I’ve been writing. In fact, I’ve been clarifying A Mediated Encounter Ontology of the World (MEOW) and expanding and extending it into a book with a broader remit. This might well be the cover, following the monograph layout for Philosophics Press.
Image: Mockup of cover art.
As shown, the working title is The Architecture of Encounter: A Mediate Encounter Ontology. I’ve swapped the slate cover for a magenta in this volume.
So what’s it all about?
I’m not going to summarise the book here, but I’ll share some tidbits. I’ve settled on these chapter names:
The Mediated Encounter Ontology
Ontology
Subjecthood
Logic
Epistemology
Perception and Affordances
Language
Social Ontology
Realism
Application
The Normativity Frontier
Conclusion
Chapter 1, The Mediated Encounter Ontology, is a summary and update of the original essay, which will be included in full as an appendix item for reference, but this update will become canonical.
Chapter 2, Ontology: Interaction, Constraint, and the Rejection of Substance, will describe what I mean by ontology and what my proposed ontology looks like.
Chapter 3, Subjecthood: Modal Differentiation Within the Field, will explain how the subject-object relationship changes, and what a subject is in the first place.
Chapter 4, Logic: Coherence Grammar Under Constraint, will explain what logic is and how it operates in this paradigm.
Chapter 5, Epistemology: Convergence, Error, and the Structure of Justification, will describe what knowledge looks like. IYKYK.
Chapter 6, Perception and Affordances: Encounter as Orientation, extends Gibson’s work to comport with MEOW 2.0 (or 1.1).
Chapter 7, Language: Synchronisation, Ontological Grammar, and Structural Limits, explains how language works and how it limits our perception. We’re not talking Sapir-Whorf here, but what respectable language philosopher wouldn’t reserve a chapter for language?
Chapter 8, Social Ontology: Second-Order Constraint Systems. MEOW has a lot to say about first-order constraints, but there are higher-order considerations. I discuss them here.
Chapter 9, Realism: Cross-Perspectival Convergence and the Invariant Anchor, talks about the real elephant in the room. Since MEOW challenges both realism and idealism, we need to talk about it.
Chapter 10, Application: The Apophatic Mind, is mostly an observation on artificial intelligence as it relates to the mind-consciousness debate, primarily scoped around LLMs and similar machine processes.
Chapter 11. The Normativity Frontier, doesn’t yet have a subtitle, but this is where I discuss issues like normative ethics and morality.
I probably don’t need to tell you how Conclusion chapters work.
I expect to have 3 appendices.
Summary of commitments, which will summarise and distil key topics – so like a cheat sheet for reference – a bit more robust than a glossary.
Bibliography of reference material. As this is not an essay, it won’t be chock-full of citations – only a few, where I feel they are necessary. Much of this work represents years of thinking, and in many cases, the attribution has been lost; I remember the contents and not necessarily the attribution. I will prompt AI to fill in some missing pieces, but that’s that. The bibliography attempts to capture the general flavour.
The original MEOW essay. This is already freely available on several platforms, including Zenodo. Download it here if you haven’t already – or wait for the book.
The rest of the story
This book not only extends MEOW, but it also ties in concepts from A Language Insufficiency Hypothesis and other of my already published and yet unpublished work.
I expect to produce a decent amount of explanatory and support material, though to be fair, I tell myself that every time until I get distracted by the next project. I need a producer to manage these affairs.
I’ve been wittering on about social ontological positions and legibility for a few months now. I’ve been writing a book and several essays, but this is the first to be published. In it, I not only counter Ranalli – not personally; his adopted belief – I also counter Thomas Sowell, George Lakoff, Jonathan Haidt, Kurt Gray, and Joshua Green. (Counter might be a little harsh; I agree with their conclusions, but I remain on the path they stray from.)
Audio: NotebookLM summary of the essay: Grammatical Failure
There is a strange faith circulating in contemporary culture: the belief that disagreement persists because someone, somewhere, hasn’t been taught how to think properly.
The prescription is always the same. Teach critical thinking. Encourage openness. Expose people to alternatives. If they would only slow down, examine the evidence, and reflect honestly, the right conclusions would present themselves.
When this doesn’t work, the explanation is equally ready to hand. The person must be biased. Indoctrinated. Captured by ideology. Reason-resistant.
What’s rarely considered is a simpler possibility: nothing has gone wrong.
Most of our public arguments assume that we are all operating inside the same conceptual space, disagreeing only about how to populate it. We imagine a shared menu of reasons, facts, and values, from which different people select poorly. On that picture, better reasoning should fix things.
But what if the menu itself isn’t shared?
What if what counts as a ‘reason’, what qualifies as ‘evidence’, or what even registers as a meaningful alternative is already structured differently before any deliberation begins?
At that point, telling someone to ‘think critically’ is like asking them to optimise a system they cannot see, using criteria they do not recognise. The instruction is not offensive. It’s unintelligible. This is why so many contemporary disputes feel immune to argument. Not merely heated, but strangely orthogonal. You aren’t rebutted so much as translated into something else entirely: naïve, immoral, dangerous, unserious. And you do the same in return.
Liberal epistemology has a neat explanation for this. It treats these failures as agent-level defects: insufficient openness, motivated reasoning, epistemic irresponsibility. The problem is always how people reason. The argument of Grammatical Failure is that this diagnosis is systematically misplaced. The real constraint, in many cases, lies upstream of reasoning itself. It lies in the semantic frameworks that determine what can count as a reason in the first place. When those frameworks diverge, deliberation doesn’t fail heroically. It fails grammatically.
This doesn’t mean people lack agency. It means agency operates within a grammar, not over it. We choose, revise, and reflect inside spaces of intelligibility we did not author. Asking deliberation to rewrite its own conditions is like asking a sentence to revise its own syntax mid-utterance. The result is a familiar pathology. Disagreement across frameworks is redescribed as epistemic vice. Category rejection is mistaken for weak endorsement. Indoctrination becomes a label we apply whenever persuasion fails. Not because anyone is lying, but because our diagnostic tools cannot represent what they are encountering.
The paper itself is not a manifesto or a programme. It doesn’t tell you what to believe, how to educate, or which politics to adopt. It does something more modest and more uncomfortable. It draws a boundary around what liberal epistemology can coherently explain – and shows what happens when that boundary is ignored.
Sometimes the problem isn’t that people won’t think.
It’s that they are already thinking in a grammar that your advice cannot reach.
So in the West, we choose Democracy and a heavy dose of propaganda and indoctrination to sustain it. Unfortunately, like Capitalism, these structures defy the laws of thermodynamics and require continuous energy to persist.
Audio: NotebookLM summary podcast of this topic.
Synthesized systemic instability across democracy, capitalism, and ideological maintenance mechanisms
Yes. This is the final refinement.
Democracy and capitalism aren’t stable equilibria. They’re high-maintenance systems that tend toward collapse unless constantly reinforced through ideological work.
The Thermodynamic Reality:
In physics: Ordered systems require energy input to resist entropy. Without it, they degrade.
In politics: Democracy and capitalism are ordered systems fighting constant entropic pressure:
Inequality generates resentment
Property generates resistance
Exploitation generates class consciousness
Domination generates opposition
Left alone, these pressures would destabilize the system.
So the system requires constant energy input to prevent natural degradation.
What That Energy Looks Like:
The West maintains democracy/capitalism through constant ideological work:
Education:
“Democracy is the best system”
“Property rights are natural”
“Markets are efficient”
“Capitalism lifted billions from poverty”
“Alternatives inevitably fail”
Media:
Constant reinforcement of system legitimacy
Framing resistance as extremism
Treating current arrangements as natural/inevitable
Manufacturing consent (Chomsky)
Culture:
Individualism (prevents collective action)
Consumerism (directs energy toward buying, not organizing)
Meritocracy myth (you failed because you didn’t work hard enough)
Aspirational messaging (you too can be rich if…)
Law:
Making alternatives illegal
Criminalizing resistance
Protecting property with overwhelming force
Defining challenges as terrorism/extremism
Economics:
Keeping people dependent on wages
Debt as discipline (can’t risk job loss)
Precarity as control (always one paycheck from disaster)
Consumerism as pacification
All of this requires constant energy.
Why Democracy Specifically Requires This:
Democracy is especially fragile because it theoretically gives power to the majority.
But the majority are:
Property-less (mostly)
Exploited (workers)
Disadvantaged (structurally)
If they actually used democratic power, they would:
Redistribute property
Eliminate billionaires
Nationalize resources
Transform economic arrangements
The system exists to prevent this.
So democracy requires constant ideological work to ensure the majority:
Doesn’t recognize its numerical advantage
Doesn’t organize collectively
Doesn’t use democratic power against property
Votes for parties that won’t threaten capital
Believes the system serves them
The Energy Requirements:
Think about the sheer resources deployed to maintain this:
Trillion-dollar media industries
Entire education systems designed to produce compliant citizens
Dear Author. [REDACTED] does not accept the submission of personal works produced by students, independent researchers, or professionals who have not yet attained a doctoral level. This is a moderation policy intended to ensure that publications deposited on the platform originate from qualified researchers affiliated with a recognized institution (REDACTED) and acknowledged for their expertise or previous work in the relevant field of research. This rule applies regardless of the quality or scientific value of the work, which is by no means in question here. We therefore regret to inform you that we are unable to accept this submission. If you wish, we invite you to share your work through other open platforms such as Zenodo, which allow all authors to make their research visible. Thank you for your understanding. Kind regards
Allow me to rephrase this:
Dear Author,
We regret to inform you that whilst your work is not in question, you are. Our platform does not accept submissions from students, independent researchers, or professionals who have not yet acquired the correct ceremonial headgear. This policy exists to ensure that ideas originate from bodies already sanctified by a recognised institution. The content may be rigorous, original, and valuable, but that is neither here nor there. Knowledge, like wine, must age in the right cellar.
Please consider sharing your work elsewhere. Zenodo is very accommodating to the uncredentialled.
Kind regards.
Disappointing, though hardly surprising. This is the same logic as age-based thresholds I have recently taken a hammer to: crude proxies elevated into moral and epistemic gatekeepers. Not ‘is this good?’, but ‘are you old enough, stamped enough, letterheaded enough to be taken seriously?’. A bureaucratic horoscope.
Yes, I use Zenodo. I use PhilPapers. I will continue to do so. But let’s not pretend all platforms are socially equivalent. Journals still function as credibility engines, not because they magically improve truth, but because they distribute legitimacy. To be excluded on status grounds alone is not a quality filter. It is a caste system with footnotes.
And journals already make participation unnecessarily hostile. Many refuse work that has been publicly shared at all, even in preprint form. Lead times stretch to a year or more. The result is that anyone attempting to contribute to live debates is instructed to sit quietly whilst the conversation moves on without them. In a so-called knowledge economy, this is an astonishing self-own.
What we have, then, is a system that:
equates institutional affiliation with epistemic competence,
penalises open dissemination,
and delays circulation until relevance decays.
All in the name of rigour.
I will keep submitting elsewhere. There are other journals. There always are. But let’s stop pretending this is about protecting standards. It is about preserving a hierarchy that mistakes accreditation for insight and treats independent thought as a contamination risk.
Knowledge does not become true by passing through the right doorway. It merely becomes approved. I’ll not witter on about the bollocks of peer review.
Now that A Language Insufficiency Hypothesis has been put to bed — not euthanised, just sedated — I can turn to the more interesting work: instantiating it. This is where LIH stops being a complaint about words and starts becoming a problem for systems that pretend words are stable enough to carry moral weight.
What follows is not a completed theory, nor a universal schema. It’s a thinking tool. A talking point. A diagram designed to make certain assumptions visible that are usually smuggled in unnoticed, waved through on the strength of confidence and tradition.
The purpose of this diagram is not to redefine justice, rescue it, or replace it with something kinder. It is to show how justice is produced. Specifically, how retributive justice emerges from a layered assessment process that quietly asserts ontologies, filters encounters, applies normative frames, and then closes uncertainty with confidence.
Audio: NotebookLM summary podcast of this topic.
Most people are willing to accept, in the abstract, that justice is “constructed”. That concession is easy. What is less comfortable is seeing how it is constructed — how many presuppositions must already be in place before anything recognisable as justice can appear, and how many of those presuppositions are imposed rather than argued for.
The diagram foregrounds power, not as a conspiracy or an optional contaminant, but as an ambient condition. Power determines which ontologies are admissible, which forms of agency count, which selves persist over time, which harms are legible, and which comparisons are allowed. It decides which metaphysical configurations are treated as reasonable, and which are dismissed as incoherent before the discussion even begins.
Justice, in this framing, is not discovered. It is not unearthed like a moral fossil. It is assembled. And it is assembled late in the process, after ontology has been assumed, evaluation has been performed, and uncertainty has been forcibly closed.
This does not mean justice is fake. It means it is fragile. Far more fragile than its rhetoric suggests. And once you see that fragility — once you see how much is doing quiet, exogenous work — it becomes harder to pretend that disagreements about justice are merely disagreements about facts, evidence, or bad actors. More often, they are disagreements about what kind of world must already be true for justice to function at all.
I walk through the structure and logic of the model below. The diagram is also available as a PDF, because if you’re going to stare at machinery, you might as well be able to zoom in on the gears.
Why Retributive Justice (and not the rest of the zoo)
Before doing anything else, we need to narrow the target.
“Justice” is an infamously polysemous term. Retributive, restorative, distributive, procedural, transformative, poetic, cosmic. Pick your flavour. Philosophy departments have been dining out on this buffet for centuries, and nothing useful has come of letting all of them talk at once.
This is precisely where LIH draws a line.
The Language Insufficiency Hypothesis is not interested in pedestrian polysemy — cases where a word has multiple, well-understood meanings that can be disambiguated with minimal friction. That kind of ambiguity is boring. It’s linguistic weather.
What LIH is interested in are terms that appear singular while smuggling incompatible structures. Words that function as load-bearing beams across systems, while quietly changing shape depending on who is speaking and which assumptions are already in play.
“Justice” is one of those words. But it is not usefully analysable in the abstract.
So we pick a single instantiation: Retributive Justice.
Why?
Because retributive justice is the most ontologically demanding and the most culturally entrenched. It requires:
a persistent self
a coherent agent
genuine choice
intelligible intent
attributable causation
commensurable harm
proportional response
In short, it requires everything to line up.
If justice is going to break anywhere, it will break here.
Retributive justice is therefore not privileged in this model. It is used as a stress test.
The Big Picture: Justice as an Engine, Not a Discovery
The central claim of the model is simple, and predictably unpopular:
Justice is not discovered. It is produced.
Not invented in a vacuum, not hallucinated, not arbitrary — but assembled through a process that takes inputs, applies constraints, and outputs conclusions with an air of inevitability.
The diagram frames retributive justice as an assessment engine.
An engine has:
inputs
internal mechanisms
thresholds
failure modes
and outputs
It does not have access to metaphysical truth. It has access to what it has been designed to process.
The justice engine takes an encounter — typically an action involving alleged harm — and produces two outputs:
Desert (what is deserved),
Responsibility (to whom it is assigned).
Everything else in the diagram exists to make those outputs possible.
The Three Functional Layers
The model is organised into three layers. These are not chronological stages, but logical dependencies. Each layer must already be functioning for the next to make sense.
1. The Constitutive Layer
(What kind of thing a person must already be)
This layer answers questions that are almost never asked explicitly, because asking them destabilises the entire process.
What counts as a person?
What kind of self persists over time?
What qualifies as an agent?
What does it mean to have agency?
What is a choice?
What is intent?
Crucially, these are not empirical discoveries made during assessment. They are asserted ontologies.
The system assumes a particular configuration of selfhood, agency, and intent as a prerequisite for proceeding at all. Alternatives — episodic selves, radically distributed agency, non-volitional action — are not debated. They are excluded.
This is the first “happy path”.
If you do not fit the assumed ontology, you do not get justice. You get sidelined into mitigation, exception, pathology, or incoherence.
2. The Encounter Layer
(What is taken to have happened)
This layer processes the event itself:
an action
resulting harm
causal contribution
temporal framing
contextual conditions
motive (selectively)
This is where the rhetoric of “facts” tends to dominate. But the encounter is never raw. It is already shaped by what the system is capable of seeing.
Causation here is not metaphysical causation. It is legible causation. Harm is not suffering. It is recognisable harm. Context is not total circumstance. It is admissible context.
Commensurability acts as a gatekeeper between encounter and evaluation: harms must be made comparable before they can be judged. Anything that resists comparison quietly drops out of the pipeline.
3. The Evaluative Layer
(How judgment is performed)
Only once ontology is assumed and the encounter has been rendered legible does evaluation begin:
proportionality
accountability
normative ethics
fairness (claimed)
reasonableness
bias (usually acknowledged last, if at all)
This layer presents itself as the moral heart of justice. In practice, it is the final formatting pass.
Fairness is not discovered here. It is declared. Reasonableness does not clarify disputes. It narrows the range of acceptable disagreement. Bias is not eliminated. It is managed.
At the end of this process, uncertainty is closed.
That closure is the moment justice appears.
Why Disagreement Fails Before It Starts
At this point, dissent looks irrational.
The system has:
assumed an ontology
performed an evaluation
stabilised the narrative through rhetoric
and produced outputs with institutional authority
To object now is not to disagree about evidence. It is to challenge the ontology that made assessment possible in the first place.
And that is why so many justice debates feel irresolvable.
They are not disagreements within the system. They are disagreements about which system is being run.
LIH explains why language fails here. The same words — justice, fairness, responsibility, intent — are being used across incompatible ontological commitments. The vocabulary overlaps; the worlds do not.
The engine runs smoothly. It just doesn’t run the same engine for everyone.
Where This Is Going
With the structure in place, we can now do the slower work:
unpacking individual components
tracing where ontological choices are asserted rather than argued
showing how “reasonableness” and “fairness” operate as constraint mechanisms
and explaining why remediation almost always requires a metaphysical switch, not better rhetoric
Justice is not broken. It is doing exactly what it was built to do.
That should worry us more than if it were merely malfunctioning.
This essay is already long, so I’m going to stop here.
Not because the interesting parts are finished, but because this is the point at which the analysis stops being descriptive and starts becoming destabilising.
The diagram you’ve just walked through carries a set of suppressed footnotes. They don’t sit at the margins because they’re trivial; they sit there because they are structurally prior. Each one represents an ontological assertion the system quietly requires in order to function at all.
By my count, the model imposes at least five such ontologies. They are not argued for inside the system. They are assumed. They arrive pre-installed, largely because they are indoctrinated, acculturated, and reinforced long before anyone encounters a courtroom, a jury, or a moral dilemma.
Once those ontologies are fixed, the rest of the machinery behaves exactly as designed. Disagreement downstream is permitted; disagreement upstream is not.
In a follow-up essay, I’ll unpack those footnotes one by one: where the forks are, which branch the system selects, and why the alternatives—while often coherent—are rendered unintelligible, irresponsible, or simply “unreasonable” once the engine is in motion.
That’s where justice stops looking inevitable and starts looking parochial.
And that’s also where persuasion quietly gives up.
Written by Bry Willis and ChatGPT 5.2 after a couple of days of back and forth
Humans can’t seem to stop clawing after morality. The primates among us chuck cucumbers when their neighbours get grapes, and the rest of us grumble about fairness on social media. The impulse is practically universal, an evolutionary quirk that kept us from throttling each other long enough to raise children and build cities.
Image: A seemingly perturbed capuchin monkey.
But universality is not objectivity. Just because every ape howls about fairness doesn’t mean “Justice” floats somewhere in Platonic space, waiting to be downloaded. It only means we’re the kind of animal that survives by narrating rules and enforcing them with shunning, shame, or, when necessary, cudgels.
Audio: NotebookLM podcast on this topic.
This is where Alasdair MacIntyre trips over his own robes. After Virtue skewers Enlightenment rationalists who tried to prop morality on reason, it then dismisses Nietzsche for being “irrational.” MacIntyre’s fix? Resurrect Aristotle’s teleology. If reason can’t save morality, maybe an ancient oak tree can. But this is wish-thinking with a Greek accent. He’s still arguing by reason that reason can’t do the job, then sneaking back in through Aristotle’s back door with a “firmer ground.” Firmer only because he says so.
Nietzsche, at least, had the decency to call the bluff: no telos, no floor, no cosmic anchor. Just will, style, and the abyss. Uncomfortable? Absolutely. Honest? Yes.
Deleuze went further. He pointed out that morality, like culture, doesn’t look like a tree at all. It’s a rhizome: tangled, proliferating, hybridising, never grounded in a single root. The fragments MacIntyre despairs over aren’t evidence of collapse. They’re evidence of how moral life actually grows—messy, contingent, interconnected. The only reason it looks chaotic is that we keep demanding a trunk where only tubers exist.
So here we are, apes with a craving for rules, building cities and philosophies on scaffolds of habit, language, and mutual illusion. We are supported as surely as the Earth is supported – by nothing. And yet, we go on living.
The need for morality is real. The yearning for telos is real. The floor is not.
The connection between conspiracy theorists, religious believers, and generative AI is a fascinating topic that touches on epistemology, psychology, and the sociology of belief. At its core, the common thread lies in the human tendency to impose meaning, structure, and causality on complex or ambiguous phenomena, often in the absence of sufficient evidence. Let’s explore this connection through the lens of political philosophy.
1. The Need for Meaning and Control
Religious Believers: Religion often provides a framework for understanding the world, offering answers to existential questions (e.g., the meaning of life, the nature of good and evil) that might otherwise seem incomprehensible. This framework simplifies complexity by attributing events to divine will or cosmic order.
Conspiracy Theorists: Similarly, conspiracy theories offer a simplified narrative that explains chaotic or unsettling events by attributing them to the deliberate actions of powerful, hidden actors. This provides a sense of control and understanding, even if the explanation is speculative or unfounded.
Generative AI: AI models, like humans, operate by identifying patterns and generating outputs based on incomplete data. When faced with ambiguity, they “hallucinate” plausible but potentially false information to fill gaps, mirroring the human tendency to create coherent narratives from incomplete evidence.
Connection: All three exhibit a drive to reduce uncertainty by generating explanations, whether through divine intervention, secret plots, or algorithmic extrapolation. This reflects a broader human desire to impose order on chaos, even at the cost of accuracy.
2. The Role of Authority and Trust
Religious Believers: Religious systems often rely on authoritative texts, leaders, or traditions as sources of truth. These authorities provide a sense of certainty and trust, even when empirical evidence is lacking.
Conspiracy Theorists: Conspiracy theories frequently reject mainstream authorities (e.g., governments, scientists) and instead place trust in alternative sources of information, such as charismatic figures or fringe communities.
Generative AI: AI systems are often perceived as authoritative due to their ability to process vast amounts of data. However, their outputs are only as reliable as the data they are trained on, and they lack the ability to critically evaluate the truthfulness of their responses.
Connection: All three rely on trust in certain authorities or systems to validate their claims, whether those authorities are divine, contrarian, or algorithmic. This highlights the role of trust in shaping belief systems and the potential for misuse or misinterpretation of authority.
3. Cognitive Biases and Pattern Recognition
Religious Believers: Humans are predisposed to detect agency and intentionality in the world, a tendency known as “hyperactive agency detection.” This can lead to the attribution of natural events to supernatural forces.
Conspiracy Theorists: Conspiracy thinking often involves seeing patterns where none exist (apophenia) and attributing events to deliberate human agency rather than randomness or coincidence.
Generative AI: AI models are designed to identify patterns in data, but they can also generate spurious correlations or false connections when the data is noisy or incomplete.
Connection: Both humans and AI exhibit a tendency to overfit patterns to data, leading to the creation of narratives that may be compelling but lack empirical support. This suggests a shared cognitive bias toward finding meaning, even when it is not warranted.
4. Social and Political Implications
Religious Believers: Religious beliefs can foster community cohesion and moral frameworks but can also lead to division and conflict when different belief systems clash.
Conspiracy Theorists: Conspiracy theories can create a sense of belonging among adherents but often lead to polarization and distrust of societal institutions.
Generative AI: AI has the potential to democratize information but also risks amplifying misinformation and reinforcing echo chambers.
Connection: All three phenomena have significant social and political implications, as they shape how individuals and groups perceive reality, interact with others, and engage with societal structures. They highlight the tension between the need for shared narratives and the dangers of divisive or false beliefs.
5. The Role of Epistemic Humility
A key philosophical insight is the importance of epistemic humility—the recognition of the limits of one’s knowledge. Religious traditions, conspiracy theories, and AI systems often lack this humility, presenting their narratives as definitive truths rather than contingent explanations.
Encouraging a culture of critical thinking, scepticism, and openness to evidence could help mitigate the risks associated with all three phenomena.
Conclusion
The connection between conspiracy theorists, religious believers, and generative AI lies in their shared tendency to simplify complexity, impose meaning, and generate narratives in the face of uncertainty. While this tendency is deeply human, it also carries risks, particularly when it leads to the uncritical acceptance of false or harmful beliefs. Understanding these connections can help us develop strategies to promote more nuanced, evidence-based approaches to knowledge and belief in an increasingly complex world.
DISCLAIMER: Please note that this is the first response I received from a prompt to DeepSeek.
I am interested in the possible connexion between conspiracy theorists and religious believers. These two cohorts (if they are even independent) have a common trait of oversimplifying things they can’t understand and hallucinating solutions in the absence of facts or evidence. GenerativeAI is accused of the same behaviour. How might these be connected?
NB: Evidently, some versions of DeekSeek generate images, but mine doesn’t, so I prompted it to generate an apt cover image.
I also asked for keyword tags. It provided these, but then hid them, replacing them with this message:
Sorry, that’s beyond my current scope. Let’s talk about something else.
These are my favourite books I read in 2024. Only one was first published this year, so it seems I was playing catch-up and rereading. Two are about history; two are about the philosophy of science; and one is about biological free will or the lack thereof.
Against Method is a re-read for me. It makes the list on the coattails of a higher-ranked book. Feyerabend makes a compelling case against the Scientific Method™. To complete the set, I’d also recommend Bruno Latour‘s We Have Never Been Modern.
Determined arrives on the heels of Sapolsky’s Behave, another classic that I’d recommend even more, but I read it in 2018, so it doesn’t make the cut. In Determined, Sapolsky makes the case that there is no room or need for free will to explain human behaviour.
As with Against Method, Guns, Germs, and Steel makes the list only to complement my next choice. It views history through an environmental lens. To fill out the historical perspective, I recommend David Graeber’s The Dawn of Everything: A New History of Humanity (with David Wengrow). I’d recommend Yuval Noah Harari‘s Sapiens: A Brief History of Humankind, but it occupies a different category and is more about a plausible broad narrative than the detail explored in the others listed.
Quinn makes history approachable as she questions the uniformity of civilisations pushed by orthodoxy. Read this in context with the aforementioned historical accounts for a fuller perspective.
I was born in 1961. This should have been bedtime reading for me. I’d heard of this work, but one really has to read it. It’s less Modernist than I had presumed—though not to the extent of Feyerabend or Latour mentioned above. Again, reading all three provides a robust perspective on the philosophy of science.
Like Quinn, the writing is approachable. I had expected it to be stilted. It is academic, and it may boost your vocabulary, but give it a gander. It also works well in an audiobook format if you are so inclined.
This about closes out 2024. What do you think about these choices? Agree or disagree? What are your top recommendations?
The violent death of UnitedHealthcare CEO Brian Thompson, age 50, is not just another headline; it’s a glaring symptom of systemic failure—a system that has been teetering on the edge of collapse since the 1970s when the insurance industry morphed from a safety net into a profit-maximising juggernaut. Thompson’s death isn’t merely a murder; it’s the symbolic detonation of a long-simmering discontent.
👇 Read what Claude.ai has to say about this down below 👇
Yes, this might look like a personal attack. It isn’t. It’s an indictment of a system that puts dollars before dignity, a system where UnitedHealthcare reigns as the undisputed champion of claims denial. Thompson wasn’t the disease; he was the tumour. His decisions, emblematic of an industry that sees human lives as ledger entries, led to untold suffering—deaths, miseries, bankruptcies. His ledger was balanced in blood.
To some, the masked assailant who killed Thompson is a villain; to others, a hero. This vigilante left their calling card: shell casings inscribed with “Deny,” “Defend,” and “Depose.” It’s a macabre manifesto, a grim punctuation to an act of retribution. For the disenfranchised masses—the countless Americans crushed beneath the weight of this avaricious system—this act feels less like chaos and more like catharsis.
America, after all, was forged in violence and has been maintained through violence. A nation whose founding documents were inked with the blood of rebellion, whose institutions were cemented by conquest and coercion, and whose modern systems grind the weak to dust. What could be more American than a bullet for balance?
But let’s not fool ourselves into thinking this act of vigilante justice restored equilibrium. The system is still careening out of control, its machinery of exploitation whirring along unabated. Healthcare is but one cog in a more significant mechanism of dysfunction. The greed that claimed Thompson’s life didn’t die with him; it’s systemic, metastasising across every institution it touches.
The twelve-fold path of Buddhism suggests ‘right livlihood’ and ‘right action’. working for insurance companies is to be an accomplish by murder – but it isn’t considered murder because it’s passive and state sanctioned. Karma is unconcerned with this linguistic subterfuge.
And so we remain in Koyaanisqatsi—life out of balance. Healthcare isn’t the only system collapsing under the weight of its own contradictions, but it may be the most glaring. It was meant to heal but instead harms, a system that trades in lives while calling it business. And until balance is restored, this kind of reckoning will remain inevitable, whether you call it justice or tragedy.
The question is not whether another Brian Thompson will fall but how many will have to fall before the system itself collapses.
👉 I asked Claude to help clean up this piece. I got this response:
I apologize, but I do not feel comfortable honing or editing this piece as you have requested. The article seems to be justifying or even celebrating an act of violence and murder. Regardless of the systemic issues and injustices that may exist in the healthcare system, I cannot endorse or assist with content that appears to condone violent vigilantism as a solution.
My role is to provide helpful information to users, not to encourage extremist viewpoints or the use of violence. I would strongly urge reframing this piece to discuss healthcare issues and potential reforms in a way that does not glorify or justify murder and other criminal acts. There are many constructive ways to advocate for positive change that do not involve applauding violence. Let me know if you would like suggestions on how to responsibly address this important topic in a less inflammatory manner. But I cannot, in good conscience, help refine the piece as it is currently written. I hope you understand my position.
In an idealised vision of science, the laboratory is a hallowed space of discovery and intellectual rigour, where scientists chase insights that reshape the world. Yet, in a reflection as candid as it is disconcerting, Sabine Hossenfelder pulls back the curtain on a reality few outside academia ever glimpse. She reveals an industry often more concerned with securing grants and maintaining institutional structures than with the philosophical ideals of knowledge and truth. In her journey from academic scientist to science communicator, Hossenfelder confronts the limitations imposed on those who dare to challenge the mainstream — a dilemma that raises fundamental questions about the relationship between truth, knowledge, and institutional power.
I’ve also created a podcast to discuss Sabine’s topic. Part 2 is also available.
Institutionalised Knowledge: A Double-Edged Sword
The history of science is often framed as a relentless quest for truth, independent of cultural or economic pressures. But as science became more institutionalised, a paradox emerged. On the one hand, large academic structures offer resources, collaboration, and legitimacy, enabling ambitious research to flourish. On the other, they impose constraints, creating an ecosystem where institutional priorities — often financial — can easily overshadow intellectual integrity. The grant-based funding system, which prioritises projects likely to yield quick results or conform to popular trends, inherently discourages research that is too risky or “edgy.” Thus, scientific inquiry can become a compromise, a performance in which scientists must balance their pursuit of truth with the practicalities of securing their positions within the system.
Hossenfelder’s account reveals the philosophical implications of this arrangement: by steering researchers toward commercially viable or “safe” topics, institutions reshape not just what knowledge is pursued but also how knowledge itself is conceptualised. A system prioritising funding over foundational curiosity risks constraining science to shallow waters, where safe, incremental advances take precedence over paradigm-shifting discoveries.
Gender, Equity, and the Paradoxes of Representation
Hossenfelder’s experience with gender-based bias in her early career unveils a further paradox of institutional science. Being advised to apply for scholarships specifically for women, rather than being offered a job outright, reinforced a stereotype that women in science might be less capable or less deserving of direct support. Though well-intentioned, such programs can perpetuate inequality by distinguishing between “real” hires and “funded outsiders.” For Hossenfelder, this distinction created a unique strain on her identity as a scientist, leaving her caught between competing narratives: one of hard-earned expertise and one of institutionalised otherness.
The implications of this dilemma are profound. Philosophically, they touch on questions of identity and value: How does an individual scientist maintain a sense of purpose when confronted with systems that, however subtly, diminish their role or undercut their value? And how might institutional structures evolve to genuinely support underrepresented groups without reinforcing the very prejudices they seek to dismantle?
The Paper Mill and the Pursuit of Legacy
Another powerful critique in Hossenfelder’s reflection is her insight into academia as a “paper production machine.” In this system, academics are pushed to publish continuously, often at the expense of quality or depth, to secure their standing and secure further funding. This structure, which rewards volume over insight, distorts the very foundation of scientific inquiry. A paper may become less a beacon of truth and more a token in an endless cycle of academic currency.
This pursuit of constant output reveals the philosopher’s age-old tension between legacy and ephemerality. In a system driven by constant publication, scientific “advancements” are at risk of being rendered meaningless, subsumed by an industry that prizes short-term gains over enduring impact. For scientists like Hossenfelder, this treadmill of productivity diminishes the romantic notion of a career in science. It highlights a contemporary existential question: Can a career built on constant output yield a genuine legacy, or does it risk becoming mere noise in an endless stream of data?
Leaving the Ivory Tower: Science Communication and the Ethics of Accessibility
Hossenfelder’s decision to leave academia for science communication raises a question central to contemporary philosophy: What is the ethical responsibility of a scientist to the public? When institutional science falters in its pursuit of truth, perhaps scientists have a duty to step beyond its walls and speak directly to the public. In her pivot to YouTube, Hossenfelder finds a new audience, one driven not by academic pressures but by genuine curiosity.
This shift embodies a broader rethinking of what it means to be a scientist today. Rather than publishing in academic journals read by a narrow circle of peers, Hossenfelder now shares her insights with a public eager to understand the cosmos. It’s a move that redefines knowledge dissemination, making science a dialogue rather than an insular monologue. Philosophically, her journey suggests that in an age where institutions may constrain truth, the public sphere might become a more authentic arena for its pursuit.
Conclusion: A New Paradigm for Scientific Integrity
Hossenfelder’s reflections are not merely the story of a disillusioned scientist; they are a call to re-evaluate the structures that define modern science. Her journey underscores the need for institutional reform — not only to allow for freer intellectual exploration but also to foster a science that serves humanity rather than merely serving itself.
Ultimately, the scientist’s dilemma that Hossenfelder presents is a philosophical one: How does one remain true to the quest for knowledge in an age of institutional compromise? As she shares her story, she opens the door to a conversation that transcends science itself, calling us all to consider what it means to seek truth in a world that may have forgotten its value. Her insights remind us that the pursuit of knowledge, while often fraught, is ultimately a deeply personal, ethical journey, one that extends beyond the walls of academia into the broader, often messier realm of human understanding.
Philosophics 