The Routledge Handbook of AI and Literature provides an invaluable resource for those interested in deepening their understanding of the variety of theories and approaches available when AI is studied or deployed in literary contexts. It also illustrates ways in which AI researchers can use literary lenses to better understand the sociotechnical dynamics and cultural imaginaries shaping human interactions with AI. Both AI and literature are understood in their broadest senses here. The book incorporates chapters that deal with Large Language Models, Generative AI, transformer architectures, story generators, and computational analysis. Literary case studies embrace performance, poetry, comics, as well as prose, and span a wide range of historical periods, from the ancient world to contemporary science fiction and Generative AI poetry. The Handbook brings together early career contributors, as well as some of the best-known names in the digital humanities and computational literary studies. It offers a fresh perspective on the past, present, and future of AI and literature that will appeal to students and scholars with relevant interests across a range of subjects, including AI Engineering, Classics, Computing, Digital Humanities, English, Ethics, Film and Television, Law, and Narratology.

Table of Contents:
Introduction 1. Why AI and literature? Will Slocombe and Genevieve Liveley Section 1: AI Authors 2. The author, poor bastard: writing, creativity, AI Caroline Basset 3. Does writing have a future? David J. Gunkel 4. A brief history of computer-generated literature: in search of the author Tuuli Hongisto 5. Emerging models of AI ‘authorship’ in popular discourse Sara Bimo Section 2: AI Voices 6. Oracle, echo, or stochastic parrot? who (or what) speaks in AI-generated literature? Siebe Bluijs 7. Free spaces of imaginal adventure: voicing silence in AI and literature Genevieve Liveley and Natalie J. Swain 8. The AI question, or what if Homer had ChatGPT? Richard Cole 9. The voice of the platform Laura Piippo Section 3: AI Interrogations 10. There has never been an intelligent literature Michael Marcinkowski 11. Shakespeare didn’t brainstorm: Why literature proves that there’s more to intelligence than AI Angus Fletcher 12. A token effort? Reflections on the authoring of (science) fiction in an age of ‘artificial intelligence’ Paul Graham Raven Section 4: AI Narratives 13. AIs reading AI narratives? Will Slocombe 14. AI 2041: critical design fiction? Jo Lindsay Walton 15. Digital, deep fake and glitch twins in the cultural imaginaries of generative AI Edward King 16. The rise of the artificial boyfriend: artificial partners past, present, and future Timothy Miller Section 5: AI Ethics 17. (Un)ethical extractions: conceptual writing, appropriation, and the poetics of the public domain Kasia Van Schaik 18. ‘Full of stories’: AI, literature, and the law Rebecca Shaw 19. Rethinking intentionality in the era of AI Joanne Lipson Freed Section 6: AI Interdisciplinarities 20. Computational literary studies and AI Katherine Bode and Charlotte Bradley 21. What to expect when you’re expecting: on the creative potential of generative AI Tony Veale 22. Electricity and Alchemy: (un)explainable AI and (un)explainable literature Genevieve Liveley Section 7: AI Narratologies 23. Towards narrative AI studies Torsa Ghosal 24. Towards an AI narratology: the possibilities of LLM classification for the quantification of abstract narrative concepts in literary studies Claudia Carroll 25. Post-digital narrative analysis Nuette Heyns Section 8: AI Co-Creations 26. Co-creative multimodal authorship as procedural performance with DALL-E Astrid Ensslin and Jason Nelson 27. Artificial theatres of the absurd Boyd Branch and Piotr Mirowski 28. Artificially funny: collaborative play at the intersection of AI, literature and humour Rachel Hamilton 29. Artificial Intelligence, the poetic process, and the critical editor Victoria Punch Postscript 30. Luddites, literature, and LLMs Kate Devlin