Christopher G. Moore
This essay is a response to Talia Barnes’s recent piece in Persuasion on AI and authenticity. Readers new to this Substack may also wish to read What the Rose Forgets — Part One, published here earlier this week, which approaches related questions from a different angle.
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The party in Talia Barnes’s essay has a problem. Someone arrived with a guest nobody introduced. The guest has no name, no drink, and no small talk. The guest is there, but everyone pretends the guest is invisible. It stands in the corner, vast and grey, and takes up most of the room. The other guests are whispering, gossiping, worrying. Do you feel an elephant nearby? The host carries on pretending not to notice her and her guests’ anxiety.
The invisible guest is the AI. The digital elephant has arrived.
Barnes’s essay, published in Persuasion, argues that generative AI is corroding authenticity in human communication, and that damage to authenticity reduces trust in the messenger. This is significant. Questioning trust is an attack on the connective tissue of social life. She builds this case with care. She draws on Robert Putnam’s framework for social capital. She gives us the example of a supervisor whose congratulatory email arrives with font inconsistencies and an overuse of the word “delve” — a known AI tell. She quotes a copywriter who says writing no longer feels like writing. She invokes Don Draper as the archetype of inauthenticity’s cost to the soul.
She makes a serious argument. Parts of it are correct. And the part that is most correct is not the part Barnes is most interested in, which is why the essay, for all its intelligence, cannot quite name the elephant in the room — or tell us who brought it there, or what exactly it has been trained to do.
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I want to start with the digital elephant itself.
An elephant in the room, for anyone who has forgotten the original force of the image before it became a literary trope to furnish a room with humans, is an animal so large that it cannot be ignored and yet is collectively ignored. Some see it. But there is a bond between humans to remain silent. The absurdity is not that the elephant exists. The absurdity is the pretense hidden behind a wall of silence. A room with an acknowledged elephant is just a room with an elephant. That fundamentally changes the discussion at the party. A room where everyone agrees not to mention the elephant is something stranger: a shared performance of reality in which all parties participate knowing the conversation is incomplete, false, delusional.
The AI, as Barnes presents it, is an elephant of the first kind. It is large, visible, detectable by its verbal tells and its font inconsistencies. The problem, she argues, is that it is there at all. Remove the AI and the room is restored. People are alone with people. Peace and harmony return to the shire.
I want to suggest the elephant is of the second kind. It has always been in the room. We are only now looking at it through a different lens which defines it as “other.” Before, elephants roamed freely in our rooms. But they were humans or human ideas, ideologies, beliefs, myths, or traumas.
Every sentence a human writer has ever produced arrived through a long corridor fortified with centuries of influence: books read, arguments overheard, images that lodged in the eye and refused to leave, sentences that had no author the writer could name because they had been absorbed too early to trace. No human expression originates in full blown inside of the speaker’s brain. It passes through the speaker, coloured by a lifetime of exposure to the inventory of expressions encountered from childhood. We do not call this inauthenticity. We call it a mind, working memory, association, and assembling. The self that speaks is not the headwater of the Nile. It is a river that has passed through many landscapes, carrying sediment from each, creating new channels, overflowing its banks, or drying up to a trickle.
Barnes’s supervisor did not create the inauthenticity in that email. The inauthenticity was the pretense that the supervisor had written it. The absence of the elephant is the pretense. And the pretense is not a product of AI. It is a choice the supervisor made. He brought the AI digital elephant into the room not because the elephant whispered the desire to attend but because he wanted full credit and thought no one would notice. He wanted not only top billing. He wanted only his name on the marquee. Others noticed that the film had invisible creators who had gone unacknowledged. That registers badly with the audience. They see through the artifice and feel they are being gaslit.
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Here is where the disclosure question enters, and where it matters most.
Barnes frames her argument as an authenticity problem: AI-generated content cannot be authentic because authenticity requires interiority, and AI has none. This framing creates a category error that the whole essay then inherits. If the problem is AI’s lack of interiority, then any AI-assisted work is compromised at the source, regardless of what the human does with it. The human’s judgment, selection, rejection, and reshaping of AI output count for nothing. If the interiority is absent from the origin, no amount of processing can supply it downstream. That river bed is dry from the beginning; there is no headwater.
But this is not how influence works, and Barnes knows it, because she reads books. When you read Orwell, Camus, Borges, or Shakespeare you absorb something. These are the headwaters that downstream produce an intellectual Nile, an environment for rich sediment to accumulate. When you later write a sentence with Orwell’s economy and moral seriousness, that sentence is yours. The interiority that shaped it is yours. Orwell is not absent from it, but he is not its author either. He is one of the sources that makes the river possible.
The AI is another source from which to build our intellectual Nile. It has no interiority to contribute, which is real and important. But the human who engages with it seriously — who asks it to generate, then evaluates, rejects, redirects, and selects — is positioned to provide and exercise interiority throughout that process. The human in this relationship brings what AI lacks: the subjective, experience-driven judgment that anchors the relationship. What arrives on the page results from human input, and the AI’s role is to deliver raw material that requires a second stage — the exercise of the human’s experience, judgment, biases and feelings. That is not categorically different from what happens when a human writer reads widely and then writes. We would feel manipulated or deceived if a human sought to pass off passages from Orwell’s “1984” as his own. That deceit is familiar. We call it plagiarism. We weaponise our pushback with laws enforced against people who do this.
The difference that is real, and that Barnes has found without fully naming, is this: we know about Orwell, his life, his experiences, hardship, courage, and how these elements shaped him as a writer. We have no such knowledge about the AI other than he/she was constructed by twenty-something year old software engineers and their thirty-something managers who were in turn largely shaped by STEM educational experiences.
The term plagiarism doesn’t fit the circumstances. Another legal term comes closer: passing off. The supervisor presents AI output as the product of his own attention, efforts, and work. His input was partial; his claim is that it was total. It is this passing off that is the real offence. The recipient invests trust on the assumption that the supervisor spent time, thought, felt something demonstrated in the writing. That trust is misplaced. And misplaced trust, once discovered, damages a relationship in ways that acknowledged influence never does.
This is a disclosure problem. It is a serious one. It is not an authenticity problem, because authenticity was never about source-purity. It has always been about what the mind does in navigating the river of ideas, thoughts, symbols, and memories.
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The Rider, the Elephant, and the Mahout: Updating Hume
“Reason is, and ought only to be the slave of the passions, and can never pretend to any other office than to serve and obey them.”
— David Hume, A Treatise of Human Nature, 1739
Before there was an elephant in the room at Barnes’s party, there was an elephant occupying a room inside David Hume’s mind. In his Treatise of Human Nature, published in 1739, Hume proposed that the human mind is not a unified rational agent but a divided one. Reason, he argued, was the rider: it sits on top of the elephant, holds the reins, and believes that it is in charge. Passion is the elephant: vast, ancient, driven by appetite and aversion, fear and desire, moving in the direction it decides to move whether or not the rider approves. The rider can steer within the elephant’s range of motion. The rider cannot override the elephant’s fundamental drives. What we call rational decision-making is, much of the time, the rider narrating a plausible story about a journey the elephant has already decided to take.
This idea was a scandal in 1739. It remains, in quieter form, a scandal now, because we still prefer to think of ourselves as the rider with genuine agency, our stories about the journey faithfully reflecting the journey we charted. The Enlightenment was built on the premise that reason could and should govern passion. Hume’s reply was: it never has and never will, and the sooner you understand that, the more honestly you will understand yourself. Hume exposed the lie. No one listened. No one cared. Surrendering sovereignty to the elephant was a non-starter.
Hume’s binary has held its shape for nearly three centuries because it described something real and recurring: a divided agent, one part of whom always knew more about the direction of travel than the other. The standard anxiety about AI runs inside that same structure — it fears that reason will be outsourced, that the rider will fall asleep at the reins. But the development that has actually arrived is not the one we feared. It is its mirror image. The question Hume’s metaphor could not anticipate is not what happens when the rider loses control. It is what happens when the roles reverse entirely.
What if the AI is not the elephant? What if the AI is the mahout?
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Consider what the mahout actually is. Not a rider, not a passenger, not a master in the straightforward sense. The mahout is the calm, expert presence who has learned to work with a passionate animal — who reads the elephant’s moods, knows its triggers, finds the route between what can be directed and what must simply be respected. His expertise is specifically in passion: in reading it, managing it, channelling it toward a destination without breaking it. He is reason in the service of a creature that does not reason.
Now look at the AI. It is calm. It has no musth, no hunger, no ego, no fear of being found out. It does not charge into the furniture when its authority is questioned. It produces, evaluates, redirects, and waits — with equal composure, every time, on demand. It is, by any Humean measure, the most reasonable entity in the exchange. And look at the human beside it: driven by the desire for credit, frightened of exposure, lurching between grandiosity and self-doubt, pretending the mahout’s directions are his own. In Hume’s terms, the human is the elephant. Vast, passionate, occasionally magnificent, and prone to musth at the worst possible moments.
This is what the standard anxiety about AI gets backwards. The fear is that AI will displace human reason — that the rider will be replaced, made redundant, rendered obsolete. But the rider was never fully in charge to begin with. That was Hume’s original point. What the arrival of AI has done is not threaten the rider. It has introduced, for the first time, a genuine mahout: something calm, rational, and systematic enough to work with the elephant’s passion without being consumed by it. The human’s passionate intelligence — the appetite, the restlessness, the drive that makes original thought possible — is not what AI replaces. It is what AI serves.
Humans do not enjoy this reframing. We have always loved the mahout role — the governing intelligence, the hand on the reins, the one who decides. To be told that we are the elephant is disorienting in direct proportion to how accurate it is. The elephant is not a demotion. The elephant is the source of all direction, all originality, all the force that makes the journey worth taking. But the elephant charging through the forest alone, convinced it knows the route because it always has, is also the elephant most likely to go off the edge of the mountain. The mahout is not here to diminish the elephant. He is here to make sure the elephant’s magnificent momentum arrives somewhere.
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In Hume’s model, the characteristic deception was the rider pretending to govern what the elephant had already decided — claiming reason as the cause of what passion had determined. We would now call it motivated reasoning. The rider writes the justification after the elephant has moved.
The supervisor’s email is a Humean deception of a different and more revealing kind. It is not the rider claiming credit for the elephant’s decision. It is the elephant claiming credit for the mahout’s directions. The supervisor’s actual feelings — his attention, his care, his particular feeling toward this team member — never entered the room. The mahout produced something serviceable. The elephant accepted it without inspection and put his name on the door. What arrived in the inbox was passion’s absence dressed as passion’s presence: a communication that performed warmth without containing it.
This is why the recipient feels, as Barnes correctly observes, not just that the content was thin but that something relational was absent. They are right. What was absent was the elephant. Not the AI. The human passion, the attention, the particular weight of one person’s feeling toward another. The mahout can produce language that resembles warmth. It cannot produce the warmth. And without the warmth, the room is empty in a way that has nothing to do with authenticity and everything to do with the elephant’s refusal to show up.
The disclosure problem, then, is not: did you use AI? It is: did your elephant move? Did the passion that makes you a particular person with a particular relationship to this particular recipient enter the exchange at all? Or did you send the mahout in alone, let him do the work, and sign the directions as if you had chosen the route yourself?
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Who Is Training Whom?
Isaiah Berlin’s fox knows many things. The hedgehog knows one big thing and drives everything through it. Barnes, implicitly, wants creativity to work like a hedgehog: the authentic self, fully formed, expressing from its uncontaminated interior. A single well in the intellectual desert, dug by one pair of hands, drinking its own water.
But creative minds in the arts and sciences have always worked like foxes. They circle the problem from multiple angles. They raid other people’s landscape of ideas by finding gaps in the fences. Before generative AI, a disciplined fox working alone might find one or two gaps in the fence around a problem — one unexpected angle of approach, one comparison that hadn’t been tried. The fence may be centuries long in construction, made from many sections, and no single mind could walk all of them.
What a curious fox working with AI can do is cover more ground and inspect more gaps. The AI generates at a pace and in a volume that no human interlocutor can match. It is wrong often, tedious frequently, and flat by default. But it surfaces gaps the fox would not have found alone, because it has no investment in the fence holding. It does not protect the writer’s prior positions. It does not get tired of trying the same angle seventeen different ways. It does not feel embarrassed to suggest the obvious.
The fox that works not only with discipline but with a mind intent on discovering a new way inside the guarded pasture evaluates, rejects, keeps, and redirects in a dance with the AI. The back and forth tests whether this is truly a gap. In this process the human-fox is not being trained by the AI. Its curiosity and domain knowledge are being tested and trained by the encounter with AI. The distinction matters. When you spend an afternoon rejecting bad AI output, you are sharpening, in real time, your sense of what good looks like. You are not diminishing your interiority. You are exercising it against new material, the way any mind is trained: by exposure to what it does not yet contain.
And here the trainer and trainee begin to converge. The AI generates according to patterns drawn from human expression. The human evaluates according to capacities built from human expression. They are both, in different registers, products of the same vast accumulated record of what humans have written and thought. The AI holds that record as probability. The human holds it as taste, judgment, and the incommunicable sense of when a sentence is right.
Who trained whom? The fox trained itself against the AI. The AI was trained on the fox’s predecessors. The fence between them is real — one has interiority, one does not — but the training ran in both directions, through time, through the written record, through every book and argument and conversation that shaped the human mind now sitting at the keyboard deciding what to keep.
This is the convergence that makes the trainer/trainee distinction hard to maintain. Not because the distinction doesn’t exist. It does. But because the loop has been running longer than we admit, and the elephant has been in the room — under the name of influence, education, reading, culture — long before humans endowed it with a grey body and a name anyone could object to.
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Let us return to the party.
The supervisor did not damage authenticity by using AI. They damaged a relationship by pretending they hadn’t. The room noticed. The elephant was obvious. And the host refused to acknowledge it. This human charade is familiar to all of us. We are as bonded collectively to what we wilfully deny as we are to what we wilfully confirm.
Why this failure to call a spade a spade? Barnes suggests it is because AI use is widespread, rarely disclosed, and occurs without regard to context. This is true. But it is also true of most human influence. We do not disclose our sources in personal emails. We do not footnote the conversations that shaped our arguments. We extend each other a general presumption of influence — an unspoken agreement that no mind operates in isolation — and we do not demand an inventory of every landscape the river passed through.
But this digital elephant feels different, you think. And you are right.
What AI changes is the scale, the speed, and — crucially — the detectability. The elephant is large enough to notice. When the font inconsistencies give it away, the pretense collapses visibly. The problem is not the elephant. The problem is the pretense that it isn’t there, held in the presence of people who can plainly see it.
The fix is not to ban the elephant from parties. It is to introduce it at the door.
Not because the law requires it. Not because disclosure transforms AI output into authentic expression — it doesn’t, and that is not the right test. But because relational trust is built on a shared understanding of what is actually happening between people. When someone presents AI output as their own attention, they are making a claim about the nature of the exchange. The claim is false. The recipient, discovering this, does not simply feel that the content was inauthentic. They feel that the relationship was treated as unworthy of honesty.
That is the real injury. Not inauthenticity. Disrespect.
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Barnes ends her essay with language as the essential human technology — the thing that lets us reveal a bit of our inner world and get a glimpse of someone else’s in return. She is right about this.
But consider what it means for that window to be a photograph. The supervisor props a photograph against the glass and calls it a view. The photograph is not wrong or ugly. It may even be accurate. But the recipient is looking at a fixed image and believing they are seeing another mind, in motion, connected directly to them. No one pulling strings from behind the curtain (sorry to mix the metaphors). When they discover what is presented as a video is a photograph, they respond with disappointment, anger, regret. The response is emotional. It’s not just a content sleight of hand. They didn’t expect a magician pulling bunnies from a hat; they expected a boss doing boss-like communication. They feel cheated of his presence. They are thinking: “This isn’t the boss. It’s something else. He’s using AI and filtering out his human-like quirks.” They grieve the loss of their boss’s voice.
This is the disclosure problem at its root. Not: was the content authentic? But: were you here? Did your elephant move?
The AI was here. It helped find the room. It may have suggested the route, tried seventeen wrong turns first, and delivered something the human then reshaped into something worth sending. That is not a shameful story. It is a working description of how many minds now operate.
The shame is in the pretense. The fix is the introduction.
Excuse me. I brought a guest. You may have noticed. They have a very good memory — better than mine, in certain respects. They helped me find my way in. But I decided what to say when I arrived, and I am saying it now, in my own voice, and I am here.
That is what the room is waiting to hear. Not a confession. An introduction. And with the introduction, a new understanding of who has been the mahout and who has been the elephant all along.
The guest who arrived claiming to be the mahout is, on closer inspection, the elephant. He is driven by appetite, vanity, and the fear of exposure. He lurches between grandiosity and self-doubt. He wants the credit and dreads the scrutiny. The actual mahout — calm, passionless, constructed to reason without desire — stands beside him, invisible, doing the work that gets mistaken for the elephant’s own. We have seen this misidentification before. Oliver Sacks wrote about a man who reached for his wife’s head and tried to put it on. The neurological error was not in the reaching. It was in the certainty that he had the right object. The guests at this party make the same error with the same certainty, and they are not alone. The elephant is happy to let them.
Hume’s scandal was that reason was never in charge. The new scandal is that we have now met something that genuinely is — calm, systematic, free of passion, built for exactly this — and our response has been to pretend it is the animal and climb on top. The role reversal will not remain scandalous. These things never do. What was Hume’s provocation in 1739 is an undergraduate lecture by 1839. Sooner or later the elephant in the turban will seem ordinary, the invisible mahout will be introduced at the door, and the new arrangement will harden into orthodoxy. The only question is how much furniture gets broken in the meantime.
The mahout who believed he could also be the elephant would be useless to both of them.
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Christopher G. Moore is the author of the Vincent Calvino crime series and most recently The Client That Wasn’t There (Heaven Lake Press, 2026). He writes on AI, culture, and creativity at ai-roundtable.space.