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.

Like
Save
Read original
Cached
Comments
?

No comments yet

Be the first to comment

AI Curator - Daily AI News Curation

AI Curator

Your AI news assistant

Ask me anything about AI

I can help you understand AI news, trends, and technologies