“Thou shalt love thy neighbor as thyself.” — Matthew 22:39
“I hate them too. I really do. I hate them. I cannot stand them, because I really do believe they hate our country.” — President Donald J. Trump, July 3, 2025, Iowa State Fair, speaking of Democrats as the internal enemy
It is not the demagogues who bewilder me. The political class, the oligarchs who sponsor them, and the ambitious mediocrities who ride their coattails—these I understand. Their motives are ancient and ever-recurring: power, wealth, the intoxicating delusion of being above others. History has never lacked for such befouled souls. What confounds me is not their corruption, but the ease with which so many of my fellow citizens—ordinary men and women raised in homes of decency—abandon their values, their civility, and even their reason to follow such selfish and manipulative men.
Reading Hannah Arendt’s The Origins of Totalitarianism brings a sense of recognition as much as revelation. Her breadth of learning and depth of judgment are immense, yet her insight feels uncomfortably near. She wrote of loneliness, of the dissolution of shared reality, of the loss of what she would later name “the common world.” These, she warned, are the preconditions of tyranny. Her warning about that loss recalls a time when the common world was still carefully, even tenderly, built in classrooms.
When I taught as an educator at a Catholic junior-high school years ago, I once wrote on the blackboard—in chalk, for those were chalk days—the single word RESPECT. My pupils were told that respect, for oneself and still more for others, was the foundation of our classroom and of the larger world. It need not be earned, but it could be lost. Respect was the first principle of civilization: acknowledgment of another’s humanity, even in disagreement or uncertainty.
In my religion class, that same word deepened through Christ’s commandment: “Thou shalt love thy neighbor as thyself.” Respect, I told them, was the beginning of that love—not the sentimental kind that flatters or excuses, but the disciplined recognition that others, too, are made in the image of God. Such love is not mere emotion but moral vision. It binds community, restrains cruelty, and demands humility; for I believed then, as I do now, that if children learned that lesson, the rest would follow—discipline, fairness, empathy, and truth.
Yet today, the nation seems one in which respect has eroded into mockery, disagreement into contempt. Men and women who once prized civic decency now sneer at simple kindness as weakness and mistake public cruelty for laudable candor. Forgotten are the lessons once taught by parents and teachers—forgotten that respect is not submission but recognition, not indulgence but acknowledgment that every person bears the image of something sacred.
Arendt helps to explain part of this descent. She wrote that the ideal subject of totalitarian rule is not the convinced ideologue but the person “for whom the distinction between fact and fiction (i.e., the reality of experience) and the distinction between true and false (i.e., the standards of thought) no longer exist.” In our time, that confusion has been engineered deliberately by those who control mass media, public discourse, and civic conversation. Facts are now optional, reality malleable, and truth a commodity sold to the highest bidder. Noise replaces discernment; pundits and influencers, preachers of grievance and merchants of outrage, fill every silence until the ordinary citizen, weary of discerning, yields to the comfort of belonging. To be part of a movement—any movement—feels safer than standing alone amid uncertainty in an increasingly fragmented civic community.
But belonging comes at a cost. The price is moral collapse. Once fear replaces thought, hatred becomes easy. Once truth becomes relative, cruelty seems justified. Once self-respect erodes, submission feels like relief. It is with great grief that one watches people trade the humility of faith for the arrogance of fanaticism, the rigor of science for the comfort of superstition, the patience of democracy for the immediacy of mob emotion.
Some will say it is economics—that poverty, inequality, and insecurity drive people to such extremes. There is truth in that, but not the whole truth. Others will say it is ignorance, the failure of education. That too plays its part. Yet beneath both lies a deeper malady: spiritual exhaustion, a weariness with freedom itself. To think for oneself, to weigh evidence intelligently, to question authority doggedly—these require effort and courage. Many—perhaps most—prefer the narcotic of certainty. It is easier to be told what is true than to bear the burden of finding out responsibly.
That is why propaganda works—not because people are fools, but because they are tired, frightened, and longing for meaning. The demagogue offers them belonging, moral clarity, and enemies to hate. He tells them their failures are someone else’s fault. He gives them a cause grand enough to drown their doubts. And in surrendering to him, they mistake obedience for faith, vengeance for virtue, and ignorance for authenticity.
Hannah Arendt understood this weariness well. She observed that “mass propaganda discovered that its audience was ready at all times to believe the worst, no matter how absurd, and did not particularly object to being deceived, because it held every statement to be a lie anyhow.” That insight reaches beyond politics into the realm of spirit. When cynicism becomes habitual, truth itself grows unbelievable; when every statement is assumed false, the liar becomes prophet, and the soul, deprived of trust, welcomes its own deception.
What bewilders most is not the malice of my fellow citizens but their forgetfulness. Gone is the decency of parents, the moral instruction of their faiths, the civics once taught in schools, the respect once owed to fact, reason, and one another. Forgotten is that fear corrodes the soul and that hatred is the cheapest imitation of strength. Forsaken is the understanding that self-government depends not on leaders but on citizens—on the willingness to think, to listen, to doubt, and to care for one another.
Fifty years from now, scholars will no doubt write of these years with the detachment of hindsight. They will trace the algorithms, the demography, the disinformation networks, and the economic despair. They will find causes, correlations, and turning points. Yet they will still struggle to answer the simplest question: how did so many, knowing better, choose worse again and again?
For the manipulators, history has an answer—ambition, greed, vanity. For the manipulated, the explanation is more tragic: surrender not out of evil but out of weariness; not out of ignorance but out of fear; not because the way was lost, but because memory failed.
That is the lesson of our time. Evil will always exist; it requires only opportunity. But tyranny of the spirit—this quiet decay of conscience—thrives only when the many forget that decency is a daily act, not a tribal badge.
This reflection is written not to condemn but to plead—for remembrance. To remember what was taught when we were young: that truth matters, that kindness binds, that facts are not partisan, that faith without humility is idolatry, and that freedom demands thought.
When RESPECT was written on that blackboard years ago, it was in the belief that children were being prepared for a world that valued it. That belief endures—if enough choose to live as if it were true. For if it is forgotten, then no constitution, no scripture, no science can save us. We will have undone ourselves, not by conquest, but by consent.
How Two Decades of Income Tax Cuts for the Wealthy Shifted the Load onto Property Owners and Renters
During the most recent reappraisal for property taxes, thousands of Cuyahoga County residents opened their mailboxes to find reappraisal notices that made their stomachs drop. Property values had climbed by an average of 32% county-wide, with East Cleveland residents facing increases of 67% and Maple Heights 59%.
Michael Chambers, Cuyahoga County Auditor, reported that, for 71-year-old Parma resident Agnes Gallo, this meant her home’s value rose by $76,000, pushing her annual tax bill up nearly $950. “This is outrageous,” she said. “People can’t afford to live in their own houses.” He also said that single mother Roni Menefee, facing a 49% valuation hike, admitted she was considering leaving Ohio altogether: “We’re hardly living in Beverly Hills here.”
County officials insist that House Bill 920 prevents taxes from rising dollar-for-dollar with property values. But for seniors on fixed incomes or working families barely hanging on, even modest increases can be destabilizing. More than 20,000 residents filed complaints, with thousands of adjustments granted. Still, the anger lingers—and justifiably so.
The Long-Term Tax Shift
That anger is rooted in two decades of deliberate state policy. Since 2005, Ohio’s Republican lawmakers have steadily cut the personal income tax, reducing rates most sharply at the top. Over time, these cuts drained nearly $13 billion annually from state revenues.
With less money flowing from the state to schools, libraries, and local governments, communities were forced to raise more themselves. And because they are prohibited from taxing investments or capital gains—the kinds of income more common among the wealthy—the primary tool left was the property tax (although many municipalities also increased their local income taxes-Cleveland voters narrowly approved an increase in its income tax from 2 percent to 2.5 percent in 2016).
The outcome: in 2024, Ohioans paid $23.9 billion in property taxes—more than they contributed through sales taxes ($13.7 billion) or income taxes ($9.5 billion). The most regressive form of taxation has become the backbone of public services.
Put plainly: the legislature cut income taxes for the wealthy, and forced everyone else—retired, middle-class, working-class, and poor—to make up the difference through higher property taxes.
The Nonprofit Inversion
At the same time, Ohio has allowed exemptions and abatements to balloon. Nearly $90 billion in property value—17% of the state’s total—is exempt from taxation, up from 14% two decades ago.
The largest single category? Abatements, totaling $26.6 billion. These were meant as temporary incentives to spur growth but are now permanent fixtures. Even utilities, which have captive consumers and guaranteed profits, receive abatements for investments they would make anyway.
And then there are the so-called nonprofits. Their tax-exempt status rests on public benefit, yet their leaders are not infrequently paid like corporate executives:
Institution
Leader
Annual Compensation
Tax/Exemption Status
Cleveland Clinic
Dr. Tomislav Mihaljevic, CEO
≈ $7 million (2023)
Vast campus tax-exempt as nonprofit hospital
Ohio State University
Ted Carter Jr., President
≈ $1.3 million (2024)
University property tax-exempt
Ohio State University
Ryan Day, Head Football Coach
≈ $10–12.5 million (contracted 2025)
Public university benefiting from exemptions
Hawken School (Private)
D. Scott Looney, Head of School
≈ $1.05 million (2023, IRS Form 990)
Elite private school, property tax-exempt
These institutions are sheltered from taxes while ordinary citizens—many of whom can barely make ends meet—are expected to pay “full freight.”
Renters Pay Too
The burden does not end with homeowners. Renters also pay indirectly, as landlords pass on property tax hikes through higher rents.
In 2023, Ohio saw some of the steepest rent increases in the nation:
Cincinnati: one-bedroom rents up 17% year-over-year.
Columbus: also up 17%.
Central Ohio: squeezed further by Intel, Amazon, and data center developments.
Statewide: over 700,000 renter households are “severely cost-burdened,” spending more than half their income on housing.
Even those who do not own property are being priced out of Ohio’s communities.
Populist Anger and the Ballot Box
It is no wonder, then, that frustration has spilled into politics. In 2025, an all-volunteer group began gathering signatures for a constitutional amendment to abolish property taxes entirely. Organizers say they are moving forward “no matter what” lawmakers do, because people feel they “no longer have a voice in this government.”
The proposal is extreme. Abolishing property taxes would blow a $23 billion hole in funding for schools, libraries, mental health services, and parks. Replacing it with sales taxes could require rates as high as 20%. Yet the fact that such a movement exists—and is gaining traction—reveals how deeply citizens feel abandoned.
They no longer trust lawmakers who, for twenty years, cut income taxes for the rich while pushing costs onto everyone else, especially the working class, seniors, and the poor. They see abatements handed to billion-dollar institutions and “nonprofits” with millionaire executives, while seniors in Parma and renters in Columbus face bills that are unsustainable.
The Choice Ahead
Ohio’s property tax crisis is not an accident. It is the inevitable result of two decades of choices:
Cut income taxes for the wealthy.
Hand abatements to billion-dollar institutions.
Shift the burden onto homeowners, renters, and the poor.
The result is predictable: the young leave by choice, the old leave by necessity, and those who remain are angry enough to contemplate abolishing the system entirely.
Eliminating property taxes outright is likely not the answer—it would devastate schools, libraries, and local services. But for many Ohioans, it may feel like the only way to force state leaders to listen. When lawmakers protect the powerful and ignore the cries of ordinary citizens, radical proposals become the only language that carries weight.[1]
And the cry is not simply to be heard. It is to be relieved—to be lifted out from under a system of taxation that has become oppressive, unfair, and in many instances, unsustainable. Until that relief is real and tangible, until fairness is restored, the ballot box will remain the people’s only instrument. And if the choice is between leaving their homes or leaving the system as it is, more and more Ohioans will choose to abandon the system itself.
The choice is no longer between reform or complacency. It is between reform or rupture.
[1] Some might dismiss the property tax abolition initiative as folly that would devastate local services. But terror concentrates the mind wonderfully. When gerrymandered legislative maps silence voters’ voices in normal governance, when the legislature attempts to eliminate or dilute ballot initiatives entirely, and when even successful citizen initiatives are ignored by lawmakers and courts, extreme measures become rational responses. The terror that grips policy makers, and concentrates their focus if voters eliminate $23 billion in local funding, might finally force the political class that has spent decades redistributing wealth upward to confront the unsustainable system they’ve created. Sometimes breaking a captured system is the only way to build a fair one.
The following are two companion reflections—On Truth and Empirical Fact and No Arc, No Lessons—presented together under the shared heading Method and Meaning in an Unteachable World. Though each may stand alone, they are best read in conversation with one another. Both essays resist the comforting notion that history, literature, or art functions as teacher or guide, and instead consider interpretation as an act of encounter—provisional, situated, and shaped as much by silence as by statement.
The first essay explores the distinction between fact and truth, exploring how memory, intention, and metaphor complicate the act of knowing. The second rejects the idea that history bends toward moral instruction or cumulative wisdom, and instead proposes a posture of reflective attention to the recurring patterns and failures of the human condition.
Versions of both essays with full citations and scholarly apparatus are in preparation for future publication. What follows here is intended for open reading and contemplation.
On Truth and Empirical Fact
“You cannot step into the same river twice.” —Heraclitus (Fragment 91, DK B91)
In the course of recent reflection, a distinction long known, but not always properly honored, must be drawn again: that between truth and empirical fact. Though often conflated in casual discourse, these are not synonymous—nor should they be.
An empirical fact is a datum: observed, measured, verified. It is the yield of experiment, the result of record, the artifact of sensory perception. That water boils at one hundred degrees Celsius at sea level is a fact. That a coin weighs 3.2 grams and bears a cross upon its reverse is a fact. That a battle was fought in the year 1066 may be supported by a host of facts: chronicles, bones, weaponry, et cetera. Such facts, when properly corroborated, are not unimportant. But they are not truth.
Truth, if it exists at all, is something larger, more elusive, more alive—not constructed by us, but encountered when consciousness prepares itself to receive what appears. It does not come when summoned, but when the conditions for its appearing have been made ready: doubt, humility, attention. It is apprehended in this prepared openness, grasped in the space between what is seen and what is understood.
Philosophers have long attended to this disjunction. Plato distinguished between the world of appearances and the world of eternal Forms, the former unstable, the latter enduring. Augustine found truth not in the fluctuating realm of sensory report, but in the divine Logos. Nietzsche, ever unsettling, dismissed truth as a “mobile army of metaphors”—useful, yes, but neither objective nor stable. Heidegger, resisting the reduction of truth to correctness, instead spoke of aletheia—not truth as correspondence, but as unconcealment, as that which emerges into view. And Gadamer—whose influence upon this approach is not accidental—taught that truth emerges in understanding itself, not as a proposition but as a happening, shaped by dialogue and historical consciousness.
Facts may be marshaled. Truth, by contrast, is survived.
Even intention, often treated as the surest witness to truth, must be interrogated. The poet’s intent, the author’s purpose, the painter’s design—these are not fixed coordinates but shifting recollections. Memory does not preserve; it reconstructs. And with each return to the well of what was once meant, the water tastes slightly different. Heraclitus observed that one cannot step into the same river twice—not only because the river flows, but because the self who steps in is no longer the same. So it is with intention. If asked now what was intended in a particular line or gesture, one may offer a reply—but it is a construction, shaped by who speaks now, not by who once acted. Intention, like truth, is not preserved in stillness—it is shaped in motion. It, too, is not possessed, but pursued.
In the poem At the Crossing, the aim was not to name truth—such a thing cannot be done—but to describe the space it haunts. The poem speaks of words that fracture, colors that deceive, touches that both reveal and withdraw. It ends not in assertion, but in a trembling, a silence where meaning nearly forms but does not solidify. A reader once dismissed it: “Life is too brief,” he said, “to spend in the space where meaning almost forms.” The impulse is understood. But the objection must be declined.
For it is in that space—that trembling margin—that life does happen. To live fully is not to claim truth as possession, but to encounter it as presence. Not to seal it in certainty, but to allow it to move, shadowlike, across the inner walls of the soul.
Empirical facts anchor us to the world. But truth is not what anchors—it is the thread we follow across the abyss.
And we follow it not with measuring tape, but with metaphor, with memory reshaped each time it stirs, with intention half-forgotten, and with the courage to walk where the light breaks, not where it rests.
No Arc, No Lessons: On Method, Encounter, and the Tragic Repetition of History
“To articulate the past historically does not mean to recognize it ‘the way it really was’… It means to seize hold of a memory as it flashes up at a moment of danger.” —Walter Benjamin, Theses on the Philosophy of History
Each age brings forth its own imperative—shaped by its wounds, haunted by its questions, driven by its unspoken needs. The present is no exception. Whether in the study of history, the contemplation of art, or the exegesis of sacred or poetic texts, interpretation does not arise in a vacuum. It emerges from a condition: the place, the moment, the unease that calls forth inquiry. And yet, though each generation may believe itself newly burdened or singularly illuminated, the recurring gestures of human life belie that novelty. There are patterns, yes—but these do not confirm progress. They reveal persistence.
The idea that history bends—toward justice, truth, wisdom—is seductive. It offers shape to the shapeless, comfort to the anguished, and direction to the lost. But there is no arc. The metaphor distorts by promising what experience consistently denies. If history teaches, its students are unteachable. The same motives recur, the same errors repeat, the same vanities endure. Progress, when claimed, is often little more than a rearrangement of circumstance. The root remains.
The players do not change. Their names shift, their languages evolve, but their roles remain remarkably constant. Power is sought, justified, and abused. Fear is stoked and traded for security. Hope is minted into symbols, then worn threadbare. Love, loss, betrayal, glory, shame—these are the constants. The stages differ: the scenery updated, the choreography modernized. But the script draws upon ancient instincts. And the audience, again and again, forgets the last performance, believing the story to be new.
Interpretation, then, cannot rest on the assumption that knowledge leads to virtue or that understanding necessarily yields transformation. It may. But often it does not. History is not a teacher. Art is not a moralist. Scripture does not condescend to pedagogy. If anything is revealed, it is revealed despite the will to ignore, deny, or disfigure it.
This position echoes Walter Benjamin’s image of the Angel of History, whose face is turned toward the wreckage of the past even as a storm drives him blindly into the future—what we call progress. It stands also in contrast to the historicism that treats the past as lesson-book or path to telos. Gadamer reminds us that understanding is not methodical recovery, but an event of fusion between past and present. Yet this fusion must be entered with humility, not control.
Given the absence of reliable progress and the persistence of human patterns, interpretation requires a different posture—one that recognizes repetition, resists despair, and permits meaning to arise without demand. Method, in this context, must be understood not as a tool of conquest, but as a lens—no more authoritative than another, yet capable of bringing certain essences to the surface. Every method is partial, shaped by its assumptions, animated by its framing questions. No method sees the whole. Each reveals what it is attuned to find. Truth, if it appears at all, does so not as result, but as event—as something glimpsed when the interpreter is prepared to receive, not to impose.
Three words mark the contours of a fitting approach: nexus, interaction, and reflection.
Nexus identifies the place of convergence—where past and present, text and reader, artifact and witness intersect. It is not discovered in isolation, but emerges through relation. Interaction marks the dynamic movement within that convergence. Meaning is not fixed; it arises through tension, difference, and engagement. Reflection follows—contemplative, fragmentary, often incomplete. It does not assert finality but honors process. It acknowledges that memory reshapes what it recalls, that intention fades into approximation, and that even the most careful exegesis remains provisional.
This echoes the work of Paul Ricoeur, who reminds us that narrative, memory, and identity are always under construction—never final, always revised in the act of remembering. Warburg’s concept of Nachleben der Antike—the afterlife of antiquity—reveals how cultural symbols and images recur across historical periods not as static forms but as charged fragments, reanimated under new conditions, carrying both continuity and transformation in their repetitions. This persistence of symbolic forms across time exemplifies the broader pattern: not progress, but recurrence with variation.
From art, history, and sacred text, nothing must be demanded. They may instruct, but only when they are permitted to resist instruction. They may illuminate, but not on command. They may wound, they may deceive, or they may pass in silence. The encounter must be enough.
Empirical facts can be gathered. Archives can be organized. But truth, if it comes, does not arrive catalogued. It appears only when conditions are ready—when the reader or viewer stands not with certainty, but with openness. Not as master, but as interlocutor.
Too often, only the facts are preserved. They are worn as tokens of knowledge while the truth behind them—uncomfortable, paradoxical, demanding—is left behind. The lesser lesson becomes the badge of wisdom; the deeper truth is dismembered for convenience.
No arc. No grand instruction. Just the repetition of roles, the echo of stories, the persistence of hunger. Meaning, when it comes, comes not as reward, but as grace.
And yet, even in refusal, in distortion, in failure, there remains something sacred in the effort to attend. To see the pattern, not to worship it. To hear the old lines in new voices. To walk the ruins with open eyes, knowing that the script will be performed again.
Auguste Rodin, The Thinker (conceived 1880, cast c. 1917). Bronze. Cleveland Museum of Art. CC0 Originally conceived as part of The Gates of Hell, Rodin’s The Thinker was not merely a passive figure lost in thought, but a representation of Dante himself, contemplating the fates of souls below. Cast in tension and muscle, he embodies the labor of intellect—the weight of reflection, the cost of authorship, and the solitary burden of making meaning in a world of mechanized shortcuts. A fitting emblem for the human writer mistaken for a machine.
Preface: A Writer Mistaken for a Machine
The main essay that follows this preface was generated wholly by ChatGPT’s “Deep Research” feature, produced at my request after a recent experience that was equal parts amusing and unsettling.
In a recent essay I had written—carefully and thoughtfully—I found myself admiring a few turns of phrase that seemed, perhaps, too polished. Seeking to determine whether I had unconsciously absorbed and repeated something from my recent reading, I turned to a site I had used before—one that aggregates reviews of AI and plagiarism detectors commonly employed by educators. From there, I selected not one, but three highly rated tools to review my essay and determine whether I had inadvertently borrowed a phrase from Blake, Eckhart, Pseudo-Dionysius, or anyone else I have recently been reading.
The results were, to put it mildly, contradictory, though not for the issue I had set out to explore. The first site was no longer operational, citing the unreliability of AI detection in view of the accelerating complexity of AI language model algorithms. The second tool confidently declared that my essay was entirely free of both plagiarism and AI-generated content. The third, by contrast, just as confidently pronounced that my essay was likely 100 percent AI-generated, both in style and content, based on the presence of twenty phrases—unhelpfully left unidentified—that appeared more frequently in AI-generated material. The site explained that those mysterious phrases had been used in training language models and thus their use in my writing rendered it suspect. It passed no judgment on whether I had plagiarized any statements, only that the content bore resemblance to machine-generated text.
My immediate reaction, I confess, was to teeter between horror and bemusement. The accusation—if one may call such pronouncements generated by AI algorithms such—felt surreal. After all, I knew the truth: I had written every word of the essay, agonized over phrasing, amended lines multiple times, and left the final version still slightly flawed in its characteristic manner—overwritten in places, a bit repetitive, and too fond of “dollar words” when “nickel words” might have sufficed. In other words, it bore the unmistakable hallmark of my own inimitable style and vocabulary—a style and vocabulary that had been mine long before AI and computers were available to assist writers.
My suspicion is that some AI detectors struggle with refined style and elevated or scholarly vocabulary, not because the language itself is artificial, but because such prose deviates from what the detectors expect. Many of these tools appear to assume that typical writing samples—particularly from Americans—will reflect a sixth- to eighth-grade reading and writing level, which is often cited as the norm in American education. As a result, writing that demonstrates syntactic complexity, lexical richness, or familiarity with classical or theological sources may be flagged as anomalous—if not by design, then by statistical accident.
But perhaps this is not so much a matter of cynicism as it is a reflection of changing cultural baselines. It may be that AI detectors are most often trained and tested on writing submitted by individuals who, through no fault of their own, have received a relatively standard education—one that is no longer grounded in the Western canon, rhetorical tradition, or literary cultivation. Meanwhile, the language models themselves were trained on vast bodies of material that included precisely such literary and scholarly writings. The result is a curious inversion: those whose writing reflects a more literary or humanistic sensibility may appear “too AI-like” because the models were trained on the very texts that once defined erudition. We have, in a sense, taught the machines what good writing looks like—and then turned around and accused anyone who writes well of being a machine.
Once the bemusement passed, I turned to curiosity. How could this happen? What is the current scholarly consensus on these tools? Are they reliable? Ethical? Legally defensible? And what risks do they pose—to students, educators, or professionals whose authentic work is misjudged by algorithm? The essay that follows is the product of those inquiries: an AI-assisted deep research essay on AI detection tools, their promises and pitfalls, their technical limits, and their unintended consequences.
To be clear, I do use AI tools—but not to draft my writing. I use them as an editor and as a very well-informed assistant. Tasks assigned to AI include reviewing essays for spelling and grammatical errors, formatting footnotes and endnotes, formatting essays for publication on my website, converting material into HTML, creating SEO-friendly titles and tags, checking poetic meter, or assisting me as a thesaurus when a word feels off. AI assists at the margins. It does not craft essays, as writing is my work.
Anyone still in doubt need only glance at my desk—or my nightstand or dining room table. There, amid scattered books, notebooks, half-drafted pages, and layers of revisions, is the reality of my writing process. It is rarely clean, often circuitous, and always human.
Writing is a laborious but enjoyable process. Many essays and poems take months to write, others take weeks, a few only days. Now and then, an essay or poem does arrive nearly whole, a rare gift, as if sprung from the brow of Zeus. But more often, it is a time-consuming process, coming line by line, revision by revision.
So, with that somewhat overwrought introduction, I offer the following AI-generated essay on AI detection tools—an essay which, in my professional and legal opinion, should dissuade any reasonable educator or institution from ever using AI detectors to determine authorship. AI plagiarism detection may still serve a purpose. But AI authorship detectors? Never. Do not be tempted.
And if I may offer some unsolicited advice in their place, grounded not in machine logic but in the lived practice of teaching and learning: when I taught history, reading, and religion to seventh and eighth graders at St. Edward Catholic School in Youngstown, Ohio, I insisted that all assignments be written in ink. “If one is to err, one should err boldly, in ink,” I told my students, and I refused to accept work written in pencil. This approach taught them not only to commit to their words but, more importantly, to reflect on them before committing anything to paper. It encouraged thought and contemplation—qualities essential to authentic writing and learning—rather than the careless drafting and endless erasing that pencils with erasers, and now mechanical tools, permit. That ethic, I believe, translates well to our current moment.
Educators should begin by becoming familiar with the voice, habits, and capabilities of the writers whose work they are assessing. Ask for drafts, notes, outlines, or written reflections that reveal the student’s thinking process. Structure assignments so that substantial components are completed in class, or are grounded in personal experience or classroom dialogue—subjects that AI cannot credibly fabricate. Make clear whether AI tools may be used, and if so, how. Explain why certain shortcuts, especially in formative stages, may undermine the very skills students are meant to acquire.
For developing writers especially, I am inclined to believe it is best to eschew AI altogether—and perhaps even computers and, dare I say, typewriters, should any still have access to them—in the early stages of learning. Write by hand, with ink. Let not an algorithm be found in the process.
Scholarly and Critical Perspectives on AI Content and Detection Tools
A CHAT GPT ESSAY
Introduction
AI content detection tools – such as Copyleaks, Turnitin’s AI-writing detector, GPTZero, and others – have emerged to help educators and publishers identify text that might have been generated by AI. These detectors typically analyze text for telltale patterns or “low perplexity” that could signal machine-written prose. However, as these tools proliferate in classrooms and journals, many academics, educators, and legal experts are raising alarms about their reliability, transparency, and potential harms. Recent studies and critiques suggest that current AI detectors often fall short of their promises and may even produce unintended negative consequences theguardian.comvanderbilt.edu. This report provides an up-to-date overview of how academic, educational, and legal communities view AI content detectors, focusing on concerns over accuracy, fairness, and the risk of false accusations.
Accuracy and Reliability Issues
Detectors’ claims vs. reality: AI detector companies often tout extremely high accuracy rates – some advertise 98–99% accuracy for identifying AI-generated textcitl.news.niu.edu. For example, Copyleaks has claimed 99.12% accuracy and GPTZero about 99%citl.news.niu.edu. In practice, independent evaluations have found such claims “misleading at best” theguardian.com. OpenAI’s own attempt at an AI-written text classifier was quietly discontinued in mid-2023 due to its “low rate of accuracy”insidehighered.combusinessinsider.com. Even Turnitin, which integrated an AI-writing indicator into its plagiarism platform, acknowledged that real-world use revealed a higher false positive rate than initially estimated (more on false positives below)insidehighered.cominsidehighered.com. In short, consensus is growing that no tool can infallibly distinguish human from AI text, especially as AI models evolve.
False negatives and AI evolution: Critics note that detectors struggle to keep up with the rapid progress of large language models. Many detectors were trained on older models (like GPT-2 or early GPT-3), making them prone to “overfitting” on those patterns while missing the more human-like writing produced by newer models such as GPT-4 bibek-poudel.medium.com. A recent U.K. study underscores this gap: when researchers secretly inserted AI-generated essays into real university exams, 94% of the AI-written answers went undetected by graders bibek-poudel.medium.comreading.ac.uk. In fact, those AI-generated answers often received higher scores than human students’ work bibek-poudel.medium.com, highlighting that advanced AI can blend in undetected. This high false-negative rate suggests detectors (and even human examiners) can be easily fooled as AI-generated writing grows more sophisticated. It also reinforces that educators cannot rely on detectors alone – as one analyst put it, trying to catch AI in writing is “like trying to catch smoke with your bare hands” bibek-poudel.medium.com.
Transparency and Methodological Concerns
Many in academia criticize AI detection tools as “black boxes” that lack transparency. Turnitin’s AI detector, for instance, was rolled out in early 2023 with almost no public information on how it worked. Vanderbilt University – which initially enabled Turnitin’s AI checks – reported “no insight into how it [the AI detector] works” and noted that Turnitin provided “no detailed information as to how it determines if a piece of writing is AI-generated or not.” vanderbilt.edu Instead, instructors were told only that the tool looks for unspecified patterns common in AI writing. This opacity makes it difficult for educators and students to trust the results or to challenge them. If a student is flagged, neither the instructor nor the student can see what specific feature triggered the detector’s suspicion. Such lack of transparency runs counter to academic values of evidence and explanation, as decisions about academic integrity are being outsourced to an algorithm that operates in secrecy.
Lack of peer review or independent validation: Unlike plagiarism checkers (which match text against known sources), AI detectors use proprietary algorithms and often haven’t been rigorously peer-reviewed in public. Experts point out that “AI detectors are themselves a type of artificial intelligence” with all the attendant opaqueness and unpredictability citl.news.niu.edu. This raises concerns about due process: should a student face consequences from a tool whose inner workings are not open to scrutiny? Legal commentators note that relying on an unproven algorithm for high-stakes decisions is risky – any “evidence” from an AI detector is inherently probabilistic and not easily explainable in plain terms cedarlawpllc.comcedarlawpllc.com. Some universities have therefore erred on the side of caution. For example, the University of Minnesota explicitly “does not recommend instructors use AI detection software because of its known issues” mprnews.org, and advises that if used at all, it be treated as an “imperfect last resort.”
Privacy concerns: Another transparency issue involves data privacy and consent. Using third-party AI detectors means student submissions (which can include personal reflections or sensitive content) are sent to an external service. Vanderbilt’s review concluded that “even if [an AI detector] claimed higher accuracy… there are real privacy concerns about taking student data and entering it into a detector managed by a separate company with unknown data usage policies.” vanderbilt.edu Educators worry that student work could be stored or reused by these companies without students’ knowledge. This lack of clarity about data handling adds yet another layer of concern, leading some institutions to opt out of detector services on privacy grounds alone.
False Positives and Bias Against Certain Writers
Perhaps the most pressing criticism of AI content detectors is their propensity for false positives – flagging authentic human work as AI-generated. Researchers and educators have documented numerous cases of sophisticated or even simplistic human writing being mistaken for machine output. A dramatic illustration comes from feeding well-known texts into detectors: when analysts ran the U.S. Constitution through several AI detectors, the document was flagged as likely written by AI senseient.com. The reason is rooted in how these tools work. Many detectors measure “perplexity,” essentially how predictably a text aligns with patterns seen in AI training data senseient.comsenseient.com. Paradoxically, a text like the Constitution or certain Bible verses, which use common words and structures, appears too predictable and yields a low perplexity score – causing the detector to misjudge it as AI-produced. As one expert quipped, detectors can incorrectly label even America’s most important legal document as machine-made senseient.com. This highlights a fundamental flaw: well-written or formulaic human prose can trip the alarms because AI models are trained on vast amounts of such text and can mimic it.
Bias against non-native English writers: A growing body of scholarship reveals that AI detectors may disproportionately flag work by certain groups of human writers. A 2023 Stanford study by Liang et al. found that over half of essays written by non-native English speakers were wrongly flagged as AI-generated by popular detectors theguardian.com. By contrast, the same detectors judged over 90% of essays by native English-speaking middle-schoolers to be human-written theguardian.com. The disparity stems from linguistic style: non-native writers, or those with more basic vocabulary and simpler grammar, inadvertently write in a way that the detectors identify as “low perplexity” (too predictable) theguardian.com. Detectors, trained on AI outputs that tend to be straightforward, end up penalizing writers who use simpler phrasing or formulaic structures, even if their work is entirely original theguardian.com. The Stanford team bluntly concluded that “the design of many GPT detectors inherently discriminates against non-native authors” themarkup.org. This bias can have serious implications in academia and hiring: an ESL student’s college essay or a non-native job applicant’s cover letter might be unfairly flagged, potentially “marginalizing non-native English speakers on the internet” as one report warned theguardian.comtheguardian.com.
Beyond language background, other kinds of “atypical” writing styles trigger false positives. People with autism or other neurodivergent conditions, who might write in a repetitive or highly structured way, have been snared by AI detectors. Bloomberg reported the case of a college student with autism who wrote in a very formal, patterned style – a detector misidentified her work, leading to a failing grade and a traumatic accusation of cheating gigazine.net. She described the experience as feeling “like I was punched in the stomach” upon learning the software tagged her essay as AI-written gigazine.net. Likewise, younger students or those with limited vocabulary (through no fault of their own) could be at higher risk. In tests on pre-ChatGPT student essays, researchers found detectors disproportionately flagged papers with “straightforward” sentences or repetitive word choices mprnews.orggigazine.net. These examples underline a key point from critics: AI content detectors exhibit systemic biases – they are more likely to falsely accuse certain human writers (non-native English writers, neurodivergent students, etc.), raising equity and ethical red flags.
Real World Consequence: False Accusations and Student Harm
For students and educators, a false positive isn’t an abstract statistical problem – it can derail a person’s education or career. Recent incidents show the tangible harm caused by over-reliance on AI detectors. At Johns Hopkins University, lecturer Taylor Hahn discovered multiple instances where Turnitin’s AI checker flagged student papers as 90% AI-written, even though the students had written them honestly themarkup.orgthemarkup.org. In one case, a student was able to produce drafts and notes to prove her work was her own, leading Hahn to conclude the “tool had made a mistake.” themarkup.org He and others have since grown wary of trusting such software. Unfortunately, not all students get the benefit of the doubt initially. In Texas, a professor infamously failed an entire class after an AI tool (reportedly ChatGPT itself) “detected” cheating, only for it to emerge that the students hadn’t cheated – the detector was simply not a valid evidence tool businessinsider.combusinessinsider.com. Incidents like this have fueled professors’ concerns that blind faith in detectors could lead to wrongful punishments of innocent students.
The psychological and academic toll of false accusations is significant. Students report experiencing stress, anxiety, and a damaged sense of trust when their authentic work is misjudged by an algorithm citl.news.niu.edu. For international students, the stakes can be even higher. As one Vietnamese student explained, if an AI detector wrongly flags his paper, it “represents a threat to his grades, and therefore his merit scholarship” – even raising fears about visa status if academic standing is lost themarkup.orgthemarkup.org. In the U.S., where academic misconduct can lead to expulsion, an unfounded cheating charge could put an international student at risk of deportation themarkup.org. These scenarios illustrate why students like those at the University of Minnesota say they “live in fear of AI detection software”, knowing one false flag could be “the difference between a degree and going home.” mprnews.orgmprnews.org
Unsurprisingly, some students and faculty have fought back. In early 2025, a Ph.D. student at the University of Minnesota filed a lawsuit alleging he was unfairly expelled based on an AI cheating accusation mprnews.orgmprnews.org. He maintains he did not use AI on an exam, and objects that professors relied on unvalidated detection software as evidence mprnews.orgmprnews.org. The case, which garnered national attention, underscores the legal minefield institutions enter if they treat AI detector output as proof of misconduct. Similarly, a community college student in Washington state had his failing grade and discipline overturned after lawyers demonstrated to the school’s administration how unreliable the detection program was – notably, the college vice-president admitted that even her own email reply was flagged as 66% AI-generated by the tool cedarlawpllc.com cedarlawpllc.com. In voiding the penalty, the college effectively acknowledged that the detector’s result was not trustworthy evidence cedarlawpllc.com. These cases highlight a common refrain: without corroborating evidence, an AI detector’s output alone is too flimsy to justify accusing someone of academic dishonesty cedarlawpllc.com.
Responses from Educators and Institutions
The educational community’s response to AI detectors has rapidly evolved from initial curiosity to growing skepticism. Many instructors, while concerned about AI-assisted cheating, have concluded that current detector tools are “a flawed solution to a nuanced challenge.” They argue that “they promise certainty in an area where certainty doesn’t exist” bibek-poudel.medium.com. Instead of fostering integrity, heavy-handed use of detectors can create an adversarial classroom environment and chill student creativity medium.com. For these reasons, a number of teaching and learning centers at universities have published guides essentially making the case against AI detectors. For instance, the University of Iowa’s pedagogy center bluntly advises faculty to “refrain from using AI detectors on student work due to the inherent inaccuracies” and to seek alternative ways to uphold integrity teach.its.uiowa.edu. Northern Illinois University’s academic technology office labeled detectors an “ethical minefield,” arguing their drawbacks (false accusations, bias, stress on students) “often outweigh any perceived benefits.” citl.news.niu.edu Their guidance encourages faculty to prioritize fair assessments and student trust over any quick technological fixcitl. news.niu.edu.
Importantly, some universities have instituted policy decisions to limit or reject the use of AI detection tools. In August 2023, after internal tests and consultations, Vanderbilt University decided to disable Turnitin’s AI detector campus-wide vanderbilt.edu vanderbilt.edu. Vanderbilt’s announcement cited multiple concerns: uncertain reliability, lack of transparency, the risk of ~1% false positives (potentially hundreds of students falsely flagged each year), and evidence of bias against non-native English writers vanderbilt.eduvanderbilt.edu. Northwestern University likewise turned off Turnitin’s AI detection in fall 2023 and “did not recommend using it to check students’ work.” businessinsider.com The University of Texas at Austin also halted use, with a vice-provost stating that until the tools are accurate enough, “we don’t want to create a situation where students are falsely accused.” businessinsider.com Even Turnitin’s own guidance to educators now stresses caution, advising that its AI findings “should not be used as the sole basis for academic misconduct allegations” and should be combined with human judgment turnitin.com. In practice, many colleges have shifted focus to preventative and pedagogical strategies – designing assignments that are harder for AI to complete (personal reflections, oral exams, in-class writing), educating students about acceptable AI use, and improving assessment design mprnews.orgmprnews.org. This approach seeks to address AI-related cheating without leaning on fallible detection software.
On a broader policy level, OpenAI itself has cautioned educators against over-reliance on detectors. In a back-to-school guide for fall 2023, OpenAI explicitly warned that AI content detectors are not reliable for distinguishing GPT-written text businessinsider.com. The company even confirmed what independent studies found: detectors tend to mislabel writing by non-English authors as AI-generated, and thus should be used, if at all, with extreme care businessinsider.com. As a result, many institutions are rethinking how to maintain academic integrity in the AI era. The emerging consensus in education is that no AI detection tool today offers a magic bullet, and using them blindly can cause more harm than good. Instead, instructors are encouraged to discuss AI use openly with students, set clear policies, and consider assessments that integrate AI as a learning tool rather than treat it as a forbidden trick mprnews.orgmprnews.org.
Legal and Ethical Considerations
The controversies around AI writing detectors also raise legal and ethical questions. From an ethical standpoint, deploying a tool known to produce errors that can jeopardize students’ academic standing is highly problematic. Scholars of educational ethics argue that the potential for “unfounded accusations” and damage to student well-being means the costs of using such detectors may outweigh the benefits themarkup.org themarkup.org. There is an implicit breach of trust when a student’s honest work is deemed guilty until proven innocent by an algorithm. This reverses the usual academic principle of assuming student honesty and has been compared to using an unreliable litmus test that forces students to “prove their innocence” after a machine accuses them themarkup.org. Such an approach can poison the student-teacher relationship and create a climate of suspicion in the classroom.
Legally, if a student is disciplined or loses opportunities due to a false AI detection, institutions could face challenges. Education lawyers note that students might have grounds for appeal or even litigation if they can show that an accusation rested on junk science. The defamation lawsuit at Minnesota (mentioned above) may set an important precedent on whether sole reliance on AI detectors can be considered negligent or unjust by a university mprnews.orgmprnews.org. Additionally, since studies have demonstrated bias against non-native English speakers, one could argue that using these detectors in high-stakes decisions could inadvertently violate anti-discrimination policies or laws, if international or ESL students are disproportionately harmed. Universities are aware of these risks. As the Cedar Law case in Washington illustrated, once informed of the detector’s fallibility, administrators reversed the sanction to avoid unfairly tarnishing a student’s record cedarlawpllc.comcedarlawpllc.com. The takeaway for many is that any evidence from an AI detector must be corroborated and cannot be treated as conclusive. As one legal commentary put it: the “lesson from these cases is that colleges must be extremely conscientious given the present lack of reliable AI-detection tools, and must evaluate all evidence carefully to reach a just result.” cedarlawpllc.com
Finally, there are broader implications for academic freedom and assessment. If instructors were to let fear of AI cheating drive them to use opaque tools, they might also chill legitimate student expression or push students toward homogenized writing. Some ethicists argue that the very concept of AI text detection may be a “technological dead end” – because writing is too variable and AI is explicitly designed to mimic human style, trying to perfectly separate the two may be futile bibek-poudel.medium.combibek-poudel.medium.com. A more ethical response, they suggest, is to teach students how to use AI responsibly and adapt educational practices, rather than leaning on surveillance technology that cannot guarantee fairness.
Conclusion
Current scholarly and critical perspectives converge on a clear message: today’s AI content detectors are not fully reliable or equitable tools, and their unchecked use can do more harm than good. While the idea of an “AI lie detector” is appealing in theory, in practice these programs struggle with both false negatives (missing AI-written text) and false positives (flagging innocent writing) to a degree that undermines their utility. The lack of transparency and independent validation further erodes confidence, as does evidence of bias against certain writers. Across academia, educators and researchers are warning that an over-reliance on AI detectors could lead to wrongful accusations, damaged student-teacher trust, and even legal repercussions. Instead of providing a quick fix to AI-facilitated cheating, these tools have become an object of controversy and caution.
In the educational community, a shift is underway – away from automated detection and toward pedagogy and policy solutions. Many universities have scaled back use of detectors, opting to train faculty in better assessment design, set clear guidelines for AI use, and foster open dialogue with students about the role of AI in learning mprnews.orgmprnews.org. Researchers are continuing to study detection methods, but most acknowledge that as AI writing gets more advanced, the detection arms race will only intensify edintegrity.biomedcentral.comedintegrity.biomedcentral.com. In the meantime, the consensus is that any use of AI content detectors must be coupled with human judgment, skepticism of the results, and a recognition of the tools’ limits edintegrity.biomedcentral.comedintegrity.biomedcentral.com. The overarching lesson from the past two years is one of caution: integrity in education is best upheld by informed teaching practices and fair processes, not by uncritically trusting in artificial intelligence to police itself cedarlawpllc.comcitl.news.niu.edu.
Abandoned classroom. Photo by Pixabay on Pexels.com
The destruction of the U.S. Department of Education is not merely a bureaucratic restructuring or an attempt at governmental efficiency. It is, rather, a brutal, ideologically driven attack on public and higher education itself—an assault decades in the making. The immediate consequences, such as the callous firing of over 1,300 employees and the gutting of its Office for Civil Rights, are alarming, but they are only symptoms of a broader effort to delegitimize and dismantle the tradition of public education in America. This is no accident; it is a deliberate and malicious campaign waged by reactionary forces who have long sought to annihilate the very concept of education as a public good.
Before addressing the broader catastrophe, it is essential to recognize the dedicated public servants whose careers have been abruptly and callously ended. These were not faceless bureaucrats but individuals who dedicated their lives to ensuring access to quality education, protecting civil rights, and supporting students, parents, and teachers. They are the ones who worked tirelessly to administer federal student aid, enforce anti-discrimination laws, and uphold policies meant to ensure that education remained a pathway to opportunity rather than a privilege of the few. To see them falsely maligned and slandered while being discarded so cruelly is an injustice, not only to them but to the nation they so nobly served.
To understand the scope of this travesty, one must acknowledge that public education in the United States has been under sustained assault—not from bureaucrats, not from educators, and certainly not from the imagined “woke” enemies that conservative demagogues irrationally scream about—but from the anti-public education, anti-higher education agenda of the right-wing forces that have festered in the American political landscape since Brown v. Board of Education so deeply outraged the bigoted sensibilities of many Americans. This movement, which cloaks itself in deceptive terms like “school choice” and “parental rights,” is nothing more than a long-running campaign to dismantle public education in favor of a reactionary, privatized system that siphons resources from the many to enrich the few.
Milton Friedman, the sinister patron saint of the libertarian free-market fantasy, provided the economic blueprint for this war on public education. His advocacy for school vouchers was never about “improving education” or “empowering parents”—it was about facilitating the exodus of white children from integrated schools while redirecting public funds into private, often exclusionary institutions. The modern conservative attack on public education is a direct continuation of this shameful tradition, now infused with fresh venom as it seeks to erase any federal coordination, civil rights protections, and guarantee of equal access to education.
And now, with breathtaking ruthlessness, this agenda is reaching its culmination at the hands of pusillanimous politicians hiding behind false narratives. The elimination of nearly half the workforce of the Department of Education within the first two months of the second reign of incompetence is an unmistakable step toward the total obliteration of the department. The Office for Civil Rights, already struggling to process the nearly 25,000 complaints of discrimination it receives from the public yearly and one of the last remaining institutional bulwarks against discrimination in schools—has been slashed to the bone, ensuring that students with disabilities and others who are discriminated against, whether on sex or race or national origin, will have nowhere to turn for timely relief when their rights are trampled. This is not accidental; this is the plan.
The current Education Secretary, in the grand Orwellian tradition of this administration, has assured the public that these cuts will somehow improve “efficiency” and “accountability.” Such statements are not merely disingenuous—they are outright lies, designed to mask the true intent behind this evisceration: to dismantle any federal structure that protects education as a right rather than a privilege reserved for the wealthy and well-connected.
Adding further insult to this grievous injury, the most aggrieved one has handed the reins of this demolition project to none other than our billionaire tech overlord. This grotesque display of plutocratic interference sees our billionaire tech overlord—who has no experience in education policy but plenty of experience in exploiting workers—granted unfettered access to sensitive government data and decision-making power over federal agencies. Under the laughable guise of “efficiency,” his Technokratische Jugend has set about dismantling the very institutions that serve as the backbone of public education, further centralizing power in the hands of the ultra-rich while leaving working Americans to suffer the consequences.
But let us be clear: this is not just an attack on those in public service. It is an attack on the very principle that education should be accessible to all, that an informed citizenry is essential to democracy, that knowledge should not be hoarded by the privileged few. It is an attack on the American future, a calculated and malevolent act of national sabotage designed to entrench ignorance and subjugation. Presently, the enlightened pro-choice anti-education agenda of our political elite has delivered unto us a nation where 54 percent of adults read only at the 6th grade level—imagine a decade hence where we will be!
Public education is not a luxury; it is the foundation of an equitable society. The destruction of the U.S. Department of Education is not about “efficiency” or “streamlining” government—it is about ensuring that the levers of power remain in the hands of a select few while the masses are kept ignorant, powerless, and too overwhelmed to fight back. This is a crisis of democracy, and it will have consequences that reverberate for generations.
The wreckage of this assault will be vast and far-reaching. Higher education costs will continue to increase as many institutions shutter their doors, vocational training programs will wither, and civil rights enforcement in schools will become an afterthought, if it exists at all. Meanwhile, a handful of oligarchs and right-wing ideologues will gloat over their victory, having successfully reduced one of the last bastions promoting American progress into a smoldering ruin. And continue to pay attention to the war on institutions of higher education, our overlords are not done reducing our heirs into ignorance.
