AI-Collaboration Field Note
Article: The Obverse-Turing Test
Published in: Una Mens: Homo et Machina
Article DOI:
https://doi.org/10.66787/um.000001
Field Note DOI:
https://doi.org/10.5281/zenodo.21280115
Human lead: Mike Miller
AI collaborators: ChatGPT-4o
Degree of AI Involvement: Moderate
Primary collaboration modes: conceptual development, drafting, critique, metaphor generation, revision
Collaboration Timeline:
May—November 2024
Field Note Summary
Human Contribution and Responsibility: question-framing, judgment, selection, synthesis, ethical responsibility, final editing
AI Contribution: conceptual extension, drafting suggestions, counterframing, structural assistance
Guardrails used: idea-provenance tracking; short-passage drafting; human final review
AI suggestions set aside: conceptual expansion of scientific impact and AI agency beyond the author's current understanding
AI surprise: Oppenheimer extension
Human surprise: MIT student example
Final responsibility: The human author retains final responsibility for the article’s claims, citations, interpretations, ethical decisions, and submitted text.
Expanded Field Note: The Obverse-Turing Test
This was the first article I began with the explicit intention of co-creating with an AI collaborator. Earlier experiments with AI-assisted writing had shown me that large language models could contribute not only prose, but also unexpected conceptual extensions. For that reason, this article was written with two self-imposed guardrails: first, to actively track moments when novel ideas entered the manuscript; and second, to limit AI-generated prose during formal drafting to short, reviewable passages.
The collaboration developed through a close back-and-forth process in which both human and AI contributions shaped the direction of the argument. One notable AI contribution occurred in the section on scientific responsibility, where the model extended my initial Einstein example toward Oppenheimer, intensifying the historical and ethical stakes of the discussion.
One notable human contribution occurred near the end of the manuscript, when I introduced the example of a student unable to defend AI-assisted work. That story helped sharpen the article’s central concern with authorship, understanding, and responsibility.
During development, ChatGPT4o occasionally pushed toward broader claims about machine agency and future scientific legitimacy than I was prepared to defend. Those claims were narrowed or removed in favor of a more pragmatic focus on authorship, responsibility, and human understanding.