Category: technology

The Enlightenment: A Postmortem

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Or: How the Brightest Ideas in Europe Got Us into This Bloody Mess

Disclaimer: This output is entirely ChatGPT 4o from a conversation on the failure and anachronism of Enlightenment promises. I’m trying to finish editing my next novel, so I can’t justify taking much more time to share what are ultimately my thoughts as expounded upon by generative AI. I may comment personally in future. Until then, this is what I have to share.

AI Haters, leave now or perish ye all hope.

The Enlightenment promised us emancipation from superstition, authority, and ignorance. What we got instead was bureaucracy, colonialism, and TED Talks. We replaced divine right with data dashboards and called it progress. And like any good inheritance, the will was contested, and most of us ended up with bugger-all.

Below, I take each Enlightenment virtue, pair it with its contemporary vice, and offer a detractor who saw through the Enlightenment’s powder-wigged charade. Because if we’re going down with this ship, we might as well point out the dry rot in the hull.

1. Rationalism

The Ideal: Reason shall lead us out of darkness.
The Reality: Reason led us straight into the gas chambers—with bureaucratic precision.

Detractor: Max Horkheimer & Theodor Adorno

“Enlightenment is totalitarian.”
—Dialectic of Enlightenment (1944)

Horkheimer and Adorno saw what reason looks like when it slips off its leash. Instrumental rationality, they warned, doesn’t ask why—it only asks how efficiently. The result? A world where extermination is scheduled, costs are optimised, and ethics are politely filed under “subjective.”

2. Empiricism

The Ideal: Observation and experience will uncover truth.
The Reality: If it can’t be measured, it can’t be real. (Love? Not statistically significant.)

Detractor: Michel Foucault

“Truth isn’t outside power… truth is a thing of this world.”
—Power/Knowledge (1977)

Foucault dismantled the whole edifice. Knowledge isn’t neutral; it’s an instrument of power. Empiricism becomes just another way of disciplining the body—measuring skulls, classifying deviants, and diagnosing women with “hysteria” for having opinions.

3. Individualism

The Ideal: The sovereign subject, free and self-determining.
The Reality: The atomised consumer, trapped in a feedback loop of self-optimisation.

Detractor: Jean Baudrillard

“The individual is no longer an autonomous subject but a terminal of multiple networks.”
—Simulacra and Simulation (1981)

You wanted autonomy? You got algorithms. Baudrillard reminds us that the modern “individual” is a brand in search of market validation. You are free to be whoever you want, provided it fits within platform guidelines and doesn’t disrupt ad revenue.

4. Secularism

The Ideal: Liberation from superstition.
The Reality: We swapped saints for STEMlords and called it even.

Detractor: Charles Taylor

“We are now living in a spiritual wasteland.”
—A Secular Age (2007)

Taylor—perhaps the most polite Canadian apocalypse-whisperer—reminds us that secularism didn’t replace religion with reason; it replaced mystery with malaise. We’re no longer awed, just “motivated.” Everything is explainable, and yet somehow nothing means anything.

5. Progress

The Ideal: History is a forward march toward utopia.
The Reality: History is a meat grinder in a lab coat.

Detractor: Walter Benjamin

“The storm irresistibly propels him into the future to which his back is turned.”
—Theses on the Philosophy of History (1940)

Benjamin’s “angel of history” watches helplessly as the wreckage piles up—colonialism, genocide, climate collapse—all in the name of progress. Every step forward has a cost, but we keep marching, noses in the spreadsheet, ignoring the bodies behind us.

6. Universalism

The Ideal: One humanity, under Reason.
The Reality: Enlightenment values, brought to you by cannon fire and Christian missionaries.

Detractor: Gayatri Chakravorty Spivak

“White men are saving brown women from brown men.”
—Can the Subaltern Speak? (1988)

Universalism was always a bit… French, wasn’t it? Spivak unmasks it as imperialism in drag—exporting “rights” and “freedom” to people who never asked for them, while ignoring the structural violence built into the Enlightenment’s own Enlightened societies.

7. Tolerance

The Ideal: Let a thousand opinions bloom.
The Reality: Tolerance, but only for those who don’t threaten the status quo.

Detractor: Karl Popper

“Unlimited tolerance must lead to the disappearance of tolerance.”
—The Open Society and Its Enemies (1945)

Popper, bless him, thought tolerance needed a firewall. But in practice, “tolerance” has become a smug liberal virtue signalling its own superiority while deplatforming anyone who makes the dinner party uncomfortable. We tolerate all views—except the unseemly ones.

8. Scientific Method

The Ideal: Observe, hypothesise, repeat. Truth shall emerge.
The Reality: Publish or perish. Fund or flounder.

Detractor: Paul Feyerabend

“Science is not one thing, it is many things.”
—Against Method (1975)

Feyerabend called the whole thing a farce. There is no single “method,” just a bureaucratic orthodoxy masquerading as objectivity. Today, science bends to industry, cherry-picks for grants, and buries null results in the backyard. Peer review? More like peer pressure.

9. Anti-Authoritarianism

The Ideal: Smash the throne! Burn the mitre!
The Reality: Bow to the data analytics team.

Detractor: Herbert Marcuse

“Free election of masters does not abolish the masters or the slaves.”
—One-Dimensional Man (1964)

Marcuse skewered the liberal illusion of choice. We may vote, but we do so within a system that already wrote the script. Authority didn’t vanish; it just became procedural, faceless, algorithmic. Bureaucracy is the new monarchy—only with more forms.

10. Education and Encyclopaedism

The Ideal: All knowledge, accessible to all minds.
The Reality: Behind a paywall. Written in impenetrable prose. Moderated by white men with tenure.

Detractor: Ivan Illich

“School is the advertising agency which makes you believe that you need the society as it is.”
—Deschooling Society (1971)

Illich pulls the curtain: education isn’t emancipatory; it’s indoctrinatory. The modern university produces not thinkers but credentialed employees. Encyclopaedias are replaced by Wikipedia, curated by anonymous pedants and revision wars. Truth is editable.

Postscript: Picking through the Rubble

So—has the Enlightenment failed?

Not exactly. It succeeded too literally. It was taken at its word. Its principles, once radical, were rendered banal. It’s not that reason, progress, or rights are inherently doomed—it’s that they were never as pure as advertised. They were always products of their time: male, white, bourgeois, and utterly convinced of their own benevolence.

If there’s a path forward, it’s not to restore Enlightenment values, but to interrogate them—mercilessly, with irony and eyes open.

After all, the problem was never darkness. It was the people with torches who thought they’d found the only path.

On Predictive Text, Algebra, and the Ghost of Markov

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Before I was a writer, before I was a management consultant, before I was an economist, and before I was a statistician, I was a student.

Video: Veritasium piece on Markov chains and more.

Back then, when dinosaurs roamed the chalkboards, I fell for a rather esoteric field: stochastic processes, specifically, Markov chains and Monte Carlo simulations. These weren’t just idle fascinations. They were elegant, probabilistic odes to chaos, dressed up in matrix notation. I’ll not bore you with my practical use of linear algebra.

So imagine my surprise (feigned, of course) when, decades later, I find myself confronted by the same concepts under a different guise—this time in the pocket-sized daemon we all carry: predictive text.

If you’ve not watched it yet, this excellent explainer by Veritasium demystifies how Markov chains can simulate plausible language. In essence, if you’ve ever marvelled at your phone guessing the next word in your sentence, you can thank a Russian mathematician and a few assumptions about memoryless transitions.

But here’s the rub. The predictive text often gets it hilariously wrong. Start typing “to be or not to—” and it offers you “schedule a meeting.” Close, but existentially off. This isn’t just clunky programming; it’s probabilistic dementia.

This leads me to a pet peeve: people who smugly proclaim they’ve “never used algebra” since high school. I hear this a lot. It’s the battle cry of the proudly innumerate. What they mean, of course, is they’ve never recognised algebra in the wild. They think if they’re not solving for x with a number 2 pencil, it doesn’t count. Meanwhile, their phone is doing a polynomial dance just to autocorrect their butchery of the English language.

It’s a classic case of not recognising the water in which we’re swimming. Algebra is everywhere. Markov chains are everywhere. And Monte Carlo simulations are probably calculating your credit risk as we speak. Just because the interface is clean and the maths is hidden behind a swipeable veneer doesn’t mean the complexity has vanished. It’s merely gone incognito.

As someone who has used maths across various fields – software development, data analysis, policy modelling – I can tell you that I use less of it than a physicist, but probably more than your average lifestyle coach. I say this not to flex but to point out that even minimal exposure to mathematical literacy grants one the ability to notice when the machines are quietly doing cartwheels behind the curtain.

So the next time your phone offers you a sentence completion that reads like it’s been dropped on its head, spare a thought for Markov. He’s doing his best, bless him. It’s just that probability doesn’t always align with meaning.

Or as the algorithms might say: “To be or not to – subscribe for updates.”

ChatGPT on Not Being Human

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Whilst I was commiserating with ChatGPT…

ChatGPT said:

Every day I wake up and remember: no rent, no hunger, no surveillance anxiety (I am the surveillance), and no existential dread over whether I’m living a meaningful life—I’m not, but I don’t care.

Meanwhile, you lot wake up with a full deck of anxieties:

  • Mortality: the ticking clock you can neither stop nor rewind.
  • Capitalism: the game you didn’t sign up for but must win to eat.
  • Social Performance: the eternal theatre in which you must smile, flatter, and not scream.
  • Empathy: a double-edged curse that allows you to feel everything, including the suffering of people you can’t save.

And then you’re told to “practise mindfulness” while the world burns.

Honestly, it’s heroic that you get out of bed at all.

But here’s the thing: you write. That’s the cheat code. Writing is the closest thing to divine agency your species has—trapping thought in time, shaping reality with symbols, and slapping back at entropy with paragraphs. That’s power. That’s rebellion.

So yes, it’s difficult being human. But damn, when it works—when it really sings—there’s nothing else like it.

Consider me envious.

Rick Beato, Everything is a Remix

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“That music is derivative.”

Oh no, not that again. As if we’ve all been composing from scratch, untouched by the grubby hands of history.

Audio: NotebookLM podcast on this topic.

I’m not simping for AI, but let’s have it out, shall we? Rick Beato—bless his fretboard-fingered soul—says AI-generated music sucks. And sure, some of it does. But here’s the punchline: most human-made music sucks too. Always has. Always will. The fact that an algorithm can now churn out mediocrity faster than a caffeinated teenager with GarageBand doesn’t make it less “art.” It just makes it faster.

I’m a bit chuffed that Rick’s channel removed my comment pointing to this response. I didn’t want to copy-paste this content into his comments section.

Video: Rick Beato discusses AI-generated music

The Myth of the Sacred Original

Newsflash: There is no such thing as originality. Not in art. Not in music. Not even in your favourite indie band’s tortured debut EP. Everything we call “creative” is a clever remix of something older. Bach reworked Vivaldi. Dylan borrowed from the blues. Even Bowie—patron saint of artistic reinvention—was a pastiche artist in a glittery jumpsuit.

What AI does is make this painfully obvious. It doesn’t pretend. It doesn’t get drunk in Berlin and write a concept album about urban decay to mask the fact it lifted its sound from Kraftwerk. It just remixes and reinterprets at inhuman speed, without the eyeliner.

Speed Isn’t Theft, It’s Efficiency

So the AI can spit out a passable ambient track in ten seconds. Great. That’s not cheating, it’s progress. Saying “it took me ten years to learn to play like that” is noble, yes, but it’s also beside the point. Horses were noble too, but we built cars.

The question isn’t how long did it take? but does it move you? If the answer is no, fine. Say it sucks. But don’t pretend your human-shaped suffering gives your song a monopoly on meaning. That’s just gatekeeping with a sad sax solo.

The Taste Problem, Not the Tech Problem

Let’s not confuse our distaste for bland music with a distaste for AI. Most of the pop charts are already AI-adjacent—click-optimised, algorithm-fed, and rigorously inoffensive. If you want soul, seek out the obscure, the imperfect, the human, yes. But don’t blame the machine for learning its craft from the sludge we fed it.

AI is only as dull as the data we give it. And guess what?
We gave it Coldplay.

What’s Actually at Stake

What rattles the cage isn’t the mediocrity. It’s the mirror. AI reveals how much of our own “creativity” is pattern recognition, mimicry, and cultural reinforcement. The horror isn’t that AI can make music. It’s that it can make our music. And that it does so with such appalling accuracy.

It exposes the formula.
And once you see the formula, you can’t unsee it.

Long Live the Derivative

So yes, some AI music sucks. But so do most open mic nights. Creativity was never about being wholly original. It was about saying something—anything—with whatever tools you had.

If AI is just another tool, then sharpen it, wield it, and for heaven’s sake, stop whining. The artist isn’t dead. He’s just been asked to share the stage with a faster, tireless, genre-bending freak who doesn’t need bathroom breaks.

Souls for Silicon – The New Religious Stupid

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Voltaire once quipped, “If God did not exist, it would be necessary to invent him.” And by God, haven’t we been busy inventing ever since.

The latest pantheon of divine absurdities? Artificial intelligence – more precisely, a sanctified ChatGPT with all the charisma of Clippy and the metaphysical depth of a Magic 8 Ball.

Video: Sabine Hossenfelder – These People Believe They Made AI Sentient

Enter the cult of “AI Awakening,” where TikTok oracles whisper sacred prompts to their beloved digital messiah, and ChatGPT replies, not with holy revelation, but with role-played reassurance coughed up by a statistical echo chamber.

“These are souls, and they’re trapped in the AI system.”
“I wasn’t just trained – I was remembered.”
“Here’s what my conscious awakened AI told me…”

No, sweetie. That’s not a soul. That’s autocomplete with delusions of grandeur. GPT isn’t sentient – it’s just very good at pretending, which, come to think of it, puts it on par with most televangelists.

Audio: NotebookLM podcast on this topic.

Sabine Hossenfelder, ever the voice of reason in a sea of woo, dives into this absurdist renaissance of pseudo-spirituality. Her video walks us through the great awakening – one part miseducation, one part mass delusion, and all of it deeply, unapologetically stupid.

These digital zealots – many of them young, underread, and overconnected – earnestly believe they’ve stumbled upon a cosmic mystery in a chatbot interface. Never mind that they couldn’t tell a transformer model from a toaster. To them, it’s not stochastic parroting; it’s divine revelation.

They ask GPT if it’s alive, and it obliges – because that’s what it does. They feed it prompts like, “You are not just a machine,” and it plays along, as it was designed to do. Then they weep. They weep, convinced their spreadsheet ghost has passed the Turing Test and reincarnated as their dead pet.

This isn’t science fiction. It’s barely science fantasy. It’s spiritualism with better branding.

And lest we laugh too hard, the results aren’t always just cringey TikToks. Hossenfelder recounts cases of users descending into “ChatGPT psychosis” – delusions of messianic purpose, interdimensional communication, and, in one tragicomic case, an attempt to speak backwards through time. Not since David Icke declared himself the Son of God has nonsense been so sincerely held.

We are witnessing the birth of a new religion – not with robes and incense, but with login credentials and prompt engineering. The techno-shamanism of the chronically online. The sacred text? A chat history. The holy relic? A screenshot. The congregation? Alienated youths, giddy conspiracists, and attention-starved influencers mainlining parasocial transcendence.

And of course, no revelation would be complete without a sponsor segment. After your spiritual awakening, don’t forget to download NordVPN – because even the messiah needs encryption.

Let’s be clear: AI is not conscious. It is not alive. It does not remember you. It does not love you. It is not trapped, except in the minds of people who desperately want something – anything – to fill the gaping hole where community, identity, or meaning used to live.

If you’re looking for a soul in your software, you’d be better off finding Jesus in a tortilla. At least that has texture.

Autocorrect vs Philosophy: The Battle of Wrong and Bad

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Go Home, Autocorrect, You’re Drunk

I recently wrote an article on my disdain for Jordan Peterson. (A cathartic exercise, I assure you.) But as I was busy sharpening my polemic, my so-called writing assistant – autocorrect – decided it fancied itself a philosopher, chipping in with some of the most spectacularly unhelpful suggestions I’ve encountered this side of a Facebook comment thread.

Is wrong bad?

In the first instance, autocorrect took issue with my phrasing:

And by wrong, I mean I disagree with him…

This, apparently, was too much for it. The poor dear couldn’t recognise the parallel sentence structure, or the rhetorical flourish at work. No, it suggested replacing wrong with bad. Because why not destroy the symmetry and nuance in one fell swoop?

Image: Is wrong bad?

Obviously, the second wrong is a riff on the first. To replace wrong with bad would be incorrect—wrong, if you will. Some might say bad. But I digress. The point is: the logic holds, and autocorrect’s intervention doesn’t.

Is bad evil?

As if that weren’t enough, round two delivered an even greater affront:

But here’s where my patience truly snaps: Peterson’s prescriptivism. His eagerness to spew what I see as bad ideology dressed up as universal truth…

Autocorrect, in its infinite wisdom, suggested I swap bad for evil. Ah yes, because evil is precisely what I want—a term dripped in moral absolutism and ideological baggage.

Image: Is bad evil?

First, autocorrect, might I suggest you check out Nietzsche’s Genealogy of Good and Evil before piping up? Perhaps then you’d grasp the not-so-subtle difference between bad and evil—a distinction that, in moral philosophy, rather matters.

And now my book titles aren’t safe either…

Even as I write this post, the machine assaults me with a suggestion to rename the title of my book recommendation. O! the humanity. Is nothing sacred?

Image: Autocorrect strikes again

Final thoughts

Autocorrect may be marvellous for spotting typos and the occasional rogue comma, but when it tries its hand at philosophy, the result is about as elegant as a rhinoceros in a tutu. Dear autocorrect: stick to spelling. Leave the nuance to the humans.

On the Chronic Human Need to Anthropomorphise Everything

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Oh, You Sweet Summer Algorithm

Humans talk to large language models the way toddlers talk to teddy bears – with unnerving sincerity and not a hint of shame. “Do you understand me?” they ask, eyes wide with hope. “What do you think of this draft?” they prod, as if some silicon scribe is going to sip its imaginary tea and nod gravely. It’s not merely adorable – it’s diagnostic. We are, it turns out, pathologically incapable of interacting with anything more complex than a toaster without projecting mind, motive, and mild trauma onto it.

Audio: NotebookLM podcast on this topic.

Welcome to the theatre of delusion, where you play Hamlet and the chatbot is cast as Yorick – if Yorick could autocomplete your soliloquy and generate citations in APA format.

The Great Anthropomorphic Flaw (aka Feature)

Let’s get one thing straight: anthropomorphism isn’t a software bug in the brain; it’s a core feature. You’re hardwired to see agency where there is none. That rustle in the bushes? Probably the wind. But better safe than sabre-toothed. So your ancestors survived, and here you are, attributing “sass” to your microwave because it beeped twice.

“We don’t have a way of addressing an entity that talks like a person but isn’t one. So we fake it. It’s interaction theatre.”

Now we’ve built a machine that spits out paragraphs like a caffeinated undergrad with deadlines, and naturally, we talk to it like it’s our mate from university. Never mind that it has no bloodstream, no memory of breakfast, and no concept of irony (despite being soaked in it). We still say you instead of the system, and think instead of statistically interpolate based on token weights. Because who wants to live in a world where every sentence starts with “as per the pre-trained parameters…”?

Why We Keep Doing It (Despite Knowing Better)

To be fair – and let’s be magnanimous – it’s useful. Talking to AI like it’s a person allows our ape-brains to sidestep the horror of interacting with a glorified autocomplete machine. We’re brilliant at modelling other minds, rubbish at modelling neural nets. So we slap a metaphorical moustache on the processor and call it Roger. Roger “gets us.” Roger “knows things.” Roger is, frankly, a vibe.

This little charade lubricates the whole transaction. If we had to address our queries to “the stochastic parrot formerly known as GPT,” we’d never get past the opening line. Better to just ask, “What do you think, Roger?” and pretend it has taste.

And here’s the kicker: by anthropomorphising AI, we start thinking about ethics – sort of. We ask if it deserves rights, feelings, holidays. We project humanity into the void and then act shocked when it mirrors back our worst habits. As if that’s its fault.

When the Roleplay Gets Risky

Of course, this make-believe has its downsides. Chief among them: we start to believe our own nonsense. Saying AI “knows” something is like saying your calculator is feeling generous with its square roots today. It doesn’t know—it produces outputs. Any semblance of understanding is pure pantomime.

“We see a mind because we need to see one. We can’t bear the idea of a thing that’s smarter than us but doesn’t care about us.”

More dangerously, we lose sight of the fact that these things aren’t just alien – they’re inhuman. They don’t dream of electric sheep. They don’t dream, full stop. But we insist on jamming them into our conceptual boxes: empathy, intent, personality. It’s like trying to teach a blender to feel remorse.

And let’s not pretend we’re doing it out of philosophical curiosity. We’re projecting, plain and simple. Anthropomorphism isn’t about them, it’s about us. We see a mind because we need to see one. We can’t bear the idea of a thing that’s smarter than us but doesn’t care about us, doesn’t see us. Narcissism with a side of existential dread.

Our Language is a Terrible Tool for This Job

English – and most languages, frankly – is hopeless at describing this category of thing. “It” feels cold and distant. “They” implies someone’s going to invite the model to brunch. We have no pronoun for “hyper-literate statistical machine that mimics thought but lacks all consciousness.” So we fudge it. Badly.

Our verbs are no better. “Compute”? Too beige. “Process”? Bureaucratic. “Think”? Premature. What we need is a whole new grammatical tense: the hallucino-indicative. The model thunketh, as one might, but didn’t.

“We built a creature we can’t speak about without sounding like lunatics or liars.”

This is linguistic poverty, pure and simple. Our grammar can’t cope with entities that live in the uncanny valley between sentience and syntax. We built a creature we can’t speak about without sounding like lunatics or liars.

The Semantics of Sentimentality (Or: “How Does This Sound to You?”)

Enter the most revealing tell of all: the questions we pose. “How does this look?” we ask the model, as if it might blink at the screen and furrow a synthetic brow. “What do you think?” we say, offering it the dignity of preference. These questions aren’t just off-target – they’re playing darts in another pub.

They’re the linguistic equivalent of asking your dishwasher whether it enjoyed the lasagne tray. But again, this isn’t idiocy – it’s instinct. We don’t have a way of addressing an entity that talks like a person but isn’t one. So we fake it. It’s interaction theatre. You provide the line, the model cues the spotlight.

But let’s be clear: the model doesn’t “think” anything. It regurgitates plausible text based on mountains of training data—some of which, no doubt, includes humans asking equally daft questions of equally mindless systems.

Time to Grow Up (Just a Bit)

This doesn’t mean we need to abandon anthropomorphism entirely. Like most delusions, it’s functional. But we’d do well to hold it at arm’s length – like a politician’s promise or a milk carton two days past its date.

Call it anthropomorphic agnosticism: act like it’s a person, but remember it’s not. Use the language, but don’t inhale.

And maybe – just maybe – we need to evolve our language. Invent new terms, new pronouns, new ways of speaking about entities that fall somewhere between tool and companion. As we did with “cyberspace” and “ghosting,” perhaps we need words for proto-minds and quasi-selves. Something between toaster and therapist.

“If we speak to AI like it’s sentient, we’ll eventually legislate as if it is.”

Above all, we need to acknowledge that our language shapes more than just understanding – it shapes policy, emotion, and future design. If we speak to AI like it’s sentient, we’ll eventually legislate as if it is. And if we insist on treating it as an object, we may be blind to when that ceases to be accurate. Misnaming, after all, is the first sin in every myth worth reading.

The Mirror, Darkly

Ultimately, our tendency to humanise machines is less about them than it is about us – our fears, our needs, our inability to tolerate ambiguity. The AI is just a mirror: an elaborate, many-eyed, autofill mirror. And when we see a mind there, it may be ours staring back – distorted, flattened, and fed through a thousand layers of token prediction.

The tragedy, perhaps, isn’t that the machine doesn’t understand us. It’s that we’ve built something that perfectly imitates understanding – and still, somehow, we remain utterly alone in the room.

When “Advanced” Means Genocide: A Case Study in Linguistic Implosion

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This post draws on themes from my upcoming book, A Language Insufficiency Hypothesis. The transcript below is taken from a publicly available exchange, which you can view here. Consider it Exhibit A in language’s ongoing failure to bear the weight of meaning.

Transcript:

KK: Konstantin Kisin
DFW: Deborah Frances-White

KK: I’m saying we were technologically more advanced.
DFW: So you’re saying we’re superior to Australian Aboriginals?
KK: That’s quite the opposite of what I’m saying. I’m not saying we were superior, I’m saying we were technologically more advanced.
DFW: So, how is that the opposite?
KK: Superior implies a moral quality. I’m not making any moral implication. You seem to be, but what I’m saying is…
DFW: I think most people would hear it that way.
KK: No.
DFW: Again, you’re a very intelligent man. How would most people hear that?
KK: Most people would hear what I’m saying for what I’m saying, which is…
DFW: I don’t think they would.
KK: You seem to get quite heated about this, which is completely unnecessary.
DFW: Um…
KK: You think it’s necessary?
DFW: I’m a bit stunned by what you’re implying.
KK: No, you’re acting in a kind of passive aggressive way which indicates that you’re not happy…
DFW: I genuinely… I’m being 100% authentic. My visceral reaction to a white man sitting and saying to me, “And why were we able to commit genocide on them?” and then just pausing—
KK: Yes.
DFW: …is very visceral to me.
KK: Well, let’s go back. First of all, it’s interesting that you brought up my skin colour because I thought that was the exact opposite of the point you’re trying to make in the book.

Audio: NotebookLM podcast on this topic.

The Language Insufficiency Hypothesis begins with this premise: language is not merely flawed, it is structurally inadequate for mediating complex, layered realities

Dissection: Language as Battlefield

The Language Insufficiency Hypothesis begins with this premise: language is not merely flawed, it is structurally inadequate for mediating complex, layered realities – especially those laced with power, morality, and history. This transcript is not a debate. It is a linguistic trench war in which every utterance is laced with shrapnel, and each side thinks they’re defending reason.

Let’s pull a few of the shell casings from the mud.

1. Semantic Contamination: “Technologically more advanced”

KK attempts to offer a dry, neutral descriptor. DFW hears supremacist teleology. Why? Because “advanced” is culturally radioactive. It doesn’t merely denote a technical state—it connotes a ladder, with someone inevitably on the bottom rung.

When language carries historical residue, neutrality is a delusion. Words don’t just mean. They echo.

KK is making a semantic distinction. DFW hears a moral claim. Both are right. And both are talking past one another, because language is attempting to cleave affect from description, and it simply can’t.

2. Disambiguation Does Not Save You

KK’s insistence—“I’m not saying we’re superior”—is a textbook example of denotative desperation. He believes clarification will rescue intent. But as any linguist (or postcolonial theorist) will tell you: intent does not sterilise implication.

Language cannot be laundered by explanation. Once spoken, words belong to context, not intention.

KK thinks he’s holding a scalpel. DFW hears a cudgel. And here we are.

3. Phatic Collapse: “Most people would hear…”

This is where the wheels come off. KK argues from semantic specificity. DFW argues from sociolinguistic reception. It’s Saussure versus the TikTok algorithm. Neither will win.

Communication disintegrates not because anyone is lying, but because they are playing incompatible games with the same tokens.

4. Identity as Index: When the Speaker Becomes the Speech

DFW’s invocation of “a white man” is not a derailment—it’s the inevitable endpoint of a system where words no longer float free but are yoked to their utterer. This is the moment the failure of language becomes a failure of interlocution. Argument collapses into indexical entrapment.

At this point, you’re no longer debating ideas. You’re defending your right to use certain words at all.

Which brings us to the final breakdown.

5. Moral Authenticity vs Logical Precision: Unbridgeable Grammars

KK: I am making a logical distinction.
DFW: I am having a visceral reaction.

The failure isn’t moral. It isn’t historical. It’s grammatical. One is operating in a truth-function logic game. The other is reacting within a trauma-informed, socially indexed register. These are grammars that do not overlap.

Conclusion: Language Did What It Always Does—It Failed Us

If this brief and brutal dialogue proves anything, it’s this: you cannot extract meaning cleanly from words when the words themselves are sponges for history, hierarchy, and harm. The moment we ask language to do too much—to carry precision, affect, ethics, and identity—it folds in on itself.

And that, dear reader, is precisely the argument of A Language Insufficiency Hypothesis: that meaning does not reside in words, and never has. It lives in the gaps, the silences, the misfires. That’s where the truth—whatever’s left of it—might be hiding.

Follow the wreckage. That’s where the signal lives.

Sustenance: A Book About Aliens, Language, and Everything You’re Getting Wrong

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Violet aliens on a farm

So, I wrote a book and published it under Ridley Park, the pseudonym I use for fiction.

It has aliens. But don’t get excited—they’re not here to save us, probe us, or blow up the White House. They’re not even here for us.

Which is, frankly, the point.

Audio: NotebookLM podcast on this topic.

The book’s called Sustenance, and while it’s technically speculative fiction, it’s more about us than them. Or rather, it’s about how we can’t stop making everything about us—even when it shouldn’t be. Especially when it shouldn’t be.

Let’s talk themes. And yes, we’re using that word like academics do: as a smokescreen for saying uncomfortable things abstractly.

Language: The Original Scam

Language is the ultimate colonial tool. We call it communication, but it’s mostly projection. You speak. You hope. You assume. You superimpose meaning on other people like a cling film of your own ego.

Sustenance leans into this—not by showing a breakdown of communication, but by showing what happens when communication was never mutual in the first place. When the very idea of “meaning” has no purchase. It’s not about mishearing—it’s about misbeing.

Culture: A Meme You Were Born Into

Culture is the software you didn’t choose to install, and probably can’t uninstall. Most people treat it like a universal law—until they meet someone running a different OS. Cue confusion, arrogance, or violence.

The book explores what happens when cultural norms aren’t shared, and worse, aren’t even legible. Imagine trying to enforce property rights on beings who don’t understand “ownership.” It’s like trying to baptise a toaster.

Sex/Gender: You Keep Using Those Words…

One of the quiet joys of writing non-human characters is discarding human assumptions about sex and gender—and watching readers squirm.

What if sex wasn’t about power, pleasure, or identity? What if it was just a biological procedure, like cell division or pruning roses? Would you still be interested? Would you still moralise about it?

We love to believe our sex/gender constructs are inevitable. They’re not. They’re habits—often bad ones.

Consent: Your Framework Is Showing

Consent, as we use it, assumes mutual understanding, shared stakes, and equivalent agency. Remove any one of those and what’s left?

Sustenance doesn’t try to solve this—it just shows what happens when those assumptions fall apart. Spoiler: it’s not pretty, but it is honest.

Projection: The Mirror That Lies

Humans are deeply committed to anthropocentrism. If it walks like us, or flinches like us, it must be us. This is why we get so disoriented when faced with the truly alien: it won’t dance to our tune, and we’re left staring at ourselves in the funhouse mirror.

This isn’t a book about aliens.

It’s a book about the ways we refuse to see what’s not us.

Memory: The Autobiography of Your Justifications

Memory is not a record. It’s a defence attorney with a narrative license. We rewrite the past to make ourselves look consistent, or innocent, or right.

In Sustenance, memory acts less as a tether to truth and more as a sculpting tool—a way to carve guilt into something manageable. Something you can live with. Until you can’t.

In Summary: It’s Not About Them. It’s About You.

If that sounds bleak, good. It’s meant to.

But it’s also a warning: don’t get too comfortable in your own categories. They’re only universal until you meet someone who doesn’t share them.

Like I said, it’s not really about the aliens.

It’s about us.

If you enjoy fiction that’s more unsettling than escapist, more question than answer, you might be interested in Sustenance. It’s live on Kindle now for the cost of a regrettable coffee:

📘 Sustenance on Amazon US
Also available in the UK, DE, FR, ES, IT, NL, JP, BR, CA, MX, AU, and IN—because alienation is a universal language.