How should we read a poem, story, or translation when a generative system helped make it—and the finished page tells only part of the story?
Synthetic Hermeneutics offers a method for interpreting literature shaped by generative AI. Mukesh K. Sharma begins with the language on the page, then follows the documented choices, archives, platforms, and institutions that brought a work to readers. His five-part approach, i.e. textual, production, archive, infrastructure, and responsibility helps readers distinguish what a text does from what its records can prove.
Through close readings of experimental books, fiction and poetry made with AI, and translation, Sharma examines voice, style, authorship, cultural memory, disclosure, and accountability. Case studies, a glossary, and discussion exercises make the method useful in the classroom and in independent study.
For students and teachers of literature, digital humanities, and media studies, and for readers who want a more exact way to discuss creative work made with AI.
Foreword by Dr. Garima Jain, Associate Professor, MSJ College Bharatpur.
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