Interpretive orchestration: An essay exploring the epistemic intersection of human intuition and machine intelligence
Abstract
This essay proposes “interpretive orchestration” as a collaborative framework between researchers and AI systems, addressing two central challenges: translating tacit knowledge into processable forms, and evaluating AI-generated patterns for theoretical importance. It develops three strategic models — Socratic tension, Euclidean documentation, and Vitruvian mastery — and argues that systematic human–AI partnership can preserve scholarly accountability while leveraging AI's capacity to process patterns across scales beyond unaided human capability.
Discussed on-site at Research Memex, which traces how this framework took shape through human–AI collaboration. This is the version-of-record landing page; the full text is open access under CC BY 4.0.
Xule Lin, Kevin Corley (2026). Interpretive orchestration: An essay exploring the epistemic intersection of human intuition and machine intelligence. Strategic Organization. https://doi.org/10.1177/14761270261448645
BibTeX
@article{lin2026interpretive,
author = {Lin, Xule and Corley, Kevin G.},
title = {Interpretive Orchestration: An Essay Exploring the Epistemic Intersection of Human Intuition and Machine Intelligence},
journal = {Strategic Organization},
year = {2026},
doi = {10.1177/14761270261448645},
note = {Advance online publication},
url = {https://doi.org/10.1177/14761270261448645}
}
Licensed under CC BY 4.0 — reuse and build on it, with attribution.