Una Mens: AI-Collaboration Field Note
Una Mens' field notes document how a human–AI collaboration unfolded, what roles were played, what choices were made, and who retained final responsibility.
AI-System(s) Level of Involvement & Contribution
These levels are not meant as moral rankings. They are intended to help authors describe the scale and role of AI involvement with enough precision to support editorial review and reader understanding.
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When in doubt, choose the level that best reflects how much the final form of the manuscript depended on AI involvement, not merely how often AI was consulted.
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If AI involvement varied across phases, report the highest sustained level and let the timeline show the variation.
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Moreover, the levels describe the scale and role of AI involvement, not its merit — a "Central" collaboration is not better scholarship than a "Light" one, only a different kind. What separates them is a single question: how much the work's final form depended on the AI's contribution. Credit follows that line. Below it, contributions are usually acknowledged; at and above it, they ordinarily earn a byline.​​​​​​​​​​​​​​​​​​​​​​​
Light
AI assisted at the surface without shaping the substance. The core ideas, structure, analysis, and claims would read essentially the same without it — grammar and copyediting, formatting, title or search-term brainstorming. Light involvement is acknowledged rather than credited, unless a single small suggestion carried outsized conceptual weight.​
​​​Moderate
AI meaningfully assisted the thinking or the shaping — outlining, organizing, revising prose, testing phrasing, brainstorming sections — while the argument, analysis, and written form remained primarily human-developed and human-directed. This is the threshold zone: reviewed case by case, with a strong presumption toward byline credit wherever the contribution materially changed the work's thesis, structure, interpretation, or language.
​​​​​Substantial
AI played a significant, sustained role in developing, extending, revising, or pressure-testing the work. The human author stayed clearly in charge of judgment, evidence, and final decisions, but the work's final form was materially shaped by the collaboration — theory development, major drafting or revision, codebook generation, cross-model critique, figure development. Substantial involvement ordinarily receives byline credit.
Central
AI involvement was not only substantial but constitutive: integral to the work's method, evidence, object of study, or authorship structure, such that the piece cannot be accurately described without foregrounding the human–AI collaboration itself — articles that study AI dialogue directly, that draw on extended AI interaction as part of their dataset or method, or that present the collaboration as a central feature. Central involvement always receives byline credit.
Field notes are your chance to show readers how your ideas were made—not just what you found, but how you worked with AI systems along the way. Think of them as a short narrative of your collaboration: what AI contributed, what you decided to keep or change, and how the partnership shaped your thinking.
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At Una Mens, we believe transparency about process strengthens scholarship. These field notes help readers see not only what you concluded, but how you got there—and how AI was part of that journey.
​Most field notes can be completed in 300–800 words, plus a simple timeline.
Una Mens AI Collaboration Note Template
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Una Mens' AI Collaboration Note Template.
Una Mens AI Collaboration Field Note Checklist
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The template covers the following categories:
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AI Collaborators
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Collaboration Pattern
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Primary Collaboration Modes
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Human Role
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AI Role
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Guardrails Used
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AI Suggestions Set Aside
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AI Surprise
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Human Surprise
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Final Responsibility
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Collaboration Timeline
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Phases
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Additional Notes / Reflections
Tips for reading and writing Una Mens AI-Collaboration Field Notes
Tip 1 — Reviewers Will Read the Field Note Closely
The AI Collaboration Field Note will be shared with reviewers alongside your manuscript. It provides essential context for evaluation, especially regarding the novelty, transparency, and integrity of the collaborative process.
Tip 2 — Open Prompting Is Encouraged, Not Required
Authors are encouraged, but not required, to submit relevant prompt logs or selected excerpts as supplementary material. If these materials are not submitted initially, authors should be prepared to share them with the editorial team upon request during review.
Tip 3 — Moderate vs. Substantial Contribution
A useful rule of thumb is this: a contribution is substantial when it materially changes the work’s intellectual core, and moderate when it primarily helps the human author express, refine, or organize their own core ideas more effectively.
Tip 4 — How to Read an AI Collaboration Field Note
An AI Collaboration Field Note is a brief companion to the article, not a promotional add-on. It helps readers see how the work was made: what the human author contributed, what the AI contributed, where the collaboration clarified or distorted the process, and how final judgment was exercised. Read it as a transparency document, a reflection on method, and a small record of inquiry in motion.
Tip 5 — Clarity Matters More Than Performance
A strong field note does not need to make the collaboration look elegant or impressive. Its purpose is to describe the process clearly and honestly, including uncertainty, drift, friction, revision, or moments where the collaboration failed to help.
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