"In the industrial age, automation came for the shoemaker and the factory-line worker," writes Dennis Yi Tenen near the start of Literary Theory for Robots. "Today, it has come for the writer, the professor, the physician, the programmer and the attorney." Like the end-of-the-planet movies that pelted the multiplexes at the turn of the millennium, newspapers and – increasingly – bookshops are awash with economists, futurologists and social semioticians talking up, down and about artificial intelligence. Even Henry Kissinger, in The Age of AI (2021), spoke of "epoch-making transformations" and an imminent "revolution in human affairs". Tenen, a tenured professor of English at New York's Columbia University, isn't nearly as apocalyptic as he initially makes out.

Anticipating the rise in Artificial Intelligence’s ability to produce original works of literature, this study suggests that literariness, or that which constitutes a text as literary, is understudied in relation to text generation. From a computational perspective, literature is particularly challenging because it typically employs figurative and ambiguous language. Literary expertise would be beneficial to understanding how meaning and emotion are conveyed in this art form but is often overlooked. We propose placing experts from two dissimilar disciplines – machine learning and literary studies – in conversation to improve the quality of AI writing. Concentrating on evaluation as a vital stage in the text generation process, the study demonstrates that benefit could be derived from literary theoretical perspectives. This knowledge would improve algorithm design and enable a deeper understanding of how AI learns and generates. This article appears in the special track on AI and Society.