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title: o1-pro-on-scale-and-ai-attempted-humor

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# o1-pro-on-scale-and-ai-attempted-humor

Great, I’ll dive into research on the future of AI in relation to personalization, creativity, and education—especially as it contrasts with artisanal, small-scale practices like block printing. I’ll also revisit the key thinkers mentioned (Benjamin, Adorno, Plato, Hegel, etc.) to help deepen the philosophical tension you're circling between scale vs singularity, the one vs the many, and reality vs simulation.

I’ll be back soon with a well-developed, theoretically-rich essay draft in a tone somewhere between Jameson and Zizek.

# Cat on a Hot Digital Surfboard: Generative AI, Block Printing, and the Quest for the “Real”

## From Slack Joke to Block Print: An Anecdotal Prelude

One afternoon, in the throes of procrastination on our lab’s Slack channel, a colleague tossed out a whimsical challenge: “Can we get an AI to make a poster of a cat water-skiing?” The suggestion was half in jest, but our curiosity was piqued. A few prompt iterations later, we were greeted by exactly that – an AI-generated image of a ginger cat gripping a tow-rope, miniature skis strapped to its paws, skimming across a turquoise bay. The image was **uncannily** convincing at first glance: sunlit spray, the cat’s fur fluttering, a determined feline gaze. And yet, something felt *off*. The cat’s eyes were just a tad too human, its posture a touch too stiff – subtle tells of unreality lurking in the pixels. We circulated the image with giddy amusement, marveling at how our idle Slack humor had conjured this digital chimera. But then our conversation took a turn: what if we turned this ephemeral AI gag into a tangible artifact? 

We embarked on a **poster-making project** to materialize the cat on water-skis. The plan was to degrade and transform the AI image by layering it with the textures of traditional block printing. First, we printed the AI-generated cat image in high-contrast grayscale, intentionally sacrificing the slick precision of the digital original. Then, using a carved linoleum block, we overprinted a wash of analog texture – a rough cyan backdrop with ragged, inky edges and a woodgrain-like pattern intruding upon the scene. The crisp lines of the AI image met the subtle imperfections of hand printing: slight mis-registrations between layers, variations in ink thickness, and the occasional speckle where a wood fiber or dust mote left its mark. In short, we gave the AI cat some **“reality effects.”** 

By **“reality effects,”** I’m alluding to Roland Barthes’s notion of *l’effet de réel*, the idea that superfluous details can signal authenticity in art and literature ([Effect of reality - Wikipedia](https://en.wikipedia.org/wiki/Effect_of_reality#:~:text=Barthes%20first%20suggested%20this%20concept,1)). Barthes observed that a stray detail in a realist novel – say, mentioning a **barometer** hanging on the wall with no plot relevance – creates an illusion of life’s presence ([Effect of reality - Wikipedia](https://en.wikipedia.org/wiki/Effect_of_reality#:~:text=Barthes%20first%20suggested%20this%20concept,1)). In our case, the stray imperfections introduced by block printing served a similar purpose: they indexed a physical process, a moment of making, thereby anchoring the fantastical image in a material reality. The **grain of the ink**, the ridges pressed by the carved linoleum, even the subtle unevenness where my hand applied less pressure – all these tactile “residues” on the poster surface acted like Barthes’s barometer. They were not part of the image’s subject (a cat joyriding on a wake), but they signified *reality itself*. The French theorist might nod in approval here: in the absence of any actual referent (no real cat ever did this stunt), we manufactured a *referential illusion* through texture. As one commentator on Barthes puts it, the photograph paradoxically gains a kind of **“grit” and texture that chafes us with a sense of the real** ([Haptic Reading | The Purgatory Press](https://johnculbert.wordpress.com/2014/01/17/haptic-reading-2/#:~:text=Roland%20Barthes%E2%80%99%20study%20of%20photography%2C,%E2%80%A6)). Our block-printed layers, similarly, added grit and grain to the AI image, a patina of presence to what was otherwise a hallucinatory digital concoction. 

This anecdotal experiment – equal parts absurd and illuminating – became the springboard for deeper reflection. What started as a joke about a water-skiing cat led us into a maze of philosophical and cultural questions. **Why did adding a simple block-print overlay make the AI image feel more satisfying?** What does that say about our craving for the tangible and the authentic in an era when **generative AI** can spit out endless unique images on demand? As we hung the finished posters around the lab (a ginger cat eternally frozen mid-splash, now bestowed with the aura of handcraft), we joked that we had performed a minor miracle: granting an AI image an **“aura”** – that elusive glow of authenticity Walter Benjamin famously said was lost in mechanical reproduction ([The Work of Art in the Age of Mechanical Reproduction - Wikipedia](https://en.wikipedia.org/wiki/The_Work_of_Art_in_the_Age_of_Mechanical_Reproduction#:~:text=The%20aura%20of%20a%20work,product%29%20diminishes%20the)) ([The Work of Art in the Age of Mechanical Reproduction - Wikipedia](https://en.wikipedia.org/wiki/The_Work_of_Art_in_the_Age_of_Mechanical_Reproduction#:~:text=aesthetic%20value%20of%20the%20original,8)). In the pages that follow, I’d like to unpack the stakes of that miracle (or perhaps tragedy). With a playful, theory-informed lens – equal parts Benjamin and Barthes, Plato and *The Matrix*, Adorno and **Adorno’s worst nightmare** (a cat on skis mass-printed for capitalist consumption?) – I will explore what our poster project reveals about generative AI, art, and pedagogy in the age of infinite reproducibility. Consider this a journey through the **magic midpoint** between the one and the many, the digital and the tactile, the infinitely scalable and the preciously finite.

## Aura, Authenticity, and the Age of Algorithmic Reproduction

When Walter Benjamin wrote *“The Work of Art in the Age of Mechanical Reproduction”* in 1935, he probably didn’t imagine a scenario involving AI-generated cat posters – but his insights resonate uncannily with our little project. Benjamin argued that mechanically reproduced art (he was thinking of photographs, lithographs, film, etc.) lacks the unique presence he called **aura** ([The Work of Art in the Age of Mechanical Reproduction - Wikipedia](https://en.wikipedia.org/wiki/The_Work_of_Art_in_the_Age_of_Mechanical_Reproduction#:~:text=The%20aura%20of%20a%20work,product%29%20diminishes%20the)). *“Even the most perfect reproduction of a work of art,”* he wrote, *“is lacking in one element: its presence in time and space, its unique existence at the place where it happens to be.”* ([The Work of Art in the Age of Mechanical Reproduction - Wikipedia](https://en.wikipedia.org/wiki/The_Work_of_Art_in_the_Age_of_Mechanical_Reproduction#:~:text=The%20aura%20of%20a%20work,product%29%20diminishes%20the)) In other words, a painting has aura because it has a singular here and now – the original canvas soaked in *this* pigment, touched by *that* artist’s hand, hanging in *that* particular gallery. A photograph or lithograph, by contrast, can be multiplied and seen anywhere, detached from the original context, thus “devaluing” the aura ([The Work of Art in the Age of Mechanical Reproduction - Wikipedia](https://en.wikipedia.org/wiki/The_Work_of_Art_in_the_Age_of_Mechanical_Reproduction#:~:text=,of%20revolutionary%20demands%20in%20the)) ([The Work of Art in the Age of Mechanical Reproduction - Wikipedia](https://en.wikipedia.org/wiki/The_Work_of_Art_in_the_Age_of_Mechanical_Reproduction#:~:text=aesthetic%20value%20of%20the%20original,8)). 

Now consider the AI-generated image. It is, in a sense, the ultimate in reproducibility – a native digital product with no singular original at all. There is no *Ur*-cat on water-skis; the image is conjured from the statistical stew of millions of other images. We might say the *algorithm* is the “original,” but that algorithm (a diffusion model, a GAN, etc.) is itself a reproducible piece of code, not a one-off creation. Each output image it generates is a copy without an original – or perhaps an original without copies, since it’s unique, but unique in a way that **any number of other uniques can be churned out ad infinitum**. The aura, in Benjamin’s sense, doesn’t even have a chance to attach itself here. The AI image’s existence is ephemeral (on a screen, or as data) and instantly multipliable (ctrl+c, ctrl+v). It is, if anything, *born without aura*. 

And yet, when we ran that cat image through a hand-operated printing process, something strange happened. We *felt* – perhaps delusionally – that we were **giving it an aura**, or at least a whiff of authenticity. The block-printed poster now has a singular existence: each print we pulled is slightly different, each one an artifact of a particular ink batch and a particular pull of the baren (printing tool) on the paper. If Benjamin argued that what withers in the age of mechanical reproduction is the aura ([The Work of Art in the Age of Mechanical Reproduction - Wikipedia](https://en.wikipedia.org/wiki/The_Work_of_Art_in_the_Age_of_Mechanical_Reproduction#:~:text=Miklos%20Legrady%20takes%20issue%20with,does%20not%20come%20from%20the)), our experiment was a kind of reverse-engineering: reintroducing a *manual* step to an infinitely reproducible image, hoping to rehydrate some aura. The resulting poster *is* “present in time and space” in a way the digital image was not – you can point to one print and say, *that one is mine, number 3 of 10, ink a bit lighter on the left side, created on a Wednesday afternoon when the lab smelled of coffee and linseed oil*. In short, we dragged the image out of the platonic nowhere of the digital and into the here-and-now of the studio.

But let’s not pat ourselves on the back too quickly. This move raises its own ironies and critical eyebrows. Theodor Adorno and Max Horkheimer, patron saints of critical theory’s pessimistic wing, would likely smirk at our attempted *aura alchemy*. In their analysis, the modern **culture industry** is incredibly adept at churning out *pseudo-individualized* products that simulate uniqueness while being fundamentally standardized ([Pseudo individualization | The Roadrunner Theorist](https://roadrunnertheory.wordpress.com/tag/pseudo-individualization/#:~:text=promotes%20%E2%80%9Cfalse%20needs%E2%80%9D%20where%20material,avenue%20for%20happiness%20and%20success)). The culture industry, they wrote, *“perpetually cheats its consumers of what it perpetually promises.”* ([Culture industry - Wikipedia](https://en.wikipedia.org/wiki/Culture_industry#:~:text=,and%20Adorno%2C%20above%20all%2C%20in)) It offers the thrill of the new, but it’s a canned newness – the same formula dressed up in novel gimmicks. Our AI cat was, arguably, the perfect culture industry product: a totally novel image (who else has a ginger tabby waterskiing at Mallory Beach?) generated by an algorithm that has basically seen every cliché image under the sun and knows how to recombine them. The novelty is a **deceptive halo**; behind it lies the homogeneous process of the machine. Adorno’s concept of **pseudo-individualization** fits eerily well: generative AI provides *“standardized mass-produced products endowed with a deceptive halo of free choice.”* ([The Facade of The American Dream | The Roadrunner Theorist](https://roadrunnertheory.wordpress.com/2013/11/26/the-facade-of-the-american-dream-2/#:~:text=We%20chose%20the%20above%20image,public%20like%20performers%20on%20a)) You feel like the image is personal – *I* prompted this, it’s my bespoke silly cat picture – but in truth it was prefigured by the AI’s training on countless similar compositions, and anyone with the same prompt could summon a lookalike. The “free choice” of the user is a mirage; the house (or rather the algorithm’s creator) always wins by imposing its patterns.

So, when we overlay block-print texture onto the AI output, are we resisting the culture industry or simply adding another layer of fetish to it? On one hand, we might read our poster as a tiny act of rebellion: we slowed down a process that is supposed to be instantaneous, we inserted the human hand where it wasn’t required, we made the AI output *less replicable* (only ten physical prints exist, not endless JPEGs). We took something born of infinite reproducibility and domesticated it into a limited edition. This has a whiff of what Benjamin hoped politicized art might do – challenge the conditions of production, reclaim aura in a revolutionary way ([The Work of Art in the Age of Mechanical Reproduction - Wikipedia](https://en.wikipedia.org/wiki/The_Work_of_Art_in_the_Age_of_Mechanical_Reproduction#:~:text=,of%20revolutionary%20demands%20in%20the)). On the other hand, perhaps we just created a designer novelty, a hybrid commodity that could itself be co-opted. (I can see it now: **“Limited-Edition AI-Analog Mashup Prints!”** sold at premium prices to those seeking the latest hip paradox). Adorno would likely warn that even our beloved **texture** could become just another style, another way the culture industry “infects everything with sameness.” As he famously said, *“Culture today is infecting everything with sameness.”* ([Culture industry - Wikipedia](https://en.wikipedia.org/wiki/Culture_industry#:~:text=,has%20become%20no%20longer%20possible)) If AI images all start adding a fake paper texture filter to seem authentic, the novelty of our approach would itself become standardized. Indeed, one can easily imagine an Instagram filter or Photoshop plugin that mimics “block print effect” on any digital image – presto, mass-produced aura on demand. Late capitalism is a slippery beast; any time you think you’ve carved out a unique niche, it finds a way to package and resell it.

These ambiguities notwithstanding, the tactile satisfaction we got from our poster suggests something important: **the aesthetic and existential difference that materiality makes**. The AI image purely on-screen was delightful, but fleeting – it felt more like a meme, a quick dopamine hit. The block-printed poster, in contrast, had *gravitas* on the wall. It occupied space; it could be touched and even smelled (that linseed oil ink has an earthy aroma). In Barthes’s terms, the **“referent”** of the photo (the actual cat on skis, which doesn’t exist) was replaced by another referent: the reality of the print itself. Barthes once wrote about being **“chafed by reality”** when a photograph’s textures made him *feel* the presence of the scene ([Haptic Reading | The Purgatory Press](https://johnculbert.wordpress.com/2014/01/17/haptic-reading-2/#:~:text=the%20viewer%20with%20reality%20itself,merely)). Lacking a real scene, our print at least allowed one to feel the presence of the printing process. The **medium became the message**, to invoke McLuhan: the roughness of the print itself became the point, a statement that “this image passed through human hands.” In an age where AI can summon endless images with zero human touch, perhaps part of the *aesthetic* appeal of works like our poster is precisely this: the **reassertion of the human touch as a visible, sensible aspect of the artifact**.

## The One and the Many: From Plato’s Cave to Hegel’s Concept (with Marx Photobombing)

Our cat poster escapade also gestures toward a timeless philosophical puzzle: the problem of **the One and the Many**. This is an ancient theme, winding from Plato through Hegel to Marx (an odd trio to invite to a cat-skiing party, but bear with me). At its core, the issue asks how unity and multiplicity relate – whether we’re talking metaphysical Forms or mass-produced commodities.

**Plato** would likely have a field day with generative AI imagery. In Plato’s metaphysics, the **realest** thing is the *Form* (the ideal essence – e.g. “Cat-ness” or “Boat-ness”), and particular objects in the world are imperfect copies of these Forms. Art, in Plato’s harsh judgment, is then a copy of a copy – *thrice removed from the truth* ([Mimesis | Imitation, Representation, Replication | Britannica](https://www.britannica.com/art/mimesis#:~:text=mimesis%2C%20basic%20theoretical%20%20principle,the%20point%20that%20it%20was)). In the *Republic*, he uses the example of a bed: the Form of Bed is made by God (or Nature), a particular bed is made by a carpenter copying that Form, and a painting of a bed is made by an artist copying the carpenter’s copy ([Mimesis | Imitation, Representation, Replication | Britannica](https://www.britannica.com/art/mimesis#:~:text=than%20of%20%E2%80%9Ccopying%E2%80%9D%29,the%20point%20that%20it%20was)). The artist’s work is thus two degrees removed from reality (and Plato didn’t even consider photographs or AIs!). One can imagine Plato wagging a finger at our AI cat: there is no Form of “cat water-skiing” (it’s an unnatural composite concept), so the AI had to mush together bits of the Form of Cat, Form of Water, Form of Skis, etc., based on thousands of already twice-removed images in its training data. The result is a **simulacrum** several removes away from any stable truth. If a painter’s depiction is suspect to Plato, a *machine-learned hallucination* of a non-existent event might be anathema – mere illusion with no grounding in the world of Forms or facts. In a Platonic lens, generative AI intensifies the concern that images lie. We are all inside a kind of **digital cave**, watching shadows thrown not even by real objects, but by other shadows (the dataset of images, themselves representations) – a hall of mirrors drifting further from the Light of Truth.

And yet, there’s a twist: Plato also believed in the power of **dialectic** (reasoned dialogue) to ascend from confusing shadows to truth. Oddly enough, one could say that generative AI has a quasi-Platonic aspiration: the neural network “abstracts” from many particular images to grasp something like the *universal* features of “a cat on water” (though it doesn’t truly *understand* it, it statistically models it). The AI then produces a new particular image that instantiates this abstract concept. There is, buried in the code, an attempt at capturing the **One (the concept)** and producing the **Many (the instances)**. It’s as if the AI is a grotesque parody of Plato’s Demiurge – taking the Forms gleaned from data and stamping out endless copies in pixels. Our block printing, by contrast, worked in the opposite direction: we took the copy (AI image) and *gave it back some of the weight of the One*, by limiting it, by making it a singular **artifact** rather than a legion of variants. Ironically, the **limited edition print** ended up closer to an *idea* – a stable concept of “this poster” – than the endlessly copyable digital file, which was more like the uncontrolled **many**.

Moving to **Hegel**, we find a more fluid interplay of one and many. Hegel’s philosophy centers on the idea that the Universal (the One) can only realize itself through the Particular (the Many). *“For Hegel, the Universal has to manifest itself as a Particular. It is not an ephemeral ghost which exists in another world, but exists materially.”* ([The Logic of Hegel's Philosophy of Right](https://www.ethicalpolitics.org/ablunden/seminars/talk1806.htm#:~:text=Universal%20and%20Particular,was%20Hegel%20who%20made%20it)) In simpler terms, any idea or universal principle is empty until it takes shape in concrete situations. The **concept of “cat”** means nothing without actual cats running around (or maybe water-skiing, if that’s your fancy). The concept of “Education” likewise only matters as it plays out in actual classrooms with actual teachers and students. Hegel would perhaps give a gentle nod toward our printing exercise as an example of the universal-particular dance: the digital image was an abstract generality (literally encoded in latent space, a probability distribution – could be instantiated in myriad ways). By physically printing it, we forced a particular instantiation with all its idiosyncrasies. We *concretized* the image in a specific medium at a specific time. In doing so, we learned something new about it (for example, that certain fine details from the digital version didn’t translate through the block print – they vanished or became smudges, revealing which elements were truly essential to the image and which were superficial). This is a very Hegelian notion: that truth emerges through the labor of making an idea concrete and **finite**, not by keeping it in an abstract, infinitely reproducible form. The universal “cat on skis” became more meaningful to us once it was this **particular** cat print with its quirks.

Hegel also has relevance to pedagogy (which we’ll dive into soon): he thought that knowledge isn’t just a universal truth handed down, but something that has to be grasped and shaped in each context – a concept only fully known when one works through its particular manifestations. Perhaps our AI generator is like a crude Absolute Spirit trying out every possible particular image to approximate an idea – but without the self-awareness that Hegelian Spirit possesses. The human, by contrast, can see the concept *through* the particular and reflect on it. In our case, we reflected on what the cat image *meant* by engaging materially with it. It was no longer an alien output from “the AI” but something we grappled with: carving out shapes, deciding which parts to emphasize in ink. We became, in a small way, co-authors of the image’s meaning. In Hegel’s terms, the **Subject (us)** came into a more genuine relation with the **Substance (the concept/image)** by this process.

Finally, **Karl Marx** enters, stage left, holding a printing press (or maybe a sledgehammer). Marx, ever the materialist, would probably shift the conversation to labor and production. The question of one and many for Marx often boils down to the relationship between the **individual worker and the mass production system**, or between the **one capitalist mode of production and the many laborers subsumed under it**. In the **fragment on machines** and in *Capital*, Marx lamented how the rise of industrial production turned workers into mere cogs performing **highly repetitive, fragmented tasks**. He famously noted that the advance of machinery in capitalism tends to reduce the worker to *“a mere fragment of a man”*, whereas the future (post-capitalist) society should aim to replace this detail-worker with *“the fully developed individual, fit for a variety of labours”*, exercising all their talents ([Marx Myths and Legends. Peter G. Stillman](https://www.marxists.org/subject/marxmyths/peter-stillman/article.htm#:~:text=trivial%20operation%2C%20and%20thus%20reduced,MER)). This observation strikes a chord when we think about the difference between **artisanal creation vs. algorithmic generation**, and likewise **small-scale teaching vs. automated education**. 

Our block printing session was delightfully **artisan**. It required a variety of skills and senses: we mixed ink (chemistry and intuition for consistency), we carved (manual dexterity and judgment), we aligned paper (an eye for composition), we applied pressure (physical effort), and we discussed the results (critical evaluation). In Marx’s terms, we got to be relatively “fully developed” individuals for that task, engaging multiple facets of our species-being (creative, manual, intellectual). Contrast that with the AI’s role: it “labors” in a highly specialized, alienated way – crunching numbers extremely fast, with no awareness or multifaceted development. Of course, the AI is not human, so it doesn’t feel alienated; but think of the human workers behind it: the engineers labeling data, the crowdworkers fine-tuning prompts, the IT staff maintaining servers. These tasks are often **hyper-specialized** and hidden. The overall process can yield millions of images, but those who contribute a piece of it may feel no connection to the final outputs. This is the epitome of mass production alienation.

Marx might also ask: who owns the means of (re)production in each case? The block printer and linoleum block – we owned those, we wielded them directly. The AI model? That’s owned by some corporation (OpenAI, Stability AI, etc.) or at least by a system beyond our direct control, built on the labor of thousands (from dataset creators to coders). In a sense, using the AI image generator was like renting the powers of a massive factory; doing the block print was like tending our own cottage workshop. The former scales massively – one click could have yielded 100 cat variants – but with each additional image, my involvement and satisfaction would diminish (after all, clicking “generate again” doesn’t deepen one’s understanding after a point). The latter (block printing) does *not* scale easily – making 100 prints would take us many days and very sore wrists – but each print pulled is satisfying and instructive. This stark contrast brings to mind Marx’s critique of the obsession with **scale and exchange-value** over use-value and qualitative experience. Capitalism loves scale because scale brings profit and control (one AI model can serve millions of users – think of the profitability!). But what about the use-value, the meaningfulness for the user or maker? Our single hand-pulled poster had more *use-value* (in terms of teaching us something, giving us pride and a story) than dozens of quick digital variations would have. 

Marx also believed that humans are inherently creative and social beings (“species-being”), and that alienated labor under capitalism stunts those capacities. In a small but telling way, our project affirmed that unalienated, hands-on labor (even if just making a funny poster) yields a richer result for the soul than an alienated process. **One** handmade poster meant more to us than **many** auto-generated images. It’s the old one-vs-many issue transposed into quality-vs-quantity.

To be clear, I’m not suggesting smashing the AI looms like a latter-day Luddite (though the image of us heroically attacking a GPU server with carving tools is amusing). Rather, I’m noting how the **finitude** and **situatedness** of an artisanal approach exposed aspects of meaning that the frictionless infinite approach glossed over. This sets the stage to discuss not just art, but *education* – where similar tensions between the one and the many, the universal and particular, the scalable and the intimate, are playing out with the rise of AI personalization in learning.

## Personalization at Scale vs. Pedagogical Intimacy: The Magic Midpoint

The ethos of Silicon Valley often boils down to a mantra: *“scale everything.”* If a human can do it well for 10 people, a machine should do it for 10 million. Education has been in these crosshairs for a while. Tech entrepreneurs dream of **personalized learning at infinite scale**: each student gets an AI tutor or a tailored curriculum, delivered via sleek software, optimizing their progress through data analytics. No need to struggle with the **finitude** of one teacher per 30 kids in a classroom; why not have one centralized AI teach *everyone*, yet *“personalize”* it to each learner’s pace and style? On paper (or rather, on screen), it sounds like a miracle solution – the *One* (a single system) providing for the *Many* (all students) in a way that makes each feel like the center of instruction. It’s the educational equivalent of that AI image model: one algorithm generating infinitely many customized outputs.

And indeed, we’ve seen huge investments and hype in this direction. Platforms that promise adaptive learning, automated feedback, even AI-driven grading. During the early 2010s MOOC boom (Massive Open Online Courses), there were lofty proclamations that the age of the physical university might soon be over – why wouldn’t everyone just watch the single best lecturer on each topic on YouTube at home, at their own pace? Why not have AI systems quiz them and fill in their individual gaps? The COVID-19 pandemic accelerated some of these experiments out of necessity, and now with new AI tools (like large language models that can act as a kind of tutor), the fantasy is recharged anew.

However, as any teacher or student who has lived through Zoom classrooms and automated homework systems can tell you, something essential often goes missing in these scaled, personalized-at-a-distance scenarios. There is a curious parallel here to our **block printing** insight. A small-scale seminar or workshop, with say 10–20 students and a teacher, is like the **block print** – it has a *magic midpoint* quality. It’s not one-of-a-kind in the way a pure tutorial (1 student, 1 teacher) would be, but it also isn’t mass-produced to the point of anonymity. It’s repeatable (the same class can be taught next semester to a new group, much as a linocut block can print multiple copies), yet each iteration is a bit different and remains **grounded in material constraints** (the class lasts an hour, the teacher has only so much energy, the room has only so many seats – analog limits that shape the experience). There is intimacy, interaction, and **situatedness**: the learning happens in a specific social context, face-to-face, where teacher and students respond to each other’s cues, questions, confusions in real time. This is inherently unscalable in a Silicon Valley sense – you can’t have one teacher meaningfully engage with 10,000 students at once. But precisely that limit is what allows depth. It’s like the limited edition print: because only a manageable number of copies exist, each one can be attended to, and the audience can perceive it as special.

By contrast, the **Silicon Valley model** of infinite personalization imagines each learner in their own bubble, interacting with a personalized feed of content. It’s personalization *without* presence. It sacrifices the *group experience* and the *teacher’s direct, full-spectrum engagement* for an automated individual pathway. This is akin to generating 10,000 digital images and handing each person a different one based on their preferences. Sure, everyone’s got something “just for them,” but no one shares an experience, and the **creator** (here an AI or pre-recorded content) cannot genuinely adapt in the rich way a human facilitator would, because it lacks true understanding and, importantly, it isn’t sharing the **life-world** of the learners. An algorithm doesn’t laugh at a student’s witty comment, or notice the moment the class collectively gasps in revelation, or feel the awkward silence that indicates a concept didn’t land. Those are social cues, bodily cues – things that exist in physical co-presence. 

It’s not unlike the difference between seeing a live play in a small theater and watching personalized TV at home. The live play doesn’t scale (only so many seats, one performance at a time), but it can be transformative in a way sitting alone with Netflix’s perfectly personalized recommendation just isn’t. Education, many of us in the humanities argue, is more like that play – a live, unrepeatable encounter – than it is like content consumption.

Our **poster project** turned out to be a lovely microcosm of this principle. Initially, we had a “personalized” image delivered by an AI – it felt tailored to our goofy prompt, but it was just us and the screen. The real fun, the real *learning* if you will, happened when we turned it into a collaborative studio exercise: mixing old and new techniques, working together on the physical prints, and then discussing all the theoretical implications (indeed, this essay is proof of that deeper engagement!). The *finitude* of the block printing process – the fact that it required time, teamwork, messy hands, and only yielded a small number of posters – actually fostered a richer experience and more reflection than if we had simply generated 100 AI images and scrolled through them in Slack. In pedagogical terms, the block printing was like a great seminar: a bit unpredictable, requiring participation and negotiation, and ultimately rewarding beyond the original plan. The infinite AI generation was like a static one-way content dump – amusing but shallow in comparison.

This is not to say technology has no place in education – far from it. But there is a **fantasy of infinite scale** that needs critiquing. Educational theorists have pointed out that so-called personalized learning software often ends up being rather isolating and even homogenizing. In an article in *Education Week*, a critic noted that much personalized learning software leads to **“students working alone on screens for much of the day,”** raising concerns about social development and the richness of learning experiences ([The Case(s) Against Personalized Learning - Education Week](https://www.edweek.org/technology/the-cases-against-personalized-learning/2017/11#:~:text=Critics%20say%20personalized%20learning%20isn%27t,mining%20students)). Even the supposed personalization can be skin-deep: many programs follow a similar template (videos + quizzes), just ordering content differently for each student. It’s a far cry from the dynamic, improvisational tailoring a live teacher does in response to an actual student’s facial expressions or probing questions.

Let’s invoke **Adorno** again: in the culture industry, even the things that purport to cater to individual tastes end up reinforcing sameness ([Culture industry - Wikipedia](https://en.wikipedia.org/wiki/Culture_industry#:~:text=,has%20become%20no%20longer%20possible)). One worries that **Silicon Valley’s version of personalized education may standardize the learning experience more than ever**, under the guise of customization ([Culture industry - Wikipedia](https://en.wikipedia.org/wiki/Culture_industry#:~:text=in%20the%20digital%20age%3A%20,24)). Everyone sits in their isolated pod, interacting with the same kind of software, the same interface, just with different worksheet questions. The holistic, messy, human aspect of education – which can include debate, digressions, ethical dilemmas, jokes, tangents that unexpectedly illuminate – gets sanded down to a smooth, efficient delivery of curriculum units.

Our **magic midpoint** of block printing can serve as a metaphor for reimagining educational technology. What if, instead of aiming to replace teachers or scale infinitely, we aim to use tech in a way that still **honors constraints and context**? For example, using AI to augment a small classroom (like generating different examples a teacher can choose from and discuss), rather than each kid on their own AI tutor. That would be like using the AI to help design a new linocut, but still having the class involved in printing it together. The point is to **embrace a bit of slowness and limitation** as features, not bugs. In block printing, the block *wears out* after a number of prints and the ink has to be reapplied each time – these constraints actually make each print slightly unique and force the artist to be intentional. In teaching, the fact that a teacher can only respond to one person at a time and that a class has to move at some collective rhythm can actually teach patience, listening, and the value of communal progress. The Silicon Valley mindset tends to see such limits as inefficiencies to be optimized away. But perhaps they are precisely what make the educational experience *meaningful*. After all, a one-on-one conversation with a teacher who remembers your name and cares about your thoughts is “inefficient” compared to an AI that can serve thousands, but its impact on a student’s intellectual growth can be immeasurably greater.

To use a tactile analogy: learning in a real classroom is like writing with a **fountain pen on paper**, where the friction slows you just enough to think as you write, and the minor variations in ink flow give character to your script. Learning solely through AI software is like typing on a slick keyboard with autocorrect – faster and more uniform, sure, but often less internally engaging (who hasn’t mindlessly accepted a suggestion without processing it deeply?). In fact, some cognitive science supports this: taking notes by hand can improve retention compared to typing, precisely because it’s slower and you must be selective. It’s as if the **friction** itself encodes meaning.

## Of Matrix Pods and the Uncanny Valley of Personalization

There is a scene in *The Matrix* (1999) that has become iconic in discussions of virtual reality and isolation. Neo, the protagonist, wakes up in a pod of goo, realizes that his entire reality was a simulated illusion fed to his brain by machines, and that he – and millions of other humans – have been **living isolated in pods**, each experiencing a personalized fake world. This dystopian image resonates as a cautionary tale for over-personalized, tech-driven existence. While we’re thankfully nowhere near literal Matrix pods in education, the metaphor is apt when considering the **uncanny, isolating dimensions of AI personalization**. 

Picture a student in the future: strapped into a VR headset, an AI tutor whispering in their ear, every lesson tailored to their exact preferences, every mistake instantly corrected by a gentle algorithmic nudge. On the surface, it sounds idyllic – no embarrassment of answering wrong in front of peers, no boredom because the AI always knows how to tweak difficulty. But zoom out: that student is alone, physically passive, and perhaps missing out on all the random, messy human interactions that are arguably central to learning (and to life). They become a solitary mind consuming a custom feed of knowledge, like a Netflix binge but with calculus and Shakespeare instead of *Tiger King*. One can’t help but find something **uncanny** in this vision. The **uncanny valley** concept usually applies to robots or animations that look almost human but not quite, causing discomfort ([The Impact of the Uncanny Valley in Consumer Technology](https://www.cmswire.com/digital-marketing/from-robots-to-ai-understanding-the-uncanny-valley-in-digital-innovation/#:~:text=The%20Impact%20of%20the%20Uncanny,representations%20look%20and%20act)). Here, we have an uncanny valley of social simulation: an AI tutor might *sound* like a friendly teacher, but we know it’s not human. The encouragement it gives, the jokes it cracks (no doubt harvested from a database of corny teacher jokes), all ring a little hollow when you realize it’s just you and the machine. As one writer quipped about such systems, the experience can hit an *“uncanny valley effect”* where the personalization feels creepy rather than comforting ([Where does AI personalisation dive into uncanny valley? - Medium](https://medium.com/@alexh.editorial/where-does-ai-personalisation-dive-into-uncanny-valley-f90f0ebef579#:~:text=Medium%20medium,hit%20hard%2C%20making%20the)).

In contrast, the **block print / small classroom** scenario is charmingly *canny* (the opposite of uncanny): it’s obviously real, imperfect, and human. If my teacher makes a corny joke, I groan along with my classmates – a shared moment. If the AI tutor makes the same joke, I might just feel oddly alone with a laugh track that isn’t really there. This hints at a psychological insight: meaning-making in both art and education is often **interpersonal**. We derive meaning not just from content, but from the context of others experiencing it with us. A meme is funny when others share it; a lesson is meaningful when it’s discussed in a group. The Silicon Valley model of one learner per personalized algorithm severs a lot of those horizontal connections among learners.

Moreover, fully personalized feeds can lead to **echo chambers** and a lack of challenge. In education, as in life, some of the most important growth happens when you encounter perspectives and difficulties that are *not* exactly tailored to your preferences. A good teacher sometimes *purposely* pushes you out of your comfort zone, or another student asks a question you never would have thought of (and the whole class benefits). In a hyper-personalized AI world, you might never be exposed to that fruitful discomfort. It’s akin to how social media algorithms show people what they “like” – which has led to bubbles of people never seeing opposing viewpoints. The *Matrix* is comfortable – until you realize it’s a prison. Likewise, a perfectly personalized educational path might be **seductive but stunting**, isolating learners in a matrix of their own prior inclinations.

A little humor in Zizekian style: one can imagine a future student rebelling not by cutting class, but by *hacking their AI tutor* to inject randomness – “Hey GPT-12, today teach me something I absolutely *don’t* want to learn!” It’s the educational equivalent of seeking the **punctum** (to recall Barthes’s term for the poignant detail that “pricks” you out of complacency ([Haptic Reading | The Purgatory Press](https://johnculbert.wordpress.com/2014/01/17/haptic-reading-2/#:~:text=the%20viewer%20with%20reality%20itself,merely))). True learning often requires these pricks, these *real* encounters that jar us. Without them, we risk a sort of solipsistic learning where the **One (the learner)** is just consuming multiple versions of themselves in mirror form.

And let’s not forget the **power dynamics**: who controls the AI platforms? A handful of big tech companies, most likely. Adorno’s concern that a *“few gigantic corporations”* could dominate culture ([Culture industry - Wikipedia](https://en.wikipedia.org/wiki/Culture_industry#:~:text=in%20the%20digital%20age%3A%20,24)) is already a reality in entertainment and tech, and it could become the reality in education. The scenario of every student plugged into, say, a Google or Meta education system is quite dystopian – a far cry from the diversity of teachers and approaches found in different schools and cultures. It’s a kind of monochrome future painted in the guise of personalized color. Our block printing exercise was, by comparison, wonderfully **decentralized and DIY**. We didn’t need a trillion-dollar company to mediate the process; a few art supplies and our own creativity sufficed. There’s an implicit argument here for the value of **small-scale, autonomous educational practices** over heavily corporatized, massive systems.

One might also talk about the **commodification** of education in the AI paradigm. When each student’s experience is mediated by software, then education becomes a product to be bought, sold, and surveilled. In the words of one critic, we risk having our *“educational system uploaded for commodification and surveillance”* ([The Messy Reality of Personalized Learning | The New Yorker](https://www.newyorker.com/news/dispatch/the-messy-reality-of-personalized-learning#:~:text=match%20at%20L232%20not%20your,and%20activist%20blogger%20in%20Pennsylvania)). The uncanny pod scenario isn’t just psychologically eerie; it’s a situation ripe for data mining and control. A student in a pod is a student who can be monitored completely – every click and hesitation logged (talk about a **Panopticon** in Foucauldian terms!). In a classroom, there is a freedom in the gaps – the unmonitored whisper, the doodling in the margins, the subtle resistance that builds critical thinking. The messy reality of in-person learning allows for *human agency* in a way the perfectly monitored personalized system might not.

Now, I realize I’ve painted a rather dark possible future. The reality will likely be more hybrid – bits of AI here, human interaction there. The key point, however, is that we should **revalue the constraints** and “inefficiencies” of traditional methods as features that preserve human dignity and depth. Just as the **smudges of the block print** made the image feel real, the little frictions and limitations of classroom learning (or artisanal art-making) give it *texture* and meaning. 

## Revaluing the Human Touch: Why Constraints and Context Matter

What did our quirky poster project ultimately teach us? Beyond the fun of seeing a cat on a hot digital surfboard, it taught us this: **material and interpersonal constraints are not obstacles to meaning – they are the preconditions of meaning**. In art, the limitations of a medium (the fact that woodblock can only capture so much detail, or that a painting must be made with physical pigments) are exactly what give works their style and individuality. In education, the limitations of scale (one teacher can only connect deeply with a limited number of students, learning takes time and effort, etc.) are what make genuine understanding possible.

It’s tempting in our era to believe that if we could just eliminate all constraints – have infinite compute, infinite data, infinite personalized pathways – we’d reach some utopia of perfect art and knowledge. But such infinity is a double-edged sword. **Meaning arises from choices, and choices only matter in the face of limitations.** A block print is meaningful partly because the artist had to choose what to carve away and what to leave, under the constraint that once carved, it can’t be easily changed. A lesson is meaningful because a teacher must choose what to focus on in a 50-minute class, and students must grapple with what they’ve got, asking questions in that fleeting moment. If you had infinite time and resources, choices lose significance – you could do everything, see everything, rewind and revise endlessly. Paradoxically, you might end up doing *nothing* of significance, adrift in limitless possibility. (Anyone who’s spent hours clicking through an endless Netflix catalog and feeling emptier by the minute knows this paradox.)

By **revaluing constraints**, I mean recognizing that the very things tech often promises to overcome might be the things we *don’t actually want to lose*. For example:

- **The Constraint of Effort:** It took effort to make our posters; that effort invested us in their outcome. Likewise, the effort a student puts into a difficult book or problem is what makes the learning stick and feel rewarding. If an AI always spoon-feeds a student just the answer, the student is robbed of the *eureka* moment earned after struggle. There’s a reason teachers sometimes respond to a question with another question – to nudge the student to think it through, because the effort of thinking is where learning happens. In educational tech, we should be wary of designs that remove all friction. Some *desirable difficulty* is important.

- **The Constraint of Community:** In a small class or a collaborative project, you can’t just do whatever you want – you have to negotiate with others’ ideas and needs. That constraint teaches empathy, communication, and the discovery that other minds can enrich or challenge your own. In contrast, a personalized AI that adapts to *you* alone reinforces *you* as the center of everything. The world, however, is not personalized to each of us; we have to share it. The communal constraint in learning prepares us for that shared world. (Our poster project, for instance, was far more interesting because it was *we* who did it, pooling our skills and then exchanging interpretations.)

- **The Constraint of Physical Presence:** This one is subtle but profound. Being physically present – whether in front of a work of art or in a classroom – engages our full sensorium. Think of how different it is to read a poem quietly versus hearing it recited live by a passionate reader in a room with an audience. The latter might give you goosebumps; the former might not. The physical context provides **cues and sensations** that deepen meaning (Barthes touching a photograph comes to mind: he speaks of the photo almost having a *temperature* or provoking a *touch response* ([Haptic Reading | The Purgatory Press](https://johnculbert.wordpress.com/2014/01/17/haptic-reading-2/#:~:text=Roland%20Barthes%E2%80%99%20study%20of%20photography%2C,%E2%80%A6))). In teaching, presence means the teacher can convey enthusiasm through tone, students can physically signal confusion or interest, and all can perhaps laugh together at an off-topic joke. These small physical interactions ground the experience in reality, making it memorable and emotionally resonant. Digital experiences, no matter how advanced, struggle to replicate that fully. Thus, the “constraint” of having to be in the same place at the same time to learn something might actually be part of why that learning sticks with you for life.

In both art and pedagogy, **meaning is co-created**. It doesn’t reside solely in the object (image or curriculum) or in the subject (viewer or student); it emerges in the *between*, the interaction. Our attempt to imbue the AI image with analog reality was an attempt to facilitate a different interaction between image and viewer – one that includes awareness of process, physicality, even the artist’s intention. Similarly, authentic education tries to create a rich interaction between teacher, students, and material. If everything is pre-packaged and hyper-optimized, those interactions flatten out.

So, rather than chasing the Silicon Valley dream of frictionless perfection, perhaps we should embrace a bit of grit. The **desert of the real**, to borrow Baudrillard’s phrase that *The Matrix* also quotes, might be more nourishing than the candyland of endless virtual comfort. In practical terms, this could mean a few things:

- In art/design: Continue exploring hybrids like we did – using AI as a tool, but reintroducing human touch and limitation to finish the work. The goal: not to reject AI, but to humanize its outputs, to bring them into our embodied world where they can acquire story and substance. (A digital cat is a meme; a block-printed cat is a story about our afternoon and all these theories we’re now unraveling.)

- In education: Leverage AI, but keep teachers central. Use tech to free teachers from drudgery (maybe grading or providing supplementary exercises) so they can focus *more* on the human, high-touch aspects of teaching – the discussions, the mentorship, the creative facilitation. And keep class sizes small where possible, valuing that over fancier devices. It might also mean teaching students the meta-skill of navigating the mix of AI and human instruction – e.g., how to critically evaluate an answer an AI tutor gives, which requires *human* critical thinking that comes from a good education! In short, **use AI to enhance the aura of teaching, not to extinguish it.**

- In culture at large: Recognize that just because something can be done at scale doesn’t mean it should replace the small-scale version. We have streaming music for billions, but vinyl records and live concerts are making a comeback for a reason – people miss the aura and presence. Maybe a similar balance will emerge in education: global online courses for accessibility, but a renewed appreciation for the intimate seminar for depth. The trick is to avoid letting one justify defunding or neglecting the other. The future shouldn’t be *either* Matrix pods *or* Socratic walks in the agora; it can be enriched by both high-tech and low-tech, if we intentionally preserve what each does best.

To circle back to theory one more time: there’s a line in Marx (echoing earlier utopian socialists) that in a better society, an individual could **“hunt in the morning, fish in the afternoon, rear cattle in the evening, criticize after dinner,”** without being forced into one role – in other words, a balanced, multifaceted life. Likewise, a balanced approach to AI in art and teaching might let us enjoy the best of both worlds: play with generative AI in the morning (for its wild many-ness), do hand-printing in the afternoon (for its grounding oneness), learn some basics from a personalized app in the evening (efficiently catching up on, say, math formulas), and then discuss big ideas with a live group after dinner (arguing philosophy face-to-face). The richness comes from the **combination**, the interplay of scales and modes, rather than a total victory of one mode over the other.

## Conclusion: The Cat’s Meow (or, Why the Real Matters)

Our cat-on-water-skis poster now hangs proudly in the corridor, often eliciting chuckles or puzzled looks from passersby. It stands as a kind of mascot for the lab – a reminder not to take technology too seriously, and not to forget the human element behind every image or idea. In crafting that poster, we inadvertently staged a collision between the futuristic and the traditional, the infinite and the finite, the virtual and the real. And from that collision, sparks of insight flew.

Philosopher Slavoj Žižek, with his characteristic humor, might say that the cat poster is a **“parallax object”** – something that reveals different truths depending on your perspective. Look at it one way, and it’s just a funny mashup produced by a clever machine. Look at it another way, and it’s a commentary on the whole history of art from Plato’s cave to Photoshop. In a similar vein, our discussions oscillated between laughing at the sheer absurdity of the image and diving into earnest critique of digital culture. This interplay of playfulness and seriousness is key. It’s reminiscent of how **Frederic Jameson** might analyze a cultural artifact: there is the *jest* on the surface and the *gest* (gesture) towards deeper political economy underneath, and it’s our job to read both levels.

So what have we ultimately learned (besides the fact that a cat will never look entirely happy about being on skis, even an AI-synthesized one)? We’ve learned that **generative AI, for all its generative genius, still benefits from a dose of reality – a reality we can provide by embedding it in human contexts and materials**. We’ve learned that **scale is not a neutral good**: more is not always better, and in fact *more* without *meaning* is just more noise. We’ve come to appreciate that sometimes the most radical move is to slow down and do something the “old-fashioned” way, not out of nostalgia, but as a deliberate re-centering of human presence in the process. 

In a world increasingly enchanted by the promise of the **one-click, the on-demand, the endlessly copyable**, our little poster reminds us of the charm of the **slight delay, the hands-on, the one-of-a-few**. It’s like the difference between a witty remark fired off in a group chat and a witty remark shared over coffee with a friend – both have their place, but only one comes with a warm smile and maybe a clink of cups.

As academic humanists (the intended readers of this essay), we are well aware that culture and technology always dance in a dialectic. The “next big thing” often reintroduces problems that old wisdom had already addressed in a different form. Plato worried about writing destroying memory; we worry about Google making knowledge too easy to look up. The early 20th century worried about film and radio dumbing down the masses (hello Adorno and Horkheimer); we worry about TikTok and AI doing the same. History doesn’t repeat, but it surely rhymes. By examining something as banal as a cat poster, we found ourselves recapitulating classic debates: **original vs. copy, art vs. artifice, individual vs. mass, teacher vs. machine**. 

In the spirit of humor and theory entwined, let me finish by imagining an absurdly ideal scenario: Walter Benjamin, Theodor Adorno, Roland Barthes, and Plato all walk into our lab and see the cat poster. Benjamin strokes his chin and says, “Ah, you have restored its aura.” Barthes adjusts his glasses and notes, “The texture – it adds a *presence*, a reality effect beyond the image’s nonsense content.” Plato harrumphs, “It’s still an imitation of an imitation, but at least it’s a *beautiful* imitation.” Adorno just crosses his arms and says, “Culture industry… even cats are not safe from it.” And then the cat itself (were it real) would meow and perhaps say, “I don’t know about your theories, I just know I felt the human hands making this; it feels… warmer.” 

In truth, we don’t have to reject AI or idealize the handmade; we just need to remember what each is good for. Generative AI can give us **the Many** – an explosion of forms and options we’d never have imagined. But it’s up to us humans to find **the One** (or the few) among those that matter, and to give those chosen ones the stamp of lived reality, whether by **printing them, discussing them, or otherwise anchoring them in our finite world**. The cat poster, in its silly way, taught us that lesson. And that’s the real magic midpoint – when technology’s abundance meets human limitation in just the right way, something meaningful can emerge, *even if it’s as frivolous as a cat who conquered the waves*. 

In an era of pods and pseudo-personalization, may we cherish the genuine personal touch. In an era of infinite copies, may we rediscover the joy of the **limited edition** – in art, in teaching, and in all our meaning-making endeavors. After all, if a cat can learn to water-ski (with a little help from AI), perhaps we humans can learn to ride the wave of new technology without losing our balance, or our souls, in the process. **Meow** – and amen.

 ([Haptic Reading | The Purgatory Press](https://johnculbert.wordpress.com/2014/01/17/haptic-reading-2/#:~:text=Roland%20Barthes%E2%80%99%20study%20of%20photography%2C,%E2%80%A6)) ([Effect of reality - Wikipedia](https://en.wikipedia.org/wiki/Effect_of_reality#:~:text=Barthes%20first%20suggested%20this%20concept,1)) ([The Work of Art in the Age of Mechanical Reproduction - Wikipedia](https://en.wikipedia.org/wiki/The_Work_of_Art_in_the_Age_of_Mechanical_Reproduction#:~:text=The%20aura%20of%20a%20work,product%29%20diminishes%20the)) ([The Work of Art in the Age of Mechanical Reproduction - Wikipedia](https://en.wikipedia.org/wiki/The_Work_of_Art_in_the_Age_of_Mechanical_Reproduction#:~:text=aesthetic%20value%20of%20the%20original,8)) ([Culture industry - Wikipedia](https://en.wikipedia.org/wiki/Culture_industry#:~:text=,has%20become%20no%20longer%20possible)) ([Pseudo individualization | The Roadrunner Theorist](https://roadrunnertheory.wordpress.com/tag/pseudo-individualization/#:~:text=promotes%20%E2%80%9Cfalse%20needs%E2%80%9D%20where%20material,avenue%20for%20happiness%20and%20success)) ([The Facade of The American Dream | The Roadrunner Theorist](https://roadrunnertheory.wordpress.com/2013/11/26/the-facade-of-the-american-dream-2/#:~:text=We%20chose%20the%20above%20image,public%20like%20performers%20on%20a)) ([Mimesis | Imitation, Representation, Replication | Britannica](https://www.britannica.com/art/mimesis#:~:text=mimesis%2C%20basic%20theoretical%20%20principle,the%20point%20that%20it%20was)) ([The Logic of Hegel's Philosophy of Right](https://www.ethicalpolitics.org/ablunden/seminars/talk1806.htm#:~:text=Universal%20and%20Particular,was%20Hegel%20who%20made%20it)) ([Marx Myths and Legends. Peter G. Stillman](https://www.marxists.org/subject/marxmyths/peter-stillman/article.htm#:~:text=trivial%20operation%2C%20and%20thus%20reduced,MER))

