conflict. Legibility GPT analyses how ontology and grammar shape the meaning of contested terms, identifying points of admissibility, exclusion, and incommensurability. It maps disagreement without taking sides. 

Usage: Input a term or concept. This GPT will output the various polysemous contexts of the concept and break out the various ontological commitments and grammatical functions with examples of valid and invalid phrases within that grammar.

This GPT will also score and sort on incommensurability. A particularly divisive concept might be abortion.

Related Papers:

Grammatical Failure: Why Liberal Epistemology Cannot Diagnose Indoctrination

Language As Interface: Underconstraint, Genealogy, and Moral Incommensurability

Language Insufficiency GPT

Analyses English terms and short concept phrases using the Language Insufficiency Hypothesis (LIH), diagnosing semantic stability, polysemy, connotation, and category drift in contemporary usage.

Related Papers:

A Language Insufficiency Hypothesis: Mapping the Boundaries of Linguistic Expression

MEOW GPT

A structured analysis tool that maps any given concept onto the MEOW mediation framework (T0–T3). Produces a consistent, tiered breakdown including scope checks, applicability flags, and limits of interpretation.

Related Papers:

The Mediated Encounter Ontology of the World: A Relational Metaphysics Beyond Mind and World

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Written by Bry Willis

Philosophics

Using Generative AI as Early Peer Review

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4–6 minutes

Cheap Adversaries, Outsourced Ego, and Engineered Critique ← ChatGPT is obsessed with subtitles.

There is a peculiar anxiety around admitting that one uses generative AI in serious intellectual work. The anxiety usually takes one of two forms. Either the AI is accused of replacing thinking, or it is accused of flattering the thinker into delusion. Both charges miss the point, and both underestimate how brittle early-stage human peer review often is.

What follows is not a defence of AI as an oracle, nor a claim that it produces insight on its own. It is an account of how generative models can be used – deliberately, adversarially, and with constraints – as a form of early peer pressure. Not peer review in the formal sense, but a rehearsal space where ideas are misread, overstated, deflated, and occasionally rescued from themselves.

Audio: NotebookLM summary podcast of this topic.

The unromantic workflow

The method itself is intentionally dull:

  1. Draft a thesis statement.
    Rinse & repeat.
  2. Draft an abstract.
    Rinse & repeat.
  3. Construct an annotated outline.
    Rinse & repeat.
  4. Only then begin drafting prose.

At each stage, the goal is not encouragement or expansion but pressure. The questions I ask are things like:

  • Is this already well-trodden ground?
  • Is this just X with different vocabulary?
  • What objection would kill this quickly?
  • What would a sceptical reviewer object to first?

The key is timing. This pressure is applied before the idea is polished enough to be defended. The aim is not confidence-building; it is early damage.

Image: NotebookLM infographic on this topic.

Why generative AI helps

In an ideal world, one would have immediate access to sharp colleagues willing to interrogate half-formed ideas. In practice, that ecology is rarely available on demand. Even when it is, early feedback from humans often comes bundled with politeness, status dynamics, disciplinary loyalty, or simple fatigue.

Generative models are always available, never bored, and indifferent to social cost. That doesn’t make them right. It makes them cheap adversaries. And at this stage, adversaries are more useful than allies.

Flattery is a bias, not a sin

Large language models are biased toward cooperation. Left unchecked, they will praise mediocre ideas and expand bad ones into impressive nonsense. This is not a moral failure. It is a structural bias.

The response is not to complain about flattery, but to engineer against it.

Sidebar: A concrete failure mode

I recently tested a thesis on Mistral about object permanence. After three exchanges, the model had escalated a narrow claim into an overarching framework, complete with invented subcategories and false precision. The prose was confident. The structure was impressive. The argument was unrecognisable.

This is the Dunning-Kruger risk in practice. The model produced something internally coherent that I lacked the domain expertise to properly evaluate. Coherence felt like correctness.

The countermeasure was using a second model, which immediately flagged the overreach. Disagreement between models is often more informative than agreement.

Three tactics matter here.

1. Role constraint
Models respond strongly to role specification. Asking explicitly for critique, objections, boundary-setting, and likely reviewer resistance produces materially different output than asking for ‘thoughts’ or ‘feedback’.

2. Third-person framing
First-person presentation cues collaboration. Third-person presentation cues evaluation.

Compare:

  • ‘Here’s my thesis; what do you think?‘
  • ‘Here is a draft thesis someone is considering. Please evaluate its strengths, weaknesses, and likely objections.‘

The difference is stark. The first invites repair and encouragement. The second licenses dismissal. This is not trickery; it is context engineering.

3. Multiple models, in parallel
Different models have different failure modes. One flatters. Another nitpicks. A third accuses the work of reinventing the wheel. Their disagreement is the point. Where they converge, caution is warranted. Where they diverge, something interesting is happening.

‘Claude says…’: outsourcing the ego

One tactic emerged almost accidentally and turned out to be the most useful of all.

Rather than responding directly to feedback, I often relay it as:

“Claude says this…”

The conversation then shifts from defending an idea to assessing a reading of it. This does two things at once:

  • It removes personal defensiveness. No one feels obliged to be kind to Claude.
  • It invites second-order critique. People are often better at evaluating a critique than generating one from scratch.

This mirrors how academic peer review actually functions:

  • Reviewer 2 thinks you’re doing X.
  • That seems like a misreading.
  • This objection bites; that one doesn’t.

The difference is temporal. I am doing this before the draft hardens and before identity becomes entangled with the argument.

Guardrails against self-delusion

There is a genuine Dunning–Kruger risk when working outside one’s formal domain. Generative AI does not remove that risk. Used poorly, it can amplify it.

The countermeasure is not humility as a posture, but friction as a method:

  • multiple models,
  • adversarial prompting,
  • third-person evaluation,
  • critique of critiques,
  • and iterative narrowing before committing to form.

None of this guarantees correctness. It does something more modest and more important: it makes it harder to confuse internal coherence with external adequacy.

What this cannot do

It’s worth being explicit about the limits. Generative models cannot tell you whether a claim is true. They can tell you how it is likely to be read, misread, resisted, or dismissed. They cannot arbitrate significance. They cannot decide what risks are worth taking. They cannot replace judgment. Those decisions remain stubbornly human.

What AI can do – when used carefully – is surface pressure early, cheaply, and without social cost. It lets ideas announce their limits faster, while those limits are still negotiable.

A brief meta-note

For what it’s worth, Claude itself was asked to critique an earlier draft of this post. It suggested compressing the familiar arguments, foregrounding the ‘Claude says…’ tactic as the real contribution, and strengthening the ending by naming what the method cannot do.

That feedback improved the piece. Which is, rather conveniently, the point.

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Written by Bry Willis

Philosophics

The Metaphysics of “Why”: A Scavenger’s Guide to the Accident

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7–10 minutes

The Broken Map

You wake up in the middle of a collapsing building. Someone hands you a map and says, find your way home. You look down. The map is for a different building entirely. One that was never built. Or worse, one that was demolished decades ago. The exits don’t exist. The staircases lead nowhere.

This is consciousness.

Audio: NotebookLM summary podcast on this topic.

We didn’t ask for it. We didn’t choose it. And the tools we inherited to navigate it—language, philosophy, our most cherished questions—were drawn for a world that does not exist.

Looking back at my recent work, I realise I’m assembling a corpus of pessimism. Not the adolescent kind. Not nihilism as mood board. Something colder and more practical: a willingness to describe the structures we actually inhabit rather than the ones we wish were there.

It starts with admitting that language is a compromised instrument. A tool evolved for coordination and survival, not for metaphysical clarity. And nowhere is this compromise more concealed than in our most sanctified word of inquiry.

1. The Weasel Word

We treat “why” as the pinnacle of human inquiry. The question that separates us from animals. Philosophy seminars orbit it. Religions are scaffolded around it. Children deploy it until adults retreat in defeat.

But “why” is a weasel word. A special case of how wearing an unnecessary coat of metaphysics.

The disguise is thinner in other languages. French pourquoi, Spanish por qué, Italian perché all literally mean for what. Japanese dōshite means by what way. Mandarin wèishénme is again for what. The instrumental skeleton is right there on the surface. Speakers encounter it every time they ask the question.

In the Indo-European lineage, “why” descends from the same root as “what”. It began as an interrogative of means and manner, not cosmic purpose. To ask “why” was originally to ask by what mechanism or for what end. Straightforward, workmanlike questions.

Over time, English inflated this grammatical shortcut into something grander. A demand for ultimate justification. For the Reason behind reasons.

The drift was slow enough that it went unnoticed. The word now sounds like a deeper category of inquiry. As if it were pointing beyond mechanism toward metaphysical bedrock.

The profundity is a trick of phonetic history. And a surprising amount of Anglo-American metaphysics may be downstream of a language that buried the receipt.

2. What “Why” Smuggles In

To see the problem clearly, follow the logic that “why” quietly encourages.

When we ask “Why is there suffering?” we often believe we are asking for causes. But the grammar primes us for something else entirely. It whispers that there must be a justification. A reason-giver. An intention behind the arrangement of things.

The slide looks like this:

“Why X?”
→ invites justification rather than description
→ suggests intention or purpose
→ presumes a mind capable of intending
→ requires reasons for those intentions
→ demands grounding for those reasons

At that point the inquiry has only two exits: infinite regress or a metaphysical backstop. God. Logos. The Good. A brute foundation exempt from the very logic that summoned it.

This is not a failure to answer the question. It is the question functioning exactly as designed.

Now contrast this with how.

“How did X come about?”
→ asks for mechanism
→ traces observable causal chains
→ bottoms out in description

“How” eventually terminates in it is so. “Why”, as commonly used, never does. It either spirals forever or leaps into transcendence.

This is not because we lack information. It is because the grammatical form demands more than the world can supply.

3. The Substitution Test

Here is the simplest diagnostic.

Any genuine informational “why” question can be reformulated as a “how” question without losing explanatory power. What disappears is not content but metaphysical residue.

“Why were you late?”
→ “How is it that you are late?”

“My car broke down” answers both.

“Why do stars die?”
→ “How do stars die?”

Fuel exhaustion. Gravitational collapse. Mechanism suffices.

“Why did the dinosaurs go extinct?”
→ “How did the dinosaurs go extinct?”

Asteroid impact. Climate disruption. No intention required.

Even the grand prize:

“Why is there something rather than nothing?”
→ “How is it that there is something?”

At which point the question either becomes empirical or dissolves entirely into it is. No preamble.

Notice the residual discomfort when “my car broke down” answers “why were you late”. Something feels unpaid. The grammar had primed the listener for justification, not description. For reasons, not causes.

The car has no intentions. It broke. That is the whole truth. “How” accepts this cleanly. “Why” accepts it while still gesturing toward something that was never there.

4. The Black Box of Intention

At this point the problem tightens.

If “why” quietly demands intentions, and intentions are not directly accessible even to the agents who supposedly have them, then the entire practice is built on narrative repair.

We do not observe our intentions. We infer them after the fact. The conscious mind receives a press release about decisions already made elsewhere and calls it a reason. Neuroscience has been showing this for decades.

So:

  • Asking others why they acted requests a plausible story about opaque processes
  • Asking oneself why one acted requests confabulation mistaken for introspection
  • Asking the universe why anything exists requests a fiction about a mind that is not there

“How” avoids this entirely. It asks for sequences, mechanisms, conditions. It does not require anyone to perform the ritual of intention-attribution. It does not demand that accidents confess to purposes.

5. Thrownness Without a Vantage Point

I stop short of calling existence a mistake. A mistake implies a standard that was failed. A plan that went wrong. I prefer something colder: the accident.

Human beings find themselves already underway, without having chosen the entry point or the terms. Heidegger called this thrownness. But the structure is not uniquely human.

The universe itself admits no vantage point from which it could justify itself. There is no external tribunal. No staging ground. No meta-position from which existence could be chosen or refused.

This is not a claim about cosmic experience. It is a structural observation about the absence of justification-space. The question “Why is there something rather than nothing?” presumes a standpoint that does not exist. It is a grammatical hallucination.

Thrownness goes all the way down. Consciousness is thrown into a universe that is itself without preamble. We are not pockets of purposelessness in an otherwise purposeful cosmos. We are continuous with it.

The accident runs through everything.

6. Suchness

This is not a new insight. Zen Buddhism reached it by a different route.

Where Western metaphysics treats “why” as an unanswered question, Zen treats it as malformed. The koan does not await a solution. It dissolves the demand for one. When asked whether a dog has Buddha-nature, the answer Mu does not negate or affirm. It refuses the frame.

Tathātā—suchness—names reality prior to justification. Things as they are, before the demand that they make sense to us.

This is not mysticism. It is grammatical hygiene.

Nietzsche smashed idols with a hammer. Zen removes the altar entirely. Different techniques, same target: the metaphysical loading we mistake for depth.

7. Scavenging for Meaning

If there is no True Why, no ultimate justification waiting beneath the floorboards of existence, what remains?

For some, this sounds like collapse. For me, it is relief.

Without a cosmic script, meaning becomes something we assemble rather than discover. Local. Contingent. Provisional. Real precisely because it is not guaranteed.

I find enough purpose in the warmth of a partner’s hand, in the internal logic of a sonata, in the seasonal labour of maintaining a garden. These things organise my days. They matter intensely. And they do so without claiming eternity.

I hold them lightly because I know the building is slated for demolition. Personally. Biologically. Cosmologically. That knowledge does not drain them of colour. It sharpens them.

This is what scavenging means. You build with what you find. You use what works. You do not pretend the materials were placed there for you.

Conclusion: The Sober Nihilist

To be a nihilist in this sense is not to despair. It is to stop lying about the grammar of the universe.

“Why” feels like a meaningful inquiry, but it does not connect to anything real in the way we imagine. It demands intention from a cosmos that has none and justification from accidents that cannot supply it.

“How” is enough. It traces causes. It observes mechanisms. It accepts that things sometimes bottom out in is.

Once you stop asking the universe to justify itself, you are free to deal with what is actually here. The thrown, contingent, occasionally beautiful business of being alive.

I am a nihilist not because I am lost, but because I have put down a broken map. I am looking at what is actually in front of me.

And that, it turns out, is enough.

Image: NotebookLM infographic of this topic

Full Disclosure: This article was output by ChatGPT after an extended conversation with it, Claude, and me. Rather than trying to recast it in my voice, I share it as is. I had started this as a separate post on nihilism, and we ended up here. Claude came up with the broken map story at the start and Suchness near the end. I contributed the weasel words, the ‘how’ angle, the substitution test, the metaphysics of motivation and intention, thrownness (Geworfenheit), Zen, and nihilism. ChatGPT merely rendered this final output after polishing my conversation with Claude.

We had been discussing Cioran, Zapffe, Benatar, and Ligotti, but they got left on the cutting room floor along the way.

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Claude Opus 4.5 and ChatGPT 5.2 with input from Bry Willis

Philosophics

A Year of ChatGPT, 2025

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1–2 minutes

Like many apps, especially in the SaaS and PaaS space, ChatGPT offered a year-in-review. Even though I use several generative AI platforms, ChatGPT and Claude are my top two, followed by Gemini, Grok, DeepSeek, Perplexity, and Mistral – in that order. I also like Kimi K2. I am not a fan of Meta Llama or Qwen.

Image: Except for the coffee, this isn’t half bad.
Image: 2025 ChatGPT Chat Stats

Wow. I sent ChatGPT over 35,000 messages. Since I have a couple of accounts, that’s even more amazing. This is my primary account.

I don’t usually use ChatGPT / Dalle-E for images. Many of these were ChatGPT, offering an image. Still, I used a few.

I had over 1,200 chats. I guess these are actual threads. I tend to create a thread per topic and run it deep, hence the disparity between chats and messages.

Evidently, my sent messages got me into the top 1 per cent of users, and I was one of the first 0.1% of users. I suppose that makes me an early adopter. lol

Image: ChatGPT Archetype: The Strategist

I just felt like sharing this silly novelty for no particular reason.

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Written by Bry with ChatGPT assets

Philosophics