The Case for Synthetic Literature Standards — References

← Back to main

← Back to main

Academic References

These sources form the theoretical foundation for evaluating synthetic literature on its own terms. They span literary theory, AI research, and critical philosophy.

Literary Theory & Critical Frameworks

• Iser, Wolfgang. The Act of Reading. Johns Hopkins University Press, 1978. — Reader-response theory on how meaning emerges between text and reader.
• Ricoeur, Paul. Time and Narrative. University of Chicago Press, 1984. — Narrative structure and temporal representation in literary works.
• Bal, Mieke. Narratology: Introduction to the Theory of Narrative. University of Toronto Press, 1985. — Structural analysis of narrative form applicable to synthetic narratives.
• Boden, Margaret. The Creative Mind: Myths and Mechanisms. Basic Books, 1990. — Foundational framework for understanding creativity as a computational process.
• Wagstaff, Kiri. "Machine-generated text: a comprehensive survey of attempts." AI & Society, 2022. — Historical survey of AI authorship from the 1960s to present.
• Peters, Debbie. Unleashing the Monster: On AI Creativity. Rowman & Littlefield, 2021. — Examines whether AI can genuinely create or merely recombine.

AI Creativity & Generation

• Mihayova, Boyana et al. "Assessing AI-Generated Text: A Survey." Computational Linguistics, 2023. — Comprehensive overview of evaluation methods and their limitations.
• Hutchins, Gabriella. Artificial You: AI and the New Art of Us. Princeton University Press, 2020. — How AI authorship reshapes creative practice across media.
• Creative Machines Consortium. The Nature of Synthetic Creativity. Columbia University, 2022. — Interdisciplinary perspective on machine-made art and literature.
• Bender, Emily M. et al. "On the Dangers of Stochastic Parrots." FAT* Conference, 2021. — Critical perspective on large language models and their societal impact.
• Walker, Marcus & Ye, Xiaoguang. "The Role of Ethics in AI-Generated Text." AI Magazine, 2023. — Ethical frameworks for AI text generation.
• Sharples, Michael. "AI and the Future of Authorship." British Journal of Educational Technology, 2023. — How AI changes our understanding of who authors a text.

Publishing & Authorship

• Asher, Nir. "AI authorship and the legal framework." Journal of Intellectual Property Law, 2023.
• Wagstaff, Kiri. "Machine-generated text: a comprehensive survey of attempts." AI & Society, 2022.
• The Riverdale Foundation. "Guidelines for the Riverdale Award for AI-Generated Art." 2023.
• Publishing industry guidelines on AI-assisted writing — practical frameworks currently in use by major publishers including Penguin Random House and Hachette.
• C2PA Consortium. "Content Credentials: Verifying the Provenance of Digital Media." 2023.
• Schwartz, Roy et al. "AI-Generated Literature: Classification, Detection, and Identification." ACL Anthology, 2023.