Cinemorphosis

Author: Jeffrey McMahon

  • 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.

  • Gollumification

    Gollumification

    Gollumification

    noun

    Gollumification names the slow moral and cognitive decay that occurs when a person repeatedly chooses convenience over effort and optimization over growth. It is what happens when tools designed to assist quietly replace the very capacities they were meant to strengthen. Like Tolkien’s Gollum, the subject does not collapse all at once; he withers incrementally, outsourcing judgment, agency, and struggle until what remains is a hunched creature guarding shortcuts and muttering justifications. Gollumification is not a story about evil intentions. It is a story about small evasions practiced daily until the self grows thin, brittle, and dependent.

    ***

    Washington Post writer Joanna Slater reports in “Professors Are Turning to This Old-School Method to Stop AI Use on Exams” that some instructors are abandoning written exams in favor of oral ones, forcing students to demonstrate what they actually know without the benefit of algorithmic ventriloquism. At the University of Wyoming, religious studies professor Catherine Hartmann now seats students in her office and questions them directly, Socratic-style, with no digital intermediaries to run interference. Her rationale is blunt and bracing. Using AI on exams, she tells students, is like bringing a forklift to the gym when your goal is to build muscle. “The classroom is a gymnasium,” she explains. “I am your personal trainer. I want you to lift the weights.” Hartmann is not being punitive; she is being realistic about human psychology. Given a way to cheat ourselves out of effort—or out of a meaningful life—we will take it, not because we are corrupt, but because we are wired to conserve energy. That instinct once helped us survive. Now it quietly betrays us. A cheated education becomes a squandered one, and a squandered life does not merely stagnate; it decays. This is how Gollumification begins: not with villainy, but with avoidance.

    I agree entirely with Hartmann’s impulse, even if my method would differ. I would require students to make a fifteen-minute YouTube video in which they deliver their argument as a formal speech. I know from experience that translating a written argument into an oral one exposes every hollow sentence and every borrowed idea. The mind has nowhere to hide when it must speak coherently, in sequence, under the pressure of time and presence. Oral essays force students to metabolize their thinking instead of laundering it through a machine. They are a way of banning forklifts from the gym—not out of nostalgia, but out of respect for the human organism. If education is meant to strengthen rather than simulate intelligence, then forcing students to lift their own cognitive weight is not cruelty. It is preventive medicine against the slow, tragic, and all-too-modern disease of Gollumification.

  • Discretionary Use Principle

    Discretionary Use Principle

    The Discretionary Use Principle begins with a simple but demanding claim: tools are not inherently good or bad, but they become harmful when used without judgment, proportion, or purpose. Whether we are talking about food, technology, or media, the decisive factor is not purity but discretion—our ability to choose deliberately rather than reflexively. The principle rejects both absolutism and indulgence. It argues instead for a calibrated life, one that privileges nourishment over stimulation, depth over convenience, while still recognizing that modern life occasionally requires shortcuts. This framework is especially useful when thinking about analog versus digital living, where moralized categories often replace careful thinking.

    It is wise to carve out a large, non-negotiable block of each day in which machines are politely but firmly excluded—no screens glowing like anxious faces, no notifications tugging at your sleeve, no algorithm whispering what to want next. Go hike where the trail refuses to optimize itself. Lift weights in a garage with nothing but an AM radio crackling like a distant campfire. Write dreams and grievances by hand in a clothbound notebook while Bach or Coltrane keeps time. This is the analog world, and it feeds parts of the nervous system that silicon cannot reach. In this sense, analog living resembles whole foods: salmon that still tastes like water and muscle, almonds that require chewing, blueberries that stain your fingers. The more time you spend here, the less bloated your spirit becomes. Digital life, by contrast, often behaves like ultra-processed food: frictionless, hyper-palatable, engineered for compulsive return, and strangely unsatisfying no matter how much you consume.

    That analogy works—until it doesn’t. Not all analog living is virtuous, just as not all “whole foods” are benign when eaten without restraint. A steady diet of eggs, clotted cream, or beef heart can quietly undo you. Likewise, not all digital experience is junk. There are serious conversations on social platforms, lucid Substack essays, and educational YouTube channels that sharpen rather than dull attention. The mistake comes when we moralize categories instead of exercising judgment. Ultra-processed food is not a single moral villain; “processed” names a method, not a fate. Steel-cut oats, frozen berries, tofu, canned beans, and whole-grain bread are processed and still nutritionally intact. Even within the ultra-processed aisle, a minimally sweetened protein bar is not the same organism as a fluorescent snack cake designed to bypass satiety. The real danger is not processing itself but the familiar cartel of refined starches, added sugars, industrial fats, flavor engineering, and low nutritional payoff.

    Seen through the Discretionary Use Principle, the lesson is neither to flee the digital world nor to surrender to it. Eat whole foods most of the time. Live analog for long, uninterrupted stretches. But do not shun all processed foods or digital tools out of misplaced virtue. Use them when discretion, efficiency, and purpose demand it. Health—nutritional or psychological—is not preserved by purity tests. It is preserved by attentiveness, proportion, and the ongoing discipline of choosing nourishment over convenience, again and again, without pretending that the choice will ever be automatic.

  • Hyper-Efficiency Intoxication Will Change Higher Learning Forever

    Hyper-Efficiency Intoxication Will Change Higher Learning Forever

    Hyper-Efficiency Intoxication

    noun

    The dopamine-laced rush that occurs when AI collapses hours of cognitive labor into seconds, training the brain to mistake speed for intelligence and output for understanding. Hyper-Efficiency Intoxication sets in when the immediate relief of reclaimed time—skipped readings, instant summaries, frictionless drafts—feels so rewarding that slow thinking begins to register as needless suffering. What hooks the user is not insight but velocity: the sense of winning back life from effort itself. Over time, this chemical high reshapes judgment, making sustained attention feel punitive, depth feel inefficient, and authorship feel optional. Under its influence, students do not stop working; they subtly downgrade their role—from thinker to coordinator, from writer to project manager—until thinking itself fades into oversight. Hyper-Efficiency Intoxication does not announce itself as decline; it arrives disguised as optimization, quietly hollowing out the very capacities education once existed to build.

    ***

    No sane college instructor assigns an essay anymore under the illusion that you’ll heroically wrestle with ideas while AI politely waits in the hallway. We all know what happens: a prompt goes in, a glossy corpse comes out. The charade has become so blatant that even professors who once treated AI like a passing fad are now rubbing their eyes and admitting the obvious. Hua Hsu names the moment plainly in his essay “What Happens After A.I. Destroys College Writing?”: the traditional take-home essay is circling the drain, and higher education is being forced to explain—perhaps for the first time in decades—what it’s actually for.

    The problem isn’t that students are morally bankrupt. It’s that they’re brutally rational. The real difference between “doing the assignment” and “using AI” isn’t ethics; it’s time. Time is the most honest currency in your life. Ten hours grinding through a biography means ten hours you’re not at a party, a game, a date, or a job. Ten minutes with an AI summary buys you your evening back. Faced with that math, almost everyone chooses the shortcut—not because they’re dishonest, but because they live in the real world. This isn’t cheating; it’s survival economics.

    Then there’s the arms race. Your classmates are using AI. All of them. Competing against them without AI is like entering a bodybuilding contest while everyone else is juiced to the gills and you’re proudly “all natural.” You won’t be virtuous; you’ll be humiliated. Fairness collapses the moment one side upgrades, and pretending otherwise is naïve at best.

    AI also hooks you. Hsu admits that after a few uses of ChatGPT, he felt the “intoxication of hyper-efficiency.” That’s not a metaphor—it’s a chemical event. When a machine collapses hours of effort into seconds, your brain lights up like it just won a small lottery. The rush isn’t insight; it’s velocity. And once you’ve tasted that speed, slowness starts to feel like punishment.

    Writing instructors, finally awake, are adapting. Take-home essays are being replaced by in-class writing, blue books, and passage identification exams—formats designed to drag thinking back into the room and away from the cloud. These methods reward students who’ve spent years reading and writing the hard way. But for students who entered high school in 2022 or later—students raised on AI scaffolding—this shift feels like being dropped into deep water without a life vest. Many respond rationally: they avoid instructors who demand in-class thinking.

    Over time, something subtle happens. You don’t stop working; you change roles. You become, in Hsu’s phrase, a project manager—someone who coordinates machines rather than generating ideas. You collaborate, prompt, tweak, and oversee. And at some point, no one—not you, not your professor—can say precisely when the thinking stopped being yours. There is no clean border crossing, only a gradual fade.

    Institutions are paralyzed by this reality. Do they accept the transformation and train students to be elite project managers of knowledge? Or do they try to resurrect an older model of literacy, pretending that time, incentives, and technology haven’t changed? Neither option is comfortable, and both expose how fragile the old justifications for college have become.

    From the educator’s chair, the nightmare scenario is obvious. If AI can train competent project managers for coding, nursing, physical therapy, or business, why not skip college altogether? Why not certify skills directly? Why not let employers handle training in-house? It would be faster, cheaper, and brutally efficient.

    And efficiency always wins. When speed, convenience, and cost savings line up, they don’t politely coexist with tradition—they bulldoze it. AI doesn’t argue with the old vision of education. It replaces it. The question is no longer whether college will change, but whether it can explain why learning should be slower, harder, and less efficient than the machines insist it needs to be.

  • Algorithmic Infotainment Drift

    Algorithmic Infotainment Drift

    Algorithmic Infotainment Drift

    noun

    Algorithmic Infotainment Drift refers to the contemporary condition in which narrative forms—films, shows, lectures, even ideas themselves—quietly abandon storytelling and inquiry in favor of algorithm-friendly spectacle and aspirational marketing, masquerading as content. Under this drift, plot becomes a thin pretext for visual bait, characters exist to model bodies, lifestyles, or attitudes, and scenes function like clickable thumbnails optimized to trigger envy, desire, or self-loathing rather than thought. What appears to be entertainment is in fact an influencer ecosystem in disguise, where the viewer is nudged not to reflect but to compare, consume, and Google diets mid-scene. The danger is not merely aesthetic but cognitive: audiences, especially students, are trained to expect meaning without effort, stimulation without depth, and authority without rigor—conditions that erode sustained attention, flatten intellectual struggle, and make higher learning feel obsolete next to the frictionless dopamine loop of the feed.

    ***

    I decided to relaunch my bodybuilding ambitions in my sixties the way all serious men do: by watching Road House. This reboot stars a Jake Gyllenhaal so aggressively sculpted he looks less like an actor and more like a marble warning label—Michelangelo with a protein sponsor. He plays a drifting barroom enforcer in Key West, a man whose résumé consists entirely of fists and moral clarity. His job is to protect a beachside dive and its plucky owner (Jessica Williams) from corrupt local heavies, which naturally culminates in a showdown with Conor McGregor, who appears to have been marinated in rage, creatine, and whatever substances are banned three agencies ago. McGregor doesn’t so much act as vibrate menacingly, like a loose chainsaw wrapped in tattoos.

    The plot, such as it exists, is thinner than dental floss. It’s a Western with tank tops: a stranger rides into town, punches everyone who deserves it, and restores order through upper-body hypertrophy. But the story is a courtesy gesture. The real point is flesh. The camera caresses delts, glides lovingly over abs, and pauses reverently on veins like a pilgrim at a shrine. This isn’t cinema; it’s a two-hour sizzle reel for protein powder, creatine, and injectable optimism. The fights feel less choreographed than sponsored. Somewhere, a supplement brand is climaxing.

    Midway through, I realized I wasn’t watching a movie—I was undergoing a comparison audit. I reached for my phone, not to check messages, but to Google “Conor McGregor diet,” as one does when confronted with the existential horror of your own carb intake. Road House doesn’t invite immersion; it invites self-loathing. It’s not entertainment so much as a glossy intervention: a reminder that you are one donut away from structural collapse while these men are carved from imported stone.

    When the credits rolled, something clarifying settled in. We no longer tell stories; we stage aspirations. Movies have become influencer decks with dialogue—Algorithmic Infotainment Drift in its purest form. Narrative is now a delivery system for vibes, bodies, and monetizable fantasy. We don’t object because we’re trained not to. The film doesn’t pretend to mean anything; it just wants to convert you—into admiration, envy, and eventually consumption.

    This drift matters, especially in higher education, because it retrains the mind. Students steeped in this culture come to expect knowledge the way Road House delivers plot: fast, polished, emotionally pre-optimized, and free of resistance. Sustained attention gets replaced by binge reflexes. Analysis gives way to vibes. Long arguments feel offensive. Ambiguity feels like a bug. And authority quietly shifts from expertise to whatever the algorithm spotlights this week. Knowledge becomes something you scroll past, not wrestle with. The result isn’t ignorance—it’s fragility. A generation trained to consume meaning, not make it, flexing hard in a world that requires endurance.

  • Screen Bilinguals and Screen Natives

    Screen Bilinguals and Screen Natives

    Screen Bilinguals

    noun

    Screen Bilinguals are those who remember Pre-Screen Life and Post-Screen Life and can mentally translate between the two. They know what it felt like to disappear into a book without notifications, to wander outdoors without documenting the evidence, and to experience friendship without performance. They may use screens constantly now, but they retain an embodied memory of undistracted attention and uncurated presence. That memory gives them perspective—and often a quiet grief.

    Screen Natives

    noun

    Screen Natives are those who never lived outside the Attention Economy. They have no experiential baseline for pre-digital reading, boredom, or intimacy. For them, screens are not tools but atmosphere. Experience arrives already framed, shareable, and optimizable. Connection is inseparable from capture, and attention has always been contested territory. What Screen Bilinguals experience as loss, Screen Natives experience as reality itself—neither chosen nor questioned, simply inherited.

    ***

    I am reasonably sure that some of the best memories of my pre-screen adolescence would not survive contact with smartphones and social media. They required a kind of reckless presence that today’s technology quietly sabotages. Every summer from 1975 to 1979, my family—along with ten others—made a pilgrimage to Point Reyes Beach, where the Johnsons’ oyster farm supplied what appeared to be bottomless truck beds of shellfish. From noon until sunset, hundreds of us devoured obscene quantities of barbecued oysters dripping with garlic butter and Tabasco, flanked by thousands of loaves of garlic bread and slabs of chocolate cake so moist they bordered on indecent. Ignoring cheerful warnings about nearby great white sightings, we periodically sprinted into the Pacific, then staggered back to the picnic tables, pecs gleaming with saltwater, to resume eating like mythological beings. In the summer of ’78, I told my parents to leave without me and caught a ride home in the bed of a stranger’s truck. Stuffed beyond reason, convinced I was some minor sea god, I lay under the stars with a gang of people I’d met hours earlier, trading delirious stories and watching the universe spin. No one documented a thing. We didn’t track calories, curate moments, or worry about time. Life simply happened to us, and that was enough.

    Those memories now trouble me. Were they the accidental privilege of being screen-bilingual—raised before devices trained us to perform our lives in public? Does being a screen native quietly thin experience itself by insisting everything be captured, filtered, and offered up for consumption? Free from the reflex to mediate, I could disappear into the moment without irony or self-surveillance. Had I grown up with screens, the day would have demanded angles, captions, and metrics. The magic would have curdled under the pressure to perform. The idea that every experience must double as content strikes me as a curse—a low-grade exile from real life, where spontaneity dies not from malice but from documentation.