A practical method for reading literature shaped by generative AI.
Mukesh K. Sharma (the book name of Mukesh Kumar)
Foreword by Dr. Garima Jain
How should we read a poem, story, or translation when a generative system helped make it? A finished page tells us what the words do, but it cannot reveal every choice that produced them. Synthetic Hermeneutics gives readers a way to examine both the writing and the available records without treating a guess as a fact.
The method in five readings
- Textual: What do the words, form, voice, and structure do?
- Production: What do records show about prompting, selection, editing, translation, and publication?
- Archive: Which sources and process records survive, and what remains unknown?
- Infrastructure: Did an interface, model version, platform, or other material condition change the work or its circulation?
- Responsibility: Who controlled a relevant decision and could explain or correct it?
The book applies this sequence to published AI-mediated literature, translation, authorship, disclosure, and cultural memory. Each chapter includes practical moves and discussion prompts. It is written for advanced students, teachers, researchers, and independent readers. No technical background in machine learning is required.
Try it in a class or reading group
Use the one-page classroom worksheet with a short passage from a work whose production has been publicly described. The exercise takes about 25 minutes. A sample of Chapter 4 explains the full protocol.
For the underlying argument, read Mukesh Kumar’s public working paper, “Synthetic Hermeneutics: A Protocol for Reading Literature in the Age of Generative AI”. It is shared as a working paper and has not been presented here as peer-reviewed journal publication.
Book and conversation
The paperback is available on Amazon. If you teach or research literary theory, digital humanities, media studies, or translation, I would welcome critical feedback on the method and its classroom use. I can also give a free 30-minute online demonstration for a class or research group. Write to mukesh@litgram.in.