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Venturing under the hood and across platform ecosystems, this book demonstrates how text-to-image models offer a new playground for racism, misogyny, and xenophobia. From photorealistic bigotry to algorithmic caricatures, cutting-edge AI tools are not just reproducing hate but remaking it in novel ways. Drawing together a technical understanding of AI systems and a deep familiarity with both hate and meme cultures, this book offers specific examples, lays out the key characteristics of generative hate, and suggests how content moderation might become more AI-attuned. Generative Hate is a call to action for scholars, technologists, and citizens to understand and confront this emerging phenomenon.
Luke Munn is a Future Fellow at the University of Queensland, Australia. Luke explores the digital cultures that increasingly shape our lives, combining a deep understanding of technical logics (code, infrastructures, architectures) with a critical awareness of race and class, gender and labor, epistemologies and ecologies. His widely published and highly cited work shapes debates on AI ethics, automated labor, digital hate, and data politics.
Meg Thomas is a PhD Candidate at the University of Queensland, Australia, and student member of the ARC Centre of Excellence for Automated Decision Making and Society. Her current research looks at how media platforms and internet cultures reshape contemporary film and TV aesthetics. More broadly, Meg’s research explores the intersections between visual cultures, aesthetics, and digital media with a focus on platformization, synthetic media, and promotional cultures.
Kunal Chand completed his PhD at the Digital Media Research Centre, Queensland University of Technology, Australia. Kunal’s research sits at the intersection of computer science, information visualisation, and digital media studies. With a background in software engineering, computer science, and machine learning, he brings a strong technical foundation to his work. Kunal contributes insights on both the operation of various AI systems and ongoing ethical concerns within the field of machine learning.
| Publication Date: | 17 August 2026 |
| Publisher: | Springer Nature Singapore |
| Imprint: | Palgrave Macmillan |
| ISBN-13: | 9789819209286 |
| Format: | Hardback |
| Page Count: | 131 |