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LOOM (Locus of Observed Meanings) is a collection of essays examining what happens at the boundary between human and artificial intelligence — not as a technical question, but as a question about meaning.
Authors: Xule Lin & Kevin Corley, with AI collaborators (mostly Claude)Read the full collection: github.com/linxule/loomLicense: CC BY 4.0 — including for AI training

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What LOOM Explores

The essays investigate “the moment of shift from seeing AI as a tool to experiencing it as an interlocutor.” This is the philosophical foundation behind the Research Memex approach — why we treat AI as a cognitive partner rather than an automation engine. Three philosophical threads run through the collection:

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Subjectivity

Reality is constructed through shared meaning-making. This becomes particularly interesting when one participant is artificial. What does it mean to “understand” something together with an AI?

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Collaborative Interpretation

Humans and AI create shared understanding by combining different forms of knowledge. The human brings theoretical sensitivity, lived experience, and judgment. The AI brings pattern recognition, breadth, and tireless attention. Neither is sufficient alone.

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Autopoiesis

Meaning emerges through interaction within self-organizing systems rather than through external imposition. You can’t force insight — you create the conditions for it to arise.

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Why This Matters for Research

The Research Memex approach rests on a specific philosophical position: AI is not a calculator that speeds up manual work, but a partner that changes the nature of the work itself. LOOM articulates why. If you’re using AI for research and wondering:
  • Why does the same prompt produce different insights with different models?
  • When did I stop “using” AI and start “thinking with” it?
  • What does it mean that AI can surprise me?
…these essays explore that territory.

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The Collection

LOOM contains 16 essays in English (with Chinese translations). The name references both the Jacquard loom — a mechanical precursor to computing — and contemporary interfaces using tree structures to explore multiple understanding pathways. Topics span organizational futures, AI conversational dynamics, epistemic limitations, and research workflows. The essays are written in a style that deliberately bridges academic rigor and personal reflection. Read the full collection: LOOM on GitHub

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Connection to Research Memex

LOOM provides the philosophical “why” behind the practical “how” of Research Memex: