Cinemorphosis

Category: culture

  • 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.

  • 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.

  • 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.

  • A College Instructor’s Biggest Challenge Is Closing the Abstraction Resistance Gap

    A College Instructor’s Biggest Challenge Is Closing the Abstraction Resistance Gap

    Abstraction Resistance Gap
    noun

    There is a widening cultural mismatch between the need for abstract intellectual capacities—critical thinking, judgment, conceptual flexibility—and a population trained to expect concrete, instant, screen-mediated results. The abstraction resistance gap opens when societies raised on prompts and outputs lose the ability to value thought that cannot be immediately displayed, optimized, or monetized. Ideas that require time, silence, and struggle arrive speaking a language the audience no longer understands. Teaching fails not because the ideas are wrong, but because they require translation into a cognitive dialect that has gone extinct.

    If you are a college writing instructor facing students who spent four years of high school outsourcing their homework to AI, you are standing on the front lines of this gap. Your task is not merely to assign essays. It is to supply a framework for critical thinking, a vocabulary for understanding that framework, and—hardest of all—a reason to choose it over frictionless delegation. You are asking students to resist the gravitational pull of machines and to decline the comfortable role of Non Player Character.

    Your enemy is not ignorance. It is time. No one becomes a critical thinker overnight. It takes years of sustained reading and what Cal Newport calls deep work: long stretches of attention without dopamine rewards. When you pause long enough to consider the difficulty of this task—and the odds stacked against it—it can drain the optimism from even the most committed instructor. You are not teaching a skill. You are trying to resurrect a way of thinking in a culture that has already moved on.

  • The Doomed Defiance of the Promethean Delusion

    The Doomed Defiance of the Promethean Delusion

    Promethean Delusion
    noun

    The Promethean impulse—named for the mythic thief who stole fire from the gods—now animates the fantasy that technological optimization can transform humans into frictionless, quasi-divine beings without cost or consequence. In this delusion, machines are no longer tools that extend human capacity; they are ladders to transcendence. Power is mistaken for wisdom. Speed for meaning. Anything that resists optimization is treated as a design flaw waiting to be patched.

    Limits become intolerable. Slowness is framed as inefficiency. Mortality is treated as a bug. Kairos—the lived, sacred time through which meaning actually forms—is dismissed as waste, an obstacle to throughput. What emerges is not liberation but derangement: expanding capability paired with a shrinking sense of what a human life is for.

    So what does it mean to be human? The answer depends on which story you choose to inhabit. The Promethean tech evangelist sees the human being as an unfinished machine—upgradeable, indefinitely extendable, and perhaps immortal if the right knobs are turned. All problems reduce to engineering: tighten this screw, loosen that one, eliminate friction, repeat.

    The Christian story is harsher and more honest. It begins with brokenness, not optimization—with mortal creatures who cannot save themselves and who long for reconciliation with their Maker. To reject this account is to rebel, to attempt demigodhood by force of will and code. As John Moriarty observed, “The story of Christianity is the story of humanity’s rebellion against God.” The dream of becoming frictionless and divine is not progress; it is a doomed defiance. It does not end in transcendence but in collapse—moral, spiritual, and eventually civilizational.

  • Kairos vs. Chronos: The Battle for Human Time

    Kairos vs. Chronos: The Battle for Human Time

    Kairos names a rare kind of time—the moment when life thickens and becomes meaningful. It is the time of attention and presence, when learning actually happens, when a sentence suddenly makes sense, when an idea lands with the force of revelation. Kairos is not counted; it is entered. You don’t measure it. You feel it. It is the time of epiphany, imagination, and inward transformation.

    Chronos, by contrast, is time broken into units and put to work. It is the time of clocks, calendars, deadlines, and dashboards. Chronos asks how long something took, how efficiently it was completed, and whether it can be done faster next time. It governs offices, classrooms, and productivity apps. Chronos is indispensable—but it is also merciless.

    Kairos belongs to myth, enchantment, and meaning. Chronos belongs to business, logistics, and quarterly reports. We need both. But when life tilts too far toward chronos, we find ourselves strapped to the Hamster Wheel of Optimization, mistaking motion for progress. The cost is steep. We don’t just lose kairos—the sacred time of depth and presence. We lose vitality, interiority, and eventually our sense of being fully alive.

    This tension animates the work of Paul Kingsnorth, particularly in Against the Machine: On the Unmaking of Humanity. Kingsnorth’s project is not nostalgia but boundary-setting. He argues that preserving our humanity requires limits—lines we refuse to cross. The dream of using machines to become demigods is not liberation; it is derangement. The fantasy of the uberhuman, endlessly optimized and frictionless, is a story told by technologists whose ambition for profit and control is vast, but whose understanding of human nature is alarmingly thin.

    Machines can extend our reach. They cannot supply meaning. That still requires kairos—time that cannot be optimized without being destroyed.

  • AI Is a Gym, But the Students Need Muscles

    AI Is a Gym, But the Students Need Muscles

    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 game: “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 sitting on their hands. Now they are overcorrecting in a frenzy, embedding AI everywhere as if saturation were the same thing as competence. It isn’t. It’s panic dressed up as innovation.

    The prevailing assumption seems to be that if AI is everywhere, mastery will somehow emerge by osmosis. But what’s actually happening is the opposite. Colleges are training students to rely on frictionless services while neglecting the very capacities that make AI usable in any meaningful way: critical thinking, the ability to learn new things, and flexible modes of analysis. The tools are getting smarter; the users are getting thinner.

    Clune faces a genuine rhetorical problem. He keeps insisting that we need abstractions—critical thinking, intellectual flexibility, judgment—but we live in a culture that has been 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, then, is not instruction but translation: What is critical thinking, and how do you sell it to people addicted to immediate, AI-generated results?

    The fish analogy holds. A fish is aquatic; water is not a preference but a prison. A young person raised entirely on screens, prompts, and optimization tools treats that ecosystem as reality itself. Like the fish, they are confined to a single environment. We can name this condition precisely. They are cognitively outsourced, trained to delegate thinking to machines as if this were normal or healthy. They are algovorous, endlessly stimulated by algorithms that quietly erode attention and resilience. They are digitally obligate, unable to function without mediation. By definition, these orientations exclude critical thinking. They produce people who are functional inside digital systems and dysfunctional 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 send them into the job market as a fragile, narrow organism. In some fields, they will be unemployable. Clune points to a telling statistic: history majors currently have an unemployment rate roughly half that of recent computer science graduates. The implication is brutal. Liberal arts training produces adaptability. Coding alone does not. As the New York Times put it in a headline Clune cites, “Goodbye, $165,000 Tech Jobs. Student Coders Seek Work at Chipotle.” AI is replacing coders. A life spent inside a tiny digital ecosystem does not prepare you for a world that mutates.

    Is AI the cause of this dysfunction? No. The damage was done long before ChatGPT arrived. I use AI constantly, and I 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 have 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 diagnose myself when I become maudlin, entropic, dissolute, misanthropic, lugubrious, or vainglorious. I have history, philosophy, and religion as reference points. All of this adds up to what we lazily call “critical thinking,” but what it really means is being fully human.

    Someone who has outsourced thought and imagination from childhood cannot suddenly use AI well. They are neither liberated nor empowered. They are brittle, dependent, and easily replaced.

    Because I am a lifelong weightlifter, I’ll offer a more concrete analogy. AI is a massive, state-of-the-art gym: barbells, dumbbells, Smith machines, hack squats, leg presses, lat pulldowns, pec decks, cable rows, preacher curls—the works. Now imagine you’ve never trained before. You’re twenty-eight, inspired by Instagram physiques, and vaguely determined to “get in shape.” You walk into this cathedral of iron with no plan, no understanding of hypertrophy, recovery, protein intake, progressive overload, or long-term discipline. You are surrounded by equipment, but you are lost. Within a month, you will quit. You’ll join the annual migration of January optimists who vanish by February, leaving the gym once again to the regulars.

    AI is that gym. It will eject most users. Not because it is hostile, but because it demands capacities they never developed. Some people will learn isolated tasks—prompting here, automating there—but only in the way someone learns to push a toaster lever. These tasks should not define a human being. When they do, the result is a Non Player Character: reactive, scripted, interchangeable.

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

    If colleges recklessly embed AI into every corner of the curriculum, they are not educating thinkers. They are manufacturing NPCs. And for that, they deserve public shame.

  • Stupidification Didn’t Start with AI—It Just Got Faster

    Stupidification Didn’t Start with AI—It Just Got Faster

    What if AI is just the most convenient scapegoat for America’s long-running crisis of stupidification? What if blaming chatbots is simply easier than admitting that we have been steadily accommodating our own intellectual decline? In “Stop Trying to Make the Humanities ‘Relevant,’” Thomas Chatterton Williams argues that weakness, cowardice, and a willing surrender to mediocrity—not technology alone—are the forces hollowing out higher education.

    Williams opens with a bleak inventory of the damage. Humanities departments are in permanent crisis. Enrollment is collapsing. Political hostility is draining funding. Smartphones and social media are pulverizing attention spans, even at elite schools. Students and parents increasingly question the economic value of any four-year degree, especially one rooted in comparative literature or philosophy. Into this already dire landscape enters AI, a ready-made proxy for writing instructors, discussion leaders, and tutors. Faced with this pressure, colleges grow desperate to make the humanities “relevant.”

    Desperation, however, produces bad decisions. Departments respond by accommodating shortened attention spans with excerpts instead of books, by renaming themselves with bloated, euphemistic titles like “The School of Human Expression” or “Human Narratives and Creative Expression,” as if Orwellian rebranding might conjure legitimacy out of thin air. These maneuvers are not innovations. They are cost-cutting measures in disguise. Writing, speech, film, philosophy, psychology, and communications are lumped together under a single bureaucratic umbrella—not because they belong together, but because consolidation is cheaper. It is the administrative equivalent of hospice care.

    Williams, himself a humanities professor, argues that such compromises worsen what he sees as the most dangerous threat of all: the growing belief that knowledge should be cheap, easy, and frictionless. In this worldview, learning is a commodity, not a discipline. Difficulty is treated as a design flaw.

    And of course this belief feels natural. We live in a world saturated with AI tutors, YouTube lectures, accelerated online courses, and productivity hacks promising optimization without pain. It is a brutal era—lonely, polarized, economically unforgiving—and frictionless education offers quick solace. We soothe ourselves with dashboards, streaks, shortcuts, and algorithmic reassurance. But this mindset is fundamentally at odds with the humanities, which demand slowness, struggle, and attention.

    There exists a tiny minority of people who love this struggle. They read poetry, novels, plays, and polemics with the obsessive intensity of a scientist peering into a microscope. For them, the intellectual life supplies meaning, irony, moral vocabulary, civic orientation, and a deep sense of interiority. It defines who they are. These people often teach at colleges or work on novels while pulling espresso shots at Starbucks. They are misfits. They do not align with the 95 percent of the world running on what I call the Hamster Wheel of Optimization.

    Most people are busy optimizing everything—work, school, relationships, nutrition, exercise, entertainment—because optimization feels like survival. So why wouldn’t education submit to the same logic? Why take a Shakespeare class that assigns ten plays in a language you barely understand when you can take one that assigns a single movie adaptation? One professor is labeled “out of touch,” the other “with the times.” The movie-based course leaves more time to work, to earn, to survive. The reading-heavy course feels indulgent, even irresponsible.

    This is the terrain Williams refuses to romanticize. The humanities, he argues, will always clash with a culture devoted to speed, efficiency, and frictionless existence. The task of the humanities is not to accommodate this culture but to oppose it. Their most valuable lesson is profoundly countercultural: difficulty is not a bug; it is the point.

    Interestingly, this message thrives elsewhere. Fitness and Stoic influencers preach discipline, austerity, and voluntary hardship to millions on YouTube. They have made difficulty aspirational. They sell suffering as meaning. Humanities instructors, despite possessing language and ideas, have largely failed at persuasion. Perhaps they need to sell the life of the mind with the same ferocity that fitness influencers sell cold plunges and deadlifts.

    Williams, however, offers a sobering reality check. At the start of the semester, his students are electrified by the syllabus—exploring the American Dream through Frederick Douglass and James Baldwin. The idea thrills them. The practice does not. Close reading demands effort, patience, and discomfort. Within weeks, enthusiasm fades, and students quietly outsource the labor to AI. They want the identity of intellectual rigor without submitting to its discipline.

    After forty years of teaching college writing, this pattern is painfully familiar to me. Students begin buoyant and curious. Then comes the reading. Then comes the checkout.

    Early in my career, I sustained myself on the illusion that I could shape students in my own image—cultivated irony, wit, ruthless critical thinking. I wanted them to desire those qualities and mistake my charisma as proof of their power. That fantasy lasted about a decade. Eventually, realism took over. I stopped needing them to become like me. I just wanted them to pass, transfer, get a job, and survive.

    Over time, I learned something paradoxical. Most of my students are as intelligent as I am in raw terms. They possess sharp BS detectors and despise being talked down to. They crave authenticity. And yet most of them submit to the Hamster Wheel of Optimization—not out of shallowness, but necessity. Limited time, money, and security force them onto the wheel. For me to demand a life of intellectual rigor from them often feels like Don Quixote charging a windmill: noble, theatrical, and disconnected from reality.

    Writers like Thomas Chatterton Williams are right to insist that AI is not the root cause of stupidification. The wheel would exist with or without chatbots. AI merely makes it easier to climb aboard—and makes it spin faster than ever before.

  • AI Normalization and the Death of Sacred Time

    AI Normalization and the Death of Sacred Time

    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 smooths the road toward a harder crash. Things may improve eventually, but only after we stop pretending that faster is the same as better, and convenience is the same as progress.