Cinemorphosis

Tag: ai

  • The Death of the Sacred Bond Between Writer and Reader

    The Death of the Sacred Bond Between Writer and Reader

    Fiction instructor Walt Hunt’s essay “The Death of the Reader” begins with a development that would have sounded absurd only a few years ago: an AI-assisted short story winning a major literary prize. The winning story, Jamir Nazir’s “The Serpent in the Grove,” took home the Granta Commonwealth Short Story Prize, prompting the now-familiar debate about authenticity. Was the story really written by a human? How much AI was involved? Can anyone tell the difference anymore? Hunt acknowledges that AI-generated prose often leaves fingerprints—certain stylistic tics, tonal smoothness, and suspiciously frictionless sentences that alert attentive readers. But he argues that critics are fixated on the wrong problem. The true casualty of AI fiction is not the writer. It is the reader.

    Before the arrival of AI-generated literature, reading rested on a fragile but meaningful act of trust. A reader entered a private room where another consciousness was waiting. Across centuries, continents, and cultures, readers formed intimate relationships with authors they would never meet. The writer offered a distinctive voice, a recognizable sensibility, a particular way of seeing the world. Sometimes the writer was a provocateur. Sometimes a companion. Sometimes a guide carrying a lantern through the darker corridors of human experience. Whatever form the relationship took, readers believed there was another person on the other side of the page.

    Now there is Claude.

    Claude is not a novelist struggling with heartbreak, obsession, grief, jealousy, or longing. Claude has never stared at a hospital ceiling at three in the morning. Claude has never fallen in love, buried a parent, betrayed a friend, or sat alone with regret. Claude is not a presence. It is a process. And because readers know this, a corrosive uncertainty enters the reading experience.

    What am I reading?

    Who wrote this?

    Did anyone write this?

    Does it matter?

    The machine turns every page into a cross-examination.

    Hunt argues that this uncertainty damages the reader more profoundly than it damages the author. The old covenant between writer and reader begins to dissolve. In its place emerges suspicion. Instead of surrendering to a voice, readers interrogate it. Instead of entering solitude, they become detectives hunting for evidence of fraud. Every elegant sentence becomes a potential counterfeit. Every emotional insight becomes grounds for skepticism.

    As Hunt observes, readers increasingly adopt a style of reading that is “self-conscious, hyperaware, restless, and anxiety-driven.” The reading experience becomes less like entering a cathedral and more like passing through airport security. We no longer relax into the rhythm of a trusted voice. We remain on guard, scanning for contraband signs of machine authorship.

    This defensive posture may prove fatal to the deepest pleasures of literature. Great reading requires vulnerability. It requires a willingness to let another mind rearrange your own. It requires trust. If every text becomes a potential deception, then reading loses its sense of encounter and becomes an exercise in verification. The reader ceases to ask, “What is this work trying to tell me?” and begins asking, “Who—or what—wrote this?”

    That shift may be the most consequential literary event of the AI age. The danger is not merely that machines will write books. The danger is that they will transform readers into skeptics incapable of the very surrender that literature requires. Long after the arguments about authorship fade, the deeper loss may remain: the disappearance of the sacred bond between a solitary reader and a solitary voice.

  • Can Philosophers Keep Their Souls in Silicon Valley?

    Can Philosophers Keep Their Souls in Silicon Valley?

    In “Someone Finally Wants to Hire Philosophers,” Lila Shroff reports what would have sounded like a punchline only a decade ago: philosophy majors may finally be getting the last laugh. For years, philosophy occupied an awkward place in the public imagination—a discipline associated with coffee-shop debates, existential handwringing, and the noble art of explaining to relatives why you were unemployed. At best, the philosopher was a thoughtful gadfly. At worst, a professional overthinker. But the rise of artificial intelligence has suddenly transformed philosophy from an intellectual curiosity into a marketable skill. Major technology companies are hiring philosophers. Universities are recruiting scholars who specialize in both AI and philosophy. The old joke about philosophy leading nowhere is beginning to age badly.

    As Shroff notes, this development should not surprise us. Philosophers have been wrestling with questions about intelligence, consciousness, morality, and the possibility of artificial minds for centuries. Long before Silicon Valley executives promised to change the world, philosophers were already asking whether a machine could think, reason, or possess something resembling a mind. Today, thinkers such as Nick Bostrom have become influential voices in the AI conversation. His book Superintelligence warned more than a decade ago that humanity might create machines whose capabilities outstrip our ability to control them. What once sounded like speculative science fiction now reads more like a boardroom agenda.

    The marriage between AI and philosophy arises from a practical concern. Technology companies want their products to appear ethical, trustworthy, and safe. A machine that accidentally promotes fraud, discrimination, or social chaos is difficult to market. Consumers are more likely to embrace AI systems that project wisdom, fairness, and restraint. In the increasingly crowded AI marketplace, virtue has become a product feature. Safety, ethics, and responsibility are not merely moral concerns; they are branding opportunities.

    Yet Shroff’s essay leaves several uncomfortable questions lingering in the air.

    First, philosophers disagree about nearly everything. That is practically the job description. If ethical questions routinely produce competing schools of thought, which philosophers do AI companies choose to hire? A utilitarian, a virtue ethicist, a libertarian, and a nihilist might evaluate the same problem and arrive at wildly different conclusions. When an AI company claims to be guided by philosophy, whose philosophy is it talking about?

    Second, corporations do not operate in a vacuum. They pursue growth, market share, influence, and profit. Given those incentives, it seems unlikely that technology companies will eagerly recruit philosophers whose views fundamentally conflict with corporate objectives. The philosopher who questions the legitimacy of the enterprise may not receive the same warm welcome as the philosopher who helps polish its public image.

    Third, what happens to philosophy itself when it becomes a lucrative career path? If technology firms reward certain ethical frameworks and ignore others, philosophers may gradually adapt their views to become more employable. Intellectual independence has always been easier to defend when no one is writing the check. Once prestige, influence, and six-figure salaries enter the picture, even the most principled thinkers may find themselves sanding off inconvenient beliefs.

    This is why I remain skeptical of any celebration of philosophy’s new status in the AI economy. There is no such thing as pure philosophy floating above human ambition. There are only human beings, complete with incentives, blind spots, loyalties, and self-interest. The partnership between AI and philosophy may produce genuinely useful ethical guidance. Or it may become an elaborate exercise in corporate virtue theater—a dazzling display of moral concern performed beneath bright lights while the machinery of profit hums steadily backstage. Whether philosophers become the conscience of artificial intelligence or merely its public relations department remains an open question.

  • Why Online Education Deserves Defending

    Why Online Education Deserves Defending

    Since the COVID lockdown, most of my teaching has migrated online. Even now, roughly three-fourths of my courses remain in the digital realm, where students encounter me less as a flesh-and-blood professor pacing beneath fluorescent lights and more as a disembodied presence living inside Canvas announcements, discussion boards, and video lectures recorded in my home office.

    To my surprise, retention rates remain strong. That fact alone suggests online learning serves a real need for many students whose lives resemble logistical hostage situations involving jobs, childcare, commutes, aging parents, unstable work schedules, and economic exhaustion. For these students, online education is not a luxury. It is the only doorway left open.

    Still, online learning clearly is not for everyone.

    Today’s Los Angeles Times article, “‘I felt like I wasn’t learning’: Community college students struggle with online education” by Adam Echelman, highlights several genuine problems now reshaping higher education.

    First, nearly 40 percent of community college classes are online, leaving many campuses eerily underpopulated. I see this myself every time I walk across campus beneath giant stretches of empty concrete where student traffic once resembled an airport terminal. Some days the college feels less like a thriving institution of learning and more like the abandoned set of a post-apocalyptic indie film where only the squirrels still believe enrollment is healthy.

    Second, online education is highly vulnerable to AI-assisted academic dishonesty. Entire assignments can now be outsourced to machines with frightening ease. Students who once copied homework from friends can now summon instant essays, summaries, reflections, and discussion-board responses generated in seconds by software that never sleeps and never complains about deadlines. Academic rigor has unquestionably been destabilized.

    Third, many students experience profound disorientation in online courses. They sit alone at glowing screens trying to decode unfamiliar interfaces, navigate modules, interpret assignment instructions, and manage deadlines without the immediate human structure of a physical classroom. Some students thrive in this environment. Others feel psychologically untethered, as though they have been dropped into an educational escape room with no map and unreliable Wi-Fi.

    All of these criticisms contain truth.

    But I still feel compelled to defend online education because face-to-face instruction creates its own formidable barriers that critics often romanticize away.

    Many students simply do not possess the time, transportation, money, childcare, emotional bandwidth, or scheduling flexibility necessary to attend traditional classes several times a week. Others suffer from social anxiety so severe that walking into a crowded classroom feels less like entering a learning environment and more like arriving for public execution. Some students experience the same confusion staring at a printed syllabus that others experience navigating Canvas. Confusion is not unique to online learning; it is part of learning itself.

    And AI has disrupted all education, not merely online education.

    The fantasy that we can restore some pristine pre-pandemic classroom paradise by dragging everyone back into physical seats ignores reality entirely. Face-to-face classes are also saturated with AI. Students use it in dorm rooms, libraries, cafeterias, parking lots, and sometimes while sitting directly in front of us pretending to take notes. The disruption is universal.

    We are living through a historical transition in which educators are desperately trying to preserve critical thinking, reading, writing, and job preparation while technological conditions mutate faster than institutional bureaucracy can respond. No one possesses perfect answers. Anyone claiming otherwise is selling nostalgia disguised as certainty.

    But I remain optimistic.

    Online teaching continues improving. Faculty are becoming more sophisticated in course design, communication, engagement strategies, video instruction, accessibility, and platform navigation. We are learning how to create clearer modules, more interactive coursework, better communication systems, and stronger student support structures. In many cases, students now receive the best aspects of both worlds: the flexibility of online access combined with increasingly refined teaching methods.

    And flexibility matters enormously.

    For many community college students, education is squeezed into the margins of adult survival. They complete assignments after ten-hour shifts, during lunch breaks, inside parked cars, while supervising children, or late at night after the household finally quiets down. Critics who romanticize the traditional campus experience often imagine eighteen-year-olds strolling across ivy-covered quads discussing philosophy beneath oak trees. Community college reality is far less cinematic. It involves exhaustion, economic pressure, and scheduling warfare.

    All of higher education is undergoing massive disruption simultaneously:

    • AI is transforming intellectual labor.
    • Student attention spans are changing.
    • Economic pressures are intensifying.
    • Online teaching technologies are improving.
    • Work and family demands are growing more brutal.

    Under these conditions, demanding a wholesale return to “the old ways” feels less like wisdom and more like denial.

    The old world is not coming back.

    That does not mean standards should collapse or that online learning is automatically superior. It means education must evolve alongside the lives students actually live rather than the lives institutions nostalgically wish they still lived.

    Online education will continue improving because necessity drives innovation with ruthless efficiency. Likewise, our understanding of how to create meaningful, rigorous, and humane education in the AI Age will continue evolving. We are not witnessing the death of learning. We are witnessing the painful reconstruction of it.

    The task now is not retreat. It is adaptation.

    It is time to move forward rather than cling romantically to a vanished academic world that technology, economics, and history have already left behind.

  • Mackenzie Shirilla: The Girl Who Became Her Feed

    Mackenzie Shirilla: The Girl Who Became Her Feed

    It was difficult to watch the Netflix documentary The Crash, which chronicles the horrifying case of two young men killed in a car crash after prosecutors argued that the driver, Mackenzie Shirilla, deliberately floored the gas pedal of her Toyota Camry to nearly one hundred miles per hour in an act deemed premeditated murder. The documentary is disturbing not merely because of the violence of the crash, but because of the portrait it paints of a young woman whose identity had become inseparable from her online performance. Mackenzie appeared trapped inside the exhausting machinery of self-curation, sculpting and broadcasting her existence with the kind of manic persistence social media now rewards as normal behavior. Her digital persona no longer seemed like an accessory to her life. It had metastasized into her life.

    Today, while listening to the podcast Blocked and Reported, I heard Jesse Singal and Katie Herzog discuss Gen Z’s eerie fluency for turning existence itself into a livestream. Both millennials sounded genuinely alienated by the phenomenon, as though they were describing a species only slightly adjacent to their own. Jesse referenced Mackenzie Shirilla’s relentless online presence as depicted in The Crash, pointing to the unsettling ease with which younger generations curate themselves for permanent digital exhibition. Yet one of the influencers discussed on the podcast commands nearly a million followers—a level of attention powerful enough to hijack almost any fragile human nervous system. Social media platforms have effectively industrialized validation, converting attention into a neurochemical slot machine that pays out in intermittent bursts of relevance, envy, and simulated affection.

    Attention itself is not the enemy. Human beings need recognition. Writers, artists, teachers, comedians, philosophers, and musicians all seek an audience because they are attempting to contribute something meaningful to the ongoing argument about what it means to be alive. But attention detached from substance becomes false gold. It glitters, intoxicates, and ultimately leaves the soul spiritually bankrupt. The dopamine cycle masquerades as significance while quietly hollowing out the self.

    The danger comes when a person can no longer distinguish between authentic identity and algorithmic performance. The online persona begins as branding, then evolves into compulsion, and finally hardens into pathology. It becomes louder, crueler, more narcissistic, and more detached from ordinary human proportion. The person starts living not for reality itself, but for its documentation. Meals become props. Relationships become content. Suffering becomes theater. Even grief gets optimized for engagement metrics. At that point, the self is no longer steering the machine; the machine is steering the self.

    Mackenzie Shirilla appears to have crossed that line. She allowed the curated self to consume the actual self. What remained was not individuality but a kind of digital possession—a consciousness warped by attention addiction, performative intensity, and emotional exhibitionism. The tragedy of The Crash is not merely that lives were destroyed in a violent instant. It is that modern culture increasingly trains young people to confuse visibility with meaning, performance with identity, and online relevance with human worth. Mackenzie lost that distinction entirely. In the end, the algorithm did not merely shape her personality. It devoured it.

  • Prove You Offer Something AI Cannot, or Become Obsolete 

    Prove You Offer Something AI Cannot, or Become Obsolete 

    After nearly forty years teaching college writing, I can say this without ceremony: AI didn’t knock—it walked in and rearranged the furniture. We weren’t ready. Now we’re scrambling to answer basic questions we once took for granted: What is our role? What, exactly, is our job? How do we evaluate a student’s work when the student can outsource the thinking? And how do we defend the value of higher education—especially the Humanities—to a public that is already drifting away?

    The backdrop isn’t kind. We face a culture that reads less and skims more, chasing quick hits of stimulation instead of sustained thought. The cost of college keeps rising while the promise of stable, predictable employment grows less certain. In that context, debates about AI feel less like speculation and more like triage. The question isn’t whether AI will reshape higher education; it’s how deeply and how quickly.

    In that vein, I read Jay Caspian Kang’s essay “Why the Future of College Could Look Like OnlyFans” with particular interest. Kang highlights the argument of Hollis Robbins, who offers a blunt standard for survival: universities justify their existence only if they provide access to faculty whose expertise exceeds what AI can deliver. Strip away the academic language, and the message is stark: prove you offer something AI cannot, or become obsolete.

    Robbins pushes the point further. In a classroom saturated with generative AI, she predicts a severe contraction—potentially eliminating a large share of faculty positions. Courses built around foundational, repeatable skills—the kind often taught in the first two years—are the most vulnerable. Specialized fields, particularly those grounded in rare knowledge or deep cultural expertise, are far less exposed. The more interchangeable the instruction, the easier it is to replace.

    That leaves instructors like me in an uneasy position. I’ve spent decades teaching literacy and critical thinking—the very skills that AI now performs with unnerving competence. If Robbins is right, those of us in broad, introductory disciplines face the sharpest edge of change. The specialists may endure. The rest of us may be folded into what she envisions as a rapid and unforgiving contraction.

    This isn’t a distant possibility. It’s a present demand. Adapt—or be edited out.

  • The Day I Logged Off the AI Panic Machine and Walked at the Beach

    The Day I Logged Off the AI Panic Machine and Walked at the Beach

    I teach college writing, which means I’ve spent the last four years staring at the AI question the way a man stares at a fire he suspects might jump the fence. When ChatGPT arrived, it didn’t knock politely. It crashed into the room like a UFO and rearranged the furniture. Since then, I’ve read what feels like a small library’s worth of essays—predictions, warnings, elegies for the essay itself—and contributed a few of my own, because that’s what we do: we metabolize disruption by writing about it.

    But there comes a point when the analysis stops clarifying and starts echoing.

    I’ve reached that point. My brain has filed a quiet injunction: no more. Not just a break from AI, but a break from reading about how exhausted everyone else is by AI. The discourse has become a hall of mirrors—each reflection slightly more fatigued than the last.

    I’ve been here before. In 2010, I had newborn twins, which is another way of saying I was living inside a low-grade emergency. The market offered guidance—books, podcasts, earnest experts—but I wanted none of it. I was already doing the job. Additional commentary felt like a second shift. Experience was loud enough; analysis was just noise layered on top.

    Both episodes point to the same condition: Applied Reality Rejection—the refusal to consume secondary discourse when you’re already neck-deep in the primary experience. When you’re in it, more talk about it doesn’t help. It dilutes.

    And here’s the part the essays rarely admit: reading about AI doesn’t soothe AI anxiety. It compounds it. Each think piece arrives like a fresh weather report announcing the same storm in slightly different prose.

    So I’m choosing friction of a better kind. I play the piano until my attention steadies. I pick up kettlebells and let gravity argue with me for a while. I walk the beach and let the horizon do what no article can—put scale back into the day. The analog world doesn’t theorize; it recalibrates.

    That was the remedy with the twins, too. Not another podcast on sleep training, but a walk, a dumb TV binge, a sweaty hour in the garage. Relief came from stepping out of the commentary loop, not diving deeper into it.

    Which is why, when I see another AI essay queued up from The Atlantic or The New Yorker, I feel a familiar tightening—and then I close the tab. Not out of contempt, but out of preservation.

    I’ve heard enough echoes. It’s time to drive two miles to Catalina Avenue and take a walk at the beach.

  • How It Feels to Grade 60 Original Essays Edited by AI

    How It Feels to Grade 60 Original Essays Edited by AI

    I assigned my students an essay that asked them to describe a place both ugly and formative—a crucible that hurt them and, in the same breath, made them. The submissions came back like a map of pressure points: a high school classroom that felt like a courtroom, a gym that smelled of rubber and dread, a mental health ward lit like an aquarium, a pre-op room where the clock ticked louder than courage, a soccer field that taught hierarchy and grace, a family home in El Salvador, a Korean farm where labor spoke in blisters. The content was theirs—specific, unborrowed, alive. But the sentences often arrived wearing a suspicious polish, the prose lacquered to a showroom shine. You could feel the editor in the room, invisible and tireless.

    I keep returning to a metaphor I can’t shake: AI is like a bodybuilder taking steroids for writing. Go in “natty,” and you present a muscular physique that is honest–well defined, maybe even impressive. Add the chemical assist and you step onstage thirty percent larger, veins penciled in, every line exaggerated into spectacle. 

    After sixty of these eye-popping essays, I felt the same deadening I get at a bodybuilding show. At first you admire the craft; then the sameness creeps in. The poses change; the effect doesn’t. Everything looks like everything else.

    This is my ambivalence, and it refuses to resolve. On one hand, AI hands students a language upgrade that would make a New York editor nod—clarity, rhythm, a vocabulary that lands. It’s as if they’ve been fast-tracked to a professional register. On the other hand, that very upgrade dilutes the experience. When strong language grows out of a human mind, it carries the friction of effort—the faint grit that makes it feel earned, inhabited. When it arrives laundered through a machine—the “stochastic parrot” Emily M. Bender warned us about—it can be dazzling and hollow at once, a chandelier with no wiring. The sentences glitter; the room stays dark.

    I’ve graded hundreds of essays for years and thought I knew the terrain—the tells of struggle, the leap from draft to draft, the moment a voice becomes unmistakably its own. Now I’m reading in a new jurisdiction with no settled law. I’m less a judge than a border agent, inspecting passports that all look freshly printed. Welcome to the literary Wild West: the gold is real, the essays are suspect, and every nugget asks the same question—where did you get this?

  • The Rise of the Cyborg Student and the Collapse of Learning

    The Rise of the Cyborg Student and the Collapse of Learning

    In her Atlantic essay “Is Schoolwork Optional Now?”, Lila Shroff describes a classroom that has quietly slipped its friction. Students entering high school around 2024 have discovered that schoolwork—once a slog of half-formed ideas, crossed-out sentences, and mild despair—can now be outsourced with the elegance of a corporate merger. With tools like Claude Code, they recline while a digital understudy attends class on their behalf, taking quizzes, drafting lab reports, and assembling PowerPoints with the glossy finish of a mid-level consultant angling for a promotion.

    Teachers respond with variety, as if novelty could outpace automation. More assignments, different formats, new prompts. It doesn’t matter. The students simply retrain their AI to shapeshift into whatever species of learner is required: the earnest analyst, the reflective humanist, the data-savvy pragmatist. The submissions arrive immaculate—coherent, polished, and suspiciously free of the small humiliations that once marked actual thinking.

    The problem is not that the work gets done. It’s that no one is being worked on. The transformation has shifted from mind to method. Students aren’t learning the material; they’re learning how to manage a machine that can impersonate someone who did.

    If that weren’t enough, the next escalation has arrived with a name designed to soothe your nerves: Einstein. This AI agent claims it can log into platforms like Canvas and complete an entire semester’s workload in a single day. It doesn’t just skim the surface. It watches lectures, digests readings, writes essays, posts discussion comments, submits assignments, and takes exams—leaving behind a digital paper trail so competent it borders on smug.

    Shroff decided to test the promise. She enrolled in an online statistics course and turned Einstein loose. Within an hour, it had completed the entire semester of work: eight modules and seven quizzes. She earned a perfect score. She also learned, by her own account, almost nothing. The grade was real. The education was imaginary.

    Einstein’s creator, Advait Paliwal, is a 22-year-old who speaks with the calm inevitability of someone announcing the weather. His argument is simple: this is a warning. Adapt or become decorative. Educators have responded with lawsuits and cease-and-desist letters, which he treats as polite acknowledgments that the problem is larger than any one person. If he hadn’t built it, someone else would have. And if you find Einstein alarming, he assures us, you should pace yourself—this is the beta version of the apocalypse. “There’s more to come.”

    Meanwhile, Silicon Valley is not retreating. It is accelerating, pouring resources into embedding AI deeper into the educational bloodstream. The irony is almost too clean: educators are losing control not only because the technology can’t be contained, but because they use it themselves. AI grades papers, drafts materials, streamlines feedback. It makes the job more efficient. It also quietly rewrites what the job is.

    The endgame is already visible. It has a name that sounds like a software feature but reads like a verdict: the Fully Automated Loop. AI generates the assignments. AI completes them. AI grades them. The student, once the point of the enterprise, becomes a spectator to a closed circuit of competence.

    We used to worry about students not doing the work. Now the work does itself.

    And when that loop closes, education doesn’t collapse in a dramatic heap. It hums. It functions. It produces results.

    It just stops producing people.

  • Lecture Drift Syndrome and the Vanishing Classroom

    Lecture Drift Syndrome and the Vanishing Classroom

    My students have been reporting a peculiar academic phenomenon: the two-hour class that contains no discernible lesson. In its place stands a performer—a professor intoxicated by the belief that a self-indulgent monologue is effective teaching. Convinced they possess the sacred “gift of gab,” they proceed to use it like a leaf blower in a library.

    And gab they do.

    They narrate their dreams with the seriousness of a Jungian symposium, decoding every symbol as if the subconscious were filing quarterly reports. They recount contractor disputes with the dramatic tension of courtroom testimony. They offer serialized updates on family feuds, restaurant conquests, tropical vacations, and medical procedures so vivid they border on malpractice to describe. They even resurrect their collegiate glory days, in which they allegedly outwitted professors and classmates alike—a mythos delivered with the confidence of a man who has never been fact-checked.

    Meanwhile, the classroom undergoes a quiet evacuation.

    Not physically—students remain seated, dutiful, nodding at appropriate intervals—but cognitively, the room is abandoned. One student is deep into a novel. Another is solving calculus proofs. Several are toggling between sports highlights and sports betting apps, hedging their attention the way day traders hedge risk. Text messages fly. Homework from other classes gets completed. What was scheduled as instruction has been repurposed into a supervised study hall with a live podcast no one asked to attend.

    The professor, of course, notices none of this.

    This is the defining pathology: two monumental blind spots. First, the inability to recognize that the monologue is not merely irrelevant but actively draining—an intellectual sedative administered over two uninterrupted hours. Second, the delusion that presence equals engagement, that a room full of bodies must also be a room full of minds.

    It is neither.

    What we are witnessing is an academic epidemic: Lecture Drift Syndrome. A condition in which a class session slowly detaches from its stated purpose and floats into the open sea of anecdote, confession, and self-display. The syllabus becomes a relic. Time warps—two hours pass, yet nothing has been learned. Themes dissolve. Structure collapses. The lecture doesn’t end so much as it dissipates.

    In the end, the classroom is no longer a site of instruction.

    It is a stage occupied by one man talking—and thirty students elsewhere.

  • Acid-Washed Jeans and Artificial Intelligence: The Rise and Fall of Instant Cool

    Acid-Washed Jeans and Artificial Intelligence: The Rise and Fall of Instant Cool

    I have a confession that belongs in the Museum of Bad Decisions: I wore acid-washed jeans in the 80s. Not casually. Not ironically. I wore them to teach college writing at twenty-four, convinced I was the cool professor—the kind of man who could annotate a thesis statement and headline a Duran Duran video without changing outfits.

    The problem, of course, is that everyone thought they were that guy. Acid-washed jeans thrived because they delivered instant mythology. You looked like you had lived—hard, fast, dangerously—when in reality you had simply survived a trip to the mall. They were rebellion by chemical treatment, authenticity by rinse cycle. For a brief, glittering moment, that illusion worked. But illusions collapse under mass adoption. When everyone looks distressed, no one looks interesting. The jeans had nowhere to go; they began at maximum volume and stayed there, screaming. Eventually, the culture regained its hearing, glanced downward, and realized it had dressed itself like survivors of a denim-related explosion. Acid wash didn’t fade—it was exiled.

    I think about that rise and fall when I look at my students’ shifting attitude toward AI. In 2022, AI arrived like those jeans: a miracle fabric promising salvation from drudgery, writer’s block, and the existential dread of the blank page. It offered pre-fabricated brilliance—the intellectual version of showing up to the gym already sweating. Students embraced it with the same breathless certainty that this time, finally, the shortcut would make them exceptional.

    Now? They roll their eyes. They call it cringey.

    What changed is not the technology but the perception of authenticity. Factory-installed insight, like factory-installed distress, has become suspect. My students are not naïve; they have finely tuned detectors for fraud. They live in a world saturated with performance—the influencer selling a life they don’t live, the hollow expert recycling borrowed ideas, the unprepared instructor filling class time by sharing his dreams and domestic dramas while they politely tune him out and read Tolstoy’s War and Peace or the entire oeuvre of J.K. Rowling. 

    AI, at its worst, slots neatly into that ecosystem. It produces language that sounds like thinking without the inconvenience of actually thinking. And my students can hear the hollowness.

    This does not mean AI is useless. At its best, it belongs alongside Word, Google Docs, and Grammarly—a tool, not a personality. But tools do not build a self. They do not generate voice, conviction, or the slow accumulation of insight that makes writing worth reading. Lean on them too heavily, and the result isn’t mastery—it’s dependency dressed up as efficiency.

    My students understand this. That’s why the fever has broken. The early hype—the belief that AI would function as a kind of intellectual superpower—has lost its grip. The spell didn’t shatter because AI failed. It shattered because people learned to recognize the difference between something that helps you think and something that pretends to think for you.

    Acid-washed jeans didn’t disappear because denim stopped working. They disappeared because people grew embarrassed of the shortcut.

    AI isn’t going anywhere.

    But the illusion that it can make you interesting just by wearing it?

    That’s already out of style.