CoCo Matrix: Taxonomy of Cognitive Contributions in Co-writing with Intelligent Agents
Ruyuan Wan, Simret Gebreegziabhe, Toby Jia-Jun Li, Karla, Badillo-Urquiola

TL;DR
This paper introduces CoCo Matrix, a taxonomy based on entropy and information gain, to analyze and categorize human-agent co-writing systems, highlighting under-explored areas and aiding reflection on cognitive processes.
Contribution
It adapts cognitive process theory to create a new taxonomy for co-writing systems, providing a framework to analyze and understand human-agent collaborative writing.
Findings
Low entropy, high information gain systems are under-explored.
CoCo Matrix categorizes 34 existing systems.
The taxonomy aids reflection on cognitive contributions.
Abstract
In recent years, there has been a growing interest in employing intelligent agents in writing. Previous work emphasizes the evaluation of the quality of end product-whether it was coherent and polished, overlooking the journey that led to the product, which is an invaluable dimension of the creative process. To understand how to recognize human efforts in co-writing with intelligent writing systems, we adapt Flower and Hayes' cognitive process theory of writing and propose CoCo Matrix, a two-dimensional taxonomy of entropy and information gain, to depict the new human-agent co-writing model. We define four quadrants and situate thirty-four published systems within the taxonomy. Our research found that low entropy and high information gain systems are under-explored, yet offer promising future directions in writing tasks that benefit from the agent's divergent planning and the human's…
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