Thinking Through AI: Literature Review as Scholarly Practice
Engaging with a body of literature means more than finding and reading papers. It means seeing how different theories speak to each other, where the gaps are, and what conversation your research joins. AI can help with all of this — but engaging with AI well is itself a scholarly practice, requiring the same critical judgment we bring to any other part of research.
We open with three orienting principles: thinking through, engagement design, and the inward lens. From there we move into live demonstrations across three AI configurations, each suited to different phases of the work. Rather than prescribing a single workflow, the talk shows how different setups offer different ways of engaging with the same underlying challenge: making sense of a body of literature and locating your own contribution within it.
The focus is on developing interpretive understanding of a literature — where the theoretical conversations are, what assumptions they rest on, where the gaps sit. After the demonstrations, participants work hands-on to begin building their own approach. No technical experience needed. The emphasis throughout is on the practice of thinking with AI, not the mechanics of prompting it.
Suggested companion reading:
- Lin, X., & Corley, K. G. (2026). Interpretive Orchestration: An Essay Exploring the Epistemic Intersection of Human Intuition and Machine Intelligence. Strategic Organization. — the foundational paper for the principles in this talk.
- Epistemic Voids #1: Citation Theater
- Research with AI #1: The Foreclosure Problem
- LOOM XVI: Are You Climbing the Right Hill?
Part of the New Scholars Generative AI Series.