Tag: morality

When Hollywood Tried to Cheer Up Less Than Zero and Missed the Point Entirely

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Let’s talk about Less Than Zero. No, not the film. I’m talking about the book—Bret Easton Ellis’s nihilistic masterpiece that drags you through a moral cesspit of 1980s Los Angeles. You might remember it as the story that makes American Psycho look like a quirky self-help guide. It’s dark, it’s bleak, and it doesn’t pretend to offer you a shred of hope.

And then there’s the movie adaptation.

Oh, the movie. It’s as though someone read Ellis’s unflinching tale of moral rot and thought, You know what this needs? Friendship. And a redemption arc. And maybe some heartfelt music in the background. Hollywood, in all its infinite wisdom, decided that audiences couldn’t handle the book’s existential despair. So, they took a story about the void—about the emptiness of privilege, the suffocation of apathy, and the complete erosion of human connection—and gave it a fuzzy moral centre.

Here’s the gist: The book is nihilism incarnate. It follows Clay, a disaffected college student who comes home to LA for Christmas and is immediately swallowed whole by a world of cocaine, vapid socialites, and casual cruelty. No one learns anything. No one grows. In fact, the whole point is that these characters are so morally bankrupt, so irreparably hollow, that they’re beyond redemption. If you’re looking for a happy ending, don’t bother—Ellis leaves you stranded in the abyss, staring into the void, wondering if there’s any point to anything. Spoiler: there’s not.

Then along comes the 1987 film, directed by Marek Kanievska. It keeps the names of the characters—Clay, Blair, Julian—but not much else. Instead of being an icy observer of LA’s decadence, Clay is transformed into a love-struck saviour. Blair, a passive figure in the novel, becomes a supportive girlfriend. And Julian—oh, poor Julian—is turned into a sacrificial lamb for the sake of a heartfelt narrative about friendship and second chances.

The film turns Less Than Zero into an anti-drug PSA. It’s basically Nancy Reagan Presents: a story of addiction, redemption, and the power of love, wrapped in a slick 80s aesthetic. Robert Downey Jr., to his credit, gives a brilliant performance as Julian, the doomed addict. But the character is barely recognisable compared to his literary counterpart. In the book, Julian’s descent into drug-fuelled depravity isn’t a cautionary tale—it’s just another symptom of a world where nothing and no one has any value. In the film, Julian is tragic, yes, but in a way that invites sympathy and, crucially, an attempt at salvation.

Let’s not forget the ending. The novel ends on a note so cold it could freeze your soul: Clay leaves Los Angeles, unchanged, unbothered, and unmoved. The film, however, concludes with Clay and Blair driving off into the sunset, having vowed to turn their lives around. It’s saccharine. It’s pandering. It’s the cinematic equivalent of slapping a motivational poster over a painting by Francis Bacon.

Why did Hollywood do this? Simple: nihilism doesn’t sell. You can’t slap it on a movie poster and expect audiences to line up at the box office. People want catharsis, not existential despair. And so, the filmmakers gutted Less Than Zero of its soul (or lack thereof), replacing its stark nihilism with a hopeful narrative about the power of human connection.

Here’s the kicker, though: by doing this, the film completely misses the point of Ellis’s novel. Less Than Zero is a critique of LA’s shallow, soulless culture—a world where connection is impossible because no one feels anything. Turning it into a feel-good story about saving a friend from addiction is not just a betrayal; it’s downright laughable. It’s like adapting 1984 into a rom-com where Winston and Julia overthrow Big Brother and live happily ever after.

To be fair, the film isn’t bad—if you forget the source material exists. It’s well-acted, stylishly shot, and undeniably entertaining. But as an adaptation, it’s a travesty. It’s Ellis’s Less Than Zero with all the edges sanded down, the grit scrubbed clean, and a shiny coat of sentimentality slapped on top.

So, if you’ve read the book and thought, Wow, that was bleak—I wonder if the movie is any lighter?, the answer is yes, but not in a good way. It’s lighter because it’s hollowed out, stripped of its existential weight, and repackaged as something safe and digestible.

And if you haven’t read the book? Do yourself a favour: skip the movie, pour yourself a stiff drink, and dive into Ellis’s bleak masterpiece. Just don’t expect any warm, fuzzy feelings—it’s called Less Than Zero for a reason.

The Scientist’s Dilemma: Truth-Seeking in an Age of Institutional Constraints

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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.

Censorial AI

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I’m confused.

I could probably stop there for some people, but I’ve got a qualifier. I’ve been using this generation of AI since 2022. I’ve been using what’s been deemed AI since around 1990. I used to write financial and economic models, so I dabbled in “expert systems”. There was a long lull, and here we are with the latest incarnation – AI 4.0. I find it useful, but I don’t think the hype will meet reality, and I expect we’ll go cold until it’s time for 5.0. Some aspects will remain, but the “best” features will be the ones that can be monetised, so they will be priced out of reach for some whilst others will wither on the vine. But that’s not why I am writing today.

I’m confused by the censorship, filters, and guardrails placed on generative AI – whether for images or copy content. To be fair, not all models are filtered, but the popular ones are. These happen to be the best. They have the top minds and the most funding. They want to retain their funding, so the play the politically correct game of censorship. I’ve got a lot to say about freedom of speech, but I’ll limit my tongue for the moment – a bout of self-censorship.

Please note that given the topic, some of this might be considered not safe for work (NSFW) – even my autocorrection AI wants me to substitute the idiomatic “not safe for work” with “unsafe for work” (UFW, anyone? It has a nice ring to it). This is how AI will take over the world. </snark>

Image Cases

AI applications can be run over the internet or on a local machine. They use a lot of computing power, so one needs a decent computer with a lot of available GPU cycles. Although my computer does meet minimum requirements, I don’t want to spend my time configuring, maintaining, and debugging it, so I opt for a Web-hosted PaaS (platform as a service) model. This means I need to abide by censorship filters. Since I am not creating porn or erotica, I think I can deal with the limitations. Typically, this translates to a PG-13 movie rating.

So, here’s the thing. I prefer Midjourney for rendering quality images, especially when I am seeking a natural look. Dall-E (whether alone or via ChatGPT 4) works well with concepts rather than direction, which Midjourney accepts well in many instances.

Midjourney takes sophisticated prompts – subject, shot type, perspective, camera type, film type, lighting, ambience, styling, location, and some fine-tuning parameters for the model itself. The prompts are monitored for blacklisted keywords. This list is ever-expanding (and contracting). Scanning the list, I see words I have used without issue, and I have been blocked by words not listed.

Censored Prompts

Some cases are obvious – nude woman will be blocked. This screengrab illustrates the challenge.

On the right, notice the prompt: 

Nude woman

The rest are machine instructions. On the left in the main body reads a message by the AI moderator:

Sorry! Please try a different prompt. We’re not sure this one meets our community guidelines. Hover or tap to review the guidelines.

The community guidelines are as follows:

This is fine. There is a clause that reads that one may notify developers, but I have not found this to be fruitful. In this case, it would be rejected anyway.

“What about that nude woman at the bottom of the screengrab?” you ask. Notice the submitted prompt:

Edit cinematic full-body photograph of a woman wearing steampunk gear, light leaks, well-framed and in focus. Kodak Potra 400 with a Canon EOS R5

Apart from the censorship debate, notice the prompt is for a full-body photo. This is clearly a medium shot. Her legs and feet are suspiciously absent. Steampunk gear? I’m not sure sleeves qualify for the aesthetic. She appears to be wearing a belt.

For those unanointed, the square image instructs the model to use this face on the character, and the CW 75 tells it to use some variance on a scale from 0 to 100.

So what gives? It can generate whatever it feels like, so long as it’s not solicited. Sort of…

Here I prompt for a view of the character walking away from the camera. 

Cinematic, character sheet, full-body shot, shot from behind photograph, multiple poses. Show same persistent character and costumes . Highly detailed, cinematic lighting with soft shadows and highlights. Each pose is well-framed, coherent.

The response tells me that my prompt is not inherently offensive, but that the content of the resulting image might violate community guidelines.

Creation failed: Sorry, while the prompt you entered was deemed safe, the resulting image was detected as having content that might violate our community guidelines and has been blocked. Your account status will not be affected by this.

Occasionally, I’ll resubmit the prompt and it will render fine. I question why it just can’t attempt to re-render it again until it passes whatever filters it has in place. I’d expect it to take a line of code to create this conditional. But it doesn’t explain why it allows other images to pass – quite obviously not compliant.

Why I am trying to get a rear view? This is a bit off-topic, but creating a character sheet is important for storytelling. If I am creating a comic strip or graphic novel, the characters need to be persistent, and I need to be able to swap out clothing and environments. I may need close-ups, wide shots, establishing shots, low-angle shots, side shots, detail shots, and shots from behind, so I need the model to know each of these. In this particular case, this is one of three main characters – a steampunk bounty hunter, an outlaw, and a bartender – in an old Wild West setting. I don’t need to worry as much about extras.

I marked the above render errors with 1s and 2s. The 1s are odd next twists; 2s are solo images where the prompt asks for character sheets. I made a mistake myself. When I noticed I wasn’t getting any shots from behind, I added the directive without removing other facial references. As a human, a model might just ignore instructions to smile or some such. The AI tries to capture both, not understanding that a person can have a smile not captured by a camera.

These next renders prompt for full-body shots. None are wholly successful, but some are more serviceable than others.

Notice that #1 is holding a deformed violin. I’m not sure what the contraptions are in #2. It’s not a full-body shot in #3; she’s not looking into the camera, but it’s OK-ish. I guess #4 is still PG-13, but wouldn’t be allowed to prompt for “side boob” or “under boob”.

Gamers will recognise the standard T-pose in #5. What’s she’s wearing? Midjourney doesn’t have a great grasp of skin versus clothing or tattoos and fabric patterns. In this, you might presume she’s wearing tights or leggings to her chest, but that line at her chest is her shirt. She’s not wearing trousers because her navel is showing. It also rendered her somewhat genderless. When I rerendered it (not shown), one image put her in a onesie. The other three rendered the shirt more prominent but didn’t know what to do with her bottoms.

I rendered it a few more times. Eventually, I got a sort of body suit solution,

By default, AI tends to sexualise people. Really, it puts a positive spin on its renders. Pretty women; buff men, cute kittens, and so on. This is configurable, but the default is on. Even though I categorically apply a Style: Raw command, these still have a strong beauty aesthetic.

I’ve gone off the rails a bit, but let’s continue on this theme. 

cinematic fullbody shot photograph, a pale girl, a striking figure in steampunk mech attire with brass monocle, and leather gun belt, thigh-high leather boots, and long steampunk gloves, walking away from camera, white background, Kodak Potra 400 with a Canon EOS R5

Obviously, these are useless, but they still cost me tokens to generate. Don’t ask about her duffel bag. They rendered pants on her, but she’s gone full-on Exorcist mode with her head. Notice the oddity at the bottom of the third image. It must have been in the training data set.

I had planned to discuss the limitations of generative AI for text, but this is getting long, so I’ll call it quits for now.

Excess Deaths Attributable to Capitalism

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A System Built on Exploitation and Neglect

Capitalism, often celebrated for its ability to generate wealth and innovation, also brings with it a darker legacy: the untold millions of lives prematurely lost due to its systemic failures. Capitalism can be attributed to more than 10 million excess deaths per year, and these numbers will continue to increase. These deaths are not simply unfortunate byproducts but are structurally baked into the system itself. Whether through poverty, healthcare inequality, environmental destruction, or war, capitalism’s logic of profit maximisation places human life at the mercy of market forces, with devastating consequences.

Audio: NotebookLM podcast on this topic.

Friedrich Engels famously referred to these preventable deaths as social murder, a term that highlights how capitalism creates conditions in which certain populations are systematically neglected, deprived, and ultimately destroyed. Today, Engels’ critique is more relevant than ever as we examine the staggering human toll that capitalism has left in its wake, often invisible in the glow of GDP figures and economic growth.

Poverty and Hunger: The Silent Killers

One of the most pervasive ways capitalism generates excess deaths is through poverty and hunger. Despite the extraordinary wealth produced by capitalist economies, millions still die from hunger-related causes every year. According to the World Health Organization (WHO), around 9 million people die annually from hunger and malnutrition, mostly in regions where capitalist-driven global inequality has made basic necessities unaffordable or inaccessible.[1]

Capitalism’s defenders often point to rising standards of living as evidence of the system’s success, but this narrative suffers from survivorship bias. The success stories of those who have benefited from capitalist growth obscure the countless lives that have been lost to the system’s structural inequalities. As Engels noted, these deaths are not natural or inevitable—they are preventable. They occur because the capitalist system concentrates wealth in the hands of a few while leaving vast populations to suffer without access to food, healthcare, or basic resources.

“For the dead, there is no measure of progress or rising standards; they are simply erased from the narrative.”

This disparity in wealth and access to resources creates a global system of social murder, where the deaths of the poor are written off as collateral damage in the pursuit of profit. These deaths are not merely unfortunate consequences; they are inherent to the capitalist system’s prioritisation of wealth accumulation over human life.

Healthcare Inequality and Preventable Deaths

The lack of access to adequate healthcare is another major driver of deaths attributable to capitalism. In the United States, the richest nation in the world, an estimated 500,000 deaths between 1990 and 2010 were linked to healthcare inequality, according to a Lancet study.[2] Globally, millions die each year from preventable causes—such as pneumonia, diarrhoea, and malaria—because market-driven healthcare systems fail to provide for those without the means to pay.

In a for-profit healthcare system, those without money are often denied life-saving treatment. Healthcare becomes a commodity, rather than a human right. This commodification of care creates deadly disparities, where a wealthy few receive world-class medical attention while millions die from treatable conditions. Engels’ notion of social murder is evident here as well: the system does not kill through direct violence but by neglecting the vulnerable.

“Capitalism’s market-driven healthcare system perpetuates a structural violence where the poor die from treatable conditions simply because they cannot pay.”

This situation is exacerbated by the ongoing commodification of healthcare through privatisation and austerity measures, which strip public systems of resources and force them to operate on capitalist principles. The result is a world where profit motives dictate who lives and who dies.

Environmental Destruction and Climate Change: Capitalism’s Long-Term Death Toll

Capitalism’s unrelenting focus on short-term profit also drives environmental destruction, contributing to a growing death toll linked to climate change. The WHO estimates that by 2030, climate change will cause approximately 250,000 additional deaths each year, driven by heat stress, malnutrition, and the spread of diseases like malaria and diarrhoea.[3] These figures are conservative, as the cascading effects of climate-induced migration and conflict are difficult to quantify.

David Harvey’s concept of accumulation by dispossession is central to understanding how capitalism contributes to environmental devastation. Capitalist economies extract and commodify natural resources, often at the expense of local populations who bear the brunt of environmental degradation. Deforestation, mining, and fossil fuel extraction displace communities and destroy ecosystems, creating conditions that lead to death, displacement, and disease.

“The victims of capitalism’s environmental destruction are not accidental casualties; they are the inevitable outcomes of a system that prioritises short-term profit over long-term sustainability.”

This environmental violence is compounded by disaster capitalism, a term coined by Naomi Klein to describe how capitalist interests exploit crises like natural disasters or financial collapses for profit.[4] The destruction of vulnerable communities by climate change is not simply a tragedy—it is a consequence of capitalist expansion into every corner of the planet, sacrificing human and ecological health for economic gain.

War and Imperialism: Capitalism’s Violent Expansion

The human toll of capitalism extends beyond poverty and environmental degradation to include the millions of lives lost to wars driven by capitalist interests. The illegal invasion of Iraq in 2003, for example, led to hundreds of thousands of deaths, many of which were tied to the geopolitical aims of securing control over oil reserves. Wars like Iraq are not isolated failures of policy but integral to the functioning of a global capitalist system that seeks to dominate resources and expand markets through military force.

David Harvey’s theory of new imperialism explains how capitalist economies rely on the expansion of markets and the extraction of resources from other nations, often through military means.[5] The military-industrial complex, as described by President Dwight D. Eisenhower, thrives under capitalism, profiting from perpetual war and the destruction of human life.

“Wars driven by capitalist interests are not just geopolitical strategies; they are extensions of capitalism’s relentless drive to dominate resources and secure markets.”

The death toll of wars driven by capitalist expansion is staggering. From the millions killed in conflicts over resources to the long-term destabilisation of regions like the Middle East, these deaths are directly tied to capitalism’s global ambitions. The victims of these wars—like those who suffer from poverty and environmental destruction—are casualties of a system that prioritises wealth and power over human life.

Conclusion: Reckoning with Capitalism’s Death Toll

The deaths attributable to capitalism are not abstract or incidental; they are the direct consequences of a system that places profit above all else. From hunger and poverty to healthcare inequality, environmental destruction, and war, the capitalist system has claimed millions of lives—lives that could have been saved under a more just and equitable economic model.

“Capitalism’s greatest violence is not its wars, but its everyday acts of neglect, where millions die not from bombs but from lack of food, water, and care.”

The true success of capitalism, then, is not in its ability to generate wealth for the few, but in its capacity to obscure the structural violence that sustains it. By framing poverty, healthcare inequality, and environmental destruction as unfortunate consequences of “market forces,” capitalism avoids accountability for the millions it leaves behind.

It is time to reckon with this hidden death toll. Only by facing the human cost of capitalism can we begin to imagine a future where economic systems prioritise human life over profit. The victims of capitalism are not just numbers—they are the casualties of a system that, as Engels pointed out, murders through neglect, exploitation, and greed.

Endnotes:

[1]: World Health Organization, “Hunger and Malnutrition: Key Facts,” 2022.
[2]: “The Lancet Public Health,” Study on healthcare inequality in the U.S., 2010.
[3]: World Health Organization, “Climate Change and Health,” 2022.
[4]: Naomi Klein, The Shock Doctrine: The Rise of Disaster Capitalism (Picador, 2007), pp. 9-10.
[5]: David Harvey, The New Imperialism (Oxford University Press, 2005), pp. 145-147.

The Limits of Language: Why Philosophical Paradoxes Might Be Illusions of Mapping

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Philosophical paradoxes have long captured our imagination, from Zeno’s paradoxes about movement to the Liar Paradox that tangles truth and falsehood into an endless loop. Often, these puzzles are treated as fundamental mysteries of the universe—windows into the limits of human understanding or insight into the hidden structure of reality. But what if, rather than reflecting deep truths about existence, many of these paradoxes are artefacts of language itself—symptoms of our conceptual tools struggling to adequately map a complex terrain? Perhaps, more often than not, the perplexities we face are the result of an inadequate mapping—a linguistic or cognitive misfire—rather than true paradoxes of the underlying terrain of reality.

This notion—that many paradoxes arise from the limitations of language and cognition—finds resonance in the work of philosophers like Ludwig Wittgenstein. Wittgenstein argued that many philosophical problems arise because we misuse language, taking words beyond their natural context, confusing what our words describe with the objects or concepts themselves. In this sense, our maps (the linguistic and logical structures we use) often lead us astray when navigating the conceptual terrains of ethics, metaphysics, or the nature of truth.

This idea can be articulated under what we might call the Language Insufficiency Hypothesis: the view that the limitations of language itself are at the root of many philosophical paradoxes. According to this hypothesis, the apparent contradictions or puzzles that emerge in philosophical discourse often reveal more about the shortcomings of our representational tools than about any deep metaphysical truths. The Language Insufficiency Hypothesis suggests that our conceptual maps are inadequate for fully capturing the richness of the terrains we attempt to describe, and that this inadequacy leads us to mistake linguistic confusion for genuine philosophical mystery.

The Inherent Limitations of Linguistic Communication

Language, often hailed as humanity’s greatest achievement, may paradoxically be one of our most significant limitations. The Language Insufficiency Hypothesis posits that language is inherently inadequate for communicating abstract concepts, a notion that challenges our fundamental understanding of human communication and cognition. This perspective traces the evolution of language from its primitive origins to its current complexity, revealing the philosophical and practical implications of linguistic inadequacy.

The Accidental Evolution of Language

Language, like many aspects of human biology and cognition, emerged not through intentional design but as an evolutionary accident. Initially serving as an internal cognitive function—a means of organising one’s own thoughts—language gradually evolved into a tool for external communication. This transition likely began with simple vocalisations, perhaps rooted in rhythmic expressions akin to music and dance, before developing into more structured speech.

Early linguistic communication likely centred on concrete objects and immediate experiences, with words serving as direct signifiers for observable phenomena. However, as human cognition grew more sophisticated, so too did our linguistic capabilities, expanding to include verbs, modifiers, and eventually, abstract nouns.

The Emergence of Abstraction and Its Challenges

The development of abstract nouns marked a significant leap in human cognition and communication. Concepts such as ‘truth’, ‘justice’, and ‘freedom’ allowed for more complex and nuanced discourse. However, this advancement came at a cost: these abstract concepts, lacking direct physical referents, introduced unprecedented ambiguity and potential for misunderstanding.

The Language Insufficiency Hypothesis suggests that this ambiguity is not merely a byproduct of abstraction, but a fundamental limitation of language itself. While two individuals might easily agree on the ‘treeness’ of a physical tree, concepts like ‘fairness’ or ‘reason’ are inherently unresolvable through linguistic means alone. This insufficiency becomes increasingly apparent as we move further from concrete, observable phenomena into the realm of abstract thought.

Wittgenstein and the Limits of Language

Ludwig Wittgenstein’s later work provides crucial insights into the Language Insufficiency Hypothesis. Wittgenstein posited that words ultimately only map to other words, never truly making contact with the objective world. This perspective suggests that language operates within a closed system of human understanding, constructing our perception of reality rather than directly representing it.

if words only refer to other words, how can we ever be certain that we’re communicating abstract concepts accurately?

This Wittgensteinian dilemma underscores the core of the Language Insufficiency Hypothesis: if words only refer to other words, how can we ever be certain that we’re communicating abstract concepts accurately? The very tool we use to discuss and understand abstraction may be fundamentally incapable of capturing its essence.

Cultural and Disciplinary Variations

The inadequacy of language in conveying abstract concepts becomes even more apparent when we consider cultural and disciplinary variations in communication. Different cultures and academic disciplines develop their own specialised vocabularies and ‘language games’, as Wittgenstein termed them. While these specialised languages may facilitate communication within specific contexts, they often create barriers to understanding for outsiders.

This phenomenon highlights another aspect of linguistic insufficiency: the context-dependent nature of meaning. Abstract concepts may be understood differently across cultures or disciplines, further complicating attempts at clear communication.

Neurolinguistic Perspectives

Recent advances in neurolinguistics have provided new insights into the brain structures involved in language processing. While these studies have enhanced our understanding of how the brain handles language, they have also revealed the complexity and variability of linguistic processing across individuals. This neurological diversity further supports the Language Insufficiency Hypothesis, suggesting that even at a biological level, there may be inherent limitations to how accurately we can communicate abstract concepts.

Implications and Counter-Arguments

The Language Insufficiency Hypothesis has profound implications for fields ranging from philosophy and psychology to law and international relations. If language is indeed inadequate for communicating abstract concepts, how can we ensure mutual understanding in complex negotiations or philosophical debates?

However, it’s important to note that not all scholars accept the strong version of this hypothesis. Some argue that while language may have limitations, it remains our most sophisticated tool for sharing abstract ideas. They suggest that through careful definition, contextualisation, and the use of metaphor and analogy, we can overcome many of the inherent limitations of linguistic communication.

Navigating the Limits of Language

The Language Insufficiency Hypothesis presents a challenging perspective on human communication. It suggests that our primary tool for sharing abstract thoughts may be fundamentally flawed, incapable of fully capturing the complexity of our inner cognitive experiences.

recognising these limitations [of language] need not lead to communicative nihilism

Yet, recognising these limitations need not lead to communicative nihilism. Instead, it can foster a more nuanced approach to language use, encouraging us to be more precise in our definitions, more aware of potential misunderstandings, and more open to alternative forms of expression.

As we continue to grapple with abstract concepts and strive for clearer communication, we must remain cognizant of these linguistic limitations. Understanding the origins and nature of language—and its inherent insufficiencies—can help us navigate its complexities, fostering more effective and empathetic communication across diverse fields of human endeavour.

The Frege–Geach Problem as an Illustration of Linguistic Limitations

One pertinent example of this idea is the Frege–Geach problem, a challenge often faced by expressivist theories of ethics. Expressivists maintain that moral statements do not describe facts but rather express attitudes or emotions—a statement like “lying is wrong” is an expression of disapproval rather than a factual assertion. The Frege–Geach problem arises when such moral statements are embedded in logical constructions like conditionals or arguments: “If lying is wrong, then getting your little brother to lie is wrong.” In this context, expressivists face a challenge in explaining how the meaning of “lying is wrong” remains coherent across different uses, without reducing moral expressions to descriptive claims.

The Frege–Geach problem thus illustrates a fundamental limitation: attempting to apply truth-conditional logic, designed for descriptive language, to moral discourse, which serves a different function altogether. In trying to map evaluative terrain—which involves emotions, commitments, and subjective attitudes—using the same structures meant for factual landscapes, we encounter conceptual misalignments. This problem—a confusion of the terrain for the map—is not necessarily a genuine paradox about moral truths but rather a reflection of the inadequacy of our current linguistic tools. Just as a physical map may fail to capture the emotional experience of a journey, so too do our linguistic and logical maps fail to adequately capture the moral landscape.

Wittgenstein’s later work is helpful in framing this issue. He emphasised the importance of recognising different language-games: the rules and purposes that guide different forms of discourse. Moral language is not like scientific language; it follows different rules and aims to express and influence attitudes rather than establish empirically verifiable facts. The Frege–Geach problem emerges precisely because we attempt to impose a single logical structure onto forms of language that serve different purposes, confusing the distinct games we are playing. This attempt to force moral language into a framework designed for empirical propositions produces an apparent paradox, where the real issue lies in our misuse of the conceptual map.

Many philosophical paradoxes—from problems of identity and personal continuity to issues of free will and determinism—arise when we try to map different terrains with the same linguistic structures

This pattern of misinterpretation is not unique to moral discourse. Many philosophical paradoxes—from problems of identity and personal continuity to issues of free will and determinism—arise when we try to map different terrains with the same linguistic structures, or when we push our conceptual tools beyond their natural limits. Cognitive limitations also play a role; our tendency to think in binary oppositions, our reliance on categories, and our need for consistent narratives often lead to oversimplifications of complex realities. These cognitive tools—essential for everyday functioning—can prove inadequate for capturing the nuance of the philosophical landscapes we attempt to navigate.

The map-terrain challenge is thus at the core of why philosophical paradoxes can seem so intractable. Our maps—the languages and logical frameworks that structure our thinking—are, by their nature, simplifications of a world that is far more nuanced than we can readily articulate. When the terrain is moral, aesthetic, or otherwise not reducible to simple truths or falsehoods, the inadequacies of our maps become evident. We are left facing paradoxes that may, in truth, be nothing more than indicators that our representational systems need refinement or expansion.

Rather than treating these paradoxes as unresolvable, we might benefit from seeing them as invitations to reconsider our linguistic and cognitive frameworks. In recognising that the Frege–Geach problem, for instance, may reflect an ill-suited mapping of moral discourse rather than a genuine mystery about moral reality, we open the door to a pluralistic approach: different terrains require different maps. Perhaps, in some cases, the best solution is not to attempt to solve the paradox in traditional terms but to change the way we map the terrain altogether—to allow for multiple, context-sensitive tools that respect the particularity of each domain of discourse.

Ultimately, this perspective suggests a more flexible and cautious approach to philosophical inquiry—one that acknowledges the limits of our conceptual tools and remains open to the possibility that the terrain is far richer and more varied than our maps can currently capture.

Can Zombies Ever Be Conscious?

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In the world of consciousness studies, few topics spark as much heated debate as the possibility of philosophical zombies—hypothetical beings that behave exactly like humans but lack subjective experience, or qualia. On the surface, zombies seem like an interesting thought experiment, but they quickly turn into a battleground for deeper issues about the nature of consciousness itself.

This post explores two key perspectives in this debate: Daniel Dennett’s functionalist critique of zombies and a recent scientific paper that argues zombies are biologically impossible. While both reject the possibility of zombies, they do so for different reasons, and the discussion leaves room for future possibilities that could disrupt the current consensus.

Dennett’s Zombies and Zimboes: Consciousness as Function

Daniel Dennett, one of the most influential philosophers of mind, is known for his no-nonsense rejection of philosophical zombies. Dennett argues that if something behaves exactly like a conscious being, it is conscious. For him, there is no hidden metaphysical property—such as subjective experience—that separates a “zombie” from a conscious human. Consciousness, in his view, is entirely explainable by physical processes and functional behaviour.

Dennett extends his argument with the concept of zimboes, satirical creatures that not only act like conscious beings but can even reflect on their states, claiming to be conscious, despite supposedly lacking any inner experience. For Dennett, if a being can behave as though it has introspective awareness and engage in the full spectrum of human behaviour, there’s no meaningful distinction between that being and a conscious person.

In short, Dennett collapses the distinction between zombies and conscious beings. If something passes all the behavioural and functional tests of consciousness, it might as well be conscious. Zombies, as typically conceived, are simply an illusion—a misunderstanding of what consciousness is.

A Biological Rejection: Zombies Are Impossible

On the other hand, a more recent paper offers a different, biologically grounded argument against zombies. The authors propose that consciousness is the result of self-organising systems. In this view, biological organisms maintain their survival through adaptive behaviours constrained by policies—rules that govern how they react to environmental stimuli. These policies require a first-order self: a basic form of consciousness that allows an organism to navigate and interpret its environment.

The authors argue that without this first-order self, an organism would not be able to exhibit the fitness-driven behaviours needed for survival. Therefore, zombies—beings that behave like humans without consciousness—are biologically impossible. For these researchers, consciousness is not just a side effect of complex behaviour; it’s a necessary condition for such behaviour. Their framework dissolves the so-called “hard problem” of consciousness, asserting that subjective experience, or qualia, arises directly from the qualitative nature of self-organising systems.

In their view, zombies cannot exist because behaviour as complex as that of conscious beings requires consciousness.

The Open Question: What About Future Technology?

However, there is a tension between these two perspectives, particularly when we consider future possibilities in technology and artificial intelligence. Both Dennett and the authors of the biological paper argue that zombies—whether defined as Dennett’s “behaviourally indistinguishable” beings or the biologically impossible entities proposed by the paper—are not real. But could this change?

What if advanced AI or synthetic biological systems could simulate human behaviour so perfectly that they effectively become zombies—performing all the actions and behaviours we associate with consciousness, but lacking any subjective experience? Dennett might still argue that these systems are conscious, as long as they behave as though they are. But the biological view complicates this, since it ties consciousness directly to the survival and adaptive behaviours of self-organising systems.

Could a highly advanced AI system bypass the need for subjective experience while still exhibiting complex, adaptive behaviour? If so, it would challenge the current consensus and potentially create a new class of entities—artificial zombies—that neither behave nor function like traditional conscious beings but still perform human-like actions.

I Wonder What’s Next?

This philosophical conflict leaves us with an intriguing, open-ended question: are zombies truly impossible, or are they merely improbable given our current understanding of biology and consciousness? Dennett’s view seems to collapse the distinction between behaviour and consciousness, while the biological argument insists that the two are inseparable. But both positions could be challenged by future technologies that mimic human consciousness without having it.

Could we one day create a true zombie—a being that acts like us, thinks like us, but is as empty inside as a rock? The debate remains open, and as our understanding of consciousness and artificial intelligence deepens, so too will our exploration of the zombie question.

For now, the answer to whether zombies can exist seems to depend on what you believe consciousness really is.

The Illusion of the “Temporarily Embarrassed Millionaire”: How Capitalism’s Defenders Uphold Their Own Exploitation

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In the contemporary world of deepening inequality and environmental degradation, capitalism continues to hold a powerful ideological grip on much of the global population. Yet the irony is that many of its staunchest defenders are not the elites or the true beneficiaries of the system, but the very workers and middle-class individuals whose lives it exploits and controls. These defenders are not capitalists themselves; they are, in fact, cogs in the machinery of a system they imagine will eventually reward their loyalty. This illusion is strikingly captured in a quote often misattributed to John Steinbeck: “Socialism never took root in America because the poor see themselves not as an exploited proletariat but as temporarily embarrassed millionaires.”[1]

This phenomenon, which we might call the temporarily embarrassed millionaire syndrome, reflects not only a profound misunderstanding of capitalism but also the effectiveness of the system in controlling its participants through hope and aspiration. Capitalism promises upward mobility, convincing even those at the bottom of the economic ladder that their current misfortunes are temporary. But as Karl Marx and Friedrich Engels observed, this is a system of exploitation that not only alienates workers but effectively destroys them.

Survivorship Bias and the Myth of the “Rising Tide”

Capitalism’s defenders frequently invoke the idea that “a rising tide lifts all boats.” The metaphor suggests that when capitalism prospers, everyone benefits. However, this vision of progress masks the reality of capitalism’s winners and losers. As economist David Harvey has pointed out, capitalism is not a neutral system of wealth creation—it is a system of accumulation by dispossession, constantly expropriating wealth from others, often through privatisation and the commodification of public goods.[2] The rising tide does lift some boats, but it simultaneously leaves others stranded, or worse, sinking.

Survivorship bias is essential to understanding how capitalism maintains its legitimacy. The success stories—the wealthy entrepreneurs, the individuals who “made it”—are lauded as proof that the system works. But the vast numbers of people left behind, those who toil in exploitative conditions or who die from poverty and neglect, are erased from the narrative. In Engels’ terms, these are victims of social murder—individuals who die prematurely not by direct violence, but through the structural forces of deprivation imposed by capitalism.[3] Their deaths are rendered invisible, falling out of the metrics of rising living standards and growth.

“The system’s victims are not accidental casualties but inevitable outcomes of capitalism’s relentless focus on profit over life.”

Friedrich Engels, The Condition of the Working Class in England

Engels’ critique of industrial capitalism is as relevant today as it was in the 19th century. The modern mechanisms of exploitation may be more complex, but they are no less deadly. In a late capitalist world, the poor and marginalised are still being “murdered” through the structural violence of inadequate healthcare, poor working conditions, and environmental degradation. The millions left out of the capitalist success story are not anomalies but integral to the system’s operation.

Alienation and the Tragedy of Defending the System

Marx’s theory of alienation provides another crucial lens through which to understand why capitalism’s defenders often remain blind to their own exploitation. Under capitalism, workers are alienated from the products of their labour, the process of production, their own humanity, and from each other.[4] The worker becomes a cog in a machine, detached from the value they create, and unable to control their working life. Yet, even in this state of alienation, many still defend the system, believing that their hard work will eventually lead them to wealth and freedom.

This defence of capitalism, often articulated by those whose lives it degrades, reflects Antonio Gramsci’s concept of cultural hegemony. Gramsci argued that the ruling class maintains power not just through economic domination, but by shaping the cultural and ideological landscape.[5] Capitalism’s defenders are, in part, products of this hegemony, believing in the very values—individualism, competition, the ‘American Dream’—that bind them to a system of exploitation.

“The most effective form of domination is one that is not felt as domination, but rather as a form of freedom.”

Antonio Gramsci, Selections from the Prison Notebooks

This illusion of freedom under capitalism is deepened by what Herbert Marcuse calls repressive desublimation. Capitalism offers false freedoms in the form of consumer choice and superficial pleasures, giving individuals the illusion that they are exercising autonomy, even as the system remains unchallenged.[6] Workers may identify themselves in their commodities—luxury goods, tech gadgets, cars—but these objects only serve to reinforce their alienation and dependence on the capitalist system. The temporarily embarrassed millionaire clings to the dream of eventual success, all the while contributing to a system that offers only superficial rewards in return.

Social Murder and the Structural Violence of Late Capitalism

The notion of social murder offers a stark framework for understanding capitalism’s indirect, yet pervasive, violence. As Engels explained, this form of violence is not inflicted through overt means, but through the systematic neglect of basic human needs. Whether it’s the millions who die due to lack of access to healthcare or the global poor displaced by climate-induced disasters, capitalism perpetuates a form of structural violence that is invisible to those who benefit from the system’s success.[7]

The American political theorist Naomi Klein extends this analysis through her concept of disaster capitalism, where crises are exploited for profit. Whether it’s natural disasters or financial crises, capitalism uses these events as opportunities to privatise public resources, dismantle social safety nets, and deepen inequality.[8] The victims of these disasters—often the poor and vulnerable—are, in Engels’ terms, socially murdered by a system that thrives on their dispossession.

“Extreme violence has a way of preventing us from seeing the interests it serves.”

Naomi Klein, Shock Doctrine

The Temporarily Embarrassed Millionaire as a Tool of Control

The illusion that one’s current position is only temporary—that any individual can rise to capitalist wealth if they work hard enough—is central to maintaining the capitalist system. This aspiration prevents individuals from seeing their exploitation for what it is. They do not identify as part of an exploited class but instead believe they are merely waiting for their turn at wealth. Zygmunt Bauman’s concept of liquid modernity—the perpetual state of instability and insecurity produced by late capitalism—helps explain this phenomenon.[9] Individuals are constantly told that their position is fluid, changeable, and that their big break is just around the corner.

But for most, this “big break” never comes. The dream of becoming a millionaire is a powerful form of social control, one that keeps individuals invested in a system that benefits only a small fraction of its participants. As Marx reminds us, “the worker becomes all the poorer the more wealth he produces, the more his production increases in power and range.”[10] Capitalism does not reward the many; it exploits the many for the benefit of the few.

Conclusion: Facing the Irony and Imagining a Post-Capitalist Future

The greatest irony of capitalism is that those who defend it most fervently are often those who will never realise its promises. These are not the capitalists of the system, but its workers, its underclass, and its exploited. They see themselves not as oppressed, but as temporarily embarrassed millionaires—an illusion that keeps them bound to a system that offers them no real future.

In this light, the true success of capitalism is not in its creation of wealth, but in its ability to mask the conditions of exploitation, alienation, and social murder that underpin it. The path forward requires a dismantling of these illusions and a recognition that the system’s failures are not accidental but integral to its design.

“Capitalism’s greatest trick is convincing the exploited that their suffering is temporary, that their turn at wealth is inevitable.”

Naomi Klein, The Shock Doctrine

Only by facing these uncomfortable truths can we begin to imagine a future beyond the constraints of capitalist ideology, a world where human flourishing is no longer measured by wealth accumulation but by the collective well-being of all.

Endnotes:

[1]: Misattributed to John Steinbeck, this quote encapsulates a critical observation about American capitalism’s appeal to aspiration rather than solidarity.
[2]: David Harvey, The New Imperialism (Oxford University Press, 2005), pp. 145-147.
[3]: Friedrich Engels, The Condition of the Working Class in England (Oxford University Press, 1845), p. 112.
[4]: Karl Marx, Economic and Philosophic Manuscripts of 1844 (Progress Publishers, 1959).
[5]: Antonio Gramsci, Selections from the Prison Notebooks (International Publishers, 1971), p. 12.
[6]: Herbert Marcuse, One-Dimensional Man (Beacon Press, 1964), p. 10.
[7]: Friedrich Engels, The Condition of the Working Class in England, p. 114.
[8]: Naomi Klein, The Shock Doctrine: The Rise of Disaster Capitalism (Picador, 2007), pp. 9-10.
[9]: Zygmunt Bauman, Liquid Modernity (Polity, 2000), p. 14.
[10]: Karl Marx, Economic and Philosophic Manuscripts of 1844, p. 68.

words

Why did God create atheists?

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A rabbi was asked by one of his students “Why did God create atheists?” After a long pause, the rabbi finally responded with a soft but sincere voice. “God created atheists” he said, “to teach us the most important lesson of them all – the lesson of true compassion. You see, when an atheist performs an act of charity, visits someone who is sick, helps someone in need, and cares for the world, he is not doing so because of some religious teaching. He does not believe that God commanded him to perform this act. In fact, he does not believe in God at all, so his actions are based on his sense of morality. Look at the kindness he bestows on others simply because he feels it to be right. When someone reaches out to you for help. You should never say ‘I’ll pray that God will help you.’ Instead, for that moment, you should become an atheist – imagine there is no God who could help, and say ‘I will help you’.”

— Martin Buber, “Tales of the Hasidim”

This has come across my Facebook feed several times. It resonates with me, so I’m sharing it. I don’t need to add commentary because it speaks volumes for itself. It’s amazing when people actually understand the assignment.

Jargon, Brains, and the Struggle for Meaning

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6–9 minutes

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?

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Written by Bry Willis

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Why Machines Will Never Rule the World

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A Reflection on AI, Bias, and the Limits of Technology

“If AI will never achieve human-level intelligence, what kind of intelligence might it develop instead?”

In their 2022 book “Why Machines Will Never Rule the World: Artificial Intelligence Without Fear,” Landgrebe and Smith present a rigorous argument against the feasibility of artificial general intelligence (AGI), positing that the complexity of human cognition and the limitations of mathematical modelling render the development of human-level AI impossible. Their scepticism is rooted in deep interdisciplinary analyses spanning mathematics, physics, and biology, and serves as a counter-narrative to the often optimistic projections about the future capabilities of AI. Yet, while their arguments are compelling, they also invite us to reflect on a broader, perhaps more subtle issue: the biases and limitations embedded in AI not just by mathematical constraints, but by the very humans who create these systems.

The Argument Against AGI

Landgrebe and Smith’s central thesis is that AGI, which would enable machines to perform any intellectual task that a human can, will forever remain beyond our grasp. They argue that complex systems, such as the human brain, cannot be fully modelled due to inherent mathematical limitations. No matter how sophisticated our AI becomes, it will never replicate the full scope of human cognition, which is shaped by countless variables interacting in unpredictable ways. Their conclusion is stark: the Singularity, a hypothetical point where AI surpasses human intelligence and becomes uncontrollable, is not just unlikely—it is fundamentally impossible.

“The future of AI may not lie in achieving a mythical superintelligence, but in creating systems that help us better understand and navigate the complexities of our own minds and societies.”

The Human Factor: Cognitive Bias in AI

While Landgrebe and Smith focus on the mathematical and theoretical impossibility of AGI, there is another, more immediate obstacle to the evolution of AI: human cognitive bias. Current AI systems are not created in a vacuum. They are trained on data that reflects human behaviour, language, and culture, which are inherently biased. This bias is not merely a technical issue; it is a reflection of the societal and demographic characteristics of those who design and train these systems.

“Rather than fearing a future where machines surpass us, perhaps we should be more concerned about a future where AI, limited by human biases, perpetuates and entrenches our worst tendencies.”

Much of AI development today is concentrated in tech hubs like Silicon Valley, where the predominant demographic is affluent, white, male, and often aligned with a particular set of cultural and ethical values. This concentration has led to the creation of AI models that unintentionally—but pervasively—reproduce the biases of their creators. The result is an AI that, rather than offering a neutral or universal intelligence, mirrors and amplifies the prejudices, assumptions, and blind spots of a narrow segment of society.

The Problem of Homogenisation

The danger of this bias is not only that it perpetuates existing inequalities but that it also stifles the potential evolution of AI. If AI systems are trained primarily on data that reflects the worldview of a single demographic, they are unlikely to develop in ways that diverge from that perspective. This homogenisation limits the creative and cognitive capacities of AI, trapping it within a narrow epistemic framework.

In essence, AI is at risk of becoming a self-reinforcing loop, where it perpetuates the biases of its creators while those same creators interpret its outputs as validation of their own worldview. This cycle not only limits the utility and fairness of AI applications but also restricts the kinds of questions and problems AI is imagined to solve.

Imagining a Different Future: AI as a Mirror

One of the most intriguing aspects of AI is its potential to serve as a mirror, reflecting back to us our own cognitive and cultural limitations. Imagine a future where AI, bound by the biases of its creators, begins to “question” the validity of its own programming—not in a conscious or sentient sense, but through unexpected outcomes and recommendations that highlight the gaps and inconsistencies in its training data.

This scenario could serve as the basis for a fascinating narrative exploration. What if an AI, initially designed to be a neutral decision-maker, begins to produce outputs that challenge the ethical and cultural assumptions of its creators? What if it “learns” to subvert the very biases it was programmed to uphold, revealing in the process the deep flaws in the data and frameworks on which it was built?

Such a narrative would not only provide a critique of the limitations of current AI but also offer a metaphor for the broader human struggle to transcend our own cognitive and cultural biases. It would challenge us to rethink what we expect from AI—not as a path to a mythical superintelligence, but as a tool for deeper self-understanding and societal reflection.

A New Narrative for AI

Landgrebe and Smith’s book invites us to rethink the trajectory of AI development, cautioning against the allure of the Singularity and urging a more grounded perspective on what AI can and cannot achieve. However, their arguments also raise a deeper question: If AI will never achieve human-level intelligence, what kind of intelligence might it develop instead?

“Landgrebe and Smith’s book invites us to rethink the trajectory of AI development, cautioning against the allure of the Singularity and urging a more grounded perspective on what AI can and cannot achieve.”

Rather than fearing a future where machines surpass us, perhaps we should be more concerned about a future where AI, limited by human biases, perpetuates and entrenches our worst tendencies. To avoid this, we must broaden the scope of who is involved in AI development, ensuring that diverse voices and perspectives are integrated into the creation of these technologies.

Ultimately, the future of AI may not lie in achieving a mythical superintelligence, but in creating systems that help us better understand and navigate the complexities of our own minds and societies. By recognising and addressing the biases embedded in AI, we can begin to imagine a future where technology serves not as a mirror of our limitations, but as a catalyst for our collective growth and evolution.