I’ve just published a new preprint on Zenodo: Disagreement Without Referees: Ontological Incommensurability and the Limits of Moral Adjudication 📄 https://doi.org/10.5281/zenodo.17932544
I welcome reviews, comments, and dissents.
This paper grows out of a frustration that will be familiar to anyone who spends time in moral or political argument: the sense that we keep talking past one another, mistaking deep incompatibilities for mere differences of opinion – and then moralising the failure to converge. Mostly, I’m tired of having to explain why my position isn’t subjectivist, relativist, quietist, nihilist, or whatever –ist flavour du jour. As with John Lennon, I complain about the –isms.
Audio: NotebookLM summary podcast of this essay.
The core claim is simple but unfashionable: many persistent disagreements are not epistemic at all. They are ontological. They do not arise within a shared background of assumptions about what exists, what counts as a reason, or what can ground normativity. They arise between incompatible background frameworks. When we treat such conflicts as if they were resolvable by better arguments, clearer communication, or more empathy, we misdiagnose the problem – and often make it worse.
The paper draws a sharp distinction between:
Disagreements of opinion, which presuppose a shared world and are, in principle, corrigible; and
Ontological disagreements, where what is contested is not the right answer, but what it would even mean for an answer to be right.
From there, I examine why charges like ‘relativism’, ‘subjectivism’, or ‘anything goes’ retain such rhetorical force despite their weak logical footing. The argument is not that these labels are false descriptions so much as that they function asboundary-maintenance devices within Enlightenment-inherited moral frames. They stabilise a sense of moral order by excluding positions that deny neutral adjudication.
Image: NotebookLM infographic. (This is the first infographic I’ve produced from NotebookLM. I’m not sure what I think of it, but I might try more directed versions in the future.)
I also take up the familiar worry that abandoning objective moral grounding leads to arbitrariness or nihilism. The paper rejects this caricature. Evaluation does not disappear when foundations are withdrawn; it relocates. What follows is not moral collapse but moral life without referees, where disagreement is managed through persuasion, coalition-building, institutional design, and power, rather than appeals to metaphysical authority.
Importantly, the paper is diagnostic, not prescriptive. It does not offer a new moral framework, a reconciliatory theory, or a solution to moral conflict. It argues instead for a clearer understanding of why some disagreements resist resolution, and for a more honest account of what remains once the fantasy of neutral adjudication is relinquished.
If nothing else, the hope is that recognising ontological incommensurability can temper the moral theatre that so often accompanies disagreement – replacing accusations of irrationality or bad faith with a clearer sense of what is, and is not, at stake.
This essay is also available on PhilPapers. For now, the full preprint is available on Zenodo at the link above.
As ever, comments are welcome – provided we’re clear about which world we think we’re standing in.
I just finished the writing and editorial parts of my Language Insufficiency Hypothesis. It still needs cover art and some administrative odds and ends, but I’m taking a day for a breather to share something about myself and my worldview. For this, I share my philosophical influences and how they support my core insights. For dramatic effect, I’ll even try to weight them to 100 per cent, leaving an ‘others’ bucket for the unaccounted ones.
Audio: NotebookLM summary podcast of this topic.
Obviously, this highly scientific accounting is about as useful as a Facebook survey or a fortune cookie, but it should reveal something. I have influences outside of philosophy, but I’ll limit this list at the start. The numbers don’t exactly add to 100% because there is a bit of cross-pollination, say, between Foucault and Nietzsche or Žižek and Hegel – or perhaps I’m just not good at maths. You decide.
Nietzsche (≈18)
Nietzsche is likely the uranium core. Haters and detractors like to diminish his contribution – and he didn’t play by the old rules – but they are wrong. He contributes value-creation, anti-moralism, perspectivism, the critique of ressentiment, the demolition of universals.
Nietzsche sits at the centre of the blast radius. Everything else is shrapnel. If there’s a thinker who detonated the Enlightenment’s pretensions more elegantly, I’ve not met them. He showed us that values are forged, not found; that morality is a genealogy of grievances; that certainty is the last refuge of the timid. In other words, he cleared the ground so the rest of us could get to work without tripping over Kantian furniture. But after Nietzsche’s uranium core, the next concentric ring becomes murkier.
Foucault (≈20%)
Foucault supplies the schematics. Where Nietzsche swung a hammer at the idols, Foucault identified the building codes. He mapped power as a set of subtle, everyday enchantments. He showed how ‘knowledge’ is simply what a society rewards with credibility. He is the patron saint of anyone who suspects normality is an instrument, not a neutral state of affairs. The world looks different once you see the disciplinary fingerprints on everything.
Derrida (≈10%)
Derrida gives me language as mischief. Meaning wobbles, slides, cracks; binaries betray themselves; every conceptual edifice contains its own trapdoor. Derrida isn’t a system; he’s an escape artist. And frankly, you can’t write anything about the insufficiency of language without genuflecting in his general direction.
Late Wittgenstein (≈15%)
The quiet structural pillar. If Derrida is the saboteur, Wittgenstein is the carpenter who informs you that the house was never stable anyway. Meaning-as-use, language-games, the dissolution of philosophical pseudo-problems: his later work underwrites virtually every modern suspicion about fixed categories and timeless essences. He doesn’t shout; he shrugs – and everything collapses neatly.
Rorty (≈5%)
Rorty replaces metaphysical longing with cultural pragmatism. He teaches you to stop hunting for capital-T Truth and instead track the vocabularies we actually live in. He’s the friendly voice whispering, ‘You don’t need foundations. You need better conversations’. His influence is felt mostly in the tone of my epistemic cynicism: relaxed rather than tragic. Besides, we disagree on the better conversations bit.
Geuss (≈4%)
If Rorty makes you light-footed, Geuss reminds you not to float off into abstraction entirely. He is the critic of moralism par excellence, the man who drags philosophy kicking and screaming back into politics. Geuss is the voice that asks, ‘Yes, but who benefits?’ A worldview without him would be a soufflé.
Heidegger (≈6%)
Selective extraction only. Being-in-the-world, thrownness, worldhood – the existential scaffolding. His political judgment was catastrophic, of course, but the ontological move away from detached subjectivity remains invaluable. He gives the metaphysics a certain grain.
Existentialists: Beauvoir, Sartre, Camus (≈6%)
They provide the atmospheric weather: choice, finitude, absurdity, revolt, the sheer mess of human freedom. They don’t define the system; they give it blood pressure. Besides, I met them before I switched to Team Nietzsche-Foucault.
Žižek, Latour, Baudrillard (≈2% combined)
These three are my licensed provocateurs.
Žižek exposes how ideology infiltrates desire.
Latour dismantles the Nature/Society binary with glee.
Baudrillard whispers that representation ate reality while we were looking at our phones.
They’re trickster figures, not architects.
Hume, Putnam, Dennett, and the Ancillaries (≈1% combined)
These are the seasonings.
Hume is the Scottish acid bath under every epistemic claim.
Putnam gives internal realism its analytic passport.
Dennett offers mechanistic metaphors you can steal even when you disagree.
Kant and Hegel hover like compulsory ghosts.
Rawls remains decorative parsley: included for completeness, consumed by none.
The Others Bucket (≈5%)
The unallocated mass: writers, anthropologists, theorists, stray thinkers you absorb without noticing. The ‘residuals’ category for the philosophical inventory – the bit fortune cookies never warn you about.
Enfin
Obviously, these ratios are more for humour than substance, but these are the thinkers I return to — the ones whose fingerprints I keep discovering on my own pages, no matter how many years or detours intervene.
Perhaps more revealing are those who didn’t make the guest list. Socrates, Plato, and Aristotle remain outside, smoking in the cold. The Stoics, Marcus Aurelius and his well-meaning self-help descendants, also failed to RSVP. In truth, I admire the posture but have little patience for the consolations – especially when they become the emotional training wheels of neoliberalism.
And then, of course, the Enlightenment patriarchs: Hobbes, Locke, Montesquieu and the rest of the constitutional furniture. I acknowledge their historical necessity the way one acknowledges plumbing – grateful it exists, uninterested in climbing inside the pipes. Rousseau, admittedly, I tolerate with something approaching affection, but only because he never pretended to be tidy.
I forgot Descartes, Voltaire, and Pascal, but it’s too late to scroll back and adjust the ledger. Consider them rounding errors – casualties of the margins, lost to the tyranny of percentages.
If anyone mentions another one – Spinoza comes to mind – I’ll try to figure out where they fit in my pantheon. Were I to render this tomorrow, the results may vary.
“Truths are illusions which we have forgotten are illusions.” — Nietzsche
Declaring the Problem
Most people say truth as if it were oxygen – obvious, necessary, self-evident. I don’t buy it.
Nietzsche was blunt: truths are illusions. My quarrel is only with how often we forget that they’re illusions.
Most people say truth as if it were oxygen – obvious, necessary, self-evident. I don’t buy it.
My own stance is unapologetically non-cognitivist. I don’t believe in objective Truth with a capital T. At best, I see truth as archetypal – a symbol humans invoke when they need to rally, persuade, or stabilise. I am, if you want labels, an emotivist and a prescriptivist: I’m drawn to problems because they move me, and I argue about them because I want others to share my orientation. Truth, in this sense, is not discovered; it is performed.
The Illusion of Asymptotic Progress
The standard story is comforting: over time, science marches closer and closer to the truth. Each new experiment, each new refinement, nudges us toward Reality, like a curve bending ever nearer to its asymptote.
Chart 1: The bedtime story of science: always closer, never arriving.
This picture flatters us, but it’s built on sand.
Problem One: We have no idea how close or far we are from “Reality” on the Y-axis. Are we brushing against it, or still a light-year away? There’s no ruler that lets us measure our distance.
Problem Two: We can’t even guarantee that our revisions move us toward rather than away from it. Think of Newton and Einstein. For centuries, Newton’s physics was treated as a triumph of correspondence—until relativity reframed it as local, limited, provisional. What once looked like a step forward can later be revealed as a cul-de-sac. Our curve may bend back on itself.
Use Case: Newton, Einstein, and Gravity Take gravity. For centuries, Newton’s laws were treated as if they had brought us into near-contact with Reality™—so precise, so predictive, they had to be true. Then Einstein arrives, reframes gravity not as a force but as the curvature of space-time, and suddenly Newton’s truths are parochial, a local approximation. We applauded this as progress, as if our asymptote had drawn tighter to Reality. But even Einstein leaves us with a black box: we don’t actually know what gravity is, only how to calculate its effects. Tomorrow another paradigm may displace relativity, and once again we’ll dutifully rebrand it as “closer to truth.” Progress or rhetorical re-baptism? The graph doesn’t tell us.
Chart 2: The comforting myth of correspondence: scientific inquiry creeping ever closer to Reality™, though we can’t measure the distance—or even be sure the curve bends in the right direction.
Thomas Kuhn was blunt about this: what we call “progress” is less about convergence and more about paradigm shifts, a wholesale change in the rules of the game. The Earth does not move smoothly closer to Truth; it lurches from one orthodoxy to another, each claiming victory. Progress, in practice, is rhetorical re-baptism.
Most defenders of the asymptotic story assume that even if progress is slow, it’s always incremental, always edging us closer. But history suggests otherwise. Paradigm shifts don’t just move the line higher; they redraw the entire curve. What once looked like the final step toward truth may later be recast as an error, a cul-de-sac, or even a regression. Newton gave way to Einstein; Einstein may yet give way to something that renders relativity quaint. From inside the present, every orthodoxy feels like progress. From outside, it looks more like a lurch, a stumble, and a reset.
Chart 3: The paradigm-gap view: what feels like progress may later look like regression. History suggests lurches, not lines, what we call progress today is tomorrow’s detour..
If paradigm shifts can redraw the entire map of what counts as truth, then it makes sense to ask what exactly we mean when we invoke the word at all. Is truth a mirror of reality? A matter of internal coherence? Whatever works? Or just a linguistic convenience? Philosophy has produced a whole menu of truth theories, each with its own promises and pitfalls—and each vulnerable to the same problems of rhetoric, context, and shifting meanings.
The Many Flavours of Truth
Philosophers never tire of bottling “truth” in new vintages. The catalogue runs long: correspondence, coherence, pragmatic, deflationary, redundancy. Each is presented as the final refinement, the one true formulation of Truth, though each amounts to little more than a rhetorical strategy.
Correspondence theory: Truth is what matches reality. Problem: we can never measure distance from “Reality™” itself, only from our models.
Coherence theory: Truth is what fits consistently within a web of beliefs. Problem: many mutually incompatible webs can be internally consistent.
Pragmatic theory: Truth is what works. Problem: “works” for whom, under what ends? Functionality is always perspectival.
Deflationary / Minimalist: Saying “it’s true that…” adds nothing beyond the statement itself. Problem: Useful for logic, empty for lived disputes.
Redundancy / Performative: “It is true that…” adds rhetorical force, not new content. Problem: truth reduced to linguistic habit.
And the common fallback: facts vs. truths. We imagine facts as hard little pebbles anyone can pick up. Hastings was in 1066; water boils at 100°C at sea level. But these “facts” are just truths that have been successfully frozen and institutionalised. No less rhetorical, only more stable.
So truth isn’t one thing – it’s a menu. And notice: all these flavours share the same problem. They only work within language-games, frameworks, or communities of agreement. None of them delivers unmediated access to Reality™.
Truth turns out not to be a flavour but an ice cream parlour – lots of cones, no exit.
Multiplicity of Models
Even if correspondence weren’t troubled, it collapses under the weight of underdetermination. Quine and Duhem pointed out that any body of evidence can support multiple competing theories.
Chart 4: orthodox vs. heterodox curves, each hugging “reality” differently
Hilary Putnam pushed it further with his model-theoretic argument: infinitely many models could map onto the same set of truths. Which one is “real”? There is no privileged mapping.
Conclusion: correspondence is undercut before it begins. Truth isn’t a straight line toward Reality; it’s a sprawl of models, each rhetorically entrenched.
Truth as Rhetoric and Power
This is where Orwell was right: “War is Peace, Freedom is Slavery, Ignorance is Strength.”
Image: INGSOC logo
Truth, in practice, is what rhetoric persuades.
Michel Foucault stripped off the mask: truth is not about correspondence but about power/knowledge. What counts as truth is whatever the prevailing regime of discourse allows.
We’ve lived it:
“The economy is strong”, while people can’t afford rent.
“AI will save us”, while it mainly writes clickbait.
“The science is settled” until the next paper unsettles it.
These aren’t neutral observations; they’re rhetorical victories.
Truth as Community Practice
Chart 5: Margin of error bands
Even when rhetoric convinces, it convinces in-groups. One group converges on a shared perception, another on its opposite. Flat Earth and Round Earth are both communities of “truth.” Each has error margins, each has believers, each perceives itself as edging toward reality.
Wittgenstein reminds us: truth is a language game. Rorty sharpens it: truth is what our peers let us get away with saying.
So truth is plural, situated, and always contested.
Evolutionary and Cognitive Scaffolding
Step back, and truth looks even less eternal and more provisional.
We spread claims because they move us (emotivism) and because we urge others to join (prescriptivism). Nietzsche was savage about it: truth is just a herd virtue, a survival trick.
Cognitive science agrees, if in a different language: perception is predictive guesswork, riddled with biases, illusions, and shortcuts. Our minds don’t mirror reality; they generate useful fictions.
Diagram: Perception as a lossy interface: Reality™ filtered through senses, cognition, language, and finally rhetoric – signal loss at every stage.
Archetypal Truth (Positive Proposal)
So where does that leave us? Not with despair, but with clarity.
Truth is best understood as archetypal – a construct humans rally around. It isn’t discovered; it is invoked. Its force comes not from correspondence but from resonance.
Here, my own Language Insufficiency Hypothesis bites hardest: all our truth-talk is approximation. Every statement is lossy compression, every claim filtered through insufficient words. We can get close enough for consensus, but never close enough for Reality.
Truth is rhetorical, communal, functional. Not absolute.
The Four Pillars (Manifesto Form)
Archetypal – truth is a symbolic placeholder, not objective reality.
Asymptotic – we gesture toward reality but never arrive.
Rhetorical – what counts as truth is what persuades.
Linguistically Insufficient – language guarantees slippage and error.
Closing
Nietzsche warned, Rorty echoed: stop fetishising Truth. Start interrogating the stories we tell in its name.
Every “truth” we now applaud may be tomorrow’s embarrassment. The only honest stance is vigilance – not over whether we’ve captured Reality™, but over who gets to decide what is called true, and why.
Truth has never been a mirror. It’s a mask. The only question worth asking is: who’s wearing it?
This isn’t a political post. It’s about language, the insufficiency of it, and the games we play when pretending words carry more weight than they do.
Luigi Mangione is the man accused of killing UnitedHealthcare CEO Brian Thompson. After his arrest, prosecutors stacked the usual charges – murder, firearms, assorted legal bric-a-brac – then added the cherry on top: domestic terrorism.
Audio: NotebookLM podcast on this topic.
Recently, a pretrial judge cut the cherry loose.
Murder, yes. Terrorism, no. Not because murder is less grotesque, but because the statutory definition won’t stretch that far without breaking.
NEW YORK, Sept 16 (Reuters) – A New York state judge dismissed on Tuesday two terrorism-related counts against Luigi Mangione over the December 2024 killing of health insurance executive Brian Thompson, though the 27-year-old remains charged with second-degree murder and eight other criminal counts in the case.
“There was no evidence presented of a desire to terrorize the public, inspire widespread fear, engage in a broader campaign of violence, or to conspire with organized terrorist groups,” Judge Gregory Carro found in a 12-page written decision (pdf). “Here, the crime – the heinous, but targeted and discrete killing of one person – is very different from the examples of terrorism set forth in the statute.” (source)
The prosecution insisted the label fit. The judge disagreed. Cue outrage, applause, and confusion. The crime is still horrific, but suddenly the word “terrorist” is off-limits.
The Elasticity of Terror
How can two educated parties look at the same set of facts and come to opposite conclusions? Because “terrorism” isn’t a Platonic form. It’s an elastic linguistic category. The prosecutor drags it out because “terrorist” is a magical word in American law: it inflates an already ugly act into a civilisation-level threat, unlocks harsher penalties, and lets politicians posture about national security.
The judge, however, reminded everyone that a bullet in Manhattan does not equal al-Qaeda. Murder, yes. Terrorism, no. Not because murder is less grotesque, but because the statutory definition won’t stretch that far without breaking.
Language Games, Legal Hierarchies
This is where it gets trickier. The judge isn’t merely “pulling rank”—though rank does matter. American jurisprudence is hierarchical: trial judges hand down rulings, appellate judges review them, and nine robed partisans in Washington can one day rewrite the whole script. On paper, these tiers are meant to iron out ambiguity. In practice, they multiply it.
Five minds say ‘constitutional,’ four say ‘unconstitutional,’ and the one-vote margin becomes binding law for 330 million people. That’s not truth; it’s hierarchy dressed in robes.
Even co-equal judges, reading the same facts, can diverge wildly. Split decisions at the Supreme Court prove the point: five minds say “constitutional,” four say “unconstitutional,” and the one-vote margin becomes binding law for 330 million people. That’s not the discovery of truth; it’s the triumph of one language game over another, enforced by hierarchy.
The Insufficiency Laid Bare
So we return to Mangioni. He has been charged with murder – the second degree flavour; that much is uncontested. But is he a “terrorist”? The prosecution said yes, the judge said no, and another judge, higher up or sitting elsewhere, might well say yes again. Each claim is defensible. Each is motivated by language, by politics, and by the institutional pressures of the bench.
And that’s the point. Language doesn’t tether itself to reality; it choreographs our endless arguments about reality. The law tries to tame it with hierarchies and definitions, but the seams always show. Mangioni is a murderer. Whether he is a terrorist depends less on his actions than on which interpretive dance is winning in the courtroom that day.
Everyone knows the line: cogito ergo sum. Descartes’ great party trick. A man alone in his study, fretting about demons, announces that because he’s doubting, he must exist. Ta-da! Curtain call. Except, of course, it’s less of a revelation than a conjuring trick: he pulls an I out of a hat that was never proved to be there in the first place. Thinking is happening, indeed – but who invited the “thinker”?
Video: David Guignion talks about Descartes’ Cogito.
And let’s not forget the dramatis personae Descartes smuggles in for atmosphere. A malicious demon, a benevolent God, both necessary props to justify his paranoia and his certainty. Philosophy as melodrama: cue organ music, lightning strike.
Audio: NotebookLM podcast on this topic.
Enter the Critics
Spinoza rolls his eyes. Doubt isn’t some heroic starting point, he says – it’s just ignorance, a lack of adequate ideas. To elevate doubt into method is like treating vertigo as a navigational tool. Error isn’t demonic trickery; it’s our own confusion.
Kant arrives next, shaking his head. Descartes thinks he’s proven a substantial “I,” but all he’s actually shown is the form of subjectivity – the empty requirement that experiences hang together. The “I think” is a necessary placeholder, not a discovery. A grammatical “you are here” arrow, not a metaphysical treasure chest.
Hegel, of course, can’t resist upping the disdain. Descartes’ I is an empty abstraction, a hollow balloon floating above reality. The self isn’t given in some solitary moment of doubt; it emerges through process – social, historical, dialectical. The cogito is the philosophical equivalent of a selfie: lots of certainty, zero depth.
The Insufficiency Twist
And yet, maybe all of them are still dancing to the same fiddler. Because here’s the real suspicion: what if the whole problem is a trick of language? English, with its bossy Indo-European grammar, refuses to let verbs stand alone. “Thinking” must have a “thinker,” “seeing” a “seer.” Grammar insists on a subject; ontology obediently provides one.
Other languages don’t always play this game. Sanskrit or Pali can shrug and say simply, “it is seen.” Japanese leaves subjects implied, floating like ghosts. Some Indigenous languages describe perception as relational events – “seeing-with-the-tree occurs” – no heroic subject required. So perhaps the real villain here isn’t Descartes or even metaphysics, but syntax itself, conscripting us into a subject-shaped theatre.
Now, I don’t want to come off like a one-trick pony, forever waving the flag of “language insufficiency” like some tired philosopher’s catchphrase. But we should be suspicious when our limited grammar keeps painting us into corners, insisting on perceivers where maybe there are only perceptions, conjuring selves because our verbs can’t tolerate dangling.
Curtain Call
So in the end, Descartes’ famous “I” might be no more than a grammatical fiction, a casting error in the great play of philosophy. The cogito isn’t the foundation of modern thought; it’s the world’s most influential typo.
A Sequel to “The Disorder of Saying No” and a Companion to “When ‘Advanced’ Means Genocide”
In my previous post, The Disorder of Saying No, I explored the way resistance to authority is pathologised, particularly when that authority is cloaked in benevolence and armed with diagnostic manuals. When one refuses — gently, thoughtfully, or with a sharp polemic — one is no longer principled. One is “difficult.” Or in my case, oppositional.
Audio: NotebookLM podcast on this topic.
So when I had the gall to call out Bill Maher for his recent linguistic stunt — declaring that a woman is simply “a person who menstruates” — I thought I was doing the rational thing: pointing out a classic bit of reductionist nonsense masquerading as clarity. Maher, after all, was not doing biology. He was playing lexicographer-in-chief, defining a term with centuries of philosophical, sociological, and political baggage as though it were a checkbox on a medical form.
I said as much: that he was abusing his platform, presenting himself as the sole arbiter of the English language, and that his little performance was less about clarity and more about controlling the terms of discourse.
My friend, a post-menopausal woman herself, responded not by engaging the argument, but by insinuating — as others have — that I was simply being contrary. Oppositional. Difficult. Again. (She was clearly moved by When “Advanced” Means Genocide, but may have missed the point.)
So let’s unpack this — not to win the debate, but to show what the debate actually is.
This Isn’t About Biology — It’s About Boundary Maintenance
Maher’s statement wasn’t intended to clarify. It was intended to exclude. It wasn’t some linguistic slip; it was a rhetorical scalpel — one used not to analyse, but to amputate.
And the applause from some cisgender women — particularly those who’ve “graduated” from menstruation — reveals the heart of the matter: it’s not about reproductive biology. It’s about controlling who gets to claim the termwoman.
it only works if you pretend the world is simpler than it is.
Let’s steelman the argument, just for the sport of it:
Menstruation is a symbolic threshold. Even if one no longer menstruates, having done so places you irrevocably within the category of woman. It’s not about exclusion; it’s about grounding identity in material experience.
Fine. But now let’s ask:
What about women who’ve never menstruated?
What about intersex people?
What about trans women?
What about cultures with radically different markers of womanhood?
You see, it only works if you pretend the world is simpler than it is.
The Language Insufficiency Hypothesis: Applied
This is precisely where the Language Insufficiency Hypothesis earns its keep.
The word woman is not a locked vault. It is a floating signifier, to borrow from Barthes — a term whose meaning is perpetually re-negotiated in use. There is no singular essence to the word. It is not rooted in biology, nor in social role, nor in performance. It is a hybrid, historically contingent construct — and the moment you try to fix its meaning, it slips sideways like a greased Wittgensteinian beetle.
“Meaning is use,” says Wittgenstein, and this is what frightens people.
If woman is defined by use and not by rule, then anyone might claim it. And suddenly, the club is no longer exclusive.
That’s the threat Maher and his defenders are really reacting to. Not trans women. Not intersex people. Not language activists or queer theorists.
The threat is ambiguity.
What They Want: A World That Can Be Named
The push for rigid definitions — for menstruation as membership — is a plea for a world that can be named and known. A world where words are secure, stable, and final. Where meaning doesn’t leak.
But language doesn’t offer that comfort.
It never did.
And when that linguistic instability gets too close to something personal, like gender identity, or the foundation of one’s own sense of self, the defensive response is to fortify the language, as though building walls around a collapsing church.
Maher’s defenders aren’t making scientific arguments. They’re waging semantic warfare. If they can hold the definition, they can win the cultural narrative. They can hold the gates to Womanhood and keep the undesirables out.
That’s the fantasy.
But language doesn’t play along.
Conclusion: Words Will Not Save You — but They Might Soothe the Dead
In the end, Maher’s definition is not merely incorrect. It is insufficient. It cannot accommodate the complexity of lived experience and cannot sustain the illusion of clarity for long.
They are defending nostalgia.
And those who cling to it — friend or stranger, progressive, or conservative — are not defending biology. They are defending nostalgia. Specifically, a pathological nostalgia for a world that no longer exists, and arguably never did: a world where gender roles were static, language was absolute, and womanhood was neatly circumscribed by bodily functions and suburban etiquette.
Ozzy and Harriet loom large here — not as individuals but as archetypes. Icons of a mid-century dream in which everyone knew their place, and deviation was something to be corrected, not celebrated. My friend, of that generation, clings to this fantasy not out of malice but out of a desperate yearning for order. The idea that woman could mean many things, and mean them differently across contexts, is not liberating to her — it’s destabilising.
But that world is gone. And no amount of menstruation-based gatekeeping will restore it.
The Real Scourge Is Ambiguity
Maher’s tantrum wasn’t about truth. It was about fear — fear of linguistic drift, of gender flux, of a world in which meaning no longer obeys. The desire to fix the definition of “woman” is not a biological impulse. It’s a theological one.
And theology, like nostalgia, often makes terrible policy.
And theology, like nostalgia, often makes terrible policy.
This is why your Language Insufficiency Hypothesis matters. Because it reminds us that language does not stabilise reality — it masks its instability. The attempt to define “woman” once and for all is not just futile — it’s an act of violence against difference, a linguistic colonisation of lived experience.
So Let Them Rest
Ozzy and Harriet are dead. Let them rest. Let their picket fence moulder. Let their signage decay.
The world has moved on. The language is shifting beneath your feet. And no amount of retroactive gatekeeping can halt that tremor.
The club is burning. And the only thing left to save is honesty.
I’m edging ever closer to finishing my book on the Language Insufficiency Hypothesis. It’s now in its third pass—a mostly subtractive process of streamlining, consolidating, and hacking away at redundancies. The front matter, of course, demands just as much attention, starting with the Preface.
The opening anecdote—a true yet apocryphal gem—dates back to 2018, which is evidence of just how long I’ve been chewing on this idea. It involves a divorce court judge, a dose of linguistic ambiguity, and my ongoing scepticism about the utility of language in complex, interpretative domains.
At the time, my ex-wife’s lawyer was petitioning the court to restrict me from spending any money outside our marriage. This included a demand for recompense for any funds already spent. I was asked, point-blank: Had I given another woman a gift?
Seeking clarity, I asked the judge to define gift. The response was less than amused—a glare, a sneer, but no definition. Left to my own devices, I answered no, relying on my personal definition: something given with no expectation of return or favour. My reasoning, then as now, stemmed from a deep mistrust of altruism.
The court, however, didn’t share my philosophical detours. The injunction came down: I was not to spend any money outside the marital arrangement. Straightforward? Hardly. At the time, I was also in a rock band and often brought meals for the group. Was buying Chipotle for the band now prohibited?
The judge’s response dripped with disdain. Of course, that wasn’t the intent, they said, but the language of the injunction was deliberately broad—ambiguous enough to cover whatever they deemed inappropriate. The phrase don’t spend money on romantic interests would have sufficed, but clarity seemed to be a liability. Instead, the court opted for what I call the Justice Stewart Doctrine of Legal Ambiguity: I know it when I see it.
Unsurprisingly, the marriage ended. My ex-wife and I, however, remain close; our separation in 2018 was final, but our friendship persists. Discussing my book recently, I mentioned this story, and she told me something new: her lawyer had confided that the judge disliked me, finding me smug.
This little revelation cemented something I’d already suspected: power relations, in the Foucauldian sense, pervade even our most banal disputes. It’s why Foucault makes a cameo in the book alongside Nietzsche, Wittgenstein, Saussure, Derrida, Borges, and even Gödel.
This anecdote is just one straw on the poor camel’s back of my linguistic grievances, a life filled with moments where language’s insufficiency has revealed itself. And yet, I found few others voicing my position. Hence, a book.
I aim to self-publish in early 2025—get it off my chest and into the world. Maybe then I can stop wittering on about it. Or, more likely, I won’t.
I’ve written a lot on the insufficiency of language, and it’s not even an original idea. Language, our primary tool for sharing thoughts and ideas, harbours a fundamental flaw: it’s inherently insufficient for conveying precise meaning. While this observation isn’t novel, recent developments in artificial intelligence provide us with new ways to illuminate and examine this limitation. Through a progression from simple geometry to complex abstractions, we can explore how language both serves and fails us in different contexts.
The Simple Made Complex
Consider what appears to be a straightforward instruction: Draw a 1-millimetre square in the centre of an A4 sheet of paper using an HB pencil and a ruler. Despite the mathematical precision of these specifications, two people following these exact instructions would likely produce different results. The variables are numerous: ruler calibration, pencil sharpness, line thickness, paper texture, applied pressure, interpretation of “centre,” and even ambient conditions affecting the paper.
This example reveals a paradox: the more precisely we attempt to specify requirements, the more variables we introduce, creating additional points of potential divergence. Even in mathematics and formal logic—languages specifically designed to eliminate ambiguity—we cannot escape this fundamental problem.
Precision vs Accuracy: A Useful Lens
The scientific distinction between precision and accuracy provides a valuable framework for understanding these limitations. In measurement, precision refers to the consistency of results (how close repeated measurements are to each other), while accuracy describes how close these measurements are to the true value.
Returning to our square example:
Precision: Two people might consistently reproduce their own squares with exact dimensions
Accuracy: Yet neither might capture the “true” square we intended to convey
As we move from geometric shapes to natural objects, this distinction becomes even more revealing. Consider a maple tree in autumn. We might precisely convey certain categorical aspects (“maple,” “autumn colours”), but accurately describing the exact arrangement of branches and leaves becomes increasingly difficult.
The Target of Meaning: Precision vs. Accuracy in Communication
To understand language’s limitations, we can borrow an illuminating concept from the world of measurement: the distinction between precision and accuracy. Imagine a target with a bullseye, where the bullseye represents perfect communication of meaning. Just as archers might hit different parts of a target, our attempts at communication can vary in both precision and accuracy.
Consider four scenarios:
Low Precision, Low Accuracy When describing our autumn maple tree, we might say “it’s a big tree with colourful leaves.” This description is neither precise (it could apply to many trees) nor accurate (it misses the specific characteristics that make our maple unique). The communication scatters widely and misses the mark entirely.
High Precision, Low Accuracy We might describe the tree as “a 47-foot tall maple with exactly 23,487 leaves displaying RGB color values of #FF4500.” This description is precisely specific but entirely misses the meaningful essence of the tree we’re trying to describe. Like arrows clustering tightly in the wrong spot, we’re consistently missing the point.
Low Precision, High Accuracy “It’s sort of spreading out, you know, with those typical maple leaves turning reddish-orange, kind of graceful looking.” While imprecise, this description might actually capture something true about the tree’s essence. The arrows scatter, but their centre mass hits the target.
High Precision, High Accuracy This ideal state is rarely achievable in complex communication. Even in our simple geometric example of drawing a 1mm square, achieving both precise specifications and accurate execution proves challenging. With natural objects and abstract concepts, this challenge compounds exponentially.
The Communication Paradox
This framework reveals a crucial paradox in language: often, our attempts to increase precision (by adding more specific details) can actually decrease accuracy (by moving us further from the essential meaning we’re trying to convey). Consider legal documents: their high precision often comes at the cost of accurately conveying meaning to most readers.
Implications for AI Communication
This precision-accuracy framework helps explain why AI systems like our Midjourney experiment show asymptotic behaviour. The system might achieve high precision (consistently generating similar images based on descriptions) while struggling with accuracy (matching the original intended image), or vice versa. The gap between human intention and machine interpretation often manifests as a trade-off between these two qualities.
Our challenge, both in human-to-human and human-to-AI communication, isn’t to achieve perfect precision and accuracy—a likely impossible goal—but to find the optimal balance for each context. Sometimes, like in poetry, low precision might better serve accurate meaning. In other contexts, like technical specifications, high precision becomes crucial despite potential sacrifices in broader accuracy.
The Power and Limits of Distinction
This leads us to a crucial insight from Ferdinand de Saussure’s semiotics about the relationship between signifier (the word) and signified (the concept or object). Language proves remarkably effective when its primary task is distinction among a limited set. In a garden containing three trees—a pine, a maple, and a willow—asking someone to “point to the pine” will likely succeed. The shared understanding of these categorical distinctions allows for reliable communication.
However, this effectiveness dramatically diminishes when we move from distinction to description. In a forest of a thousand pines, describing one specific tree becomes nearly impossible. Each additional descriptive detail (“the tall one with a bent branch pointing east”) paradoxically makes precise identification both more specific and less likely to succeed.
An AI Experiment in Description
To explore this phenomenon systematically, I conducted an experiment using Midjourney 6.1, a state-of-the-art image generation AI. The methodology was simple:
Generate an initial image
Describe the generated image in words
Use that description to generate a new image
Repeat the process multiple times
Attempt to refine the description to close the gap
Continue iterations
The results support an asymptotic hypothesis: while subsequent iterations might approach the original image, they never fully converge. This isn’t merely a limitation of the AI system but rather a demonstration of language’s fundamental insufficiency.
A cute woman and her dog stand next to a tree
One can already analyse this for improvements, but let’s parse it together.
a cute woman
With this, we know we are referencing a woman, a female of the human species. There are billions of women in the world. What does she look like? What colour, height, ethnicity, and phenotypical attributes does she embody?
We also know she’s cute – whatever that means to the sender and receiver of these instructions.
I used an indefinite article, a, so there is one cute woman. Is she alone, or is she one from a group?
It should be obvious that we could provide more adjectives (and perhaps adjectives) to better convey our subject. We’ll get there, but let’s move on.
and
We’ve got a conjunction here. Let’s see what it connects to.
her dog
She’s with a dog. In fact, it’s her dog. This possession may not be conveyable or differentiable from some arbitrary dog, but what type of dog is it? Is it large or small? What colour coat? Is it groomed? Is it on a leash? Let’s continue.
stand
It seems that the verb stand refers to the woman, but is the dog also standing, or is she holding it? More words could qualify this statement better.
next to a tree
A tree is referenced. Similar questions arise regarding this tree. At a minimum, there is one tree or some variety. She and her dog are next to it. Is she on the right or left of it?
We think we can refine our statements with precision and accuracy, but can we? Might we just settle for “close enough”?
Let’s see how AI interpreted this statement.
Image: Eight Midjourney renders from the prompt: A cute woman and her dog stand next to a tree. I’ll choose one of these as my source image.
Let’s deconstruct the eight renders above. Compositionally, we can see that each image contains a woman, a dog, and a tree. Do any of these match what you had in mind? First, let’s see how Midjourney describes the first image.
In a bout of hypocrisy, Midjourney refused to /DESCRIBE the image it just generated.
Last Midjourney description for now.
Let’s cycle through them in turn.
A woman is standing to the left of an old-growth tree – twice identified as an oak tree. She’s wearing faded blue jeans and a loose light-coloured T-shirt. She’s got medium-length (maybe) red-brown hair in a small ponytail. A dog – her black and white dog identified as a pitbull, an American Foxhound, and an American Bulldog – is also standing on his hind legs. I won’t even discuss the implied intent projected on the animal – happy, playful, wants attention… In two of the descriptions, she’s said to be training it. They appear to be in a somewhat residential area given the automobiles in the background. We see descriptions of season, time of day, lighting, angle, quality,
A woman is standing to the right of an old-growth tree. She’s wearing short summer attire. Her dog is perched on the tree.
An older woman and her dog closer up.
A read view of both a woman and her dog near an oak tree.
As it turned out, I wasn’t thrilled with any of these images, so I rendered a different one. Its description follows.
The consensus is that ‘a beautiful girl in a white dress and black boots stands next to a tree’ with a Jack Russell Terrier dog. I see birch trees and snow. It’s overcast. Let’s spend some time trying to reproduce it. To start, I’m consolidating the above descriptions. I notice some elements are missing, but we’ll add them as we try to triangulate to the original image.
A beautiful girl in a white dress and black boots stands next to a tree in a winter forest with birch trees. A Jack Russell Terrier dog is nearby, and the weather is cloudy. The photo has a cinematic style. --ar 128:71
This is pretty far off the mark. We need to account for the overall setting and composition, relative positioning, clothing, hair, camera, perspective – even lighting and film emulsion.
Let’s see how we can refine it with some adjectives. Before this, I asked Anthropic’s Claude 3.5 to describe the image. Perhaps we’ll get more details.
An atmospheric winter photograph was taken in what appears to be a birch and pine forest. The ground is partially covered with snow, creating a patchy pattern of white snow and brown leaves or soil. In the image, there's a person wearing winter attire consisting of a white knit turtleneck sweater, a white skirt, dark knee-high socks, and grey lace-up boots. They're standing against a large tree trunk with their arms crossed. Next to them is a Jack Russell Terrier mix dog with distinctive brown and white colouring. The dog appears to be well-behaved, sitting attentively beside the tree. The composition is quite striking, with the massive dark tree trunk serving as a central focal point against the misty, winter forest background. The white clothing of the person creates a visual echo with the white bark of birch trees visible in the background, as well as with the patches of snow on the ground. The overall mood of the photo is somewhat moody and contemplative, enhanced by what appears to be overcast lighting and the misty quality of the forest in the background. The colour palette is largely monochromatic, dominated by whites, greys, and browns, which adds to the winter atmosphere of the scene.
We don’t seem to be moving in a good direction. Let’s modify the initial prompt.
A beautiful girl in a white dress and tall laced black boots stands facing the camera to the right of large oak tree centred in the foreground of a winter forest with birch trees in the background. To the left of the tree is a Jack Russell Terrier dog looking at the camera, and the weather is cloudy. The photo has a cinematic style. --ar 128:71
I’ll allow the results to speak for themselves. Let’s see if we can’t get her out of the wedding gown and into a white jumper and skirt. I’ll bold the amends.
A beautiful girl in a white jumper and skirt wearing black leggings and tall laced black boots stands facing the camera to the right of large oak tree centred in the foreground of a winter forest with birch trees in the background. To the left of the tree is a Jack Russell Terrier dog looking at the camera, and the weather is cloudy. The photo has a cinematic style. --ar 128:71
s
A beautiful young woman with long brown hair pulled to the side of her face in a white jumper and white skirt wearing black leggings under tall laced black boots stands facing the camera to the right of large oak tree centred in the foreground of a winter forest with birch trees in the background. Patchy snow is on the ground. To the left of the tree is a Jack Russell Terrier dog looking at the camera, and the weather is overcast. The photo has a cinematic style. --ar 128:71
What gives?
I think my point has been reinforced. I’m getting nowhere fast. Let’s give it one more go and see where we end up. I’ve not got a good feeling about this.
A single large oak tree centred in the foreground of a winter forest with birch trees in the background. Patches of snow is on the ground. To the right of the oak tree stands a beautiful young woman with long brown hair pulled to the side of her face in a white jumper and white skirt wearing black boots over tall laced black boots. She stands facing the camera. To the left of the tree is a Jack Russell Terrier dog looking at the camera, and the weather is overcast. The photo has a cinematic style. --ar 128:71
With this last one, I re-uploaded the original render along with this text prompt. Notice that the girl now looks the same and the scene (mostly) appears to be in the same location, but there are still challenges.
After several more divergent attempts, I decided to focus on one element – the girl.
As I regard the image, I’m thinking of a police sketch artist. They get sort of close, don’t they? They’re experts. I’m not confident that I even have the vocabulary to convey accurately what I see. How do I describe her jumper? Is that a turtleneck or a high collar? It appears to be knit. Is is wool or some blend? does that matter for an image? Does this pleated skirt have a particular name or shade of white? It looks as though she’s wearing black leggings – perhaps polyester. And those boots – how to describe them. I’m rerunning just the image above through a describe function to see if I can get any closer.
These descriptions are particularly interesting and telling. First, I’ll point out that AI attempts to identify the subject. I couldn’t find Noa Levin by a Google search, so I’m not sure how prominent she might be if she even exists at all in this capacity. More interesting still, the AI has placed her in a scenario where the pose was taken after a match. Evidently, this image reflects the style of photographer Guy Bourdin. Perhaps the jumper mystery is solved. It identified a turtleneck. I’ll ignore the tree and see if I can capture her with an amalgamation of these descriptions. Let’s see where this goes.
A photo-realistic portrait of Israeli female soccer player Noa Levin wearing a white turtleneck sweater, arms crossed, black boots, and a short skirt, with long brown hair, standing near a tree in a winter park. The image captured a full-length shot taken in a studio setting, using a Canon EOS R5 camera with a Canon L-series 80mm f/2 lens. The image has been professionally color-graded, with soft shadows, low contrast, and a clean, sharp focus. --ar 9:16
Close-ish. Let’s zoom in to get better descriptions of various elements starting with her face and hair.
Now, she’s a sad and angry Russian woman with (very) pale skin; large, sad, grey eyes; long, straight brown hair. Filmed in the style of either David LaChapelle or Alini Aenami (apparently misspelt from Alena Aenami). One thinks it was a SnapChat post. I was focusing on her face and hair, but it notices her wearing a white (oversized yet form-fitting) jumper sweater and crossed arms .
I’ll drop the angry bit – and then the sad.
Stick a fork in it. I’m done. Perhaps it’s not that language is insufficient; it that my language skills are insufficient. If you can get closer to the original image, please forward the image, the prompt, and the seed, so I can post it.
The Complexity Gradient
A clear pattern emerges when we examine how language performs across different levels of complexity:
Categorical Distinction (High Success)
Identifying shapes among limited options
Distinguishing between tree species
Basic color categorization
Simple Description (Moderate Success)
Basic geometric specifications
General object characteristics
Broad emotional states
Complex Description (Low Success)
Specific natural objects
Precise emotional experiences
Unique instances within categories
Abstract Concepts (Lowest Success)
Philosophical ideas
Personal experiences
Qualia
As we move up this complexity gradient, the gap between intended meaning and received understanding widens exponentially.
The Tolerance Problem
Understanding these limitations leads us to a practical question: what level of communicative tolerance is acceptable for different contexts? Just as engineering embraces acceptable tolerances rather than seeking perfect measurements, perhaps effective communication requires:
Acknowledging the gap between intended and received meaning
Establishing context-appropriate tolerance levels
Developing better frameworks for managing these tolerances
Recognizing when precision matters more than accuracy (or vice versa)
Implications for Human-AI Communication
These insights have particular relevance as we develop more sophisticated AI systems. The limitations we’ve explored suggest that:
Some communication problems might be fundamental rather than technical
AI systems may face similar boundaries as human communication
The gap between intended and received meaning might be unbridgeable
Future development should focus on managing rather than eliminating these limitations
Conclusion
Perhaps this is a simple exercise in mental masturbation. Language’s insufficiency isn’t a flaw to be fixed but a fundamental characteristic to be understood and accommodated. By definition, it can’t be fixed. The gap between intended and received meaning may be unbridgeable, but acknowledging this limitation is the first step toward more effective communication. As we continue to develop AI systems and push the boundaries of human-machine interaction, this understanding becomes increasingly critical.
Rather than seeking perfect precision in language, we might instead focus on:
Developing new forms of multimodal communication
Creating better frameworks for establishing shared context
Accepting and accounting for interpretative variance
Building systems that can operate effectively within these constraints
Understanding language’s limitations doesn’t diminish its value; rather, it helps us use it more effectively by working within its natural constraints.
Welcome to Part 6 of a Week-Long Series on the Evolution and Limits of Language! This article is part of a seven-day exploration into the fascinating and often flawed history of language—from its primitive roots to its tangled web of abstraction, miscommunication, and modern chaos. Each day, we uncover new layers of how language shapes (and fails to shape) our understanding of the world.
If you haven’t yet, be sure to check out the other posts in this series for a full deep dive into why words are both our greatest tool and our biggest obstacle. Follow the journey from ‘flamey thing hot’ to the whirlwind of social media and beyond!
Specialised Languages: Academia’s Jargon Olympics
If you thought normal language was confusing, let’s take a moment to appreciate the true champions of linguistic obscurity: academics. Welcome to the world of specialised languages, where entire fields of study have developed their own language games that make even Wittgenstein’s head spin.
Here’s how it works: Every discipline—science, law, philosophy—creates its own jargon to describe the world. At first, it seems helpful. Instead of using vague terms, you get precise definitions for complex ideas. But what started as a way to improve communication within a field quickly turned into a linguistic arms race, where the more obscure and convoluted your terms are, the smarter you sound. You’re not just a lawyer anymore—you’re someone who’s ready to throw “res ipsa loquitur” into casual conversation to leave everyone else in the room wondering if they’ve missed a memo.
The problem? If you’re not part of the club, good luck understanding what anyone is talking about. Want to read a physics paper? Prepare to learn a whole new vocabulary. Need to get through a legal document? You’ll be knee-deep in Latin phrases before you even get to the point. And don’t even try to decipher a philosophical text unless you’re ready to battle abstract nouns that have been stretched and twisted beyond recognition.
It’s not just the words themselves that are the issue—it’s the sheer density of them. Take “justice” for example. In philosophy, you’ve got theories about distributive justice, retributive justice, restorative justice, and a hundred other variations, each with its own set of terms and conditions. And that’s before we even touch on how “justice” is defined in legal circles, where it becomes an even more tangled mess of case law and precedent. Every field is playing its own version of the “justice” game, with its own rules and definitions, and none of them are interested in comparing notes.
This is the academic world in a nutshell. Each discipline has built its own linguistic fortress, and unless you’ve spent years studying, you’re not getting in. But here’s the kicker: even within these fields, people are often misunderstanding each other. Just because two scientists are using the same words doesn’t mean they’re on the same page. Sometimes, it’s more like a game of intellectual one-upmanship—who can define the most obscure term or twist a familiar word into something completely unrecognisable?
And let’s not forget the philosophers. They’ve turned linguistic acrobatics into an art form. Good luck reading Foucault or Derrida without a dictionary (or five) on hand. You might walk away thinking you understand their points, but do you really? Or have you just memorised the jargon without actually grasping the deeper meaning? Even scholars within these fields often argue over what was really meant by a certain text—Barthes, after all, famously declared the “death of the author,” so it’s not like anyone really has the final say on meaning anyway.
So here we are, knee-deep in jargon, trying to communicate with people who, technically, speak the same language but are operating within entirely different rulesets. Every academic discipline has its own secret code, and if you don’t know it, you’re lost. Even when you do know the code, you’re still at risk of miscommunication, because the words that look familiar have been stretched and shaped to fit highly specific contexts. It’s like being fluent in one dialect of English and then suddenly being asked to write a thesis in legalese. Good luck.
In the end, academia’s specialised languages don’t just make things harder—they actively create barriers. What started as a way to improve precision has turned into an obstacle course of incomprehensible terms, where the real challenge is just figuring out what anyone’s actually saying. And let’s be honest, even if you do figure it out, there’s no guarantee it’s going to mean the same thing next time you see it.
Neurolinguistics: Even Our Brains Can’t Agree
So far, we’ve seen how language is a mess of miscommunication, cultural differences, and academic jargon. But surely, at least on a biological level, our brains are all on the same page, right? Well, not exactly. Welcome to the wonderful world of neurolinguistics, where it turns out that even the very organ responsible for language can’t get its act together.
Here’s the deal: Neurolinguistics is the study of how the brain processes language, and while it’s fascinating, it’s also a bit of a buzzkill for anyone hoping for consistency. See, your brain and my brain don’t process language in the same way. Sure, we’ve got similar hardware, but the software is wildly unpredictable. There are individual differences, cultural influences, and developmental quirks that all affect how we understand and produce language. What’s simple for one brain might be completely baffling to another.
Take, for example, something as basic as syntax. Chomsky might have told us we all have a universal grammar hard-wired into our brains, but neurolinguistics has shown that how we apply that grammar can vary significantly. Some people are wired to handle complex sentence structures with ease—think of that friend who can follow 10 different clauses in a single breath. Others? Not so much. For them, even a moderately tricky sentence feels like mental gymnastics. The brain is constantly juggling words, meanings, and structures, and some brains are better at it than others.
But the real kicker is how differently we interpret words. Remember those abstract nouns we’ve been wrestling with? Well, it turns out that your brain might be interpreting ‘freedom’ or ‘justice’ completely differently from mine – not just because of culture or upbringing, but because our brains physically process those words in different ways. Neurolinguistic studies have shown that certain regions of the brain are activated differently depending on the individual’s experience with language. In other words, your personal history with a concept can literally change how your brain lights up when you hear or say it.
And don’t even get me started on bilingual brains. If you speak more than one language, your brain is constantly toggling between two (or more) linguistic systems, which means it’s running twice the risk of misinterpretation. What a word means in one language might trigger a completely different association in another, leaving bilingual speakers in a constant state of linguistic flux. It’s like trying to run two operating systems on the same computer—things are bound to get glitchy.
But here’s the real kicker: Even within the same person, the brain can’t always process language the same way all the time. Stress, fatigue, emotional state—all of these factors can influence how well we handle language on any given day. Ever tried to have a coherent conversation when you’re tired or angry? Good luck. Your brain isn’t interested in nuance or deep philosophical ideas when it’s in survival mode. It’s just trying to get through the day without short-circuiting.
So, not only do we have to deal with the external chaos of language – miscommunication, different contexts, shifting meanings – but we also have to contend with the fact that our own brains are unreliable interpreters. You can use all the right words, follow all the right grammar rules, and still end up with a garbled mess of meaning because your brain decided to take a nap halfway through the sentence.
In the end, neurolinguistics reminds us that language isn’t just a social or cultural problem – it’’’s a biological one too. Our brains are doing their best to keep up, but they’re far from perfect. The very organ that makes language possible is also responsible for making it infinitely more complicated than it needs to be. And if we can’t rely on our own brains to process language consistently, what hope do we have of ever understanding anyone else?
Philosophics 