To recap: we’ve seen how AI can thrust us into a world of infinite choice by theoretically translating (or eventually writing) any book out there, which is interesting from the point of view of connecting us with literature and cultures from around the world, but also exhausting, since we have more than enough to read/watch/listen to already; and then we saw how it can—with some prompting—help publishers market and explain their books. And in both instances, the material generated by AI (the Proust samples, the ��copy) is not dramatically better or worse than what the majority of humans can craft.

That said, I stated at the top (some 8,000 words ago) that my goal with these posts was to affirm the human and our ability to sense the uncanny valley of AI creations—and avoid them. Now, as we enter the final stretch, I’m going to try and convince you that not only can we sniff out AI, but that over the next five years, as a culture, we’re going to turn away from TikTok and short form narratives, reject the AI-pocalypse that is flooding our timelines, and instead seek out the full human experience, as presented by actual, living, breathing humans. Not sure I can convince myself of this hot take, but regardless, you’ll finally find out which Proust translation is which . . .

*

And we’re going to start with one of the best podcasts I’ve listened to all year: . A six-part series created and produced by , which is described as such:

Shell Game is a��podcast about things that are not what they seem, hosted by journalist Evan Ratliff. In Season One, that thing is Evan’s voice. By creating a voice clone and hooking it up to an AI chatbot, Evan set out to discover what happens when you try to take control of the very technology that threatens to replace you. Shell Game was named one of the the best podcasts of 2024 by New York Magazine and called “awesome” by The Verge. Over the course of six episodes, Evan’s voice agents talk to spammers and scammers, to Evan’s friends and family, to colleagues and sources, to other AIs, and even to a therapist—all to better understand what AI voice is able to do, what it can’t yet do, and what to expect from a future in which more and more of the people we encounter in the world aren’t real.

I’m not going to get into the details of how he does this (you can listen to the first episode and find out), but as mentioned in that (AI-created?) copy, he created a “voice agent”—an AI that uses recordings of your voice and backend scripts to do things for you such as call the doctor and set up an appointment, dispute a credit card charge, or, ideally, attend a Zoom meeting while you get wasted poolside.

This is, to put it bluntly, horrifying shit. We’ve had robocalls for ever and ever, but this is truly next level. For instance, in one episode he has his voice agent call a bunch of his friends. Some of them cotton on immediately, but one . . . doesn’t. And he’s totally unnerved by it for months afterward. (“Am I really talking to real Evan?” “Of course this is the real Evan.” “That’s what your AI said as well.”) It’s eerie to hear the recordings of AI Evan talking to a therapist at BetterHelp who takes Evan’s voice agent completely at face value. (Can you spot the difference by someone with mental health issues and an AI?) He even goes so far as to have his voice agent provide all the promotional interviews about the podcast to the tech media.

When I first discovered this podcast, I found it hilarious. Even though the concept is unnerving to say the least, the voice agent messes up a ton and you feel secure in human superiority. But by the end of the series, I was reading this a performance piece, à la Nathan Fielder. (Especially��.) Real-life Evan’s affect is pretty flat, but his AI’s is . . . odd. The pitch is a bit off. It’s a bit too excitable. It’s 99% of the way there, but you can sense the robot in the background. But putting that oddness into real life situations—the very situations that all big companies are striving for, where the only people on Zoom are AI voice agents who then summarize the content of the meeting for their real life counterparts—is funny, sure, but also illuminating as it points to something about being human that’s hard to define, but easy to recognize.

Like I said, most of his friends—along with the tech reporter interviewing AI Evan and also the founder of the voice agent service who AI Evan talks with (“I just wanted to create a system so I could have an AI call my mom.”)—recognize the ruse immediately. Then it’s up to them if they’re going to just go along with it or blow up AI Evan’s spot. And when they do, especially when they poke at AI Evan just a little bit, uncomfortably comedic things happen. Especially because the AI tends to lie and invent stuff. (See Part II, but exaggerate those little lies.) And because it gets confused—a lot. And repetitive. There’s so much, “Hey, it’s Evan. Great to hear from you. We should catch up soon” in this show.

But the three main points from Shell Game that relate to this winding series of posts are that 1) every technological advance removes something from the current state of being human (such as eliminating the richness of phone calls for two-dimensional texts; or as the phone did previously by reducing the need for face-to-face contact), 2) these things are proliferating like mad and anyone can make one and train it up in next to no time, and 3) the technology is stuck in the middle, where it’s most useful in theory, incapable of running a meeting. (My god, I only wish. I would give anything to send ChadGPT to all meetings ever.) And Evan’s fear is that we’ll remain stuck there, in the midddle, indefinitely. Anxious that AI will take over our lives and jobs, continually investing time and money into its “education,” but also encountering, over and again, these weird limitations that nevertheless mark it as inhuman. Like, for instance, the two AI translations of Proust that you most certainly have identified by now! Or, um . . .

*

This taps into a fear I’ve held for years, what I call in my head the “Interminable Middle,” or in a more dramatic, catchier fashion, the “Heat Death of Culture”: the sheer proliferation of content—be it books, short TikToks, images, music, tweets, AI voice agents that call me or talk to me in meetings—is so overwhelming that we only choose to interact with culture that we’re already familiar with, and as a result of that familiarity, everything seems . . . pretty good. Not horrible, not genius. But satisfies that “certain itch.” An itch of looking for something new that’s just like what you already like. Which, from a business point of view, we’ve always been moving in that direction, since it would eliminate risk and increase the probability of knowing that a particular cultural artifact—one that’s a close imitation of the trends and aesthetics behind a recent mega-success—would be a hit.

It’s expensive and financially risky to publish something that’s too��unusual. Not books that are “weird,” but books that are sui generis, use a style, structure, language, or method that will leave most readers questioning whether this is genius, or overrated, or just gobbledygook. The whole of literary history rides this line. Books that, in the moment, seem like insane gambles given the state of reading and book buying and what’s successful; but which, from the vantage point of the present, are brilliant bets on smart innovation.

From����to��. From����to��. There are dozens of these sorts of books out there that we could all name. What we can’t identify are the ones that fade away almost immediately. The counterexamples that, under different circumstances of time and brand and chance, could’ve been the truly “innovative” book that is talked about five years after publication.

Here are two extreme business models to choose from: 1) use AI to produce 10,000 literary works a year (including a ton of translations), by which you essentially create your own trends simply by creating a massive volume of work, teaching your AI to analyze then follow these trends in order to capitalize on them, or, 2) pay someone to analyze whatever amount of words they’re literally capable of reading, digesting that knowledge, then picking a book that could��become legendary, but is more likely to flop.

If you want money, pick number 1; choose 2 if you want to have fun. And likely lose your livelihood.

*

Although the best presses have a great editorial vision��and��enough variations and sheer volume of titles to sustain them, the second option can strike a lot of people as a form of gatekeeping. We’ll come back to this, but for the moment, I just want to acknowledge that the more people who make decisions about what does and doesn’t get get published, about what’s presented as “excellent” or “innovative” or “unique,” the better.

Regardless, from a reader’s point of view, this all sounds exhausting. Is there a need��for 10,000 new works of literature every year, just so a company can not just cover costs to stay afloat, but earn enough to produce 12,000 new books the next year? Not really. And if you want to know the state of our world, including all self-published works, ebook only publications, etc., it’s highly likely around 3 million new books are coming out every year—a majority of which are fiction. By contrast, twelve thou seems manageable.

When you reach this level of production, two things seem to happen: 1) according to the and , very very few works are astronomically popular, and almost everything else attracts next to no attention, and 2) it’s more rewarding to consume what you know is pretty good, than to spend the time looking for the uniquely genius.��

As such, the power law gets reinforced, a fewer range of works reach an ever larger amount of consumers and, because we’re chasing the “infinite middle” of culture of mass appeal amid infinite choices, everything becomes a 3.5. On GoodReads, almost all books published today are a standard deviation away from a 3.5 rating. Everything is pretty good to most people.

And if AI ran the business, churning product to be consumed by smaller and more specific audiences—but with a handful of creations every year being loved by seemingly everyone—most everything we encountered would probably be��pretty good. Passable. Human, AI, who cares? If it’s in front of me, is good enough, feels comfortable, and meets enough of my priors . . . I’d read at least 20-30 pages. And I’ll forget 95% of what I read or watch within five years. Or will conflate it with other things. It’ll all seem vaguely the same to me. Whether this is due to the difficulty of finding the unique amid an overwhelming amount of “decent” art or the onset of dementia—only time will tell!

But maybe it’s just because I read too much . . . Although if you don’t? . . . How will you ever know what’s good vs. satisfying, singular vs. competent? How do you make judgment when you can’t even experience a fraction of the possibilities?

That’s the Heat Death of the Universe I hand-wring over.

��*

And, looking toward the future, this situation is only going to get worse. You think there’s a lot of information available to you��now? Every technological innovation multiples the amount of available information. You have more pictures on your phone than were taken, globally, in, say, 1974. Information proliferates. Faster and faster all the time.

*

Let’s talk about Proust and his slow-lived, limited-information life. His going to bed habits as described to us across the years.

Six different translations of the opening pages of Proust are presented in Part I of this series. Four done by humans, two by AI. (Part II reveals that the was produced by Google Translate.)

For a long time, I went to bed early. Sometimes, as soon as my candle had gone out, my eyes closed so quickly that I didn’t have time to say to myself: “I’m falling asleep.” And, half an hour later, the thought that it was time to go to sleep woke me up; I wanted to put down the volume that I believed I still had in my hands and blow out my light; I had not stopped thinking while sleeping about what I had just read, but these reflections had taken a somewhat particular turn; it seemed to me that I myself was what the work was talking about: a church, a quartet, the rivalry of Francis I and Charles V.

To me, this it too long, too clunky. Also, although this gives away the game—note the use of “volume.” How often have you said, “I need to set down this volume.” It’s a book. It’s always a book you read in bed.

Of the six samples, number 2 is the only other one that uses the word “volume”:

For a long time, I went to bed early. Sometimes, barely had I blown out my candle, my eyes would close so quickly that I did not have time to say to myself, “I’m falling asleep.” And, half an hour later, the thought that it was time to seek sleep would awaken me; I wanted to put down the volume which I believed was still in my hands and blow out my light; I had not ceased to make reflections in my sleep on what I had just read, but these reflections had taken on a somewhat particular turn; it seemed to me that I myself was what the work spoke of: a church, a quartet, the rivalry of François I and Charles V.

And that, dear reader, was created by ChatGPT.

What’s really remarkable about this experiment was that my class, almost unanimously, chose number 2 as the best of the samples. And, , I can see why. It’s arguably the smoothest and, in some almost indefinable way, the least anxious. (But definitely the most 3.5.)

Your traction with the others may vary, but let’s look at James Grieve’s (sample 5):

Time was when I always went to bed early. Sometimes, as soon as I snuffed my candle, my eyes would close before I even had time to think, “I’m falling asleep.” And half an hour later, wakened by the idea that it must be time to go to sleep, I would feel the desire to put away my book, which I thought I was still holding, and blow out the light. While I had been sleeping, my mind had gone on thinking over what I had just been reading, although these thoughts had taken an odd turn—I had the impression that I myself had turned into the subject of the book, whether it was a church, a string quartet or the rivalry between François I and Charles V.

That opening line is so divisive! “Time was when I always went to bed early.” It barrels ahead, unlike the pause in “For a long time, I went to bed early.” Straight propulsion! And then “I snuffed my candle”??? That’s so bold! (See: “my candle scarcely out.” See: “when I had put out my candle.” “I snuffed.“) And I can bet, without knowing him at all, that there was significant thought put into this more than average deviation from the typical translation. And, he probably second-guessed himself at some point, uncertain if his choice works or if people will like it.

This is a human translation. Humans are messy. They fuck up and worry and doubt and fart and live. (And swear! That’s how you know I wrote this. Swearing is human.) It’s in the anxiety that we sense the human.

You feel anxiety in old Marcel, that’s for sure. (I love you, Marcel! I just need some space. To better appreciate you.)

Is��that��what we sense when we encounter AI? The smooth, over-confident, unquestioning nature of what it produces? But how many people stop to notice that?

*

Just so you have the full list, the translators are: Lydia Davis (1), ChatGPT (2), Original Moncrieff (3), Google Translate (4), James Grieve (5), and the Moncrieff revised by Kilmartin (6).

*

*

*

As AI improves and becomes increasingly capable of mimicking human creativity— translating our words, capturing our voices, and even calling my ex-wife so that I don’t have to—we risk losing the human touch that imbues our creations with authenticity.

And that’s precisely why the human experience will always matter. In a world flooded with AI-generated content, it’s the unique spark of the human that will stand out even more. Our imperfections, our quirks, our ability to perceive beauty in unexpected places—these are the qualities that define us and make our creations resonate. AI can churn out endless content—so much endless content—but it can’t replicate the singular.

Being human means more than just processing information; it’s about being messy. As we move forward, I believe we’ll see a resurgence of interest in the messy, in the uniquely human aspects of art and culture. People will seek out those authentic voices, the ones that speak to our shared humanity in ways no algorithm can. The more automated and digitized the world becomes, the more we’ll crave the real, the raw, the deeply personal.

We have an incredible opportunity to use AI not just to replace us but to amplify what makes us special. It can help us reach new audiences, break down barriers, and explore creative possibilities we never imagined. But it will always be our bullshit that breathes life into those possibilities.

So let’s embrace this new era with optimism. Let’s use these tools to tell our stories, to connect across cultures and languages, to share what it means to be alive in ways that only humans can. The future isn’t about AI taking over; it’s about making work-life shorter and our free-time longer—so that we can play.

*

Today, I want to look at the possibility of AI assisting publishers—and translators, and authors, and readers—in ways other than simply creating more products to sell. AI as a productive tool for marketing and, with a little luck, book discovery. In other words: Can AI help solve some of our decision fatigue both by finding you the book you should be reading and/or by helping marketing directors and publicists present books in the best possible way?

This is��frequently��on my mind—especially when it comes to writing book descriptions (aka, jacket copy), or to be honest, creating any of the materials our distributor (Consortium/Ingram) need in order to sell our books. They always have us enter in this information over what would be winter break for me (late-December through early-January), or right at the end of the school year (May). The info they need then, for pre-sales meetings,�� is referred to as a book’s metadata, and, one the base level, is super easy and quick to produce. Things like ISBN, Title, Author, Translator, Price, Rights Territories, etc. Objective, simple, factual bits of information.

But after that, things get more squishy . . . For instance, there are , which are used to categorize books, such as “FICTION / Literary” or “FICTION / Romance / Paranormal / Shifters” or “FICTION / World Literature / Scotland / 20th Century.” There are thousands of these spread across fifty-three categories. And some books (think Dubravka Ugresic’s nonfiction, think Dmitry Bykov’s hybrid work —which is about Zelenskiy, but is neither biography not cultural criticism) can fall into a number of these categories. Although figuring out exactly which categories they fall into can be confusing. (There are thousands. And although Consortium is helpful in this, no one involved in the labeling process knows both the book itself and the full list of options.) Regardless, this is an act of marketing that we have to perform as publishers. We choose what other books this book gets grouped with, and, I can only assume, some labels, some categories, would help sell more copies of a book than others through the specificity and that label’s audience.

From there, things get more subjective and require marketing insight and consideration to be optimally effective:�� bios, translator bios, keywords, and my least favorite: jacket copy. Writing jacket copy is one of my least favorite things to do, since what appeals to me about a book might not be what draws in anyone else. (I remember John O’Brien criticizing my copy because I originally used the term “postmodern.” Worth noting that he had no issue with this line from the copy for��—first jacket copy of mine to go out into the world—which reads, in part, “22-year-old philosophy student whose buttocks are so beautiful their description has been banned from the printed page.” Clearly, people prefer a nice butt to postmodern shenanigans.)

One of the issues with jacket copy—especially for translations—is that, frequently, this information has to be entered into Ingram’s system (CoreSource) before I’ve had time to edit the books, or even read them in full. This is partly my own fault for announcing books too far in advance (sometimes before the translations have even arrived), but honestly, I work just about a year in advance for the bulk of my editorial projects. And, to make this concrete, I’ll have to submit descriptions for books coming out in March 2026 before the end of this��year.

This copy isn’t fixed in stone, but it does go out to Amazon, Bookshop.org, Edelweiss+ (site for booksellers and reviewers), our website, etc., etc., so it’s pretty damn important. It’s also the basis the sales reps use to describe our books to buyers at bookstores, and is likely what book review editors will also see.

As with the Proust AI translation exercise detailed in Part I—I haven’t forgotten, you’ll get the answer key soon!—it’s debatable how much value is added by having slightly better copy. But there is great value in freeing up your time and mental energy for other projects. And my god how I stress out over writing copy! If only I knew what words and phrases people gravitated toward (butts?), or what’s worked in the past, or if there’s a secret formula . . .

Enter AI! Every day, I’m barraged by dozens of ads for how AI can make my work life easier and more efficient. “Remember when we wrote emails without AI?” is a scoff I hear on the regular. (To those few who receive them, could you imagine AI writing my��emails? I joked about this a couple years back in this post, but seriously, if you think these posts are long and rambling and digressive and sort of dirty, you should be one of my pen pals!) But given just how much corporations are leaning into the whole “integrate AI into your workflow” thing—and I admit, there are many benefits, and many emails I’ve received should have been written by AI so the sender would’ve avoided sounding like a simpleton, or simply to fix the tone—maybe it is possible that AI could solve jacket copy . . . Not to mention the other two metadata categories that cause me fits: Key Selling Points (reasons why anyone would want this book, independent of its content) and Publicity Plans (which all sort of fall into a pattern of sameness, given how little time and few resources we have to get truly creative and go big). Save me, ChatGPT! Make my metadata better!

*

Before going to ChatGPT to explore the possibilities, I fooled around with some knock-off AI options, such as , the name of which delights me. I found it in a Reddit thread where someone wanted an AI service so they could ask questions about specific books. (To make essay writing for class easier, I assume.) This is the headline at the top of its very sparse webpage:

Search for a book that you want to ask questions to – Powered by ChatGPT

You only need the book title, and Artificial Intelligence takes care of the rest

Promising! Or at least potentially fun.

Now, I had my doubts as to whether this service would actually have any Open Letter books listed, but lo and behold, ��pops right up!

As you can see, what I asked AI Book Nerd (which really should have its own Instagram account to share the weirdest query results) was to summarize NETD.��And here’s the nonsense it spat out:

WTF. Like, literally, What. In. The. Fuck.

What blows my mind about this is that our jacket copy is readily available! It’s eminently findable! That’s truly what I was expecting to get as a response. “The conquest of Mexico is over, and Juan de Toñanes is one of so many soldiers without glory who roam like beggars for the land they helped subdue. When he receives one last mission, to hunt down a renegade Indian who’s called the Father . . .” I mean, it’s right there. What is this “mysterious literary society in Madrid”? And “Grigor Fedorov”??�� GTFO.

Now, it’s super easy to goof on AI mistakes—and easy to feed it misinformation so that it believes “belief” has 3 S’s in it—and sure, it’ll get better, but at first glance, what it seems best at is lying and gaslighting users. For instance, in prepping our recent newsletter about the release of Dubravka Ugresic’s , I wanted to revisit the .��So I googled “Kirkus Reviews Dubravka Ugresic” and received this tiny, and totally inaccurate, summary from Gemini AI, Google’s in house AI service.

That “overview” is immediately above the top search result which, duh and or obviously, happens to be the . So, in short, Google has an AI summary bot that can’t incorporate data from��its own search engine????

Again, the value in pointing out these flaws is mostly humorous. (Or maybe a work of performative art. Tune in to Part III for more on that.) Although, before shifting gears, I do have one more funny to make. I asked ChatGPT over the summer to write “an ode to J.D. Vance in the style of Rupi Kaur” and I got this gem:

your cushions hold
the weight of my dreams
the spills
of my late-night thoughts

Amazing! And wow! Can’t figure out that Kirkus��reviewed , but is right on point with J.D. and his couch proclivities. This is the future.

*

But what if we swerve from the idea of AI being able to digest a text, distill it, and know how to market it to actual humans for a second, and instead look to AI for helping us wade through the endless amount of product out there? We’ve fretted about “the algorithm” for years, noting how Instagram ads “just happen” to match up with the topics we were just��talking about. We know that Amazon, for decades now, has used their special algorithm to recommend products and has been working on “” to send you products you didn’t know you needed until they arrive.

AI adds some wrinkles to this concept. Although it’s built via algorithms, AI veers from calculation into the realm of “intelligence,” making decisions based on factors that aren’t 100% mathematic. Totally linked ideas, yet separate.

There have been a lot of algorithmic-based book recommendation engines over the years outside of Amazon. BookLamp (defunct after being sold to Apple to be the algorithm powering the wildly popular [sic] Apple Books app), , , . All of these apply different strategies for how they evaluate and compare books—for instance, Small Demons is all about proper nouns, BookLamp used “Book DNA” à la Pandora to parse books across hundreds of “genetic” elements—but all of these rely on their inputs and the human thinking behind how to categorize and group books.

For example: When BookLamp was available, I once asked it to recommend books I would like if I liked����and, based on the “BookDNA” which included high marks in “Vehicular Fiction” and “Southern Family Saga” recommend to me a YA title about a teenager growing up in Mississippi. Swing and a miss!

Or, in the case of WhichBook—where you choose four categories and how extreme you want the recommendations to be in each—I asked for something “funny,” “disturbing,” “unusual,” and with “extreme sexual content” and was lead directly to . Regardless, although the connection between the service’s structure and the user’s input are connected by advanced algorithms, these tend to have�� wildly inaccurate recommendations.

But if making fun of bad AI results is silly and not advancing any ideas, dunking on the algorithm is just as pointless. In terms of books—or any cultural product—the algorithm ignores style. The connections made between artworks have to be more easily mappable. Figuring out how to quantify Faulkner’s style is too advanced for the machine circa 2013.

By contrast, an AI recommendation bot could, in theory, make decisions for you that aren’t so beholden to this sort of quantified analysis. In the abstract, these recommendations would be more akin to our own decision-making process—current mood, environmental trends, overall vibes, inexplicable longings—and would be more focused on what you should read now for the greatest benefit, whatever that may be. (Acquiring knowledge, entertainment, linguistic puzzling, fodder for the cocktail party at the country club.) I could input the 30 books on my current “to read” pile and it would decide for me what to read, and in what order. Although maybe it would lie? Tell me “there is no new book by Kate Atkinson”?

*

So, the question is: can it do that? I mean, I asked ChatGPT to convince me why the St. Louis Cardinals would win the World Series this year and it referenced a half-dozen players who haven’t played for the team in years. Devoted as I am to actual experiential results and not just half-assed theorizing, I literally just had this conversation with ChatGPT:

CWP: tell me what book i should read next

ChatGPT: I can recommend a book based on what you’re interested in! Do you prefer fiction or non-fiction? Any particular genres or themes you enjoy, like sci-fi, fantasy, history, or personal development? Let me know what you’re in the mood for.

CWP: literary fiction in translation that is linguistically and structurally complicated

[ChatGPT recommends by Haruki Murakami,����and����by Roberto Bolaño,����by Andrei Bely, and����by Julio Cortázar. Three of these are three of my favorite books of all time.]

CWP: I’ve read all of those. Give me a similar recommendation from a book released in 2024

ChatGPT: For a literary fiction recommendation in translation from 2024, you might enjoy by Agustín Fernández Mallo, translated from Spanish by Thomas Bunstead. Set in a dystopian future, this experimental novel blends fiction, philosophy, and reflections on artificial intelligence, while examining the nature of human relationships. Its complex narrative and style, reminiscent of Borges and Bolaño, explore the meaning of love and humanity in an era dominated by technology. It’s expected to be a rich, structurally intricate read, ideal for those who appreciate both intellectual depth and narrative experimentation​. Another upcoming release is by Marina Yuszczuk, translated from Spanish by Heather Cleary. This feminist, gothic novel interweaves two time periods and explores themes of loneliness, desire, and motherhood through the stories of a vampire in 19th-century South America and a modern-day woman in Buenos Aires​.

Both of these works promise the kind of linguistic and structural complexity you’re looking for!

[OK. Wow. I may think Mallo is overrated, but I’ve read everything available in English. And a book about AI talking about the human vs. inhuman? Sounds . . . familiar. And anything Heather Cleary translates is gold.]

CWP: based on what I’ve told you, out of these three books, which should I read next: by Rachel Kushner, by Kate Atkinson, or by Jose Donoso?

ChatGPT: Based on your preference for linguistically and structurally complicated fiction, I would recommend reading ““ by José Donoso next. This novel is an intricate masterpiece of Latin American literature, known for its surreal, fragmented narrative and dense prose. It delves deep into themes of madness, identity, and reality, with a nonlinear structure that constantly shifts between perspectives and timelines. The complexity of the novel aligns well with your interest in challenging, layered texts.

While Rachel Kushner’s and Kate Atkinson’s are both engaging in their own ways, neither matches the level of linguistic experimentation and structural innovation found in Donoso’s work. offers a unique, immersive challenge that seems perfectly suited to your tastes!

I thought it would be fun to try and unpack some of these ideas against Proust’s very slow, very over-stuffed masterpiece, since most of these are very contemporary concerns that revolve around the explosion of information and ways of accessing it, whereas Marcel spends so much time idling, chasing chicks, attending parties, explaining the intricacies of ballroom and salon life by namedropping hundreds of ducs, duchesses, marquises, and the like, with the Dreyfus Affair being one of the few topical topics presented in the book of which most (some? a few?) of today’s readers will have previous knowledge.

[There’s a reason that, for volume four alone, there are 402 footnotes spread across 30 pages. That’s one of the seven volumes. One.]

I wrote an intro post alluding to this scheme, then one when I finished Swann’s Way, then . . . disappeared for most of 2024.

That was bound to happen—I’m not good at carrying through on my schemes—but there’s also a larger reason, which is where I want to start this, the second official entry in my scheme (with parts three and four coming later this week). Namely, I want to be a polyamorous reader.

I mean, it always��sounds��good at the start of year to commit to some big, overarching goal. (Hence, New Year’s resolutions.) It’s exciting to think that every day I’d have 10, um, pages of Proust penetrating my mind until I had consumed him whole. But after 60, 70, 200 days of mostly the same things—party, girls, jealousy, striations of high society, it all gets a little . . . vanilla. I need some variety. I’m not a one-author sort of man!

Given that 99% of my reading time is dedicated to editing books for Open Letter (, , , ) or Dalkey Archive (, ) and cranking out OCR conversions so that as many Dalkey titles as possible are available to interested readers (for a bit more detail about this, backlists, POD, etc., see forthcoming post), I have very little time for “fun” reading. And there are new books by , , , , , , , , .[1] That doesn’t even include other books, like Megan McDowell’s retranslation of����(dying to get to),��the books I’ve been carrying around for years, or the books that I’m addicted to thanks to the all-too brilliant Apple+ TV App Streaming TV show. And there are thousands more backlist titles I’d like to discover or reread—including the hundreds of Dalkey titles that I want to either a) make available available again for readers like you, or b) that I need to reread for my longer book project. (I’m not��giving up on this project. Trust me?)

In short: Proust is great, but I need to have some other connections. I’m sorry, Marcel, but we’re gonna need to open this shit up. It’s not you . . . well, it’s sort of you . . . but really, it’s just that there are so so many attractive options out there, all available to me, all offering up varying levels of joy and satisfaction. And what would life be like if you didn’t explore your larger interests? I’m not leaving you, Marcel, I’m not. I just don’t need your 10 pages a day . . . We can extend this relationship . . . cool things off a bit . . . deescalate, as the kids say . . . I mean, I��only��have 1,301 pages left. We’ll get there. It’ll be OK.

*

Before we get to the personal, let’s start at the practical. At the highest level of publishing��as��business. Publishing as activity to produce product that produces money. A level that makes me uncomfortable—where not everybody on staff could possibly read all their own books—but one that AI, our hand-wringing meta-topic for the next three posts could play a significant role. So that’s where we’ll start: how AI (ChatGPT being the tool most people are familiar with, and is what I used while writing this) could impact larger publishing issues of strategy and production.

Totally oversimplifying here, but: All budgets consist of fixed costs (salaries, operational expenses like rent and supplies, things that are constant regardless of how many books are produced), and variable costs (advances, individual book marketing expenses, printing costs, etc., things that are contingent on the details of the individual products and how many of them are produced), which are offset by revenues generated by sales (frontlist and backlist, subrights, merchandise [haha]) and, in the case of nonprofits, donations. (If you’re a press like Biblioasis or Deep Vellum with a indie bookstore associated with the press, that could also be a revenue stream. And you should all get to Windsor, Ontario. Biblioasis’s store is a dream.) Which, from a capitalist viewpoint, flows into the idea that the more profitable products you can produce while keeping fixed costs low will lead to long-term financial success. Profits. Bonuses. Private jets.

For example, let’s lowball it all and say a press has five employees and fixed costs of $400,000/year ($320,000 in salaries and benefits, $50,000 in rent and utilities, $30,000 in other business expenses). And let’s just use $20,000 as a starting point for the cost of doing an individual book—in a traditional fashion with advances and fees paid to the author and translator (when applicable)—costs $20,000 to produce ($10,000 in artist expenses, $8,000 in printing, $2,000 in marketing).

If you do one single book a year, your overall expenses are $420,000 and you would have to sell approximately 60,000 units of a book with a list price of $20 to simply break even—which would necessitate and additional $140,000 in printing bills (on top of the initial $8,000), and at the end of which, you would owe around $90,000 in royalties . . .

[Just to clarify, of that $20 list price, $10 goes as a discount to retailers, and ~30% of net receipts to your distributor, so you’d earn about $7/unit. And that doesn’t include extraneous fees, which tend to be legion if you’re with any of the main distributors—aka Ingram Publishing Services—available to indie presses. If you’re able to do your own��distribution, this whole model would change, adding on astronomically high warehouse and technology costs, many new employees, etc., but you wouldn’t have to pay yourself for doing the distribution, so your net income per book should be higher.]

From here, things get scaled: Publish 10 books and your overall budget needs to be $620,000 and you need to sell 88,571 total units or 8,857 per title just to break even. Move it to 50 titles a year and, well, your employees will hate you (remember, we set the number of staff at five for this exercise) and you’ll face issues of differentiation and sales velocity (topics for later), but the overall budget is $1,420,000, requiring 202,857 total net sales, or 4,057 per title. Again, this is only to offset expenses—not even turn a profit! We’re starting to get into a space where you can squint and see a pathway to the black . . . (Although, again, the printing cost of $8,000 does not accommodate this volume of sales. I’m working on an Excel model of all this mostly to see if I can. And because I’m a dork.)

I’m leaving out several things, intentionally. Sales of foreign rights and audiobooks would contribute to the bottom line, sure, but not in a way significant enough to really alter this model. Donations would, but, again, that’s a different post. Backlist sales would though, significantly. As John O’Brien would say, “If we had 500 backlist titles selling an average of 75 copies a year, that would be 37,500 units and a couple hundred thousand in sales and would act like a functioning endowment of sorts.” This is especially fruitful if you already have the stock sitting in a warehouse, or if you just put all your titles up in LightningSource (a print-on-demand service at Ingram) and save on all upfront printing costs for books that will likely sell a consistent 40-100 copies a year.

Plugging this backlist treasure-trove into my model above, if you did 50 books a year, had that five employee set-up, cranked out product, and had a giant backlist (say 1,000 titles) to rely on, you would only need to sell 2,557 units on average of each frontlist title (the new books coming out in a given year, versus backlist, which is everything from the past) over the course of a year.

If you’re interested, I’m planning on writing more about this same thing with relation to Dalkey’s backlist in the next which is, ostensibly, about ‘s Cuanduine Trilogy.

And this sort of scheming plays a large role in the Mining the Dalkey Archive��book I’m slowly working on (forthcoming sometime, maybe, fingers crossed). Publishing runs like a Ponzi scheme, printing Peter to pay Mary to steal from Paul, and John added his own twists to this.

But here and now, we’re about to take two very bleak turns, play a game, and set up the next two pieces of this series (which are shorter! Most of the heavy lifting is here).

*

I promise you that by the end, I’ll reassert the integral importance of editorial vision as it relates to readership, being a global literary citizen, and value, but for today, we’re going Pure Amoral Capitalist.

As anyone in the industry knows, predicting overall book sales is a bit of a fool’s errand. There’s not enough market research to provide useful comps, things breakout for random reasons (remember the year of adult coloring books?), the best titles fail because of a pandemic. But if you do this for long enough—like twenty-five years—you can get pretty good at assessing the floor and ceiling for a given book. “That’ll probably sell 700, but could do 2,000 if things broke the right way, or 300 if they don’t” is a typical statement with insanely broad error bars. Give me enough historical data and time, and I can probably get this within 300 or so units for 90% of books, but the point is: Assuming you can sell, on average, 3,500 copies of a book in one year is a wild swing, and hard to pull off for most presses smaller than New Directions, Graywolf, or New York Review Books.

This��used��to be possible, but, tipping my pitches here, there are just too many books nowadays. With so many options, so much noise, the average sales per title have been depressed over the past couple decades. A certain percentage of titles take off and sell far more than 3,000, but the rest don’t even sniff that number.

As such, and employing Dark Capitalist Mojo, the most likely route to broad financial success is throwing more and more��books into the marketplace while keeping a chokehold on fixed expenses. Something is sure to stick! Turn publishing away from an editorial enterprise into a numbers game. And what if you can do that by keeping down��both��fixed costs and variable ones? Like, what if you didn’t have to pay a printing bill unless it was tied to actual sales (the print to order strategy mentioned above, but for everything)?�� And/or cut down on artist expenses?

Print-to-order is a reality to be addressed elsewhere, but limiting payments to artists is where AI comes in.

*

For years now, in my World Literature and Translation class, the first assignment is an evaluation of multiple translations of the same piece of literature. I’ve used multiple versions of ��for years—always fun and, in lieu of , it’s interesting that the Pevear and Volokhonsky never fared well, and to be honest, that was also my least favorite of the translations—but this year I got bored and decided to switch things up. And trick my students in the process.

What I did was provide them with six unmarked samples (you can download all six versions if you want to play along at home , , , , , ) of the opening pages of Proust’s . (Now that I’m blowing this game, next time I teach this, I should probably use part of . Following with my prescribed rubric, the spirit of volume two—especially the Balbec section about all the young girls blossoming around Marcel and the peripatetic nature of his attraction to each—hovers over the rest of this post.) I told them��nothing��about where these came from—just that they had to pick the one they would publish and write a paper articulating why that version, both in terms of what sets it apart from the others and how those others fall short.

Here’s the opening from each of the six versions:

For a long time, I went to bed early. Sometimes, my candle scarcely out, my eyes would close so quickly that I did not have time to say to myself: “I’m falling asleep.” And, half an hour later, the thought that it was time to try to sleep would wake me; I wanted to put down the book I thought I still had in my hands and blow out my light; I had not ceased while sleeping to form reflections on what I had just read, but these reflections had taken a rather peculiar turn; it seemed to me that I myself was what the book was talking about: a church, a quartet, the rivalry between François I and Charles V. (Version 1)

For a long time, I went to bed early. Sometimes, barely had I blown out my candle, my eyes would close so quickly that I did not have time to say to myself, “I’m falling asleep.” And, half an hour later, the thought that it was time to seek sleep would awaken me; I wanted to put down the volume which I believed was still in my hands and blow out my light; I had not ceased to make reflections in my sleep on what I had just read, but these reflections had taken on a somewhat particular turn; it seemed to me that I myself was what the work spoke of: a church, a quartet, the rivalry of François I and Charles V. (Version 2)

For a long time I went to bed early. Sometimes, when I had put out my candle, my eyes would close so quickly that I had not even time to say “I’m going to sleep.” And half an hour later the thought that it was time to go to sleep would awaken me; I would try to put away the book which, I imagined, was still in my hands, and to blow out the light; I had been thinking all the time, while I was asleep, of what I had just been reading, but my thoughts had run into a channel of their own, until I myself seemed actually to have become the subject of my book: a church, a quartet, the rivalry between François I and Charles V. (Version 3)

For a long time, I went to bed early. Sometimes, as soon as my candle had gone out, my eyes closed so quickly that I didn’t have time to say to myself: “I’m falling asleep.” And, half an hour later, the thought that it was time to go to sleep woke me up; I wanted to put down the volume that I believed I still had in my hands and blow out my light; I had not stopped thinking while sleeping about what I had just read, but these reflections had taken a somewhat particular turn; it seemed to me that I myself was what the work was talking about: a church, a quartet, the rivalry of Francis I and Charles V. (Version 4)

Time was when I always went to bed early. Sometimes, as soon as I snuffed my candle, my eyes would close before I even had time to think, “I’m falling asleep.” And half an hour later, wakened by the idea that it must be time to go to sleep, I would feel the desire to put away my book, which I thought I was still holding, and blow out the light. While I had been sleeping, my mind had gone on thinking over what I had just been reading, although these thoughts had taken an odd turn—I had the impression that I myself had turned into the subject of the book, whether it was a church, a string quartet or the rivalry between François I and Charles V. (Version 5)

For a long time I would go to bed early. Sometimes, the candle barely out, my eyes closed so quickly that I did not have time to tell myself: “I’m falling asleep.” And half an hour later the thought that it was time to look for sleep would awaken me; I would make as if to put away the book which I imagined was still in my hands, and to blow out the light; I had gone on thinking, while I was asleep, about what I had just been reading, but these thoughts had taken a rather peculiar tum; it seemed to me that I myself was the immediate subject of my book: a church, a quartet, the rivalry between Fran9ois I and Charles V. (Version 6)

I’ll give you the results of my mini-survey later, but before anything else is revealed, you should take a minute and pick out a) which one(s) you would read/publish, and b) which one(s) you absolutely would not. Hint: Four are by human translators, two aren’t.

*

This class took place at the height of AI Anxiety within our industry. . . . Nobody wanted to lose their job to a fucking AI—especially AI “trained” on the backs of human labor.

You can probably see where this is going . . . Operating under the core-capitalist principle of making as much money as possible, consequences be damned, a publisher could be pulled to employ AI to create its works. At first blush, I suspect we’d all hesitate at the idea that AI could invent a full book . . . ? Have you read ? (No. Not the one you’re thinking of.) There’s so much shit out there in the world that is competently written, but not particularly good. Using various prompts and scripts, reference points, and craft books, I’m willing to bet that we’re not far away from version X.X of ChatGPT being produce something that’s passable. () And the same goes for translation. (We wouldn’t be so anxious if we didn’t think it was at least possible.) The real question is: What makes a piece of writing “passable”? And if it’s “passable,” is that good enough? Would you��really know if that totally mid book you stumbled up and decided to read for whatever reason was written by a “real,” living writer.

My argument—which is more of a hot take, a wish-fulfillment fantasy—is that there is something inherently human in human-created art, something we can’t identify but that we’re attracted to. As if our subconscious can feel the uncanny valley and then subtly rejects it. What does it mean to be inhuman though? And what does that look like when there are just words on a page? But you have to wait for Part III to get the full picture of my bold—and way too optimistic—statement about the future of culture.

For now though . . . AI shit passes when it comes to translation. It’s not perfect, it may not even be great, but in a void with no referents, it probably won’t stand out. Poor writing is. Poorly written books are published. AI is “good enough.”

By now, I’m sure you’ve picked out one of the AI versions above—but did you identify both?

*

Remember the 3% Problem? I’ve been distancing myself from it for a bit to focus less on production and more on the books that are published, but for anyone unaware,�� this “problem”—and the name of this blog—comes from the fact that 3% of the total number of books published in the U.S. are in translation. I can give you a mathematical argument that in 2024 that percentage is actually much lower; I can show you that the average number of translations actually published has been on the rise, with peaks and valleys, over the past couple decades.

The point is: There are so many great books in the world, so many essential voices, and no possible way to publish even a fraction of them given the publishing constraints detailed above. The sales aren’t there to make the money work. Full stop.Beyond that, how many books could all the professional English-language translators in the world produce in a given year? Ignore the low wages and fact these translators would need to sustain themselves, somehow, I’m just thinking of the time.��It’s a fascinating thought experiment to try and establish the upper limit of translation possibility. Is it . . . 10,000 books? 25,000? 100,000? Whatever the ceiling might be, it’s for sure only a fraction of a fraction of a fraction of the total works published in a given year—and a microscopic percentage of all that already exists out there.

But, you know, if AI was “good enough” . . . and you invested heavily in production . . . there’s no reason you couldn’t churn out 1,000 translations a year, paying no one except for the original rights holder, a typesetter (soon to be replaced by AI that can take InDesign templates and go) and a proofreader (hahahaha who the fuck cares) and someone to upload the files into LightningSource. These books likely wouldn’t sell very many copies, but if they each sold a minimum of 200? And, say, 100 of them sell 1,000 units, 1o sell 5,000, and 1 sells 25,000? It’s a numbers game, baby, and the more titles you make available, the more likely you are to hit the lotto with one of them.

*

Thinking about publishing 1,000 books a year gives me hives. Hell, more that 24 is a bit of a nightmare for a small press or anyone hoping to read and think about each of the books they publish. I can’t even decide which book to read next for fun, in my spare time. I finished Spook Street by Mick Herron last night as my “book for fun” (currently editing António Lobo Antunes’s��, proofing Stanley Elkin’s , doing a final pass on Javier Serena’s��, correcting the OCR of Eshkol Nevo’s , and reading Layla Martinez’s����for a different post—all “work” books) and have no fewer than thirty titles in front of me (plus a dozen or more on my Kindle) that I really want to read. But how does one make a choice? You’ll never read everything, so just pick something . . .

But what if I want to watch something instead? I can’t even guesstimate how many movies I’ve missed out on in the past decade, and I have subscriptions to Netflix, Hulu, Max, Disney+, Apple+ TV, Paramount+ (enough with the plusses already!), and probably something I forgot about, like Tubi or Criterion.

Although honestly, I just want to find time to listen to music. I have 1,929 songs in my “2024 Music” playlist to explore. And that’s��only��releases from this year. (And doesn’t include a single Chappell Roan song or Taylor Swift remix.)

All of that is real, and even if it’s presented in a cheesy way (or corny? what food metaphor is most dismissive these days?), the point is valid: there’s no shortage of content. If I were 30 years younger (or 40??), you could add to my content consumption habits hours of YouTube videos, short-form video content on Instagram and TikTok, and other social media platforms that traffic in information sharing as entertainment and time-wasting—it’s overwhelming. There is simply too much information.

Making a choice in the face of infinite choices requires heuristics to help trim things down to a reasonable number. Although I don’t think you��can��get to a reasonable number while engaging with the “new.” You can stay in the 1990s music wise and forget all things that came out since. Revisit the list of movies you imprinted on. Or, what I tend to do with books (remember that list of authors above?), is read all the new titles by authors I already know I like. That’s a good bet, and gives my reading life a sort of continuity. Even if it’s not their best work, it’s likely to be comfortable, familiar. (Although, to be honest, I choose the books I read by setting up strange schemes for myself related to ideas I want to write about, such as the NBA and NTA longlists for Translated Literature. Or fucking Proust.)

Translated literature functions as a sort of sub-genre that helps in terms of selection. You could, if you so chose, read a significant percentage of translations published in a given year. But that’s because the new number of translated works of fiction and poetry coming out in a given year is around 600. Now, imagine if there were an additional 10,000 literary translations available every year. How would you parse that? What are you missing out on? How do you find a community when, if everyone you know followed their own impulse, it’s possible that none of you ever read the same book?

Decision-making is a notoriously energy consuming activity. It’s why certain successful businessmen own endless variations of the same suit—they don’t have to waste time deciding what to wear. But seriously, it’s exhausting trying to wade through all the entertainment possibilities available to us. And the available information multiplies all the time. As a result, no matter how much media one consumes, it’s a smaller and smaller percentage of the whole. Which, for some, can be anxiety making. It’s daunting! And, for the average person, leads back to consuming the things you already know, or the things that are incredibly popular (see: nostalgia).

And that’s where we’ll leave things for today. Up next: AI and marketing.

[1] These names will come up again later in an important context.