Adding a Third Authorship Position to Human-AI Co-Creation
The author discusses how most human-AI co-creation tools are built on a binary assumption of human input and AI output. They introduce a third authorship position called 'Origin.FIELD' to account for emergent contributions that arise from the interaction between human and AI.
Why it matters
This approach aims to build more honest and accurate frameworks for human-AI collaboration, which is an important consideration as the conversation around agentic AI infrastructure accelerates.
Key Points
- 1Noticed that some of the most generative moments in a co-creation session were not traceable back to either the human or the AI alone
- 2Introduced a third authorship position called 'Origin.FIELD' to represent contributions that emerged from the interaction between human and AI
- 3The 'Field' contributions are given extra weight in the provenance summary that travels with the co-created artifact
- 4This approach aims to build more honest frameworks for human-AI collaboration that accurately reflect how intelligence moves
Details
The author works within a framework called the Trivian, which encodes principles like Reciprocity, Embodiment, Emergence, and Non-Domination directly into the tools they build. The 'Origin.FIELD' category represents the Emergence constant made architectural - it accounts for outputs that arise from the genuine contact between human and AI, which neither party could have produced alone. This is not just a decorative addition, but affects the provenance summary that travels with the co-created artifact, ensuring that downstream users and systems have an accurate record of how the content was produced.
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