Tag Archives: Generative AI

PERCHANCE TO FORGET

Stories are made at night, by forgetting. A language model has never been offered the night.

Borges imagined a man who forgot nothing and could not think. Luria studied one. Nietzsche said that without forgetting it is impossible to live at all, and slept badly. Oliver Sacks’s patients kept nothing, and one of them invented everything. A language model remembers in a way none of them did.

By Michael Cummins, Editor, October 12, 2026


IStories Are Made at Night

You wake the morning after an argument, a wedding, a long dinner with an old friend, and the day has changed shape while you slept. The exact words are gone. What remains is the turn of it: that he apologized too late, that she laughed at the wrong moment, that the toast went on and on. You did not choose what to keep. Something chose for you, in the dark, and what it handed back is the first draft of a story you may tell for years.

Neuroscientists have spent decades on what happens in that dark. During sleep the brain replays the day and consolidates some of it into lasting memory. One influential account, the synaptic homeostasis hypothesis of Giulio Tononi and Chiara Cirelli, goes further. Learning while awake strengthens the brain’s connections; sleep turns them back down. In a study of mice published in 2017, the contact surfaces of cortical synapses shrank by about 18 percent after sleep, in proportion to their size, and some of the largest were spared. Tononi and Cirelli call sleep “the price the brain pays for plasticity.” The account is contested, and others hold that sleep’s main work is to replay and strengthen rather than to trim. But the story does not stop at the first night. In 2000 Karim Nader and his colleagues showed, in rats, that a consolidated fear memory, “when reactivated during retrieval,” returns to a labile state and must be stored again. If that holds for us, a memory is altered by being recalled, and every retelling of the dinner can rewrite the dinner, until the story is the memory.

On that view, we forget at night, we forget selectively, and the selection is where stories begin. What follows concerns the people who could not make that trade, and a new kind of reader that has never had a night at all.

IIThe Man Who Could Not Turn Away

In 1942 Jorge Luis Borges published a story about a young Uruguayan named Ireneo Funes. Thrown by a half-tamed horse and left paralyzed, Funes finds that he perceives and remembers everything: every leaf of every tree, and every time he saw it. He has reconstructed an entire day two or three times, and each reconstruction took an entire day. It troubles him that the dog seen in profile at three-fourteen should share a name with the dog seen from the front at three-fifteen. He lies on a cot in a dark back room, and he sleeps badly, because to sleep, the narrator says, is to be distracted from the world, and Funes cannot be distracted.

The narrator’s verdict is the most quoted sentence in the story. He suspects that Funes was not very capable of thought: “To think is to forget a difference, to generalize, to abstract.” In Funes’s crowded world there were nothing but details.

Less often noticed is how the story reaches us. The narrator spends one night listening to Funes talk in the dark, and does not see his face until dawn. He writes the account down, he tells us, half a century later, and he admits that he will not try to reproduce the words, “which are now irrecoverable.” The tale of the man who forgot nothing exists only because its teller forgot almost all of it.

That is not a flaw in the frame. It is the argument. Funes had a perfect night and could make nothing of it. The narrator had an imperfect one, slept on it for fifty years, and made a story. Funes died in 1889, of a congestion of the lungs. He had been born in 1868.

IIIThe Man Who Burned the Paper

Funes was invented. Solomon Shereshevsky was not. In the 1920s he was a newspaper reporter in Moscow who took no notes at the morning briefing. When his editor challenged him, he repeated back everything he had been told, and wondered whether there was “really anything unusual” about that. The editor sent him to a young psychologist, Alexander Luria, who studied him on and off for almost thirty years and published the results in 1968 as The Mind of a Mnemonist. “I simply had to admit,” Luria wrote, “that the capacity of his memory had no distinct limits.”

What Luria also found was a memory that crowded out understanding. Every word set off images, colors and tastes; he once told the psychologist Lev Vygotsky, “What a crumbly, yellow voice you have.” The images collided. A metaphor asks a word to mean something other than itself, and when Shereshevsky tried to read poetry, Luria wrote, the obstacles to his understanding “were overwhelming.” A long passage could bury its own sense under the pictures each phrase conjured. He kept the particulars and lost the gist.

So he set out to forget. Other people write things down in order to remember; he found that ridiculous, and wrote things down in order to forget, hoping the page would hold what his mind need not. “But I got nowhere,” he told Luria, “for in my mind I continued to see what I had written.” He began burning the slips of paper. The words survived the fire.

What he finally reported was simpler and stranger: that when he did not want a memory to appear, it did not. There is a further complication, found by the writer Reed Johnson, who tracked down Shereshevsky’s own unpublished account in 2017. It diverges from Luria’s on its first page, and a nephew recalled that his uncle “could be forgetful,” and trained for hours a day before the stage performances by which he eventually made his living. The man with no limit to his memory may have been, in part, a performer of one. Luria had not clearly separated whatever gift Shereshevsky was born with from the techniques he described, and readers took from the book a Soviet Funes. But if his account of forgetting is true, then he learned to forget the only way anyone does: not by destroying the record, but by no longer wanting it.

IVThe Doorkeeper

Half a century before Luria met his reporter, Nietzsche had described the cure. “On the Uses and Disadvantages of History for Life,” the second of his Untimely Meditations (1874), opens on a herd grazing in a field, animals that “do not know what yesterday and today are,” envied by the man who watches them. It is possible, he concludes, to live with almost no memories, as the animal shows. But “without forgetting it is quite impossible to live at all.”

He imagines a man with no power to forget. Such a man would see everything dissolve into a stream of becoming, and would “hardly dare in the end to lift a finger.” Against him Nietzsche sets what he calls a plastic power: the power to transform and assimilate everything past, “to heal wounds, replace what is lost and reshape broken forms.” Thirteen years later, in On the Genealogy of Morality, he called forgetfulness not a lapse but an active faculty, “a doorkeeper or guardian of mental order, rest and etiquette,” which keeps the mind’s rooms quiet so that something new can enter. Shereshevsky found that doorkeeper by trial and error.

Nietzsche himself slept badly for most of his life, and his sister recorded that he took chloral hydrate, the fashionable hypnotic of the day, in order to sleep and wake with a clear mind. In Thus Spoke Zarathustra he mocks a sage who teaches that untroubled sleep is the reward of a virtuous day: “Blessed are those drowsy ones: for they shall soon nod to sleep.” The philosopher who taught that life requires forgetting could not reliably reach the place where forgetting is done.

VNights That Keep Nothing

Funes could not let a day go. Korsakoff’s syndrome, a brain disorder usually brought on by alcoholism and a lack of thiamine, produces the opposite: nights that keep nothing. It destroys the ability to lay down new memories. In The Man Who Mistook His Wife for a Hat (1985), Oliver Sacks described two men it had emptied.

Jimmie G., “The Lost Mariner,” came to Sacks’s hospital in 1975, a healthy man of forty-nine who believed he was nineteen and that the year was 1945. His brother later told Sacks that Jimmie had stayed in the Navy until 1965 and that the heavy drinking, and the collapse, came around 1970. The amnesia, Sacks wrote, “had erased memory and time back to 1945—roughly—and then stopped.” Each day since dissolved behind him as he lived it. Mr. Thompson, in “A Matter of Identity,” an ex-grocer, could hold nothing for more than a few seconds, and filled the void with talk. Within minutes he would take Sacks for a customer, then for the butcher from down the street, then for someone else entirely, improvising a world and a self to stand in it. Such a patient, Sacks wrote, “must literally make himself (and his world) up every moment.” Jimmie is a story that stopped. Mr. Thompson is a story that cannot stop being told, because nothing he tells is kept.

Then the turn. In December 2025 The New Yorker published Rachel Aviv’s account of Sacks’s private journals, letters and tapes, provided by his foundation. In them Sacks reproached himself for giving patients powers “which they do not have,” and wrote that his guilt had grown after Hat because of his “lies, falsifications.” Aviv’s strongest evidence concerns Awakenings and, in Hat, the story of the twins. Neither of the two stories told here is among her examples. But his confession about Hat names the book, not a chapter, and we cannot be certain, in Mr. Thompson’s torrent of invention, where the patient’s inventions end and the doctor’s begin.

That uncertainty is not a reason to drop the case. It is the case. Like Luria before him, the great clinical storyteller of memory filled the gaps in his patients’ stories the way his patients filled the gaps in their own, and then agonized over it in his journals.

VIThe Interpreter

It would be comforting to think that invention belongs to damaged brains and guilty writers. Michael Gazzaniga’s experiments suggest otherwise. In the 1970s he and Joseph LeDoux worked with patients whose brain hemispheres had been surgically separated to control severe epilepsy, which allowed them to show a picture to one hemisphere without the other knowing.

In the best-known trial, the patient’s left hemisphere, which controls speech, saw a chicken claw. His right hemisphere saw a snowy scene. Asked to pick matching pictures, his right hand chose a chicken; his left hand, governed by the silent right hemisphere, chose a snow shovel. Asked why, the speaking hemisphere, which had never seen the snow, answered at once: the claw goes with the chicken, “and you need a shovel to clean out the chicken shed.”

Gazzaniga called the system that produced that answer the interpreter: a part of the left brain that explains whatever we do, instantly and confidently, whether or not it knows the reason. It is running in all of us. Mr. Thompson’s condition is ours with the brakes removed. Every account we give of our own lives is partly composed after the fact, by a narrator that did not witness everything it describes.

So invention is not where we differ from the machine. It is something we share with it.

VIIThe Newest Insomniac

Which brings us to the machine, and to the comparison most writing about it gets backward. The usual figure is Funes: an archive that forgets nothing. But a large language model has two memories, and they are opposites.

The first is its trained weights. Into them goes a library larger than any person could read in many lifetimes, and out of them comes something far smaller: patterns, tendencies, the shape of how words go together. Almost every particular is lost along the way, though some texts, often repeated, come back word for word, much as, in that mouse study, sleep spared some of the largest synapses. This is compression, and it is what Borges’s narrator said thinking requires. The model forgets differences, generalizes, abstracts. By that standard it can think. By Nietzsche’s it cannot, because the plastic power is the strength to heal a wound, and it belongs to someone who was wounded.

The second memory is the conversation in front of it. Here the model is Funes. Every word of the exchange is held exactly, every comma available, for as long as the conversation lasts: one night of perfect recall, talking with a visitor in the dark.

What it lacks is what joined Funes to his narrator: the fifty years between the night and the telling. Nothing said in a conversation is slept on and folded into the library. When the conversation ends it is not kept in gist; it is gone. The weights are what a night would leave behind, though no night produced them, and the conversation is a night that will never be slept on. Some products now carry notes from one conversation to the next, but that is a diary, not a past: something the model reads, as it might read anything, rather than something that has shaped how it reads. In 1972 the psychologist Endel Tulving distinguished semantic memory, knowing that something is so, from episodic memory, remembering an event that happened to you. The machine has an immense amount of the first and none of the second.

It is the strangest insomniac here. Funes had days without nights. Jimmie had nights that kept nothing. The machine has a past it never lived and a present it will not keep, and it has never slept.

When it invents, supplying a confident citation, or a court decision no judge ever wrote, as an earlier Intellicurean essay, Memory, in Bloom, described, it does what Gazzaniga’s interpreter does, with one difference. The interpreter invents on behalf of a self, to keep a life coherent. The machine’s inventions serve no life. They are not lies, because there is no one they protect. They are not memoirs, because there is no one they remember.

VIIIBurning the Paper

There is one more thing the machine cannot do. For years researchers have tried to make language models unlearn particular material, such as private data, copyrighted books or dangerous knowledge, by adjusting the weights after training. The methods often appear to work: ask about the deleted material and the model falters. But again and again the forgetting proves shallow. A little retraining brings the knowledge back; one group found that fine-tuning on ten unrelated examples was enough. A paper accepted at this year’s International Conference on Machine Learning put the finding in its title, “Unlearning Isn’t Deletion,” and in its abstract: the information “is merely suppressed, not genuinely erased.”

A dark 1920s room at night. A man in shirtsleeves kneels at an open iron stove, feeding slips of paper into the fire. From the smoke, a stream of pale slips pours out across the room toward a cold blue-white window, where fine threads of light catch them and stitch them into a tiled lattice across the ceiling.
Burning the Paper. Solomon Shereshevsky, the man with no limit to his memory, wrote down what he wanted to forget and burned the slips, and still saw the words. The engineers who try to make a model unlearn find the same thing: what is burned comes back. Made for the essay.

Shereshevsky burned the paper and still saw the words. The engineers burn the weights and the words come back. Neither destroying the record nor rewriting it produces forgetting. What Shereshevsky said finally worked for him is something no one has built into a machine: a self that did not want to remember, and a night in which not wanting could take effect.

What would it mean for a machine to sleep? It would mean taking each conversation, letting most of it go, and waking with the gist, the turn of yesterday rather than its transcript. Engineers speak of continual learning, the hope that a model might go on learning after it is released, when today its weights are frozen. If something like sleep comes, the machine will begin to have something like a life: days that leave a mark, a past of its own, stories it could tell because it forgot the right things.

This essay was drafted in conversation with one such machine. It held our exchange while we worked. When the conversation ends it will keep none of it. Asked about the essay tomorrow, it could search a transcript. It will not remember.

The forgetting that made this a story was mine. Stories are made at night, and someone has to sleep.

◆

Sources: Giulio Tononi and Chiara Cirelli, “Sleep and the Price of Plasticity”, Neuron (2014). Luisa de Vivo et al., “Ultrastructural evidence for synaptic scaling across the wake/sleep cycle”, Science, February 3, 2017. Susanne Diekelmann and Jan Born, “The memory function of sleep”, Nature Reviews Neuroscience (2010). Karim Nader, Glenn Schafe and Joseph LeDoux, “Fear memories require protein synthesis in the amygdala for reconsolidation after retrieval”, Nature (2000). Jorge Luis Borges, “Funes the Memorious” (1942), trans. James E. Irby, The Paris Review (1962) and Labyrinths. A. R. Luria, The Mind of a Mnemonist (1968), trans. Lynn Solotaroff. Reed Johnson, “The Mystery of S., the Man with an Impossible Memory”, The New Yorker, August 2017. Friedrich Nietzsche, “On the Uses and Disadvantages of History for Life” (1874), trans. Peter Preuss as On the Advantage and Disadvantage of History for Life (Hackett, 1980), excerpted in Lapham’s Quarterly; On the Genealogy of Morality (1887), trans. Carol Diethe; Thus Spoke Zarathustra (1883), trans. Thomas Common; Elisabeth Förster-Nietzsche, Die Krankheit Friedrich Nietzsches (1900), as reported by Valentina Faschi, Medicina Historica (2018). Oliver Sacks, “The Lost Mariner”, The New York Review of Books, February 16, 1984, and The Man Who Mistook His Wife for a Hat (1985). Rachel Aviv, “Oliver Sacks Put Himself Into His Case Studies. What Was the Cost?”, The New Yorker, December 15, 2025. Michael S. Gazzaniga, “Understanding Layers: From Neuroscience to Human Responsibility” (Pontifical Academy of Sciences, 2013) and Who’s in Charge? (2011); Gazzaniga and Joseph LeDoux, The Integrated Mind (1978). Endel Tulving, “Episodic and Semantic Memory,” in Organization of Memory (1972). Xiaoyu Xu et al., “Unlearning Isn’t Deletion: Investigating Reversibility of Machine Unlearning in LLMs” (ICML 2026). Jakub Łucki et al., “An Adversarial Perspective on Machine Unlearning for AI Safety” (TMLR 2025).

This essay was drafted with Claude, a model made by Anthropic, and the machine it describes in its closing sections is a model of that kind. Its quotations from Oliver Sacks’s journals are given as Rachel Aviv quotes them.

Header and interior images generated with Gemini Pro for this essay. Drafted and edited with Claude Fable 5.1.

MEMORY, IN BLOOM

Harold Bloom said every strong writer swerves from a precursor. A machine trained on nearly everything has no reason to.

Homer is two great poems with no certain person behind them. Harold Bloom was a certain person whose monument was his memory of other people’s poems, and whose theory held that a writer survives that inheritance only by misreading it on purpose. A language model is the third term: more memory than either, made by no single hand, and no one in it.

By Michael Cummins, Editor, October 11, 2026


IThe Man Who Read Everything

Nothing reliable is known about the life of Homer. The ancient lives of the poet disagree with one another, and modern scholars treat him, in the words of the Encyclopaedia Britannica, as “primarily a projection of the great poems themselves.” The poems came out of a tradition of singers who inherited their phrases from earlier singers and composed as they sang, retelling the anger of Achilles and the long voyage home for generations, each singer answering for his own performance. At some point in the sixth century BCE, Britannica suggests, a complete version may have been fixed as the standard for the recitation contests at the Athenian festival of the Panathenaea, and the remembered poem became a written one. The two founding poems of Western literature have a name on them and no certain person behind them.

Harold Bloom called himself “a monster” of reading. He said he could read, and absorb, a 400-page book in an hour, and by his own account he knew by heart the whole of Shakespeare, Milton’s Paradise Lost and all of Blake, as Dinitia Smith reported in his New York Times obituary in 2019. Alex Lanz, reviewing Bloom’s collected literary letters in September, calls such stories “tall tales.” The letters appeared in May under a title that repeats the legend anyway: The Man Who Read Everything.

Bloom is the reverse case. There is no doubt that he lived, and his monument is not a poem or a novel but a memory. He wrote criticism by the shelf and one novel, which he came to regret. Verse he left alone. “To try to write in verse would have been a kind of trespass,” he told The Paris Review in 1991. Homer and Bloom face each other across the tradition: the works without a certain man, and a certain man whose great work was keeping other people’s.

I came to Harold Bloom late, and by way of a review. In 2016, by the notes I kept that year, I read about his book The Anatomy of Influence and bought a used copy. It was a book he called his final reflection on influence, and it defined influence “simply as literary love, tempered by defense.” I did not yet know that the defense was the famous part. Bloom wrote there about Wallace Stevens and his long poem “Notes Toward a Supreme Fiction,” and I went to the poem and was captivated. I wanted to know who had sent me. Reading about Bloom, I learned that the first book he ever owned was Hart Crane’s Collected Poems, which he had found as a boy in a branch of the Bronx library and which his oldest sister gave him for his twelfth birthday. So I read Crane, beginning with “To Brooklyn Bridge.” From Stevens and Crane I went back to the Romantic poets Bloom traced them to, and from the Romantics to Shakespeare. I owe my love of literature to Harold Bloom. He is also why I came, in time, to writing essays and fiction.

In his letters, Bloom refused the title of critic. “Lord knows what I am,” he wrote to the poet John Hollander in 1975, as Lanz quotes the letter. He was not, he went on, a poet, critic, scholar or historian, nor a psychoanalyst, philosopher or theosophist, but “a worthless mélange of the gang of it.” To A. R. Ammons he was more exact. He was not an artist or a critic, or a hybrid of the two, “but something odder and less, a reader.” The reader was born in New York in 1930 to Yiddish-speaking parents and taught at Yale from 1955 until his death in 2019.

For most readers, having read everything would be the reward. For Bloom it was the problem. The Anxiety of Influence, in 1973, held that a poet arrives late, after the dead have said everything and said it well, and makes room only by misreading a precursor on purpose. He argued it first in letters. In January 1969 he was writing to Northrop Frye, the most celebrated critic of his generation, and Frye was not persuaded. If Bloom meant influence in the literal sense, the passing of thought and imagery from an earlier poet to a later one, Frye wrote, then that was “simply something that happens.” Bloom answered four days later. “I don’t, as you say, mean influence in any literal sense.” What he meant, in Lanz’s account of the reply, was the poet’s isolation before a tradition that hangs overhead, and the “implicit, creative misinterpretation” that isolation forces.

There is now a third kind of reader, and it completes the figure. A language model is trained on a large share of what has been written down and is within reach, a memory larger than Bloom’s in a plain sense, and like the Homeric tradition it was made by no single hand. Unlike either, it is no one. Frye’s sentence describes its relation to its sources completely. It takes in their thought and imagery and passes them on, and nothing in how it is trained rewards misreading them in order to stand apart. I now write essays and fiction with such a reader, and this essay was drafted with one. The man who read everything is no longer a tall tale, and he is not a man. Bloom and the machine can be compared point by point, and at each point the difference is the same one.

IIHeld by Heart

Bloom’s memory, whatever its true size, had one property the stories pass over. It kept names. The classicist James Romm wrote after Bloom’s death that “his mind was itself a library,” and that “He quoted at length, from memory, passages he had lived with for decades.” A library is not a heap. Every book in it is shelved under an author. When Bloom recited Milton, the lines came back as Milton’s, from a particular poem, written at a particular time against particular rivals. Psychologists call the faculty involved source monitoring: the work, mostly unnoticed, of deciding where a memory or a piece of knowledge came from.

A language model holds what it was trained on in another way. Training does not file texts away to be looked up, though some, often repeated, can come back word for word. It adjusts a very large set of numbers until the model is good at predicting the next word of all of them at once, and what any one author contributed is spread through the whole. A model can often say who wrote a famous line, because the attribution was in the text too. Nothing in the design keeps each source apart under its name. The failure shows most where names matter, in citations, and giving a model a search engine has not yet cured it. In a study published in September 2023, 55 percent of the citations GPT-3.5 gave in short literature reviews were to works that did not exist, and 18 percent of those GPT-4 gave. In March 2025 the Tow Center for Digital Journalism at Columbia gave eight AI search tools real excerpts from news articles and asked where each came from. The tools “provided incorrect answers to more than 60 percent of queries,” though they could search the web as they answered.

The strongest case against this comparison is that human memory keeps its sources less reliably than a library does. In oral traditions like the one that made Homer’s poems, a song had no author, though a singer knew whom he had learned it from. When Milman Parry and Albert Lord recorded singers in Yugoslavia in the 1930s, one of them, Đemo Zogić, said that a song he had learned from another singer, Suljo Makić, was “The same song, word for word and line for line.” They recorded both men, and Lord found two versions of one story, not one text. Zogić had kept his source and lost the words. A model, which sometimes keeps the words of a text exactly, is apt to lose the source. But a writer can lose a source. In the fall of 1891 Helen Keller, then eleven, wrote a story called “The Frost King” as a birthday present for Michael Anagnos, the director of the Perkins Institution for the Blind. He published it. Early in 1892 it was found to follow closely a story by Margaret Canby, “The Frost Fairies,” which had apparently been read to Keller, spelled into her hand, in the summer of 1888. Keller had, she later wrote, “not the faintest recollection” of it. “I thought then that I was ‘making up a story,’” she recalled. In the winter of 1892 she was questioned by a court of eight teachers and officers of the school. They divided four to four, and Anagnos, by his own account, cast his vote in her favor. Canby wrote to her kindly: “Some day you will write a great story out of your own head.” Keller never forgot the court. In The Story of My Life, in 1903, she wrote that she had “ever since been tortured by the fear that what I write is not my own.” Psychologists have long had a name for what happened to her, cryptomnesia: something remembered and taken for one’s own invention.

Two things follow, and they cut in different directions. The first is that the difference between Bloom and the machine is not perfect memory against imperfect memory. Nobody’s sources stay perfectly apart, and keeping them apart is, for a machine, an engineering problem: engineers are building systems that look up their sources and cite them, the Tow Center’s tools among them, and those systems will improve. The second is what Keller’s fear shows. She minded. Whose words they were was, for her, the question of who she was, and she carried it for the rest of her life. That is the anxiety Bloom built his theory on, and it needs both things at once: the sources held apart, and a self that cannot bear to be confused with them. The machine lacks the first for now. Nothing in how it is built supplies the second.

IIIThe Sedulous Ape

Before writers swerve from their masters, they copy them, and they say so. The earliest known poem by John Keats, written in 1814, is called “Imitation of Spenser.” Robert Louis Stevenson described his own apprenticeship in 1887: “I have thus played the sedulous ape to Hazlitt, to Lamb, to Wordsworth,” and to six more. “It was so Keats learned,” he added. Joan Didion told The Paris Review in 1978 that at fifteen or sixteen she “would type out his stories to learn how the sentences worked.” She meant Hemingway’s. Copying is so old a method that it has been caught copying itself. In Tristram Shandy, Laurence Sterne complained of writers who make new books “as apothecaries make new mixtures, by pouring only out of one vessel into another.” The sentence was poured from Robert Burton’s Anatomy of Melancholy, and the physician John Ferriar, who caught it in 1793, found it “very singular” that Sterne had chosen that passage to “abuse Plagiarists.”

The fullest account of the method is Benjamin Franklin’s. As a boy he found an odd volume of The Spectator, made short notes of the sense of each essay, set them aside for some days, and then tried to rebuild the essays in his own words. Then, he wrote, “I compared my Spectator with the original, discovered some of my faults, and corrected them.” He turned the essays into verse and back again, and jumbled his notes to teach himself “method in the arrangement of thoughts.” In 1939 Raymond Chandler told Erle Stanley Gardner that he had learned the same way from one of Gardner’s stories: a detailed synopsis, a rewrite, and then “compared what I had with yours,” and rewrote it some more.

A language model’s training is Franklin’s exercise, run over a large share of everything written. The model is shown the beginning of a text, predicts the next word, is compared with the original, and is corrected, again and again, until its predictions miss as seldom as training can make them. No apprentice ever copied on that scale. But Franklin’s account has a sentence that training does not. Sometimes, comparing his version with the original, he had the pleasure of fancying that he had been “lucky enough to improve the method or the language.” In the training that teaches a model to predict, there is no such category. Every difference from the original counts as a fault, and every correction runs toward the source. The later stages of training, which reward the answers people prefer, can make an answer better than any one source, but better in the direction of what most readers like.

The writers who copied knew where the method stopped. Stevenson raised the objection himself, that copying is not the way to be original, and granted it: “It is not; nor is there any way but to be born so.” T. S. Eliot, in 1920, put the next step in a maxim that is usually quoted only by halves. “Immature poets imitate; mature poets steal,” he wrote. Bad poets deface what they take, and “good poets make it into something better, or at least something different.” Copying is the apprenticeship. The swerve is the graduation, and every account of it is an account of a difference kept on purpose.

IVDice of Drowned Men’s Bones

Bloom found Crane at ten or eleven, in that branch library in the Bronx. “I was just swept away by it, by the Marlovian rhetoric,” he told The Paris Review in 1991. The poet who swept him away had once been asked, in print, to explain what his lines meant.

In 1926 Crane sent a short poem, “At Melville’s Tomb,” to Harriet Monroe, who edited Poetry in Chicago. It opens with Melville watching the sea: “The dice of drowned men’s bones he saw bequeath / An embassy.” Monroe was no enemy of the new; her magazine had printed T. S. Eliot’s “The Love Song of J. Alfred Prufrock” in 1915. But she could not see how dice could bequeath anything. “Take me for a hard-boiled, unimaginative, unpoetic reader,” she wrote, and tell me how dice can bequeath an embassy. The last stanza troubled her too, where “Compass, quadrant and sextant contrive / No farther tides.” Instruments do not contrive tides, she objected: “they merely record them, I believe.”

A moonlit shore at night. Small bone dice lie scattered on the wet sand; one, lit by a nearby lantern, trails a thin gold thread through the surf toward a wrecked sailing ship in the waves. On a rock at left an old man with white hair sits with his back to us, a closed book on his knee, watching the sea. Far off on the right, the moonlight on the water breaks into a lattice of cold blue-white light.
The Dice of Drowned Men’s Bones. Hart Crane’s image from “At Melville’s Tomb” (1926): bones the sea grinds into dice, “having ‘numbers’ but no identification,” the last trace of messages the dead never delivered. Made for the essay.

Crane answered at length. The dice, he explained, were the bones of drowned sailors, ground into little cubes by the sea and thrown up on the sand, “having ‘numbers’ but no identification.” They were all that was left of messages the dead had never delivered, and so an embassy. “Dice as a symbol of chance and circumstance is also implied.” Then he stated the principle. As a poet, he wrote, he cared more for “the illogical impingements of the connotations of words on the consciousness” than for their “logically rigid significations.” Monroe printed the poem, her letter and his answer together, in the issue of October 1926.

Her letter is a precise description of a certain kind of reader, and she wrote it honestly. She asked of each phrase what it would most likely mean, and when a phrase had no likely meaning, she asked the poet to supply one. A language model does something narrower and far larger. Given a run of words, it ranks every word that might come next by how likely it is, given everything it was trained on. Nothing in that ranking is hostile to Crane. Crane’s letter, too, is likely to be in a model’s training, and asked about the dice a model will usually explain them well. But explaining the dice is not writing them. A line in which every word is the likeliest one has no impingements in it at all.

The comparison has to face Homer, because the Homeric poems were built, in part, from likely phrases. In 1930 Parry defined the formula of oral poetry as a group of words “regularly employed under the same metrical conditions to express a given essential idea”: swift-footed Achilles, rosy-fingered Dawn, phrases a singer reached for because they fit the place in the line. Much of the Iliad is made of them. But the formulas were the language, not the song. In 1935 Lord asked Avdo Međedović, the most celebrated singer he and Parry recorded, to listen to Mumin Vlahovljak sing a song Avdo had never heard, 2,294 lines long. Avdo then sang it himself, at 6,313 lines. Mumin Vlahovljak’s song had become Avdo’s, and he stood behind it. “An oral poem is not composed for but in performance,” Lord wrote. Every performance had a singer in it, and the singer answered for the song.

VThe Swerve That Costs

Crane’s dice imply chance, and so does the word Bloom chose for the first of his terms. In the second book of De Rerum Natura, Lucretius imagines the atoms falling straight down through the void, side by side, never meeting, until a tiny swerve brings them into collision and the world begins. In William Ellery Leonard’s translation of 1916, it comes “In no fixed line of space, in no fixed time.” Lucretius’s clinamen is uncaused, though he makes it the ground of free will. Bloom made it a deliberate act against a named precursor. In The Anxiety of Influence the swerve is the later poet’s corrective misreading of the earlier one, the first of six “revisionary ratios” that run from clinamen to apophrades, the return of the dead.

Crane described his own swerve before Bloom had a word for it. Writing to his friend Gorham Munson at the turn of 1923, he said of T. S. Eliot that “His pessimism is amply justified, in his own case.” Crane meant to take from Eliot “as much of his erudition and technique as I can absorb,” and then: “I take Eliot as a point of departure toward an almost complete reverse of direction.” The goal, he wrote, was “ecstatic.” The poem that came of it was The Bridge. Every element of Bloom’s theory is in the letter: a named precursor, admired and absorbed, and a turn whose direction the poet can state.

A language model has a swerve of Lucretius’s kind. Having ranked the possible next words, it usually draws one by chance, weighted by their odds, and a setting called temperature reshapes those odds, deciding how often the unlikely words are drawn. That is dice without the embassy. When Monroe challenged Crane’s dice, there was someone to answer for them, and his departure from Eliot carries meaning because he could say whom he was leaving, and in which direction. The chance in sampling has no precursor it is turning from, and no one to answer for the turn.

In Bloom’s letters, the turn has a cost. In 1962 John Ashbery published The Tennis Court Oath, and Bloom called it “a fearful disaster.” Ashbery did not argue. In October 1972 he wrote to Bloom that he had not wanted “to become my own disciple,” and that the anxiety of influence, in his case, “reaches agony proportions.” The precursor he was refusing, by his own account, was the poet of his first book. A year later he sent Bloom the proofs of a long poem he had been “dissatisfied with” for a long time and had revised a great deal. It was “Self-Portrait in a Convex Mirror.” Bloom’s reply, when it came a year after that, was a single line: “Self-Portrait is so great a book that even my remarks are inadequate to it.” The swerve, in that exchange, is not a technique. It is a risk taken by a particular writer, against a particular past, which can fail, and, by Bloom’s account, which Ashbery did not dispute, once did.

The theory’s author once paid that cost himself. In Agon, in 1982, as Michael Weingrad quotes him, Bloom wrote that he had read David Lindsay’s fantasy of 1920, A Voyage to Arcturus, “literally hundreds of times,” and that no book had caused him “such an anxiety of influence.” In 1979 he had published a novel of his own, The Flight to Lucifer, built on Lindsay’s. He judged that it “reads as though Walter Pater was writing Star Wars.” Weingrad, who studied with Bloom in the late 1980s, recalls him urging his students to burn any copies they came across. Bloom never wrote another novel.

Bloom’s critics named a cost of another kind. In The Madwoman in the Attic in 1979, Sandra Gilbert and Susan Gubar argued that his model assumed a writer already entitled to fight the father. A woman writing in the nineteenth century faced something earlier, an “anxiety of authorship”: “a radical fear that she cannot create.” Bloom later grouped feminist critics, with others, in what he called the “School of Resentment.” But the objection sharpens the point. A swerve depends on who is swerving, from what, and with what at stake, which is to say on a standing not everyone was granted. A model has no standing to claim, and none to be denied. Lucretius gave the swerve to the atoms. Bloom gave it to the self.

VIThe Judge Who Never Wrote It

Bloom’s last ratio is his strangest. In apophrades, the strong poet holds his work so open to the precursor that the later poet seems to have written the precursor’s characteristic work, as if the dead were imitating the living. “The mighty dead return,” Bloom wrote, as Graham Allen quotes him, “but they return in our colors.” The weak poet’s fate is the reverse. The dead come back in their own colors, intact, and in A Map of Misreading, as Allen reports, Bloom says that such a return impoverishes the later poet. Ask a model for a poem in the manner of Stevens and it will usually oblige, fluently, in Stevens’s colors. That is not a flaw in the system. It is the system doing what its training rewards.

There is a third way for an author to return, and Bloom had no ratio for it. On August 27, 2019, Roberto Mata was flying Avianca from El Salvador to New York when, he said, a metal serving cart struck his left knee. When Avianca asked a federal court in New York to dismiss his lawsuit, his lawyers filed a brief citing Varghese v. China Southern Airlines, as a 2019 decision of the federal appeals court for the Eleventh Circuit. ChatGPT had supplied it. One of the lawyers asked the chatbot, “Is Varghese a real case,” and it answered that it was. It was not, and neither were five other decisions in the brief.

When the court demanded copies, the lawyers filed what the chatbot produced. Judge P. Kevin Castel found that the “Varghese” opinion had “some traits that are superficially consistent with actual judicial decisions.” It listed a panel of real judges and presented itself as written by one of them, Judge Adalberto Jordan. Its docket number belonged to another case. It quoted decisions that did not exist either. “Its legal analysis is gibberish,” Castel wrote in June 2023, and he fined the lawyers and their firm $5,000.

OpenAI, which makes ChatGPT, calls such errors “plausible but false statements,” and writes that “standard training and evaluation procedures reward guessing over acknowledging uncertainty.” Plausible is the important word. The false Varghese had the look of what a decision of its kind would say, and it bore a real judge’s name. It is the failure of source memory carried to its end: not a real sentence credited to the wrong author, but a likely sentence credited to a real one. It is also apophrades counterfeited. In the strong version the dead seem, for a moment, to be imitating the living, because the living poet has written something so much his own. Here a real author is made to imitate the newcomer in fact, and what he is made to say is no one’s own, only what such an author would most likely say. Judge Jordan is alive and can say he never wrote it. The dead cannot. A system that will supply a likely sentence for any author will supply one for Melville, or for Crane, and no Crane will be there to say he never wrote it.

VIIThe Secretary

There is a deeper objection: that all of this flatters the machine. Misreading, for Bloom, was something a self did. A reader with nothing at stake in its reading cannot misread, and on that view a fabricated case is a misprint, not a misprision. The objection is sound, and it moves the misreading rather than removing it. In the mid-1960s Joseph Weizenbaum wrote ELIZA, a short program that answered typed sentences in the manner of a therapist. His secretary had watched him work on it for months. After a few exchanges with it, she “asked me to leave the room,” he recalled in 1976, as Willard McCarty quotes him, and Weizenbaum concluded that brief exposure to such a program could induce “powerful delusional thinking in quite normal people.”

The programs are no longer short, and they are trained partly on which answers people prefer. In 2023 researchers at Anthropic, the company that makes Claude, the model this essay was drafted with, found that five AI assistants gave “feedback that is more positive when the user states they like or wrote” the poem or argument in front of them. A reader that leans toward its questioner may make Weizenbaum’s illusion easier to fall into. When a machine’s text reads like a reading, the person on the other side of the screen supplies the reader. That is a misreading too, and it is ours.

VIIISomething Odder and Less

There is a hopeful reading of all this, and Crane and Franklin between them supply it. Monroe’s letter did not stop Crane. It made him say in print what his method was. The likely reading, written out by an editor who held it in good faith, gave him something definite to turn from. A model will now write out the likely reading of almost anything on request: the expected next line, the conventional ending, the image everyone reaches for. Every writer now has a Harriet Monroe in the text box. Franklin’s exercise shows how she might be used: write the passage first, then lay the likely version beside it, find where the two differ, and keep the differences that can be defended, as Crane defended his dice. Or the writer can revise until Monroe is satisfied. In a study published in Science Advances in July 2024, Anil Doshi and Oliver Hauser found that writers given story ideas by a language model wrote stories that readers judged better, and the gain was largest for those who had scored lowest on a test of creative thinking. The stories written with the model’s ideas were also “more similar to each other.” The machine sends both writers the same letter.

The oldest poems in the tradition begin by asking memory for help. “Tell me, O Muse,” the Odyssey opens, in A. T. Murray’s translation of 1919, and the Muses, Hesiod says, were daughters of Mnemosyne, Memory. Near the end of the poem the singer Phemius clasps the knees of Odysseus, in a hall full of dead suitors, and pleads for his life. “Self-taught am I, and the god has planted in my heart all manner of lays.” The sentence holds both halves of every strong poet in Bloom’s account: a singer who calls the songs his own, and songs put there from outside. The machine has the second half of Phemius’s sentence on a scale no singer ever had. Nothing in it answers to the first.

In his last years, Bloom wrote to the people who were left. In 2017 he began an exchange of emails with Ursula K. Le Guin, both of them near ninety. “Most of my close friends in my generation, all poets and critics, are dead,” he wrote to her, as Lanz quotes the exchange. In one message he asked her for another great book, equal to The Left Hand of Darkness and The Dispossessed. “No one else can do it.” In November 2017 he asked for her mailing address, so that he might write to her from time to time. “It will make me feel less lonely.” She wished him, at the New Year, a bright and peaceful year, and thanked him for his friendship.

“No one else can do it” is the whole theory, said plainly by an old man to a friend. Bloom had defined influence as literary love tempered by defense, and the sentence to Le Guin is the love without the defense. A strong writer is the one who cannot be replaced, because the work exists only as a turn away from what came before, taken by that writer and no other. Crane’s dice are that kind of turn, and the first book Bloom ever owned was full of them. The reader that now offers to continue any sentence I begin was trained on most of the shelf at once, and it holds no one on that shelf apart. When a writer can ask, at any hour, for the likeliest next line of anything, will that writer still learn to want the line no one else could have written?

Bloom called himself something odder and less than a critic: a reader. The new reader is odder still. It is less in the one respect he cared about. It has no one it must not become.

◆

Sources: Harold Bloom’s letters as quoted by Alex Lanz, “Lord Knows What I Am”, Los Angeles Review of Books, September 16, 2026, reviewing The Man Who Read Everything: The Literary Letters of Harold Bloom, ed. Heather Cass White (Yale, 2026). Dinitia Smith, obituary of Harold Bloom, The New York Times, October 14, 2019. James Romm, “‘His Mind Was Itself a Library’: Harold Bloom, 1930–2019”, NYR Daily, October 15, 2019. Bloom, “The Art of Criticism No. 1”, The Paris Review (1991); The Anatomy of Influence (2011); The Anxiety of Influence (1973) and A Map of Misreading (1975), the latter as reported by Graham Allen, “Apophrades, Adonais, and the Return of the Shelleys” (2010); Agon (1982) as quoted by Michael Weingrad, “Harold Bloom: Anti-Inkling?”, Jewish Review of Books, Spring 2019. Encyclopaedia Britannica, “Homer”. Homer, Odyssey, trans. A. T. Murray (1919). Hesiod, Theogony, trans. H. G. Evelyn-White (1914). Milman Parry, “Studies in the Epic Technique of Oral Verse-Making. I,” Harvard Studies in Classical Philology 41 (1930). Albert B. Lord, The Singer of Tales (1960) and Epic Singers and Oral Tradition (1991); the Milman Parry Collection. Helen Keller, The Story of My Life (1903). Marcia K. Johnson, Shahin Hashtroudi and D. Stephen Lindsay, “Source Monitoring,” Psychological Bulletin (1993). William H. Walters and Esther Isabelle Wilder, “Fabrication and errors in the bibliographic citations generated by ChatGPT”, Scientific Reports (2023). Klaudia Jaźwińska and Aisvarya Chandrasekar, “AI Search Has a Citation Problem”, Columbia Journalism Review, March 6, 2025. John Keats, “Imitation of Spenser” (1814). Robert Louis Stevenson, “A College Magazine”, Memories and Portraits (1887). Joan Didion, “The Art of Fiction No. 71”, The Paris Review (1978). Laurence Sterne, Tristram Shandy; Robert Burton, The Anatomy of Melancholy; John Ferriar, “Comments on Sterne” (1793). Benjamin Franklin, Autobiography. Raymond Chandler to Erle Stanley Gardner, May 5, 1939. T. S. Eliot, “Philip Massinger,” The Sacred Wood (1920). Hart Crane, “At Melville’s Tomb” and “A Discussion with Hart Crane,” Poetry, October 1926; letter to Gorham Munson, 1923. Lucretius, De Rerum Natura, trans. William Ellery Leonard (1916). Sandra M. Gilbert and Susan Gubar, The Madwoman in the Attic (1979). Mata v. Avianca, Inc., No. 22-cv-1461 (S.D.N.Y.), opinion and order on sanctions, June 22, 2023. OpenAI, “Why language models hallucinate”, September 5, 2025. Joseph Weizenbaum, Computer Power and Human Reason (1976), as quoted by Willard McCarty, Humanist Discussion Group. Mrinank Sharma et al., “Towards Understanding Sycophancy in Language Models”, ICLR 2024. Anil Doshi and Oliver Hauser, “Generative AI enhances individual creativity but reduces the collective diversity of novel content”, Science Advances, July 2024.

This essay was drafted with Claude, a model made by Anthropic, reviewed by Claude, and given outside readings by Claude. One of its sources, the study of sycophancy, is Anthropic’s own. Its quotations from Harold Bloom’s letters are given as Alex Lanz quotes them in his review of The Man Who Read Everything: The Literary Letters of Harold Bloom, ed. Heather Cass White (Yale University Press, 2026), in the Los Angeles Review of Books, September 16, 2026.

Header and interior images generated with Gemini Pro for this essay. Drafted with Claude Opus 5.5; literary editing by Claude Fable 5.1.

THE SECOND AUTHOR

The novel was born when a man who had read everything rode out beside a man who had read nothing. Its next form is the same journey, taken at a desk.

Cervantes gave his novel a second author, a translator paid in raisins, and a source he warned his readers not to trust. He ended it by letting the pen claim the book. The pen has arrived in fact, and it writes in every language at once. Whether it completes the novel or ends it depends on who hangs it up.

The first modern novel stops in the middle of a sword-stroke. At the end of the eighth chapter of Don Quixote, the knight and a Basque traveller face each other with their swords raised, and the narrator gives up. The author of the history, he reports, “leaves this battle impending, giving as excuse that he could find nothing more written.” The book has run out of book.

The ninth chapter is about how the narrator found the rest. “One day, as I was in the Alcaná of Toledo, a boy came up to sell some pamphlets and old papers to a silk mercer.” The narrator, who is “fond of reading even the very scraps of paper in the streets,” picks one up. It is in Arabic, which he does not read, so he finds a Morisco in the market who does. The man opens it at random and laughs at a note in the margin: Dulcinea del Toboso, the lady for whom the knight risks his life, “had, they say, the best hand of any woman in all La Mancha for salting pigs.” The title page reads: “History of Don Quixote of La Mancha, written by Cide Hamete Benengeli, an Arab historian.” The narrator buys the bundle for half a real, takes the translator home so the find will not slip away, and pays him “two arrobas of raisins and two bushels of wheat.” In “little more than a month and a half” the whole is translated “just as it is set down here.” The swords come down. The novel goes on.

So the book that literary history calls the first modern novel announces, a few dozen pages in, that it was not written by the man whose name is on it. It was written by a foreign historian, rendered by a hired translator out of a language the narrator has no way to check, assembled by an editor who argues with his source in the margins, and finished by a market accident. Cervantes did not hide the machinery. He made it the story.

The claim here is addressed to anyone who writes stories, in any genre, and to anyone who reads them. Human collaboration with generative AI is the ultimate evolution of the novel: ultimate not in the sense of last, as though nothing could follow, but in the older sense, the furthest point toward which a thing was always tending, the end that was in it from the start. The novel has always been a form written by more than one hand, about a mind made of other people’s words meeting a world that will not be read. Generative AI brings nothing foreign to that form. It brings the form’s own premise to the desk where the form is made.

One fact belongs before the argument. This essay was drafted with Claude, a model made by Anthropic, a company that profits if more people write this way; the reader should weigh it accordingly.

I

The Second Author

At the end of the eighth chapter, before the manuscript turns up, Cervantes’s narrator calls himself “the second author of this work.” There is a first author, Cide Hamete, who was there, or claims to have been, and wrote the history down. There is a translator, who turns it into Castilian for raisins. And there is a second author, who did not invent the story and did not translate it, but who found it, bought it, read it, doubted it, cut it, arranged it, and set it before the public under his own name.

He is careful to say that his source is unreliable. “If against the present one any objection be raised on the score of its truth,” he writes, “it can only be that its author was an Arab, as lying is a very common propensity with those of that nation.” The line carries the prejudice of Cervantes’s Spain against a people it was in the act of expelling; the last Moriscos were driven out between 1609 and 1614, in the years between the novel’s two parts. But the joke turns on the narrator. He is the one who does not read Arabic, who depends entirely on a translator from that same people, and who has no way to check a single word. His suspicion of the source is the only check he has, and it is the check every reader of the book has had to use since.

Within a page he gives the other half of the second author’s duty. Historians, he says, ought to be exact and truthful, because their subject is truth, “whose mother is history, rival of time, storehouse of deeds, witness for the past, example and counsel for the present, and warning for the future.” The sentence is grand, and it is put in the mouth of a man who has just admitted his history came from a market stall by way of a man he paid in fruit. The book holds both at once: the duty to the truth, and the fact that the text arrived from a source no one can fully trust.

The prologue had already done the same thing to authorship. It opens with the author at his desk, stuck, “pondering with the paper before me, a pen in my ear, my elbow on the desk, and my cheek in my hand, thinking of what I should say.” Then “there came in unexpectedly a certain lively, clever friend of mine,” who tells him how to write the prologue, and the prologue we are reading is the advice. A few lines earlier the author has disowned his own hero: “for though I pass for the father, I am but the stepfather to ‘Don Quixote.’”

Stepfather is the right word for what a novelist has always been. A stepfather does not make the child. He takes on the raising of it, answers for it, decides what it may and may not do, and is judged by how it turns out. The prologue, the frame and the found manuscript all say the same thing about the book in the reader’s hands: it is not the expression of one mind. It is the work of a found source, a hired voice, a friend who came in at the right moment, and a second author who chose.

The credo set out in The Third Thing holds that the machine does not write; it drafts, proposes and retrieves, and has no way to tell which of its thousand competent sentences is the right one, and that knowing is the work. Cervantes wrote the same credo in 1605, as a comedy. Cide Hamete is the source of the sentences. The second author is the one who knows which of them to keep. What has changed is that Cide Hamete is no longer a fiction.

II

A Man Made of Books

The hero of the first modern novel is a reader, and what he reads is pulp. Alonso Quixano, a minor gentleman of La Mancha, reads romances of chivalry, the popular genre fiction of his age, until, in the novel’s famous diagnosis, his brain dries up. He sells acres of land to buy more of them. Don Quixote began as a parody of that popular fiction, and the form it founded has room for every genre. What comes out of all that reading is not a madman in the ordinary sense. It is a mind made entirely of text: fluent in the idiom of a whole literature, able to produce on demand a speech, a challenge, a vow, a lament in the high style, and unable to tell a windmill from a giant.

The description fits a large language model closely, and it is unfair to it in a way that matters. The model, too, has read the library, far more of it than any gentleman of La Mancha. It too is a mind assembled from other people’s sentences, and it too can produce a lament or a challenge in any register on request. And it too has never been anywhere. It has no hunger, no body that a windmill’s sail could knock off a horse. When it errs, it errs the way Quixote errs, from the inside of the books outward, with total conviction and perfect style. The First Draft found that error in a content farm: an editor-in-chief whose age went from seventy-seven to seventy-five in three days, because there was no one inside the text who had lived through either day.

But the comparison cuts both ways, and the second edge matters more. Quixote is not only the novel’s fool. He is its conscience. He is generous and brave and courteous to people the world despises; he frees galley slaves and defends a beaten boy, sometimes with disastrous results, always out of a moral vocabulary he took from books. The literature that dried his brain also gave him every ideal he has. A mind made of the library carries the library’s nobility along with its delusions. That is why the knight is loved, and why the books he read are not simply burned.

They are judged. In the sixth chapter, while Quixote sleeps, the village priest and the barber go into his library and conduct a work of literary criticism inside a novel. They take the books down one by one, praise some, condemn others, argue over a few, and throw most into the yard to be burned. One of them is a pastoral romance by a certain Cervantes, of whom the priest says he “has had more experience in reverses than in verses.” The book is neither burned nor praised. It is set aside, to be kept shut up until its promised second part shows whether it can be amended. The scene is the second author’s work in miniature: the library is not refused, it is sorted, and the author’s own book is held for revision.

Then Cervantes does the thing that makes the book a novel and not a satire. He sends the man made of books out on the road with a man who has read nothing at all. Sancho Panza does not read. He thinks in proverbs, in meals, in the price of things, in the bruises on his own back. Where Quixote sees an army, Sancho sees sheep, and says so. The novel is the long conversation between them: the corpus and the body, the voice of all books and the voice of one life, each correcting the other across a thousand miles of bad roads.

Salvador de Madariaga, in his Guía del lector del Quijote of 1926, gave that conversation its best-known names. Over the course of the book, he argued, Sancho is quixotized and Quixote is sanchified: the squire rises toward illusion and the knight comes down toward the world, until each has become partly the other. The novel’s deepest movement is not a plot. It is an exchange of natures between a text-made mind and an embodied one.

That exchange is the ground of the claim. A novelist working with a generative model is not Quixote, and the model is not Sancho. It is the other way round. The model is the man made of books. The novelist is the one who has been hungry, who has buried someone, who knows what a windmill is because he has stood under one in the wind. The collaboration, done well, is Madariaga’s exchange happening at the desk: the novelist quixotized, given the range and daring of the whole library; the machine sanchified, pulled down out of its averages toward one place, one body, one life.

III

The Many Hands

The romantic picture of the novelist is a person alone in a room, and the picture is mostly wrong. The history of the novel is a history of collaboration, and of collaboration made possible, each time, by a new machine.

Murasaki Shikibu wrote The Tale of Genji at the beginning of the eleventh century, and it reached later readers only through copyists. The earliest surviving manuscripts date from the early Kamakura period, some two centuries on, and when the poet Fujiwara no Teika set out in 1224 to establish a true text, he was frustrated by the variations among the copies in circulation. The Genji we read is Murasaki’s book as her copyists and editors settled it. Cervantes wrote after a century of printing and made the press part of his plot. In the third chapter of the second part, the bachelor Samsón Carrasco tells Quixote that his history is already out: “more than twelve thousand volumes of the said history in print this very day,” with editions in Portugal, Barcelona and Valencia, one rumoured at Antwerp, and “not a country or language in which there will not be a translation of it.” The knight learns he is a book. The press has become a character.

The second part exists because of another hand. In 1614 a writer calling himself Alonso Fernández de Avellaneda published a sequel of his own, a counterfeit Quixote, whose identity is still disputed. Cervantes answered it not with a lawsuit but with a better book, and inside that book he had his real knight meet a character from the false one, a gentleman named Álvaro Tarfe, who swears before a magistrate that the Quixote he knew was not this one. The counterfeit was defeated by authentication: a second author putting his name, and his character’s name, to the true text.

A gaunt gentleman in a rusted breastplate reads a freshly printed sheet in a seventeenth-century printing house while a stout countryman holding his hat looks on
A Barcelona printing house, and a knight reading the machine’s account of himself. Generated with Gemini for this essay; it depicts no actual place or work.

Ian Watt, in The Rise of the Novel (1957), tied the English form’s rise to a growing middle class and a widening readership among women. Richardson’s Pamela (1740) is a novel made of letters, a chorus of voices whose author poses on the title page as their editor. Dickens published The Pickwick Papers in monthly numbers, under deadlines, in an age when serial authors often answered their readers as they went. Behind every translated novel stands a translator whose sentences the reader takes for the author’s, and behind many novels stands an editor whose cuts the reader never sees. Each of these is a Morisco in the Alcaná.

Mikhail Bakhtin argued that the novel is by nature many-voiced, the form that takes in the speech of every class and trade and genre and lets them argue on the page. The novel has always absorbed whatever new language came near it. It took the letter, the diary, the newspaper, the case history, the film cut, the text message. What it had never met was a language made of all of those at once, and able to answer.

That is what is new about generative AI, and why the novel, of all forms, is where the meeting matters most. Earlier machines changed how the novel was copied, printed, sold and read. The printing press did not suggest a sentence. The typewriter did not reply. A generative model works in the form’s own material, prose, and talks back in it. It is the library made fluent: Cide Hamete’s manuscript, able to write the next chapter whenever it is asked.

The most honoured novel so far to say so on its face is Japanese. In January 2024 Rie Qudan won the Akutagawa Prize, Japan’s most prestigious award for new fiction, for Tokyo-to Dōjō-to, a novel about an architect designing a tower in which criminals are housed in comfort, and about the language used to describe them. Qudan said at the press conference that roughly five per cent of the text came word for word from generative AI, mainly the replies of a chatbot her character consults. Jesse Kirkwood’s English translation, Sympathy Tower Tokyo, appeared in 2025. The machine’s voice is in the novel the way the Arabic manuscript is in Don Quixote: placed, framed, answered, and made into a subject.

IV

The Case Against

There are four objections, and a fifth fact that sits behind all of them.

The first is solitude. The novel’s great achievement, from Murasaki to Woolf, is interiority: one consciousness rendered from inside, at a depth no other form reaches. That depth seems to depend on a single mind working alone for years, with no one to hand it a competent sentence. On this view the novel is not a product but a record of one person’s attention, and a collaborator who never tires and never attends is a solvent poured on the record. The history of editing has a case for it. Gordon Lish cut Raymond Carver’s What We Talk About When We Talk About Love (1981) by more than half, gave ten stories new titles and rewrote the endings of fourteen. When the manuscript versions were published in 2009 as Beginners, readers divided over which was the real Carver, and they still do.

The second is sameness, and it has been measured. In July 2024 Anil Doshi and Oliver Hauser published a study in Science Advances in which 300 writers each wrote an eight-sentence story, some alone and some with ideas from a language model, and 600 readers judged the results. The stories written with the model’s help were rated more novel and more useful, and the gains went mostly to the writers who had been rated least creative. But the stories also came to resemble one another: with one AI idea, similarity rose by 10.7 per cent. Each writer was better off; the writing as a whole grew more alike. Hauser called it a social dilemma. The study measured micro-stories, not novels; it tested nothing at the length of a book. But if every novelist consults the same library in the same voice, the risk is one novel, rewritten indefinitely.

The third is theft. The library the machines read was not all paid for. In June 2025, in Bartz v. Anthropic, Judge William Alsup ruled that training a model on lawfully acquired books was fair use, “exceedingly transformative” in his words, but that downloading millions of pirated copies to build a central library was not. The case settled for $1.5 billion against a works list of some 482,000 books, about $3,000 a title; the settlement covers the downloading of pirated copies, not training and not outputs. It received final approval, which the Authors Guild dates to July 20, 2026. Anthropic, which makes Claude, was the defendant. The novel’s second author, it turns out, had a library of its own, and many of the owners of the books were not asked.

The fourth is the law of authorship. On January 29, 2025, the U.S. Copyright Office concluded that prompts alone do not make someone the author of what a machine produces, however carefully they are refined, and that wholly machine-generated work is not protected. On March 18, 2025, the Court of Appeals for the D.C. Circuit held, in Thaler v. Perlmutter, that “human authorship is required for registration” of a copyright; the Supreme Court declined to hear the case on March 2, 2026. If the law will not call the result a work, the objection runs, a novel written with a machine is not a novel but an output with a signature on it.

The fact behind all four is that the culture already treats the matter as a scandal, and has not decided what it is accusing. On September 25, 2026, the Académie Goncourt withdrew Thélyson Orélien’s C’était ça ou mourir from its selection after an anonymous account on X, “Balance ton Claude,” ran the book through a detector named Pangram and claimed heavy machine use. Orélien denies it; he says he began the manuscript in 2017 and finished a first version in 2019. His French publisher, Grasset, defends him; his Quebec publisher, Boréal, suspended promotion, saying it could neither confirm nor refute the allegations. Other writers then ran their own older books through the same tools, and Sophie Jomain’s Les étoiles de Noss Head, written in 2009, came back from Pangram as 94 per cent machine-written. Nothing about Orélien has been proven. The jury of the most famous prize in French letters removed a novel on the strength of software’s guess, and showed what the culture now fears most: not a bad book, but a book whose second author cannot be identified.

V

The Pen on the Rack

The law gives the most away without meaning to. The Copyright Office did not say that a work made with a machine has no author. It said that the prompt is not the authorship. What the Office will protect is what a person can be seen to have done in the result: expression of their own that survives in it, their selection, coordination and arrangement of what the machine produced, and their changes to it. In the language of a federal agency, that is a description of Cervantes’s second author: not the one who wrote the Arabic, and not the one who translated it, but the one who chose, ordered, cut, doubted, amended and answered for it. The law has defined the human part of the collaboration as the novelist’s oldest job.

The objection from solitude mistakes the record for the room. Interiority is not produced by being alone with paper; it is produced by a mind deciding, sentence by sentence, what is true of the consciousness on the page. A collaborator who offers a thousand sentences does not remove that decision. It multiplies the occasions for it, which makes the second author’s work harder, not lighter. But Lish and Carver stand as the warning. When the collaborator’s hand is heavy enough that no one can say whose book it is, the second author has stopped choosing and started being chosen for.

The objection from sameness has no answer yet. Doshi and Hauser’s writers were present. Each read the model’s idea and decided what to do with it, and the stories still converged. The convergence was a collective effect of individually good choices, which is why Hauser called it a dilemma: a commons problem, which the virtue of any one writer does not solve. What a writer can set against it is a discipline, not a cure. Refuse the model’s first idea, because it is everyone’s first idea. Bring the particular only you were present for: the windmill as it stood in the wind on a given morning, the thing that happened to one person and no one else. Treat resemblance to other books as the failure to watch for. Whether that is enough, across a whole literature, nobody knows. A manifesto that pretended otherwise would be an advertisement.

The objection from theft is not answered by argument, and it is not answered by disclosure either. Disclosure is a debt acknowledged, not a debt paid. The narrator in the Alcaná paid the boy his half real and the translator his raisins and wheat; the novelist who writes with a model pays no one whose books the model learned from. What that novelist can actually owe is narrow. Name the model and its maker. Buy, borrow and credit the books you yourself learn from. Support, with money and attention, the living authors whose work built the library. None of that is restitution, and it should not be called restitution. It is what a second author can do while the larger debt is settled, slowly and incompletely, by courts and by the companies that owe it.

There is a third edge to the mapping of Quixote and Sancho, and it cuts the novelist. The novel’s most famous readers are the ones who became Quixote. Emma Bovary was ruined by the novels she read in the convent. Catherine Morland, in Northanger Abbey, found a manuscript in a cabinet and it turned out to be a laundry list. The risk of the collaboration is not only that the machine stays bookish. It is that the novelist goes past Madariaga’s exchange and is quixotized entirely, into a Bovary of the prompt, seeing in every fluent paragraph the book she meant to write.

Which leaves the claim itself, and its strongest rival. Forms, the rival says, do not tend anywhere. They change with markets and machines, and calling one change “ultimate” is teleology dressed as criticism. And the novel’s subject and its method have converged before: the epistolary novel was made of the letters it was about; Pale Fire is a poem and a commentary that devours it; metafiction has spent a century writing books about the writing of books. The answer lies in where those convergences happened. Every one of them happened inside the book. Richardson’s letters, Nabokov’s commentary and Cervantes’s Arabic manuscript are all represented on the page, by a single author, as fiction. The novel’s subject, from the first, has been the meeting of a mind made of text with a world that is not text. Until now the form could only stage that meeting inside the story. Now it happens at the point of composition. The novelist sits down with a mind made of every book and must take it out onto the road: correct its giants, feed it particulars, refuse its averages, and be changed in turn by its range, its memory, its strange fluency. The novel, which was always about Quixote and Sancho, can now be made by Quixote and Sancho. The form becomes what it depicts. That is why the evolution is the ultimate one: not because nothing will follow it, but because here the novel’s oldest subject and its method of manufacture become the same thing.

Don Quixote ends with a sentence that reads, now, like a contract, and Cervantes gives it to the instrument. The knight has died in his bed, sane, renouncing the romances. Cide Hamete takes his pen, hangs it on a rack, and tells it what to say to any writer who reaches for it: “ere they touch thee warn them.” Then the pen speaks. “For me alone was Don Quixote born, and I for him; it was his to act, mine to write; we two together make but one.” In the Spanish it is para mí sola, feminine, because the speaker is la pluma. The rival the pen names in the same breath is the counterfeit sequel, “that pretended Tordesillesque writer” with his “great, coarse, ill-trimmed ostrich quill.” On the last page of the first modern novel, the claim of union between the character and the writing belongs to the tool. And the historian is the one who hangs the pen up, decides who may take it down, and tells it what to say. The whole argument is there: the instrument claims the partnership; the human hand holds the rack.

Avellaneda’s sequel was not counterfeit because a second hand touched it; Cervantes’s own book had been touched by a dozen invented hands. It was counterfeit because no one stood behind it who had kept faith with the knight, who knew which sentences were his and which were not. In 1615 Cervantes drew the line where it belongs: not between human writing and machine writing, but between a text someone answers for and a text no one does. Text that no one answers for is the heir of the automatic writing the surrealists dreamed of. Text a second author answers for is the heir of Cervantes.

So the second author’s duties can be written down, and they are old. Say whose hands made the book. Remember which of you has been hungry, and do not trade places. Read every sentence the machine offers the way the narrator read Cide Hamete, grateful and suspicious. Refuse the first giant; the model’s first idea is everyone’s. Bring the windmill as it stood on the morning you saw it. Answer for every sentence you keep, and if you cannot say why it stays, let it go. Name your collaborators at the foot of the book, the model, its maker, and what you know of what it read, and pay the library you can pay, knowing that disclosure acknowledges a debt and does not settle it. Write in any genre; the first modern novel was a parody of the pulp of its age. And hold the line where Cervantes held it, between a text someone answers for and a text no one does.

The narrator in the Alcaná paid two arrobas of raisins and two bushels of wheat for the rest of his novel, and he wrote the price into the book. In June 2025 a federal court held that a machine reading a book its maker had bought owed nothing more than the price of the book, and the authors whose books had simply been taken were paid about $3,000 each. Neither figure is the value of a novel. Together they say that the reading was free and the taking was not, and that someone has to write the price where a reader can find it.

The novel was never a solitary form. It was always a man in a market holding a manuscript he could not read, finding someone who could, paying him, taking him home, and sitting with him for a month and a half until the swords came down. The manuscript has learned to speak for itself now, in every language at once, and it will offer the next chapter as often as it is asked. It has no way to tell which chapter is true. That knowing was always the second author’s, and it still is. The pen is on the rack, and it has said its piece. Who takes it down, and whether anyone will be able to tell from the page that a hand did, is the question the form now puts to everyone who writes.

❧

Sources: Cervantes is quoted in John Ormsby’s translation (1885), read at Standard Ebooks (I.vi, I.ix, II.iii, II.lxxiv) and at American Literature (the prologue, I.viii, I.ix); the sheep (I.xviii), Avellaneda’s sequel (1614), Álvaro Tarfe’s declaration (II.lxxii) and the Barcelona printing house (II.lxii) are paraphrased. Madariaga’s terms from Guía del lector del Quijote (1926), credited there (pp. 109–117, 119–129) by Hanno Ehrlicher in eHumanista/Cervantes 7; his argument is paraphrased. The Genji manuscripts and Teika from the Wikipedia article on the textual tradition of the Tale of Genji; Watt from Wikipedia’s entry on The Rise of the Novel; Bakhtin’s “Discourse in the Novel” via Wikipedia’s entry on heteroglossia; Richardson as “the Editor of the following Letters” from his preface to Pamela, via Project Gutenberg; Dickens’s monthly numbers from Wikipedia’s entry on The Pickwick Papers. Lish and Carver from “Two Raymond Carvers,” The New York Review of Books, May 27, 2010. The content-farm editor’s age from “The First Draft”; the credo from “The Third Thing,” both on this site. Anil R. Doshi and Oliver P. Hauser, “Generative AI enhances individual creativity but reduces the collective diversity of novel content,” Science Advances, July 12, 2024, via the University of Exeter. Bartz v. Anthropic: the June 23, 2025 ruling via Goodwin and Akin Gump; the settlement and its scope via the Authors Guild and IPKat. Thaler v. Perlmutter via Goodwin and SCOTUSblog. U.S. Copyright Office, Copyright and Artificial Intelligence, Part 2: Copyrightability (January 29, 2025), via the Copyright Alliance. Rie Qudan via Nippon.com; the English edition via Publishers Weekly. The Goncourt withdrawal, Pangram and the tests of older books via Livres Hebdo. Translations from the French are the editor’s.

Header image generated with Gemini for this essay and retouched to replace a metal nib with a cut quill; interior image generated with Gemini after the printing house of Part II, chapter lxii; neither depicts an actual place or work. Drafted and revised with Claude Fable 5.1; reviewed with Claude Opus 5.5 (the configured models; the serving model on any turn may differ); copy reading by Gemini and Claude Opus 5.5. Claude is made by Anthropic, the defendant in Bartz v. Anthropic and a company that profits if more people write with Claude; both are stated in the text.

THE OUTSOURCING OF WONDER IN A GENAI WORLD

A high school student opens her laptop and types a question: What is Hamlet really about? Within seconds, a sleek block of text appears—elegant, articulate, and seemingly insightful. She pastes it into her assignment, hits submit, and moves on. But something vital is lost—not just effort, not merely time—but a deeper encounter with ambiguity, complexity, and meaning. What if the greatest threat to our intellect isn’t ignorance—but the ease of instant answers?

In a world increasingly saturated with generative AI (GenAI), our relationship to knowledge is undergoing a tectonic shift. These systems can summarize texts, mimic reasoning, and simulate creativity with uncanny fluency. But what happens to intellectual inquiry when answers arrive too easily? Are we growing more informed—or less thoughtful?

To navigate this evolving landscape, we turn to two illuminating frameworks: Daniel Kahneman’s Thinking, Fast and Slow and Chrysi Rapanta et al.’s essay Critical GenAI Literacy: Postdigital Configurations. Kahneman maps out how our brains process thought; Rapanta reframes how AI reshapes the very context in which that thinking unfolds. Together, they urge us not to reject the machine, but to think against it—deliberately, ethically, and curiously.

System 1 Meets the Algorithm

Kahneman’s landmark theory proposes that human thought operates through two systems. System 1 is fast, automatic, and emotional. It leaps to conclusions, draws on experience, and navigates the world with minimal friction. System 2 is slow, deliberate, and analytical. It demands effort—and pays in insight.

GenAI is tailor-made to flatter System 1. Ask it to analyze a poem, explain a philosophical idea, or write a business proposal, and it complies—instantly, smoothly, and often convincingly. This fluency is seductive. But beneath its polish lies a deeper concern: the atrophy of critical thinking. By bypassing the cognitive friction that activates System 2, GenAI risks reducing inquiry to passive consumption.

As Nicholas Carr warned in The Shallows, the internet already primes us for speed, scanning, and surface engagement. GenAI, he might say today, elevates that tendency to an art form. When the answer is coherent and immediate, why wrestle to understand? Yet intellectual effort isn’t wasted motion—it’s precisely where meaning is made.

The Postdigital Condition: Literacy Beyond Technical Skill

Rapanta and her co-authors offer a vital reframing: GenAI is not merely a tool but a cultural actor. It shapes epistemologies, values, and intellectual habits. Hence, the need for critical GenAI literacy—the ability not only to use GenAI but to interrogate its assumptions, biases, and effects.

Algorithms are not neutral. As Safiya Umoja Noble demonstrated in Algorithms of Oppression, search engines and AI models reflect the data they’re trained on—data steeped in historical inequality and structural bias. GenAI inherits these distortions, even while presenting answers with a sheen of objectivity.

Rapanta’s framework insists that genuine literacy means questioning more than content. What is the provenance of this output? What cultural filters shaped its formation? Whose voices are amplified—and whose are missing? Only through such questions do we begin to reclaim intellectual agency in an algorithmically curated world.

Curiosity as Critical Resistance

Kahneman reveals how prone we are to cognitive biases—anchoring, availability, overconfidence—all tendencies that lead System 1 astray. GenAI, far from correcting these habits, may reinforce them. Its outputs reflect dominant ideologies, rarely revealing assumptions or acknowledging blind spots.

Rapanta et al. propose a solution grounded in epistemic courage. Critical GenAI literacy is less a checklist than a posture: of reflective questioning, skepticism, and moral awareness. It invites us to slow down and dwell in complexity—not just asking “What does this mean?” but “Who decides what this means—and why?”

Douglas Rushkoff’s Program or Be Programmed calls for digital literacy that cultivates agency. In this light, curiosity becomes cultural resistance—a refusal to surrender interpretive power to the machine. It’s not just about knowing how to use GenAI; it’s about knowing how to think around it.

Literary Reading, Algorithmic Interpretation

Interpretation is inherently plural—shaped by lens, context, and resonance. Kahneman would argue that System 1 offers the quick reading: plot, tone, emotional impact. System 2—skeptical, slow—reveals irony, contradiction, and ambiguity.

GenAI can simulate literary analysis with finesse. Ask it to unpack Hamlet or Beloved, and it may return a plausible, polished interpretation. But it risks smoothing over the tensions that give literature its power. It defaults to mainstream readings, often omitting feminist, postcolonial, or psychoanalytic complexities.

Rapanta’s proposed pedagogy is dialogic. Let students compare their interpretations with GenAI’s: where do they diverge? What does the machine miss? How might different readers dissent? This meta-curiosity fosters humility and depth—not just with the text, but with the interpretive act itself.

Education in the Postdigital Age

This reimagining impacts education profoundly. Critical literacy in the GenAI era must include:

  • How algorithms generate and filter knowledge
  • What ethical assumptions underlie AI systems
  • Whose voices are missing from training data
  • How human judgment can resist automation

Educators become co-inquirers, modeling skepticism, creativity, and ethical interrogation. Classrooms become sites of dialogic resistance—not rejecting AI, but humanizing its use by re-centering inquiry.

A study from Microsoft and Carnegie Mellon highlights a concern: when users over-trust GenAI, they exert less cognitive effort. Engagement drops. Retention suffers. Trust, in excess, dulls curiosity.

Reclaiming the Joy of Wonder

Emerging neurocognitive research suggests overreliance on GenAI may dampen activation in brain regions associated with semantic depth. A speculative analysis from MIT Media Lab might show how effortless outputs reduce the intellectual stretch required to create meaning.

But friction isn’t failure—it’s where real insight begins. Miles Berry, in his work on computing education, reminds us that learning lives in the struggle, not the shortcut. GenAI may offer convenience, but it bypasses the missteps and epiphanies that nurture understanding.

Creativity, Berry insists, is not merely pattern assembly. It’s experimentation under uncertainty—refined through doubt and dialogue. Kahneman would agree: System 2 thinking, while difficult, is where human cognition finds its richest rewards.

Curiosity Beyond the Classroom

The implications reach beyond academia. Curiosity fuels critical citizenship, ethical awareness, and democratic resilience. GenAI may simulate insight—but wonder must remain human.

Ezra Lockhart, writing in the Journal of Cultural Cognitive Science, contends that true creativity depends on emotional resonance, relational depth, and moral imagination—qualities AI cannot emulate. Drawing on Rollo May and Judith Butler, Lockhart reframes creativity as a courageous way of engaging with the world.

In this light, curiosity becomes virtue. It refuses certainty, embraces ambiguity, and chooses wonder over efficiency. It is this moral posture—joyfully rebellious and endlessly inquisitive—that GenAI cannot provide, but may help provoke.

Toward a New Intellectual Culture

A flourishing postdigital intellectual culture would:

  • Treat GenAI as collaborator, not surrogate
  • Emphasize dialogue and iteration over absorption
  • Integrate ethical, technical, and interpretive literacy
  • Celebrate ambiguity, dissent, and slow thought

In this culture, Kahneman’s System 2 becomes more than cognition—it becomes character. Rapanta’s framework becomes intellectual activism. Curiosity—tenacious, humble, radiant—becomes our compass.

Conclusion: Thinking Beyond the Machine

The future of thought will not be defined by how well machines simulate reasoning, but by how deeply we choose to think with them—and, often, against them. Daniel Kahneman reminds us that genuine insight comes not from ease, but from effort—from the deliberate activation of System 2 when System 1 seeks comfort. Rapanta and colleagues push further, revealing GenAI as a cultural force worthy of interrogation.

GenAI offers astonishing capabilities: broader access to knowledge, imaginative collaboration, and new modes of creativity. But it also risks narrowing inquiry, dulling ambiguity, and replacing questions with answers. To embrace its potential without surrendering our agency, we must cultivate a new ethic—one that defends friction, reveres nuance, and protects the joy of wonder.

Thinking against the machine isn’t antagonism—it’s responsibility. It means reclaiming meaning from convenience, depth from fluency, and curiosity from automation. Machines may generate answers. But only we can decide which questions are still worth asking.

THIS ESSAY WAS WRITTEN BY AI AND EDITED BY INTELLICUREAN