# Interpretive orchestration: An essay exploring the epistemic intersection of human intuition and machine intelligence

**Authors**: Xule Lin, Kevin G. Corley
**Venue**: Strategic Organization (2026)
**DOI**: https://doi.org/10.1177/14761270261448645
**License**: https://creativecommons.org/licenses/by/4.0/


## 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.


## Links

- [Publisher (DOI)](https://doi.org/10.1177/14761270261448645)
- [SSRN](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6629679)
- [Code](https://github.com/linxule/interpretive-orchestration-paper)


## Cite

Xule Lin, Kevin G. Corley (2026). Interpretive orchestration: An essay exploring the epistemic intersection of human intuition and machine intelligence. Strategic Organization. https://doi.org/10.1177/14761270261448645

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Discussed on-site at [Research Memex](/writing/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.


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*This file is one rendering. The HTML surface is another. The source remains: https://linxule.com/papers/interpretive-orchestration*