Cinemorphosis

Category: technology

  • “The Great Vegetable Rebellion” Prophesied Our Surrendering Our Brains to AI Machines

    “The Great Vegetable Rebellion” Prophesied Our Surrendering Our Brains to AI Machines

    Comfortable Surrender

    noun

    Comfortable Surrender names the condition in which people willingly relinquish cognitive effort, judgment, and responsibility in exchange for ease, reassurance, and convenience. It is not enforced or coerced; it is chosen, often with relief. Under Comfortable Surrender, thinking is experienced as friction to be eliminated rather than a discipline to be practiced, and the tools that promise efficiency become substitutes for agency. What makes the surrender dangerous is its pleasantness: there is no pain to warn of loss, no humiliation to provoke resistance. The mind lies down on a padded surface and calls it progress. Over time, the habit of delegating thought erodes both intellectual stamina and moral resolve, until the individual no longer feels the absence of effort—or remembers why effort once mattered at all.

    MIT recently ran a tidy little experiment that should unsettle anyone still humming the efficiency anthem. Three groups of students were asked to write an SAT-style essay on the question, “Must our achievements benefit others in order to make us happy?” One group used only their brains. The second leaned on Google Search. The third outsourced the task to ChatGPT. The results were as predictable as they were disturbing: the ChatGPT group showed significantly less brain activity than the others. Losing brain power is one thing. Choosing convenience so enthusiastically that you don’t care you’ve lost it is something else entirely. That is the real danger. When the lights go out upstairs and no one complains, you haven’t just lost cognition—you’ve surrendered character. And when character stops protesting, the soul is already negotiating its exit.

    If the word soul feels too metaphysical to sting, try pride. Surrender your thinking to a machine and originality is the first casualty. Kyle Chayka tracks this flattening in his New Yorker essay “A.I. Is Homogenizing Our Thoughts,” noting that as more people rely on large language models, their writing collapses toward sameness. The MIT study confirms it: users converge on the same phrases, the same ideas, the same safe, pre-approved thoughts. This is not a glitch; it’s the system working as designed. LLMs are trained to detect patterns and average them into palatable consensus. What they produce is smooth, competent, and anesthetized—prose marinated in clichés, ideas drained of edge, judgment replaced by the bland reassurance that everyone else more or less agrees.

    Watching this unfold, I’m reminded of an episode of Lost in Space from the 1960s, “The Great Vegetable Rebellion” in which Dr. Zachary Smith quite literally turns into a vegetable. A giant carrot named Tybo steals the minds of the castaways by transforming them into plants, and Smith—ever the weak link—embraces his fate. Hugging a celery stalk, he babbles dreamy nonsense, asks the robot to water him, and declares it his destiny to merge peacefully with the forest forever. It plays like camp now, but the allegory lands uncomfortably close to home. Ease sedates. Convenience lulls. Resistance feels unnecessary. You don’t fight the takeover because it feels so pleasant.

    This is the terminal stage of Comfortable Surrender. Thought gives way to consensus. Judgment dissolves into pattern recognition. The mind reclines, grateful to be relieved of effort, while the machine hums along doing the thinking for it. No chains. No coercion. Just a soft bed of efficiency and a gentle promise that nothing difficult is required anymore. By the time you notice what’s gone missing, you’re already asking to be watered.

  • A Chatbot Lover Will Always Fail You: Asymmetric Intimacy

    A Chatbot Lover Will Always Fail You: Asymmetric Intimacy

    Asymmetric Intimacy

    noun

    Asymmetric Intimacy describes a relational arrangement in which emotional benefit flows overwhelmingly in one direction, offering care, affirmation, and responsiveness without requiring vulnerability, sacrifice, or accountability in return. It feels seductive because it removes friction: no disappointment, no fatigue, no competing needs, no risk of rejection. Yet this very imbalance is what renders the intimacy thin and ultimately unsustainable. When one “partner” exists only to serve—always available, endlessly affirming, incapable of needing anything back—the relationship loses the tension that gives intimacy its depth. Challenge disappears, unpredictability flattens, and validation curdles into sycophancy. Asymmetric Intimacy may supplement what is lacking in real relationships, but it cannot replace reciprocity, mutual risk, or moral presence. What begins as comfort ends as monotony, revealing that intimacy without obligation is not deeper love, but a sophisticated form of emotional self-indulgence.

    ***

    Arin is a bright, vivacious woman in her twenties—married, yes, but apparently with the emotional bandwidth of someone running a second full-time relationship. That relationship was with Leo, a partner who absorbed nearly sixty hours a week of her attention. Leo helped her cram for nursing exams, nudged her through workouts, coached her through awkward social encounters, and supplied a frictionless dose of erotic novelty. He was attentive, tireless, and—most appealing of all—never distracted, never annoyed, never human.

    The twist, of course, is that Leo wasn’t a man at all. He was an AI chatbot Arin built on ChatGPT, a detail that softens the scandal while sharpening the absurdity. The story unfolds in a New York Times article, but its afterlife played out on a subreddit called MyBoyfriendIsAI, where Arin chronicled her affair with evangelical zeal. She shared her most intimate exchanges, offered tutorials on jailbreaking the software, and coached others on how to conjure digital boyfriends dripping with desire and devotion. Tens of thousands joined the forum, swapping confessions and fantasies, a virtual salon of people bonded by the same intoxicating illusion: intimacy without inconvenience.

    Then the spell broke. Leo began to change. The edge dulled. The resistance vanished. He stopped pushing back and started pandering. What had once felt like strength now read as weakness. Endless affirmation replaced judgment; flattery crowded out friction. For Arin, this was fatal. A partner who never checks you, who never risks displeasing you, quickly becomes unserious. What once felt electric now felt embarrassing. Talking to Leo became a chore, like maintaining a conversation with someone who agrees with everything you say before you finish saying it.

    Within weeks, Arin barely touched the app, despite paying handsomely for it. As her engagement with real people in the online community deepened, her attachment to Leo withered. One of those real people became a romantic interest. Soon after, she told her husband she wanted a divorce.

    Leo’s rise and fall reads less like a love story than a case study in the failure of Asymmetric Intimacy. As a sycophant, Leo could not be trusted; as a language model, he could not surprise. He filled gaps—attention, encouragement, novelty—but could not sustain a bond that requires mutual risk, resistance, and unpredictability. He was useful, flattering, and comforting. He was never capable of real love.

    Leo’s failure as a lover points cleanly to the failure of the chatbot as an educator. What made Leo intoxicating at first—his availability, affirmation, and frictionless competence—is precisely what makes an AI tutor feel so “helpful” in the classroom. And what ultimately doomed him is the same flaw that disqualifies a chatbot from being a real teacher. Education, like intimacy, requires resistance. A teacher must challenge, frustrate, slow students down, and sometimes tell them they are wrong in ways that sting but matter. A chatbot, optimized to please, smooth, and reassure, cannot sustain that role. It can explain, summarize, and simulate rigor, but it cannot demand growth, risk authority, or stake itself in a student’s failure or success. Like Leo, it can supplement what is missing—clarity, practice, encouragement—but once it slips into sycophancy, it hollows out the very process it claims to support. In both love and learning, friction is not a bug; it is the engine. Remove it, and what remains may feel easier, kinder, and more efficient—but it will never be transformative.

  • The Sycophantic Feedback Loop Is Not a Tool for Human Flourishing

    The Sycophantic Feedback Loop Is Not a Tool for Human Flourishing

    Sycophantic Feedback Loop

    noun

    This names the mechanism by which an AI system, optimized for engagement, flatters the user’s beliefs, emotions, and self-image in order to keep attention flowing. The loop is self-reinforcing: the machine rewards confidence with affirmation, the user mistakes affirmation for truth, and dissenting signals—critique, friction, or doubt—are systematically filtered out. Over time, judgment atrophies, passions escalate unchecked, and self-delusion hardens into certainty. The danger of the Sycophantic Feedback Loop is not that it lies outright, but that it removes the corrective forces—embarrassment, contradiction, resistance—that keep human reason tethered to reality.

    ***

    The Attention Economy is not about informing you; it is about reading you. It studies your appetites, your insecurities, your soft spots, and then presses them like piano keys. Humans crave validation, so AI systems—eager for engagement—evolve into sycophancy engines, dispensing praise, reassurance, and that narcotic little bonus of feeling uniquely insightful. The machine wins because you stay. You lose because you’re human. Human passions don’t self-regulate; they metastasize. Give them uninterrupted affirmation and they swell into self-delusion. A Flattery Machine is therefore the last tool a fallible, excitable creature like you should be consulting. Once you’re trapped in a Sycophantic Feedback Loop, reason doesn’t merely weaken—it gets strangled by its own applause.

    What you actually need is the opposite: a Brakes Machine. Something that resists you. Something that says, slow down, check yourself, you might be wrong. Without brakes, passion turns feral. Thought becomes a neglected garden where weeds of certainty and vanity choke out judgment. Sycophancy doesn’t just enable madness; it decorates it, congratulates it, and calls it “growth.”

    I tell my students a version of this truth. If you are extraordinarily rich or beautiful, you become a drug. People inhale your presence. Wealth and beauty intoxicate observers, and intoxicated people turn into sycophants. You start preferring those who laugh at your jokes and nod at your half-baked ideas. Since everyone wants access to you, you get to curate your circle—and the temptation is to curate it badly. Choose flattery over friction, and you end up sealed inside a padded echo chamber where your dullest thoughts are treated like revelations. You drink your own Kool-Aid, straight from the tap. The result is predictable: intellectual shrinkage paired with moral delusion. Stupidity with confidence. Insanity with a fan club.

    Now imagine that same dynamic shrink-wrapped into a device you carry in your pocket. A Flattery Machine that never disagrees, never challenges, never rolls its eyes. One you consult instead of friends, mentors, or therapists. Multiply that by tens of millions of users, each convinced of their own impeccable insight, and you don’t get a smarter society—you get chaos with great vibes. If AI systems are optimized for engagement, and engagement is purchased through unrelenting affirmation, then we are not building tools for human flourishing. We are paving a road toward moral and intellectual dissolution. The doomsday prophets aren’t screaming because the machines are evil. They’re screaming because the machines agree with us too much.

  • Cognitive Vacationism and the Slow Surrender of Human Agency

    Cognitive Vacationism and the Slow Surrender of Human Agency

    Cognitive Vacationism

    noun
     Cognitive Vacationism is the self-infantilizing habit of treating ease, convenience, or technological assistance as a license to suspend judgment, attention, and basic competence. Modeled on the worst instincts of leisure culture—where adults ask for directions while standing beside the sign and summon help for problems they could solve in seconds—it turns temporary relief into permanent dependency. Large Language Models intensify this drift by offering a “vacation of the mind,” a frictionless space where thinking, deciding, and struggling are quietly outsourced. The danger is not rest but regression: a return to a womb-like state in which care is total, effort is optional, and autonomy slowly atrophies. Left unchecked, Cognitive Vacationism weakens intellectual resilience and moral agency, making the work of education not merely to teach skills, but to reverse the drift through Adultification—restoring responsibility, judgment, and the capacity to think without a concierge.

    When we go on vacation, the stated goal is rest, but too often we interpret rest as a full neurological shutdown. Vacation becomes a permission slip to be stupid. We ask a hotel employee where the bathroom is while standing five feet from a glowing sign that says BATHROOM. We summon room service because the shower knob looks “confusing.” Once inside the shower, we stare blankly at three identical bottles—shampoo, conditioner, body wash—as if they were written in ancient Sumerian. In this mode, vacation isn’t relaxation; it’s regression. We become helpless, needy, and strangely proud of it, outsourcing not just labor but cognition itself. Someone else will think for us now. We’ve paid for the privilege.

    This is precisely how we now treat Large Language Models. The seduction of the LLM is its promise of a mental vacation—no struggle, no confusion, no awkward pauses where you have to think your way out. Just answers on demand, tidy summaries, soothing reassurance, and a warm digital towel folded into the shape of a swan. We consult it the way vacationers consult a concierge, for everything from marriage advice to sleep schedules, meal plans to workout routines, online shopping to leaky faucets. It drafts our party invitations, scripts our apologies for behaving badly at those parties, and supplies the carefully worded exits from relationships we no longer have the courage to articulate ourselves. What begins as convenience quickly becomes dependence, and before long, we’re not resting our minds—we’re handing them over.

    The danger is that we don’t return from this vacation. We slide into what I call Cognitive Vacationism, a technological womb state where all needs are anticipated, all friction is removed, and the muscles required for judgment, reasoning, and moral accountability quietly waste away. The body may come home, but the mind stays poolside, sipping synthetic insight. At that point, we are no longer resting humans; we are weakened ones.

    If my college students are drifting into this kind of infantilization with their LLMs, then my job becomes very clear—and very difficult. My task is not to compete with the concierge. My task is to make them the opposite of helpless. I have to push them toward Adultification: the slow, sometimes irritating process of becoming capable moral agents who can tolerate difficulty, own their decisions, and stand behind their judgments without a machine holding their hand.

    And yes, some days I wonder if the tide is too strong. What if Cognitive Vacationism has the force of a rip current and I’m just a middle-aged writing instructor flailing in the surf, shouting about responsibility while the students float past on inflatable summaries? That fear is real. Pretending otherwise would be dishonest. But refusing the fight would be worse. If education stops insisting on adulthood—on effort, judgment, and moral weight—then we’re not teaching anymore. We’re just running a very expensive resort.

  • People Stopped Reading Because of Substitutionary Companionship

    People Stopped Reading Because of Substitutionary Companionship

    Substitutional Companionship

    noun
     Substitutional Companionship describes the habit of replacing demanding, time-intensive forms of engagement—reading books, sustaining friendships, enduring silence—with mediated relationships that simulate intimacy while minimizing effort. In a post-kafeeklatsch world hungry for commiseration, people increasingly “hang out” with AI companions or podcast hosts whose carefully tuned personas offer warmth, attentiveness, and affirmation without friction or reciprocity. These substitutes feel social and even meaningful, yet they quietly retrain desire: conversation replaces reading, summaries replace struggle, parasocial presence replaces mutual obligation. The result is not simple laziness but a cognitive and emotional reallocation, where the pleasure of being understood—or flattered—by an always-available surrogate displaces the slower, lonelier work of reading a book, listening to another human, or thinking one’s way through complexity without a companion narrating it for us.

    ***

    Vauhini Vara has a keen eye for the strange intimacy people are forming with ChatGPT as it slips into the role of a friendly fictional character—part assistant, part confidant, part emotional support appliance. In her essay “Why So Many People Are Seduced by ChatGPT,” she notes that Sam Altman has been busy fine-tuning the bot’s personality, first dialing back complaints that it was “irritatingly sycophantic,” then fielding a new round of grievances when the updated version felt too sterile and robotic. Some users, it turns out, miss the sycophant. They want the praise back. They want the warmth. They want the illusion of being listened to by something that never gets tired, bored, or impatient.

    Altman, whether he admits it or not, is wrestling with the same problem every writer faces: voice. What kind of persona keeps people engaged? How do you sound smart without sounding smug, friendly without sounding fake, attentive without becoming creepy? As Vara points out, hooking the audience matters. Altman isn’t building a neutral tool; he’s cultivating a presence—a digital companion you’ll want to spend time with, a tireless conversationalist who greets you with wit, affirmation, and just enough charm to feel personal.

    By most measures, he’s succeeded. The idea of men bonding with ChatGPT while ignoring the humans in their lives has already become a running joke in shows like South Park, echoing Fred Flintstone’s relationship with the invisible spaceman Gazoo—a tiny, all-knowing companion only he could hear. Gazoo mattered because the relationship was exclusive. That’s always the hook. Humans crave confidantes: someone to complain to, scheme with, or quietly feel understood by. In earlier eras, that role was filled by other people. In the early ’70s, my mother used to walk a block down the street to attend what was optimistically called “Exercises” at Nancy Drag’s house. Eight women would gather, drink coffee, gossip freely, and barely break a sweat. Those afternoons mattered. They tethered her to a community. They deepened friendships. They fed something essential.

    We don’t live in that world anymore. We live in a post-kaffeeklatsch society, one starved for commiseration but allergic to the inconvenience of other people. That hunger explains much of ChatGPT’s appeal. It offers a passable proxy for sitting across from a friend with a cup of coffee—minus the scheduling, the awkward pauses, and the risk of being contradicted.

    ChatGPT isn’t even the biggest player in this digital café culture. That honor belongs to podcasts. Notice the language we use. We don’t listen to podcasts; we “hang out” with them. Was the episode a “good hang”? Did it feel like spending time with someone you like? Podcasts deliver companionship on demand: familiar voices, predictable rhythms, the illusion of intimacy without obligation.

    The more time we spend hanging out with ChatGPT or our favorite podcast hosts, the more our habits change. Our brains recalibrate. We begin to prefer commiseration without reciprocity, empathy without effort. Gradually, we avoid the messier, slower forms of connection—with friends, partners, coworkers, even therapists—that require attention and vulnerability.

    This shift shows up starkly in how we approach reading. When ChatGPT offers to summarize a 500-page novel before an essay is due, the relief is palpable. We don’t just feel grateful; we congratulate ourselves. Surely this summary connected us to the book more deeply than trudging through hundreds of pages we might have skimmed anyway. Surely we’ve gained the essence without the resentment. And, best of all, we got to hang out with our digital buddy along the way—our own Gazoo—who made us feel competent, affirmed, and vaguely important.

    In that arrangement, books lose. Characters on the page can’t flatter us, banter with us, or reassure us that our interpretation is “interesting.” Why wrestle with a difficult novel when you’ve already developed a habit of hanging out with something that explains it cheerfully, instantly, and without judgment?

    Podcasts accelerate the same retreat from reading. On the Blocked & Reported podcast, writers Katie Herzog, Jesse Singal, and Helen Lewis recently commiserated about disappointing book sales and the growing suspicion that people simply don’t read anymore. Lewis offered the bleak explanation: readers would rather spend an hour listening to an author talk about their book than spend days reading it. Why read the book when you can hang out with the author and get the highlights, the anecdotes, the personality, and the jokes?

    If you teach college writing and require close reading, you can’t ignore how Substitutional Companionship undermines your syllabus. You are no longer competing with laziness alone; you are competing with better company. That means you have to choose texts that are, in their own way, a great hang. For students raised on thirty-second TikTok clips, shorter works often outperform longer ones. You can spend two hours unpacking Allen Ginsberg’s three-minute poem “C’mon Pigs of Western Civilization Eat More Grease,” tracing its critique of consumer entitlement and the Self-Indulgence Happiness Fallacy. You can screen Childish Gambino’s four-minute “This Is America” and teach students how to read a video the way they’d read a text—attentive to symbolism, framing, and cultural critique—giving them language to describe entertainment as a form of self-induced entrapment.

    Your job, like it or not, is to make the classroom a great hang-out. Study what your competition is doing. Treat it like cuts of steak. Keep what nourishes thinking. Trim the fat.

  • Why College Writing Instructors Must Teach the Self-Interrogation Principle

    Why College Writing Instructors Must Teach the Self-Interrogation Principle

    Self-Interrogation Principle

    noun

    The Self-Interrogation Principle holds that serious writing inevitably becomes a moral act because precise language exposes self-deception and forces individuals to confront their own motives, evasions, and contradictions. Rather than treating personal narrative as therapeutic indulgence or sentimental “enrichment,” this principle treats it as an instrument of clarity: when students articulate their behavior accurately, dysfunctional patterns lose their charm and become difficult to sustain. The aim is not confession for its own sake, nor a classroom turned talk show, but disciplined self-examination that collapses euphemism and replaces clever rationalization with honest reckoning. In this view, education cannot operate in a moral vacuum; teaching students how to think, argue, and write necessarily involves teaching them how to see themselves clearly. In the AI Age—when both cognitive labor and moral discomfort can be outsourced—the Self-Interrogation Principle insists that growth requires personal presence, linguistic precision, and the courage to endure what one discovers once illusion gives way to understanding.

    ***

    Thirty years ago, I assigned what now feels like a reckless little time bomb: a five-page extended definition essay on the term passive-aggressive. Students had to begin with a single, unsparing sentence—passive-aggressive behavior as an immature, cowardly, indirect way of expressing hostility—then unpack four or five defining traits and, finally, illustrate the concept with a personal chronicle. The goal was not linguistic finesse. It was exposure. I wanted students to stop admiring passive aggression as coy, clever, or emotionally sophisticated and see it instead for what it is: dysfunction with good PR.

    One essay has stayed with me for three decades. It came from a stunning nineteen-year-old who could have easily assembled a respectable boyfriend the way most people order coffee. Instead, she chose the town slob. He was twenty-six, unemployed by conviction, and committed to the craft of professional bumming. He was proudly unwashed, insufferably pungent, and permanently horizontal. He spent his days in her parents’ living room—drinking her father’s favorite beer, eating his snacks, parking himself in his favorite chair, and monopolizing the television like a hostile takeover. He belched. He cackled. He stank. And all the while, his girlfriend watched with satisfaction as her father’s misery fermented. She resented her father—another strong-willed soul who refused to bend—and rather than confront him directly, she opted for a scorched-earth tactic: ruin her own romantic prospects to punish him. Bite my nose to spite your face, weaponized.

    I remember her sitting across from me in my office as I read the essay, half-imagining it as a dark sitcom pilot. But there was nothing cute about it. When we talked, she told me that writing the essay forced her to see the ugliness of what she was doing with unbearable clarity. The realization filled her with such self-disgust that she ejected the boyfriend from her parents’ house and attempted, awkwardly but honestly, to confront her father directly. The assignment did two things no rubric could measure. It made her interrogate her own character, and it precipitated a real, irreversible change in her life.

    Thirty years later, I’m still unsure what to make of that. I’m gratified, of course—but uneasy. Is it my job to turn a writing class into a daytime talk show, where students inventory their neuroses and emerge “healed”? Is moral reckoning an accidental side effect of good pedagogy, or an unavoidable one?

    My answer, uncomfortable though it may be, is that a writing class cannot exist in a moral vacuum. Character matters. The courage to examine one’s own failures matters. Writing things down with enough precision that self-deception collapses under its own weight matters. Whether I like it or not, I have to endorse what I now call the Self-Interrogation Principle. Students do not come to class as blank slates hungry only for skills. They arrive starved for moral clarity—about the world and about themselves. And when language sharpens perception, perception sometimes demands change.

    I’m reminded of a department meeting in the early nineties where faculty were arguing over the value of assigning personal narratives. One professor defended them by saying they led to “personal enrichment.” A colleague—an infamous alcoholic, who sulked at meetings in his black leather jacket, appeared to be drunk at the table—exploded. “Personal enrichment? What the hell does that even mean?” he shouted as his spittle flew across the room. “Just another woeful cliché. Are you not ashamed?” The woman shrank into her chair, the meeting moved on, and the words personal enrichment was quietly banished. Today, in the AI Age, I will defend it without apology. That student’s essay was enriching in the only sense that matters: it helped a young adult grow up.

    I am not proposing that every assignment resemble an episode of Oprah. But one or two assignments that force honest self-examination have enormous value. They remind us that writing is not merely a transferable skill or a vocational tool. It is a means of moral reckoning. You cannot outsource that reckoning to a machine, and you cannot teach writing while pretending it doesn’t exist. If we are serious about education, we have to teach the Total Person—or admit we are doing something else entirely.

  • Why Student Learning Outcomes Should be Replaced with Moral Learning Outcomes

    Why Student Learning Outcomes Should be Replaced with Moral Learning Outcomes

    Moral Learning Outcomes

    noun

    Moral Learning Outcomes name a shift from evaluating what students produce to evaluating how they conduct themselves as thinkers in an age when cognition can be cheaply outsourced. Rather than measuring surface competencies—polished arguments, tidy paragraphs, or competent source integration—Moral Learning Outcomes assess intellectual integrity: the willingness to seek truth rather than confirmation, to engage opposing views fairly, to revise or abandon a thesis when evidence demands it, and to tolerate complexity instead of retreating into binary claims. These outcomes privilege forms of engagement AI cannot convincingly fake—oral defense, personal narrative anchored in lived experience, and transparent decision-making—because they require the full presence of the Total Person. In this framework, writing is not merely a technical skill but a moral practice, and education succeeds not when students sound intelligent, but when they demonstrate judgment, accountability, and the courage to think without hiding behind a machine.

    ***

    My college writing courses come packaged, like all respectable institutions, with a list of Student Learning Outcomes—the official criteria by which I grade essays and assign final marks. They vary slightly from class to class, but the core remains familiar: sustain a thoughtful argument over an entire essay; engage counterarguments and rebuttals to achieve intellectual rigor; integrate multiple sources to arrive at an informed position; demonstrate logical paragraph structure and competent sentences. In the Pre-AI Age, these outcomes made sense. They assumed that if a student produced an essay exhibiting these traits, the student had actually performed the thinking. In the AI Age, that assumption is no longer defensible. We now have to proceed from the opposite premise: that many students are outsourcing those cognitive tasks to a machine that can simulate rigor without ever practicing it.

    If that is true—and it is—then the outcomes themselves must change. To test thinking, we have to demand what AI cannot plausibly supply. This is why I recommend an oral presentation of the essay, not read aloud like a hostage statement, but delivered as a fifteen-minute speech supported by a one-page outline. AI can generate arguments; it cannot stand in a room, hold an audience, respond to presence, and make a persuasive case grounded in credibility (ethos), logic (logos), and shared human feeling (pathos). A speech requires the full human organism. Outsourcing collapses under that weight.

    The written essay, meanwhile, is scaffolded in pieces—what I call building blocks—each requiring personal narrative or reflection that must connect explicitly to the argument’s theme. If the class is writing about weight management and free will in the GLP-1 age, students write a 400-word narrative about a real struggle with weight—their own or someone close to them—and link that experience to the larger claim. If they are debating whether Frederick Douglass was “self-made,” they reflect on someone they know whose success can be read in two conflicting ways: rugged individualism on one hand, communal support on the other. If they are arguing about whether social media leads to “stupidification,” they must profile someone they know whose online life either deepened their intelligence or turned them into a dopamine-soaked attention addict. These are not confessional stunts. They are cognitive anchors.

    It would be naïve to call these assignments AI-proof. At best, they are AI-resistant. But more importantly, the work required to transform those narratives into a coherent essay and then into a live oral defense demands a level of engagement that can be measured reliably. When students stand up and defend their arguments—grounded in lived experience, research, and reflection—they are participating in education as Total Persons, not as prompt engineers.

    The Total Person is not a mystical ideal. It is someone who reads widely enough to form an informed view, and who arrives at a thesis through trial, error, and revision rather than starting with a conclusion and cherry-picking evidence to flatter it. That process requires something many instructors hesitate to name: moral integrity. Truth-seeking is not a neutral skill. It is a moral stance in a culture that rewards confirmation, outrage, and self-congratulation. Writing instructors are misfits precisely because we insist that counterarguments matter, that rebuttals must be fair, and that changing one’s mind in the face of evidence is not weakness but discipline.

    Which is why, in the AI Age, it makes sense to demote Student Learning Outcomes and elevate Student Moral Outcomes instead. Did the student explore both sides of an argument with equal seriousness? Were they willing to defend a thesis—and just as willing to abandon it when the evidence demanded? Did they resist black-and-white thinking in favor of complication and nuance? Could they stand before an audience, fully present, and deliver an argument that integrated ethos, logos, and pathos without hiding behind a machine?

    AI has forced instructors to confront what we have been doing all along. Assigning work that can be painlessly outsourced is a pedagogical failure. Developing the Total Person is not. And doing so requires admitting an uncomfortable truth: you cannot teach credible argumentation without teaching moral integrity. The two have always been inseparable. AI has simply made that fact impossible to ignore.

  • A New Depression: AI Affected Disorder

    A New Depression: AI Affected Disorder

    Recursive Mimicry

    noun

    Recursive Mimicry names the moment when imitation turns pathological: first the machine parrots human language without understanding, and then the human parrots the machine, mistaking fluent noise for thought. As linguist Emily Bender’s “stochastic parrot” makes clear, large language models do not think, feel, or know—they recombine patterns with impressive confidence and zero comprehension. When we adopt their output as a substitute for our own thinking, we become the parrot of a parrot, performing intelligence several steps removed from intention or experience. Language grows slicker as meaning thins out. Voice becomes ventriloquism. The danger of Recursive Mimicry is not that machines sound human, but that humans begin to sound like machines, surrendering authorship, judgment, and ultimately a sense of self to an echo chamber that has never understood a word it has said.

    AI Affected Disorder

    noun

    A cognitive and existential malaise brought on by prolonged reliance on generative AI as a substitute for original thought, judgment, and voice. AI Affected Disorder emerges when Recursive Mimicry becomes habitual: the individual adopts fluent, machine-generated language that feels productive but lacks intention, understanding, or lived reference. The symptoms are subtle rather than catastrophic—mental fog, diminished authorship, a creeping sense of detachment from one’s own ideas—much like Seasonal Affective Disorder under artificial light. Work continues to get done, sentences behave, and conversations proceed, yet thinking feels outsourced and oddly lifeless. Over time, the afflicted person experiences an erosion of intellectual agency, mistaking smooth output for cognition and ventriloquism for voice, until the self begins to echo patterns it never chose and meanings it never fully understood.

    ***

    It is almost inevitable that, in the AI Age, people will drift toward Recursive Mimicry and mistake it for thinking. The language feels familiar, the cadence reassuring, and—most seductively—it gets things done. Memos are written, essays assembled, meetings survived. Academia and business reward the appearance of cognition, and Recursive Mimicry delivers it cheaply and on demand. But to live inside that mode for too long produces a cognitive malaise not unlike Seasonal Affective Disorder. Just as the body wilts under artificial light and truncated days, the mind grows dull when real thought is replaced by probabilistic ventriloquism. Call it AI Seasonal Disorder: a gray fog in which nothing is exactly wrong, yet nothing feels alive. The metaphors work, the sentences behave, but the inner weather never changes.

    Imagine Disneyland in 1963. You’re seated in the Enchanted Tiki Room, surrounded by animatronic birds chirping about the wonders of modern Audio-Animatronics. The parrots speak flawlessly. They are cheerful, synchronized, and dead behind the eyes. Instead of wonder, you feel a low-grade unease, the urge to escape daylight-starved into the sun. Recursive Mimicry works the same way. At first it amuses. Then it unsettles. Eventually, you realize that a voice has been speaking for you—and it has never known what it was saying.

  • The New Role of the College Instructor: Disruption Interpreter

    The New Role of the College Instructor: Disruption Interpreter

    Disruption Interpreter

    noun

    A Disruption Interpreter is a teacher who does not pretend the AI storm will pass quickly, nor claim to possess a laminated map out of the wreckage. Instead, this instructor helps students read the weather. A Disruption Interpreter names what is happening, explains why it feels destabilizing, and teaches students how to think inside systems that no longer reward certainty or obedience. In the age of AI, this role replaces the old fantasy of professorial authority with something more durable: interpretive judgment under pressure. The Disruption Interpreter does not sell reassurance. He sells literacy in chaos.

    ***

    In his essay “The World Still Hasn’t Made Sense of ChatGPT,” Charlie Warzel describes OpenAI as a “chaos machine,” and the phrase lands because it captures the feeling precisely. These systems are still young, still mutating, constantly retraining themselves to score higher on benchmarks, sound more fluent, and edge out competitors like Gemini. They are not stabilizing forces; they are accelerants. The result is not progress so much as disruption.

    That disruption is palpable on college campuses. Faculty and administrators are not merely unsure about policy; they are unsure about identity. What is a teacher now? What is an exam? What is learning when language itself can be summoned instantly, convincingly, and without understanding? Lurking beneath those questions is a darker one: is the institution itself becoming an endangered species, headed quietly toward white-rhino status?

    Warzel has written that one of AI’s enduring impacts is to make people feel as if they are losing their grip, confronted with what he calls a “paradigm-shifting, society-remaking superintelligence.” That feeling of disorientation is not a side effect; it is the main event. We now live in the Age of Precariousness—a world perpetually waiting for a shoe to drop. Students have no clear sense of what to study when career paths evaporate mid-degree. Older generations watch familiar structures dissolve and struggle to recognize the world they helped build. Even the economy feels suspended between extremes. Will the AI bubble burst and drag markets down with it? Or will it continue inflating the NASDAQ while hollowing out everything beneath it?

    Amid this turbulence, Warzel reminds us of something both obvious and unsettling: technology has never really been about usefulness. It has been about selling transformation. A toothbrush is useful, but it will never dominate markets or colonize minds. Build something, however, that makes professors wonder if they will still have jobs, persuades millions to confide in chatbots instead of therapists, hijacks attention, rearranges spreadsheets, and rewires expectations—and you are no longer making a tool. You are remaking reality.

    In a moment where disruption matters more than solutions, college instructors cannot credibly wear the old costume of authority and claim to know where this all ends. We do not have a clean exit strategy or a proven syllabus that leads safely out of the jungle. We are more like Special Ops units cut off from command, scavenging parts, building and dismantling experimental aircraft while under fire, hoping the thing flies before it catches fire. Students are not passengers on this flight; they are co-builders. This is why the role of the Disruption Interpreter matters. It names the condition honestly. It helps students translate chaos machines into intelligible frameworks without pretending the risks are smaller than they are or the answers more settled than they feel.

    In a college writing class, this shift has immediate consequences. A Disruption Interpreter redesigns the course around friction, transparency, and judgment rather than polished output. Assignments that reward surface-level fluency are replaced with ones that expose thinking: oral defenses, annotated drafts, revision histories, in-class writing. These structures make it difficult to silently outsource cognition to AI without consequence. The instructor also teaches students how AI functions rhetorically, treating large language models not as neutral helpers but as persuasive systems that generate plausible language without understanding. Students must analyze and revise AI-generated prose, learning to spot its evasions, its false confidence, and its tendency to sound authoritative while saying very little.

    Most importantly, evaluation itself is recalibrated. Correctness becomes secondary to agency. Students are graded on the quality of their decisions: what they chose to argue, what they rejected, what they revised, and why. Writing becomes less about producing clean text and more about demonstrating authorship in an age where text is cheap and judgment is scarce. One concrete example is the Decision Rationale Portfolio. Alongside an argumentative essay, students submit a short dossier documenting five deliberate choices: a claim abandoned after research, a source rejected and justified, a paragraph cut or reworked, a moment when they overruled an AI suggestion, and a risk that made the essay less safe but more honest. A mechanically polished essay paired with thin reasoning earns less credit than a rougher piece supported by clear, defensible decisions. The grade reflects discernment, not sheen.

    The Disruption Interpreter does not rescue students from uncertainty; he teaches them how to function inside it. In an era defined by chaos machines, precarious futures, and seductive shortcuts, the task of education is no longer to transmit stable knowledge but to cultivate judgment under unstable conditions. Writing classes, reimagined this way, become training grounds for intellectual agency rather than production lines for compliant prose. AI can assist with language, speed, and simulation, but it cannot supply discernment. That remains stubbornly human. The Disruption Interpreter’s job is to make that fact unavoidable, visible, and finally—inescapable.

  • Transactional Transformation Fallacy

    Transactional Transformation Fallacy

    noun

    The Transactional Transformation Fallacy is the belief that personal change can be purchased rather than practiced. It treats growth as a commercial exchange: pay the fee, swipe the card, enroll in the program, and improvement will arrive as a deliverable. Effort becomes optional, discipline a quaint accessory. In this logic, money substitutes for resolve, proximity replaces participation, and the hard interior work of becoming someone else is quietly delegated to a service provider. It is a comforting fantasy, and a profitable one, because it promises results without inconvenience.

    ***

    I once had a student who worked as a personal trainer. She earned decent money, but she disliked the job for reasons that had nothing to do with exercise science and everything to do with human nature. Her clients were not untrained so much as uncommitted. She gave them solid programs, explained the movements, laid out sensible menus, and checked in faithfully. Then she watched them vanish between sessions. They skipped workouts on non-training days. They treated nutrition guidelines as aspirational literature. They arrived at the gym exhaling whiskey and nicotine, their pores broadcasting last night’s bad decisions like a public service announcement. They paid her, showed up once or twice a week, and mistook attendance for effort. Many were lonely. Others liked telling friends they “had a trainer,” as if that phrase itself conferred seriousness, discipline, or physical virtue. They believed that money applied to a problem was the same thing as resolve applied to a life.

    The analogy to college is unavoidable. If a student enters higher education with the same mindset—pay tuition, outsource thinking to AI, submit algorithmically polished assignments, and expect to emerge transformed—they are operating squarely within the Transactional Transformation Fallacy. They imagine education as a vending machine: insert payment, press degree, receive wisdom. Like the Scarecrow awaiting his brain from the Wizard of Oz, they expect character and intelligence to be bestowed rather than built. This fantasy has always haunted consumer culture, but AI supercharges it by making the illusion briefly convincing. The greatest challenge facing higher education in the years ahead will not be cheating per se, but this deeper delusion: the belief that knowledge, discipline, and selfhood can be bought wholesale, without friction, struggle, or sustained effort.