The Routledge Handbook of AI and LiteratureBy WillSlocombe and GenevieveLiveley (eds.), New York: Routledge, 2024. 396 pp. $280.00 (hardcover). ISBN: 978‐1‐03‐218694‐8

The Routledge Handbook of AI and Literature (2024), edited by Will Slocombe and Genevieve Liveley, offers a timely and authoritative interdisciplinary intervention that bridges computational science and the humanities, critically engaging with the challenges and opportunities posed by generative AI, particularly large language models (LLMs). Situated within C. P. Snow's “two cultures” debate, the volume shifts the focus from AI in literature (as representation) to AI and literature (as implication), treating them as a dynamic conjunction rather than separate domains. In doing so, it foregrounds interaction, creativity, and ethical risk, offering a coherent framework that redefines the intellectual scope of literary inquiry in the algorithmic age. Section 1 “AI Authors” revisits the contested boundary between human and machine creativity. Essays by Caroline Basset, David J. Gunkel, and Sara Bimo problematize authorship by exposing its anthropocentric bias and legal instability. Rather than asking whether AI can write, they interrogate what writing means when detached from the human subjects. Such discussion effectively extends the post-structuralist “death of the author” into the post-human condition. Sections 2 and 3 interrogate AI's dual function as expressive and cognitive apparatus, revealing how machine mediation destabilizes conventional notions of voice and authorship while exposing the epistemic limits of artificial cognition. In “AI Voice,” Biebe Bluijs frames AI voice as a blend of human and nonhuman agencies, while Genevieve Liveley and Natalie J. Swain explore the potential for AI systems to learn the interpretive role of silence, illustrating how AI challenges conventional understanding of communicative intentionality. Piippo's analysis of platform algorithms foregrounds the rhetorical and affective shaping of AI-generated content, and Cole's engagement with the Homeric tradition positions iterative composition as a site where AI provokes reflection on human creative practice. Extending this inquiry, Section 3 “AI Interrogations” shifts from representation to epistemology: Marcinkowski reveals how AI reproduces structural inequalities, Fletcher underscores its lack of causal reasoning, and Raven contrasts machine patterning with human reflexivity and intentionality. Together, these discussions advance a post-humanist epistemology that positions AI not as an imitation of human intellect but as a critical pivot through which literature rethinks the boundaries of cognition, agency, and authorship itself. Sections 4 and 5 extend the book's inquiry into the intersections of AI and literature, respectively, focusing on narrative representation and ethical implications. In “AI Narratives,” Will Slocombe problematizes the very notion of constructing a digital corpus of AI fiction, while Jo Lindsay Walton proposes “critical design fiction” via AI 2041, noting how paratexts tend to neutralize cautionary critiques into techno-solutionist paradigms. Complementing these debates, Edward King and Timothy Miller explore how AI reshapes identity and intimacy under the pressure of digital capitalism. Transitioning from representation to responsibility, “AI Ethics” addresses the moral and juridical dimensions of AI-generated texts: Kasia Van Schaik critiques data extraction through the lens of conceptual writing, Rebecca Shaw examines algorithmic reasoning in legal discourse, and Joanne Lipson Freed advocates New Formalism as a means to counter platform-driven partisanship. What makes these inquiries particularly compelling is their insistence on examining AI as a practice embedded in the material operations of digital capitalism, thereby transforming abstract ethical debates into concrete analyses of power, labor, and cultural production in the algorithmic age. The book's final three sections constitute its most distinctive scholarly intervention by integrating technical, narratological, and performative perspectives to reconfigure the dialogue between AI and literary studies. Section 6 “AI Interdisciplinarities” redefines computational literary criticism as a performative epistemology (Katherine Bode and Charlotte Bradley), while Tony Veale and Genevieve Liveley respectively assess the creative potential and interpretive opacity of LLMs, the latter urging for renewed human agency within algorithmic systems. Section 7 “AI Narratologies” exemplifies the methodological synthesis: Torsa Ghosal links AI-driven narrative forms to ethical and cultural critique, Claudia Carroll quantifies narratological features through machine learning, and Nuette Heyns revises Genette's categories for post-digital narrative dynamics. Section 8 “AI Co-Creations” examines the nuanced dynamics and creative practice emerging from human–AI collaboration—whether through procedural multimodality (Astrid Ensslin and Jason Nelson), experimental performance (Boyd Branch and Piotr Mirowski), and the interplay of human and algorithm (Rachel Hamilton). Unlike earlier works that treat interdisciplinarity as a thematic integration, the book operationalizes it as a methodological practice. This shift is crucial, as it redefines the study of AI and literature from comparative inquiry to a collaborative epistemology that generates new modes of knowledge production. One of the book's most notable achievements lies in its integrative scope and critical coherence. It synthesizes theoretical reflection with applied inquiry, creating a shared vocabulary for disciplines that rarely converse. The editors' introduction and cross-references among contributors foster an unusual sense of dialogue rather than fragmentation, which is often a weakness of large edited collections. Nevertheless, certain limitations persist. The volume's case studies remain predominantly Anglophone, with limited attention to non-Western literature or multilingual AI corpora. Moreover, while the collection is rich in theoretical insight, it occasionally underrepresents the pedagogical implications of integrating AI into literary curricula. These gaps, however, do not diminish the book's scholarly value; rather, they point toward fertile ground for future research. Overall, the Routledge Handbook of AI and Literature can be read as a comprehensive mapping of the interdisciplinary terrain linking literature and AI. By charting the theoretical, methodological, ethical, and practical dimensions of this emerging field, it provides a wide-angle view that illuminates key debates and methods within literary scholarship, thereby serving as a qualified paradigm for inquiry in a broader cultural and social research. This study is an independent work of Tianyan Xie. The data that support the findings of this study are available from the corresponding author upon reasonable request.