The Yale Review | Three Authors on AI and the Future of Writing

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AI and the Future of Writing

A roundtable of authors discuss the ramifications for art—and life.

Ayad Akhtar, Daniel Kehlmann, and<br>Meghan O’Rourke

ON APRIL 8, at Yale University, Ayad Akhtar, Daniel Kehlmann, and Meghan O’Rourke, three writers at the vanguard of creative engagement with AI, gathered with James Surowiecki, a journalist and senior editor at The Yale Review, to talk about AI and the future of the humanities. The following conversation ranged across the social ramifications of the LLM era, from changes in our cognition to shifting notions about the nature of language itself. The transcript has been edited and condensed for clarity and concision.

—the editORs

JAMES SUROWIECKI I want to start with a really big question, but Meghan suggested that might not be the best way in. So I’ll start by easing in. Can you describe your relationship to AI at the moment?

MEGHAN O’ROURKE That is not a small question.

DANIEL KEHLMANN It’s a great question, and it’s very hard to answer. It’s not a stable relationship, because I’m still in the process of finding out what AI is and what it can do. It can be extremely helpful and utterly amazing. And, at the same time, most of us will agree that it is very dangerous. It’s very hard to have a stable inner relationship to something like that.

MO’R That’s exactly what I would have said. My relationship to AI is filtered through engaging with it as a cultural critic. I’m using it in order to write about it, and then finding it unexpectedly disarming—and, sometimes, useful. I tell myself that I have a distanced, critical relationship to it. I don’t, not totally. I’m struck, using it, by how quickly we anthropomorphize, and how susceptible we are to the power of language written in the first person.

I felt a cognate thinning, if you will, and ordering—a deeper shift. It was in the texture of our interactions.

AYAD AKHTAR In 2021, I spoke at the Philip Roth Lecture in Newark about what I called “selected affinity,” a play on the idea of “elective affinity.” It increasingly seemed to me that our cognition was at the service of automated processes. I had been feeling, I think since 2018, something elusive and systemized, as if patterns of language and behavior seemed more fixed, somehow, finding ordinal tracks, if you will.

In a way, it reminded me of what happened when the internet came of age and you saw a difference in the texture of novels: something about the research process that had become expansive and yet somehow just a little more hollow than the pre-internet novel, as if the results of the research process had less of a sense of being truly lived in.

Similarly, I felt a cognate thinning, if you will, and ordering—a deeper shift. It was in the texture of our interactions. You could see it in TV and in the movies, in publishing—the kinds of things that were getting made, the way that dramaturgical choices were being deployed. A particular hewing to the logic of a different kind of attention. It felt like it was connected to the devices where so much of our lives were increasingly being lived, a response and result of automated cognition.

Of course, in retrospect, it was about aggregation, about what we all now would call algorithmic choice: the regime of surveillance and behavior-influencing technology that was making choices for us. Selected affinities. We didn’t really have language for it at the time, but it was happening. I would say in response to your question, Jim, that the large language models are an incredible opportunity to lift the hood and see the process at work, a process that has been with us for some time and has become fundamental to all our lives.

JS What is the relationship between automated cognition tools generally—the algorithm, et cetera—and then the LLMs specifically? How is the experience of dealing with an LLM similar to or different from using Google Maps?

DK Like all important scientific revolutions and discoveries, it teaches us something about ourselves. Freud famously made that point of the three great humiliations: learning that Earth is not the center of the cosmos, that we descended from apes, and that we are not even masters of our own minds. And then on the other hand, you have the great technical revolutions and scientific discoveries, and they usually represent something glorious about the human mind, like the discovery of the steam engine, the airplane, and the first computers.

Now we have something that’s one of the truly great scientific revolutions, and at the same time, it’s a deep humiliation, on the level of finding that Earth is not the center of the universe or that we descended from animals. We have both at the same moment. And the people who are programming it—and I’m not even sure that programming is the right word—the people who are building AI, they’re not really philosophically equipped to...