Cinemorphosis

Category: technology

  • Humanification

    Humanification

    It is not my job to indoctrinate you into a political party, a philosophical sect, or a religious creed. I am not here to recruit. But it is my job to indoctrinate you about something—namely, how to think, why thinking matters, and what happens when you decide it doesn’t. I have an obligation to give you a language for understanding critical thinking and the dangers of surrendering it, a framework for recognizing the difference between a meaningful life and a comfortable one, and the warning signs that appear when convenience, short-term gratification, and ego begin quietly eating away at the soul. Some of you believe life is a high-stakes struggle over who you become. Others suspect the stakes are lower. A few—regrettably—flirt with nihilism and conclude there are no stakes at all. But whether you dramatize it or dismiss it, the “battle of the soul” is unavoidable. I teach it because I am not a vocational trainer turning you into a product. I am a teacher in the full, unfashionable sense of the word—even if many would prefer I weren’t.

    This battle became impossible to ignore when I returned to the classroom after the pandemic and met ChatGPT. On one side stood Ozempification: the seductive shortcut. It promises results without struggle, achievement without formation, output without growth. Why wrestle with ideas when a machine can spit out something passable in seconds? It’s academic fast food—calorie-dense, spiritually empty, and aggressively marketed. Excellence becomes optional. Effort becomes suspicious. Netflix beckons. On the other side stood Humanification: the old, brutal path that Frederick Douglass knew by heart. Literacy as liberation. Difficulty as transformation. Meaning earned the hard way. Cal Newport calls it deep work. Jordan Peele gives it a name—the escape from the Sunken Place. Humanification doesn’t chase comfort; it chases depth. The reward isn’t ease. It’s becoming someone.

    Tyler Austin Harper’s essay “ChatGPT Doesn’t Have to Ruin College” captures this split perfectly. Wandering Haverford’s manicured campus, he encounters English majors who treat ChatGPT not as a convenience but as a moral hazard. They recoil from it. “I prefer not to,” Bartleby-style. Their refusal is not naïveté; it’s identity. Writing, for them, is not a means to a credential but an act of fidelity—to language, to craft, to selfhood. But Harper doesn’t let this romanticism off the hook. He reminds us, sharply, that honor and curiosity are not evenly distributed virtues. They are nurtured—or crushed—by circumstance.

    That line stopped me cold. Was I guilty of preaching Humanification without acknowledging its price tag? Douglass pursued literacy under threat of death, but he is a hero precisely because he is rare. We cannot build an educational system that assumes heroic resistance as the norm. Especially not when the very architects of our digital dystopia send their own children to screen-free Waldorf schools, where cursive handwriting and root vegetables are treated like endangered species. The tech elite protect their children from the technologies they profit from. Everyone else gets dopamine.

    I often tell students this uncomfortable truth: it is easier to be an intellectual if you are rich. Wealth buys time, safety, and the freedom to fail beautifully. You can disappear to a cabin, read Dostoevsky, learn Schubert, and return enlightened. Most students don’t have that option. Harper is right—institutions like Haverford make Humanification easier. Small classes. Ample support. Unhurried faculty. But most students live elsewhere. My wife teaches in public schools where buildings leak, teachers sleep in cars, and safety is not guaranteed. Asking students in survival mode to honor an abstract code of intellectual purity borders on insult.

    Maslow understood this long ago. Self-actualization comes after food, shelter, and security. It’s hard to care about literary integrity when you’re exhausted, underpaid, and anxious. Which is why the Ozempic analogy matters. Just as expensive GLP-1 drugs make discipline easier for some bodies, elite educational environments make intellectual virtue easier for some minds. Character still matters—but it is never the whole story.

    Harper complicates things further by comparing Haverford to Stanford. At Stanford, honor codes collapse under scale; proctoring becomes necessary. Intimacy, not virtue alone, sustains integrity. Haverford begins to look less like a model and more like a museum—beautiful, instructive, and increasingly inaccessible. The humanities survive there behind velvet ropes.

    I teach at a community college. My students are training for nursing, engineering, business. They work multiple jobs. They sleep six hours if they’re lucky. They don’t have the luxury to marinate in ideas. Humanification gets respectful nods in class discussions, but Ozempification pays the rent. And pretending otherwise helps no one.

    This is the reckoning. We cannot shame students for using AI when AI is triage, not indulgence. But we also cannot pretend that a life optimized for convenience leads anywhere worth going. The challenge ahead is not to canonize the Humanified or condemn the Ozempified. It is to build an educational culture where aspiration is not a luxury good—where depth is possible without privilege, and where using AI does not require selling your soul for efficiency.

    That is the real battle. And it’s one we can’t afford to fight dishonestly.

  • Ozempification: A Cautionary Tale

    Ozempification: A Cautionary Tale

    The 2025 Los Angeles wildfires, blazing with apocalyptic fury, prompted me to do something I hadn’t done in years: dust off one of my radios and tune into live local news. The live broadcast brought with it not just updates but an epiphany. Two things, in fact. First, I realized that deep down, I despise my streaming devices—their algorithm-driven content is like an endless conveyor belt of lukewarm leftovers, a numbing backdrop of music and chatter that feels canned, impersonal, and incurably distant. Worst of all, these devices have pushed me into a solipsistic bubble, a navel-gazing universe where I am the sole inhabitant. Streaming has turned my listening into an isolating, insidious form of solitary confinement, and I haven’t even noticed.

    When I flipped on the radio in my kitchen, the warmth of its live immediacy hit me like a long-lost friend. My heart ached as memories of radio’s golden touch from my youth came flooding back. As a nine-year-old, after watching Diahann Carroll in Julia and Sally Field in The Flying Nun, I’d crawl into bed, armed with my trusty transistor radio and earbuds, ready for the night to truly begin. Tuned to KFRC 610 AM, I’d be transported into the shimmering world of Sly and the Family Stone’s “Hot Fun in the Summertime,” Tommy James and the Shondells’ “Crystal Blue Persuasion,” and The Friends of Distinction’s “Grazing in the Grass.” The knowledge that thousands of others in my community were swaying to the same beats made the experience electric, communal, alive—so unlike the deadening isolation of my curated streaming playlists.

    The fires didn’t just torch the city—they laid bare the fault lines in my craving for connection. Nostalgia hit like a sucker punch, sending me down an online rabbit hole in search of a high-performance radio, convinced it could resurrect the magic of my youth. Deep down, a sardonic voice heckled me: was this really about better reception, or just another pitiful attempt by a sixty-something man trying to outrun mortality? Did I honestly believe a turbo-charged radio could beam me back to those transistor nights and warm kitchen conversations, or was I just tuning into the static of my own existential despair?

    Streaming had wrecked my relationship with music, plain and simple. The irony wasn’t lost on me either. While I warned my college students not to let ChatGPT lull them into embracing mediocre writing, I had let technology seduce me into a lazy, soulless listening experience. Hypocrisy alert: I had become the very cautionary tale I preached against.

    Enter what I now call “Ozempification,” inspired by that magical little injection, Ozempic, which promises a sleek body with zero effort. It’s the tech-age fantasy in full force: the belief that convenience can deliver instant gratification without any downside. Spoiler alert—it doesn’t. The price of that fantasy is steep: convenience kills effort, and with it, the things that actually make life rich and rewarding. Bit by bit, it hollows you out like a bad remix, leaving you a hollow shell of passive consumption.

    Over time, you become an emotionally numb, passive tech junkie—a glorified NPC on autopilot, scrolling endlessly through algorithms that decide your taste for you. The worst part? You stop noticing. The soundtrack to your life is reduced to background noise, and you can’t even remember when you lost control of the plot.

    But not all Ozempification is a one-way ticket to spiritual bankruptcy. Sometimes, it’s a lifeline. GLP-1 drugs like Ozempic can literally save lives, keeping people with severe diabetes from joining the ranks of organ donors earlier than planned. Meanwhile, overworked doctors are using AI to diagnose patients with an accuracy that beats the pre-AI days of frantic guesswork and “Let’s Google that rash.” That’s Necessary Ozempification—the kind that keeps you alive or at least keeps your doctor from prescribing antidepressants instead of antibiotics.

    The true menace isn’t just technology—it’s Mindless Ozempification, where convenience turns into a full-blown addiction. Everything—your work, your relationships, even your emotional life—gets flattened into a cheap, prepackaged blur of instant gratification and hollow accomplishment. Suddenly, you’re just a background NPC in your own narrative, endlessly scrolling for a dopamine hit like a lab rat stuck in a particularly bleak Skinner box experiment.

    As the fires in L.A. fizzled out, I had a few weeks to prep my writing courses. While crafting my syllabus and essay prompts, Mindless Ozempification loomed large in my mind. Why? Because I was facing the greatest challenge of my teaching career: staying relevant when my students had a genie—otherwise known as ChatGPT—at their beck and call, ready to crank out essays faster than you can nuke a frozen burrito.

    After four years of wrestling with AI-assisted essays and thirty-five years in the classroom, I’ve learned something unflattering about human nature—especially my own. We are exquisitely vulnerable to comfort, shortcuts, and the soft seduction of the path of least resistance. Given enough convenience, we don’t just cut corners; we slowly anesthetize ourselves. That quiet slide—where effort feels offensive and difficulty feels unnecessary—is the endgame of Ozempification: not improvement, but a gentle, smiling drift toward spiritual atrophy.

  • Good-Enoughers

    Good-Enoughers

    In the fall of 2023, I was standing in front of thirty bleary-eyed college students, halfway through a lesson on how to spot a ChatGPT essay—mainly by its fondness for lifeless phrases that sound like they were scraped from a malfunctioning inspirational calendar. That’s when a business major raised his hand with the calm confidence of someone revealing a trade secret and said, “I can guarantee you everyone on this campus uses ChatGPT. We don’t submit it raw. We tweak a few sentences, paraphrase a little, and boom—no one can tell.”

    Before I could respond, a computer science student piled on. “It’s not just for essays,” he said. “It’s my life coach. I ask it about everything—career moves, crypto, even dating.” Dating advice. From ChatGPT. Somewhere, right now, a romance is unfolding on AI-generated pillow talk and a bullet-pointed list of conversation starters.

    That was the moment I realized I was staring at the biggest educational rupture of my thirty-year career. Tools like ChatGPT have three superpowers: obscene convenience, instant availability, and blistering speed. In a world where time is money and most writing does not need to summon the ghost of James Baldwin, AI is already good enough for about 95 percent of professional communication. And there it is—the phrase that should make educators break out in hives: good enough.

    “Good enough” is convenience’s love language. Imagine waking up groggy and choosing between two breakfasts. Option one is a premade smoothie: beige, foamy, nutritionally ambiguous, and available immediately. Option two is a transcendent, handcrafted masterpiece—organic fruit, thick Greek yogurt, chia seeds, almond milk—but to get it you must battle orb spiders in your backyard, dodge your neighbor’s possessed Belgian dachshund, and then spend quality time scrubbing a Vitamix before fighting traffic. Which one do most people choose?

    Exactly. The premade sludge. Because who has time for spider diplomacy and blender maintenance before a commute? Convenience wins, quality loses, and you console yourself with the time you saved. Eventually, you stop missing the better option altogether. That slow adjustment—lowering your standards until mediocrity feels normal—is attenuation.

    Now swap smoothies for writing. Writing is far harder than breakfast, and millions of people are quietly recalibrating their expectations. Why labor over sentences when the world will happily accept algorithmic mush? Polished prose is becoming the artisanal smoothie of communication: admirable, expensive, and increasingly optional. AI delivers something passable in seconds, and passable is the new benchmark.

    For educators, this is not a quirky inconvenience. It’s a five-alarm fire. I did not enter this profession to train students to become connoisseurs of adequacy. I wanted to cultivate thinkers, stylists, arguers—people whose sentences had backbone and intent. Instead, I find myself in a dystopia where “good enough” is the new gospel and I’m preaching craft like a monk selling calligraphy at a tech startup demo day.

    In medicine, the Hippocratic Oath is “Do no harm.” In teaching, the unspoken oath is blunter and less forgiving: never train your students to become Good-Enoughers—those half-awake intellectual zombies who mistake adequacy for achievement and turn mediocrity into a permanent way of life.

    Whatever role AI plays in my classroom, one line is nonnegotiable. The moment I use it to help students settle for less—to speed them toward adequacy instead of depth—I’m no longer teaching. I’m committing educational malpractice.

  • Cognitive Thinning and Cognitve Load-Bearing Capacity

    Cognitive Thinning and Cognitve Load-Bearing Capacity

    In his bracing essay “Colleges Are Preparing to Self-Lobotomize,” Michael Clune accuses higher education of handling AI with the institutional equivalent of a drunk chainsaw. The subtitle gives away the indictment: “The skills that students will need in an age of automation are precisely those that are eroding by inserting AI into the educational process.” Colleges, Clune argues, spent the first three years of generative AI staring at the floor. Now they’re overcorrecting—embedding AI everywhere as if saturation were the same thing as competence. It isn’t. It’s panic dressed up as innovation.

    The prevailing fantasy is that if AI is everywhere, mastery will seep into students by osmosis. But the opposite is happening. Colleges are training students to rely on frictionless services while quietly abandoning the capacities that make AI usable in any serious way: judgment, learning agility, and flexible analysis. The tools are getting smarter. The users are getting thinner.

    That thinning has a name. Cognitive Thinning is the gradual erosion of critical thinking that occurs when sustained mental effort is replaced by convenience. It sets in when institutions assume that constant exposure to powerful tools will produce competence, even as they dismantle the practices that build it. As AI grows more capable, students are asked to do less thinking, tolerate less uncertainty, and carry less intellectual weight. The result is a widening imbalance: smarter systems paired with slimmer minds—efficient, polished, and increasingly unable to move beyond the surface of what machines provide.

    Clune wants students to avoid this fate, but he faces a rhetorical problem. He keeps insisting on abstractions—critical thinking, intellectual flexibility, judgment—in a culture trained to distrust anything abstract. Telling a screen-saturated society to imagine thinking outside screens is like telling a fish to imagine life outside water. The first task isn’t instruction. It’s translation.

    The fish analogy holds. A fish is aquatic; water isn’t a preference—it’s a prison. A young person raised entirely on screens, prompts, and optimization tools treats that ecosystem as reality itself. Like the fish, they know only one environment. We can name this condition precisely. They are cognitively outsourced, trained to delegate thought as if it were healthy. They are algovorous, endlessly stimulated by systems that quietly erode attention and resilience. They are digitally obligate, unable to function without mediation. By definition, these orientations crowd out critical thinking. They produce people who function smoothly inside digital systems and falter everywhere else.

    Drop such a person into a college that recklessly embeds AI into every course in the name of being “future-proof,” and you don’t produce adaptability—you produce fragility. In some fields, this fragility is fatal. Clune cites a telling statistic: history majors now have roughly half the unemployment rate of recent computer science graduates. The implication is blunt. Liberal education builds range. Narrow technical training builds specialists who snap when the environment shifts. As the New York Times put it in a headline Clune references: “Goodbye, $165,000 Tech Jobs. Student Coders Seek Work at Chipotle.” AI is replacing coders. Life inside a tiny digital ecosystem does not prepare you for a world that mutates.

    Is AI the cause of this dysfunction? No. The damage predates ChatGPT. I use AI constantly—and enjoy it. It sharpens my curiosity. It helps me test ideas. It makes me smarter because I am not trapped inside it. I have a life beyond screens. I’ve read thousands of books. I can zoom in and out—trees and forest—without panic. I have language for my inner life, which means I can catch myself when I become maudlin, entropic, dissolute, misanthropic, lugubrious, or vainglorious. I have history, philosophy, and religion as reference points. We call this bundle “critical thinking,” but what it really amounts to is being fully human.

    Someone who has outsourced thought and imagination since childhood cannot suddenly use AI well. They aren’t liberated. They’re brittle—dependent, narrow, and easily replaced.

    Because I’m a lifelong weightlifter, let me be concrete. AI is a massive, state-of-the-art gym: barbells, dumbbells, Smith machines, hack squats, leg presses, lat pulldowns, pec decks, cable rows—the works. Now imagine you’ve never trained. You’re twenty-eight, inspired by Instagram physiques, vaguely determined to “get in shape.” You walk into this cathedral of iron with no plan, no understanding of recovery, nutrition, progressive overload, or discipline. You’re surrounded by equipment—and completely lost. Within a month, you quit. You join the annual migration of January optimists who vanish by February, leaving the gym to the regulars.

    AI is that gym. It doesn’t eject users out of malice. It ejects them because it demands capacities they never built. Some people learn isolated tricks—prompting here, automating there—but only the way someone learns to push a toaster lever. When these tasks define a person, the result is a Non Player Character: reactive, scripted, interchangeable.

    Students already understand what an NPC is. That’s why they fear becoming one.

    If colleges embed AI everywhere without building the human capacities required to use it, they aren’t educating thinkers. They’re manufacturing NPCs—and they deserve to be called out for it.

    Don’t wait for your institution to save you. Approach education the way you’d approach a gym. Learn how bodies actually grow before touching the weights. Know the muscle groups. Respect recovery. Understand volume, exhaustion, and nutrition. Do the homework so the gym doesn’t spit you out.

    The same rule applies to AI. To use it well, you need a specific kind of mental strength: Cognitive Load-Bearing Capacity. This is the ability to use AI without surrendering your thinking. You can see it in ordinary behaviors: reading before summarizing, drafting before prompting, distrusting answers that sound too smooth, and revising because an idea is weak—not because a machine suggested a synonym. It’s the capacity to sit with confusion, compare sources, and arrive at judgment rather than outsource it.

    This capacity isn’t innate, and it isn’t fast. It’s built through resistance: sustained reading, outlining by hand, struggling with unfamiliar ideas, revising after failure. Students with cognitive load-bearing capacity use AI to pressure-test their thinking. Students without it use AI to replace thinking. One group grows stronger and more adaptable. The other becomes dependent—and replaceable.

    Think of AI like a piano. You can sit down and bang out notes immediately, but you won’t produce music. Beautiful playing requires trained fingers, disciplined ears, and years of wrong notes. AI works the same way. Without cognitive load-bearing capacity, you get noise—technically correct, emotionally dead. With it, the tool becomes expressive. The difference isn’t the instrument. It’s the musician.

    If you want to build this capacity, forget grand reforms. Choose consistent resistance. Read an hour a day with no tabs open. Write before prompting. Ask AI to attack your argument instead of finishing it. Keep a notebook where you explain ideas in your own words, badly at first. Sit with difficulty instead of dodging it. These habits feel inefficient—and that’s the point. They’re the mental equivalent of scales and drills. Over time, they give you the strength to use powerful tools without being used by them.

  • The Hamster Wheel of Optimization

    The Hamster Wheel of Optimization

    In “AI Has Broken High School and College,” Damon Beres stages a conversation between Ian Bogost and Lila Shroff that lands like a diagnosis no one wants but everyone recognizes. Beres opens with a blunt observation: today’s high school seniors are being told—implicitly and explicitly—that their future success rests on their fluency with chatbots. School is no longer primarily about learning. It has become a free-for-all, and teachers are watching from the sidelines with a whistle that no longer commands attention.

    Bogost argues that educators have responded by sprinting toward one of two unhelpful extremes: panic or complacency. Neither posture grapples with reality. There is no universal AI policy, and students are not using ChatGPT only to finish essays. They are using it for everything. We have already entered a state of AI normalization, where reliance is no longer an exception but a default. To explain the danger, Bogost borrows a concept from software engineering: technical debt—the seductive habit of choosing short-term convenience while quietly accruing long-term catastrophe. You don’t fix the system; you keep postponing the reckoning. It’s like living on steak, martinis, and banana splits while assuring yourself you’ll start jogging next year.

    Higher education, Bogost suggests, has compounded the problem by accumulating what might be called pedagogical debt. Colleges never solved the hard problems: smaller class sizes, meaningful writing assignments, sustained feedback, practical skill-building, or genuine pipelines between students and employers. Instead, they slapped bandages over these failures and labeled them “innovation.” AI didn’t create these weaknesses; it simply makes it easier to ignore them. The debt keeps compounding, and the interest is brutal.

    Bogost introduces a third and more existential liability: the erosion of sacred time. Some schools still teach this—places where students paint all day, rebuild neighborhoods, or rescue animals, learning that a meaningful life requires attention, patience, and presence. Sacred time resists the modern impulse to finish everything as fast as possible so you can move on to the next task. AI dependence belongs to a broader pathology: the hamster wheel of deadlines, productivity metrics, and permanent distraction. In that world, AI is not liberation. It is a turbocharger for a life without meaning.

    AI also accelerates another corrosive force: cynicism. Students tell Bogost that in the real world, their bosses don’t care how work gets done—only that it gets done quickly and efficiently. Bogost admits they are not wrong. They are accurately describing a society that prizes output over meaning and speed over reflection. Sacred time loses every time it competes with the rat race.

    The argument, then, is not a moral panic about whether to use AI. The real question is what kind of culture is doing the using. In a system already bloated with technical and pedagogical debt, AI does not correct course—it traps us in what I call the Hamster Wheel of Optimization: A cultural condition in which speed, efficiency, and constant output are mistaken for progress, trapping individuals and institutions in endless motion without direction or meaning. On the Hamster Wheel of Optimization, short-term convenience is endlessly prioritized while long-term costs—intellectual, moral, and human—quietly accumulate. Learning becomes task completion, education becomes workflow management, and sacred time is crowded out by deadlines, metrics, and permanent distraction. AI does not create this condition; it accelerates it, serving as a turbocharger for a system already addicted to doing more, faster, and cheaper, even as depth, reflection, and purpose steadily erode.

  • Pedagogical Liminality

    Pedagogical Liminality

    Lila Shroff argues that education has entered its Wild West phase in her essay “The AI Takeover of Education Is Just Getting Started,” and she’s right in the way that makes administrators nervous and instructors quietly exhausted. Most of you are not stumbling innocents. You are veterans of four full years of AI high school. You no longer engage in crude copy-and-paste plagiarism. That’s antique behavior. You’ve learned to stitch together outputs from multiple models, then instruct the chatbot to scuff the prose with a few grammatical imperfections so it smells faintly human and slips past detection software. This is not cheating as shortcut; it is cheating as workflow optimization.

    Meanwhile, many high school teachers congratulate themselves for assigning Shakespeare, Keats, and Dostoevsky while willfully ignoring the obvious. Students are using AI constantly—for summaries, study guides, feedback, and comprehension scaffolding. AI is CliffsNotes on growth hormones, and pretending otherwise is an exercise in institutional denial.

    Educators, of course, are not standing outside the saloon wagging a finger. We are inside, ordering fizzy drinks. Shroff notes that teachers now use AI to design assignments, align curriculum to standards, grade against rubrics, and complete the paperwork that keeps schools legally hydrated. Nearly a third of K–12 teachers reported weekly AI use last year, and that number has only climbed as profession-specific tools like MagicSchool AI churn out rubrics, worksheets, and report-card comments on demand. The teacher as craftsman is quietly mutating into the teacher as editor.

    AI tightens its grip most aggressively where schools are already bleeding resources. In districts short on tutors and counselors, AI steps in as a substitute for services that were never funded in the first place. This is not reform; it is triage. And once institutions develop a taste for saving money by not hiring tutors and counselors, it is naïve to think teaching positions will remain sacred. Cost-cutting rarely stops at the first ethical boundary it crosses.

    That is why this moment feels like the Wild West. There is no shared map. Some schools welcome AI like a messiah. Others quarantine it like a contagious disease. Many simply shrug and admit they are baffled. Policy is reactive, inconsistent, and often written by people who do not understand the technology well enough to regulate it intelligently.

    I see the consequences every week in my college classroom. I read plenty of AI slop—essays with flawless grammar and no pulse, paragraphs that gesture toward ideas they never quite touch. Some students have checked out entirely, outsourcing not just sentences but thinking itself. And yet AI is also an undeniable equalizer. Students emerging from underfunded schools with sixth-grade literacy levels are now submitting essays with clean syntax and logical structure. They use AI to outline arguments, test thesis ideas, and stabilize skills they were never taught. The tool giveth, and the tool holloweth out.

    People like to invoke “too big to fail,” but the analogy doesn’t hold. We don’t know which AI—ChatGPT, Gemini, Claude, or some yet-unseen contender—will dominate. What we do know is that AI is already embedded in education, culture, and the economy. There is no reversing this process. The toothpaste is not going back in the tube, no matter how sternly we lecture it.

    So understand this about me and my fellow instructors: we don’t know what we’re doing. Our roles are unsettled. Our identities are unstable. We are feeling our way through a dark cave without a map and without guarantees. There may be light ahead, or there may not.

    The only sane posture is humility—paired with curiosity, caution, and a sober gratitude that even a force this disruptive may yield benefits we are not yet wise enough to recognize. The name for this condition is Pedagogical Liminality: the in-between state educators now inhabit as teaching crosses from the pre-AI world into an uncharted machine age. Old rules no longer hold. New ones have not yet solidified. The ground keeps shifting under our feet.

    In this state, arrogance is dangerous. Despair is paralyzing. Certainty is counterfeit. Pedagogical Liminality is not failure; it is the honest middle passage—awkward, uncertain, and unavoidable—before a new educational order can be named.

  • Mediocrity Amplification Effect

    Mediocrity Amplification Effect

    As you watch your classmates use AI for every corner of their lives—summarizing, annotating, drafting, thinking—you may feel a specific kind of demoralization set in. A sinking question forms: What does anything matter anymore? Is life now just a game of cheating the system efficiently? Is this where all the breathless hype about “the future” has landed us—an economy of shortcuts and plausible fraud?

    High school student Ashanty Rosario feels this acutely. She gives voice to the heartbreak in her essay “I’m a High Schooler. AI Is Demolishing My Education,” a lament not about laziness but about loss. She doesn’t want to cheat. But the tools are everywhere, glowing like emergency exit signs in a burning building. Some temptations, she understands, are structural.

    Her Exhibit A is devastating. A classmate uses ChatGPT to annotate Narrative of the Life of Frederick Douglass. These annotations—supposed proof of engaged reading—are nothing more than copy-paste edu-lard: high in calories, low in nutrition, and utterly empty of struggle. The form is there. The thinking is not.

    Rosario’s frustration echoes a moment from my own classroom. On the last day of the semester, one of my brightest students sat in my office and casually admitted that he uses ChatGPT to summarize all his reading. His father is a professor. He wakes up at five for soccer practice. He takes business calculus for fun. This is not a slacker. This is a time-management pragmatist surviving the twenty-first century. He reads the summaries, synthesizes the ideas, and writes excellent essays. Of course I wish he spent slow hours wrestling with books—but he is not living in 1954. He is living in a culture where time is scarce and AI functions as an oxygen mask.

    My daughters and their classmates face the same dilemma with Macbeth. Shakespeare’s language might as well be Martian for a generation raised on TikTok compression and dopamine drip-feeds. They watch film adaptations. They use AI to decode plot points so they can answer study questions without sounding like they slept through the Renaissance. Purists howl that this is cheating. But as a writing instructor, I suspect teachers benefit from students who at least know what’s happening—even if the knowledge arrives via chatbot. Expecting a fifteen-year-old to read Macbeth cold is like assigning tensor calculus to a preschooler. They haven’t done their priors. So AI becomes a prosthetic. A flotation device. A translation machine dropped into classrooms years overdue.

    Blaming AI for educational decline is tempting—but it’s also lazy. We live in a society where reading is a luxury good and the leisure class quietly guards the gates.

    In the 1970s, I graduated from a public high school with literacy skills so thin you could read the room through them. I took remedial English my freshman year of college. If I were a student today, dropped into 2025 with those same deficits, I would absolutely lean on AI just to keep my head above water. The difference now is scale. Today’s students aren’t just supplementing—they’re optimizing. They tell me this openly. Over ninety percent of my students use AI because their skills don’t match the workload and because everyone else is doing it. This isn’t a moral collapse. It’s an arms race of survival.

    Still, Rosario is right about the aftermath. “AI has softened the consequences of procrastination,” she writes, “and led many students to avoid doing any work at all. There is little intensity anymore.” When thinking becomes optional, students drift into algorithmic sleepwalking. They outsource cognition until they resemble NPCs in a glitching video game—avatars performing the motions of thought without the effort. My colleagues and I see it every semester: the fade-out, the disengagement, the slow zombification.

    Colleges are scrambling. Should we police AI with plagiarism detectors? Ban laptops? Force students to write essays in blue books under watchful eyes like parolees in a literary halfway house? Should we pretend the flood can be held back with a beach towel?

    Reading Rosario’s complaint about “cookie-cutter AI arguments,” I thought of my lone visit to Applebee’s in the early 2000s. The menu photos promised ambrosia. The food tasted like something engineered in a lab to be technically edible yet spiritually vacant. Applebee’s was AI before AI—an assembly line of flavorless simulacra. Humanity has always gravitated toward the easy, the prepackaged, the frictionless. AI didn’t invent mediocrity. It just handed it a megaphone.

    Rosario is no Applebee’s soul. She’s Michelin-level in a world eager to microwave Hot Pockets. Of course her heart sinks when classmates settle for fast-food literacy. I want to tell her this: had she been in high school in the 1970s, she would have witnessed the same hunger for shortcuts. The tools would be clumsier. The prose less polished. But the gravitational pull would be identical. The urge to bypass difficulty is not technological—it’s ancestral.

    What’s new is scale and speed. In the AI age, that ancient hunger is supercharged by what I call the Mediocrity Amplification Effect: the phenomenon by which AI accelerates and magnifies our long-standing temptation to dilute effort and settle for the minimally sufficient. Under this effect, tools meant to assist learning become accelerants of shortcut culture. Procrastination carries fewer consequences. Intensity drains away. Thinking becomes optional.

    This is not a new moral failure. It is an old one, industrialized—private compromise transformed into public default, mediocrity polished, normalized, and broadcast at scale. AI doesn’t make us lazy. It makes laziness louder.

  • On the Importance of Cultivating a New Lexicon for Education in the Machine Age

    On the Importance of Cultivating a New Lexicon for Education in the Machine Age

    If you’re a college student who used AI all through high school, you’ve probably already heard the horror stories. Professors who ban AI outright. They pass out photocopied essays and poems and you have to annotate them with pens and pencils. The only kind of writing you do for a grade is in-class blue books dragged out like museum artifacts. Class participation grades hover over your head like a parole officer. You quietly avoid these instructors. Sitting in their classrooms would feel like being a fish dropped onto dry land.

    You grew up with screens. These Boomer professors grew up in a Pre-Screen Universe—a world that shaped their intellect, habits, and philosophy before the internet rewired everything. Now they want to haul you back there, convinced that salvation lies in reenactment. You can smell the desperation. You can also smell the futility. This is a waiting game, and you know how it ends. AI is not going away. The toothpaste is not going back in the tube. The genie is not returning to the bottle. You will use AI after graduation because the world you are entering already runs on it. These Pre-Screen Professors will eventually retire, ranting into the void. You don’t have time to wait them out. You’re here to get an education, and you’re not going to turn your back on AI now, not after it helped you make the Dean’s List in high school. 

    And yet—here’s the part you can’t ignore—you’re not wrong to be uneasy. You know what happens when AI use goes overboard. When thinking is outsourced wholesale, something essential atrophies. The inner fire dims. Judgment weakens. Agency erodes. Your sense of self vanishes. You become an NPC: responsive but not reflective, efficient but hollow. A form of hell with good grammar and polished syntax but hell nevertheless.

    So the problem isn’t whether to use AI. The problem is how to use it without surrendering yourself to it. You need a balance. You need to work effectively with machines while remaining unmistakably human. That requires more than rules or bans. It requires a new language—terms that help you recognize the traps, name the tradeoffs, and choose deliberately rather than drift.

    That’s what this lexicon is for. It is not a manifesto against technology or a nostalgic plea to return to chalk and silence. It’s a survival guide for the Machine Age—realistic, unsentimental, and shared by students and instructors alike. On one hand, you must learn how to navigate AI to build a future. On the other, you must learn how not to lose yourself in the process. This lexicon exists to help you do both.

  • Medium Essentialism Fallacy

    Medium Essentialism Fallacy

    Medium Essentialism Fallacy
    noun

    The mistaken belief that certain formats—books over video, radio over television—are inherently more imaginative or intellectually serious than others. The medium essentialism fallacy assumes depth scales with page count or technological austerity, treating a 400-page novel as automatically superior to a four-minute online video, or a golden-age radio drama as more “imaginative” than contemporary television. It sanctifies books by default (the novel, the monograph), nostalgically elevates radio (the era of voices and silence), and dismisses TV and online video as diluted forms—ignoring examples like Severance or Childish Gambino’s “This Is America,” where compression, symbolism, and craft do heavy intellectual lifting. In medium essentialism, imagination is misattributed to format rather than earned through execution.

  • Books Aren’t Dead—They’ve Just Lost Their Monopoly

    Books Aren’t Dead—They’ve Just Lost Their Monopoly

    Are young people being vacuum-sealed into their screens, slowly zombified by AI and glowing rectangles? This is the reigning panic narrative of our moment, a familiar sermon about dehumanization and decline. In his essay “My Students Use AI. So What?” linguist John McWhorter asks us to ease off the apocalypse pedal and consider a less hysterical possibility: the world has changed, and our metaphors haven’t caught up.

    McWhorter opens close to home. His tween daughters, unlike him, are not bookworms. They are screenworms. He once spent his leisure hours buried in books; now he, too, spends much of his reading life hunched over a phone. He knows what people expect from him—a professor clutching pearls over students who read less, write with AI, and allegedly let their critical thinking rot. Instead, he disappoints the doom merchants. Screens replacing books, he argues, is not evidence of “communal stupidity.” It is evidence of migration.

    Yes, young people read fewer books for pleasure. McWhorter cites a 1976 study showing that 40 percent of high school seniors had read at least six books for fun in the previous year—a number that has since cratered. But this does not mean young people have abandoned language. Words are everywhere. Print no longer monopolizes thought. Screens now host essays, debates, Substack newsletters, podcasts, and long-form conversations that reveal not a hunger deficit but a format shift. As McWhorter puts it, the explosion of thoughtful digital writing signals demand for ideas, not their extinction.

    He is not naïve about online slop. He limits the digital junk his daughters would otherwise inhale all day. Still, he resists the snobbery that treats ubiquity as proof of worthlessness. “The ubiquity of some content doesn’t mean it lacks art,” he writes—a useful reminder in an age that confuses popularity with emptiness. Much online culture is disposable. Some of it is sharp, inventive, and cognitively demanding.

    McWhorter also dismantles a familiar prejudice: that books are inherently superior because they “require imagination.” He calls this argument a retroactive justification for bias. Reading his rebuttal, I’m reminded that Childish Gambino’s four-minute video “This Is America,” watched tens of millions of times on YouTube, is so dense with political symbolism and cultural critique that it could easily spawn a 300-page monograph. Imagination is not a function of page count.

    He takes aim at another antique claim—that radio was more imaginative than television. Citing Severance, McWhorter argues that contemporary TV can engage the imagination and critical thinking as effectively as any golden-age broadcast. Medium does not determine depth. Craft does.

    McWhorter also punctures our nostalgia. Were people really reading as much as we like to believe? When he was in college, most students avoided assigned texts just as enthusiastically as students do now. The pre-digital world had CliffNotes. Avoidance is not a TikTok invention.

    He reserves particular scorn for recklessly designed syllabi: professors assigning obscure philosophical fragments they never explain, using difficulty as décor. The syllabus looks impressive; students are left bewildered. McWhorter learned from this and streamlined his own reading lists, favoring coherence over intimidation.

    AI, however, has forced real change. The five-paragraph essay is finished; machines devour it effortlessly. McWhorter has responded by designing prompts meant to outrun AI’s comfort zone and by leaning harder on in-class writing. One of his questions—“How might we push society to embrace art that initially seems ugly?”—aims to provoke judgment rather than summary. I’m less confident than he is that such prompts are AI-proof, but I take his point. A philosophically demanding question tethered to specific texts still forces students to synthesize, even if AI hovers nearby. He also emphasizes graded participation, returning thinking to the room rather than the cloud.

    McWhorter’s larger argument is pragmatic, not permissive. Technology will keep changing. Education always lags behind it. The task of instructors is not to reverse technological history but to adapt intelligently—to identify what new tools erode, what they amplify, and how to redesign teaching accordingly. Panic is lazy. Nostalgia is misleading. The real work is harder: staying alert, flexible, and honest about both the costs and the gains.