Not gonna lie, it has always been a dream of mine, a marker of being a Real Writer, to do a New York Times Book Review “By the Book” interview, and this summer I did it. Really fun — I got to praise a lot of writers I truly admire (including Janet Malcolm, who I sort of hoped would read it, and who died the day before the interview came out.) and hopefully helped generate some publicity for Shape.
I also recently got beta access to Open AI’s “GPT-3” text-generation engine. So I thought it would be fun to give it part of my interview and see what happened if I asked it to continue.
Here are some results. What’s bold is text I supplied to GPT-3 (along with the whole text of the interview previous to that line.) This uses the davinci engine, with temperature set to 0.7.
What kind of reader were you as a child? Which childhood books and authors stick with you most?
I read “The Little House on the Prairie” series as it came out, and I think I really liked them. I reread “The Hobbit” and “The Lord of the Rings” many times. I loved “The Hobbit” so much I would reread the whole thing and just skip the long chapters. The first adult book I read was “The Heart Is a Lonely Hunter” by Carson McCullers, when I was 10 or 11, because I loved the title so much. It was a little hard to get into because it was so slow, but I was so happy to be reading a book that was all about people being sad, because I was so sad!
What’s the best book you’ve ever received as a gift?
“The Go-Between,” by L. P. Hartley. I know it’s a cliché, but it’s so perfect.
If you could require the president to read one book, what would it be?
Note that GPT-3 has enough text to recognize this as a “By The Book” interview, because the two questions it generates are indeed on the standard list of questions that the NYTBR asks authors. “Temperature” is a measure of how constrained GPT-3 feels to pick the word it seems most likely at each stage. One cool thing about the interface is it gives you the probability distribution it drew from for each word. THe word “Heart” above, for instance, is one of the lowest-probability words in the above response; GPT-3 rated it the 11th most likely next word, with a probability of 0.8%. Top three were “Cat” (4.0%), “Aut” (1.7%), and “Fountain” (1.7%). Wait, “Aut”? Yeah — GPT-3 uses “tokens,” not words, and sometimes these are parts of words, or even just initial letters. I imagine “Aut” could have been the beginning of “Autobiography” or “Author.” Presumably running the algorithm at a lower temperature would have made it much more likely I’d have read something starting with “The Cat.” Having settled on “Heart,” the following word “is” came in with an 87% probability, far above the next most likely candidate, “of.”
In fact, it’s kind of cool how the OpenAI interface displays these probabilities, so I’m gonna screenshot and include:

Red means unlikely, green means likely — so you can see very clearly the red “Heart” and the green “Is.” Note that the standard questions from “By the Book” are almost all green once you get past the first word; you’re on a track the algorithm’s very confident about. “The Go-Between,” by L.P. Hartley is a real book, by the way, though not one I’d ever heard of, and not one I think my earlier responses could fairly be said to make you think I’d like. The answer itself, though, while it’s not my style, is very much “By the Book” style.
Here’s what you get at temperature 0:
What kind of reader were you as a child? Which childhood books and authors stick with you most?
I was a voracious reader, but I don’t remember any particular books. I remember the feeling of being in a room with a book. I remember the feeling of being in a room with a book and a window. I remember the feeling of being in a room with a book and a window and a tree outside the window. I remember the feeling of being in a room with a book and a window and a tree outside the window and a friend in the room. I remember the feeling of being in a room with a book and a window and a tree outside the window and a friend in the room and a dog in the room. I remember the feeling of being in a room with a book and a window and a tree outside the window and a friend in the room and a dog in the room and a cat in the room. I remember the feeling of being in a room with a book and a window and a tree outside the window and a friend in the room and a dog in the room and a cat in the room and a hamster in the room. I remember the feeling of being in a room with a book and a window and a tree outside the window and a friend in the room and a dog in the room and a cat in the room and a hamster in the room and a goldfish in the room. I remember the feeling of being in a room with a book and a window and a tree outside the window and a friend in the room and a dog in the room and a cat in the room and a hamster in the room and a goldfish in the room and a bird in the room. I remember the feeling of being in a room with a book and a window and a tree outside the window and a friend in the room and a dog in
This is pretty typical. If you pick the most likely “next word” every time, you get stuck repeating yourself, getting more and more certain that staying in the loop is the right thing to do because after all it’s what you’ve been doing! The only even moderately low-probability words here occur when a new animal is introduced to the room.
What about temperature 1, giving GPT-3 maximal license to draw less-likely next tokens? (Maybe temp 1 means literally draw from the imputed distribution? I’m not sure.)
What kind of reader were you as a child? Which childhood books and authors stick with you most?
Neil Postman recommended “Wind in the Willows,” which my mother read to me and I read at my mother’s knee, many many times, more times than I can count. I come back to it every year or so, and it’s still a great book. I also was nuts about “Blondie”; the single joke in the joke book never loses its appeal for me. I loved “Black Beauty” and several other Victorian kids’ classics with similar emotional power; I haven’t read them again yet because I never have any time. I can’t forget how much I loved it the first time I read it.
Anything you’d recommend to someone new to your books?
“Lovecraft Country,” without a doubt. Also my essay in the Yale series, “Mao II and Then Some.” I also think my Song of Ice and Fire “house style” recaps (here, here, here and piecemeal here); they’re the most comfortable thing I’ve written. Even my husband likes them, and he doesn’t care about the show or the books. And the recent article on swaddling.
Edited to make explicit that in-kind donations by the author also serve as p.r. I should have included them, which I wish I had done.
Well, this is the most fun at any rate. I love the idea that Neil Postman was recommending books to childhood me, and to my mom, I guess. This one actually feels to me the most like my own prose style, even as the things it says don’t quite make sense? Maybe there’s a tradeoff between style and sense. At any rate, there is no actual essay called “Mao II and Then Some,” but that’s 100% a title I would use, and DeLillo really is a writer I admire and didn’t mention in the piece. “Anything you’d recommend to someone new to your books?” is not one of NYTBR’s standard questions for this feature, but doesn’t it sound like one? Oh, here’s the color chart so you can see how much redder and more daring this output is.

Impressive work — and let me emphasize that I just did those three runs and that’s what I showed you, no cherry-picking of the best output. Not something that makes me feel easily impersonable, of course. But I didn’t give it that much of my writing….!