The Integrated Creativity Network (ICN): A Framework for Mapping Distributed Creativity in Human–AI Systems

This preprint proposes the Integrated Creativity Network (ICN), a framework that synthesizes Sternberg & Karami’s 8P model with Actor–Network Theory (ANT) to analyse creativity in human–AI systems. Rather than treating creativity as a property of an individual or a tool, ICN traces how creative outcomes are distributed across people, prompts, datasets, models, interfaces, institutions, and evaluative cultures. The paper (1) reframes each 8P element (Person, Process, Press, Product, Place, Persuasion, Problem, Propulsion) as relationally enacted within heterogeneous networks; (2) translates ANT concepts (e.g., translation, enrolment, interessement) into an analytic vocabulary for creativity research; and (3) outlines practical options for process tracing and network mapping in applied contexts (e.g., art practice, photography workflows, generative pipelines). A practice-led proof-of-concept case study from AI-assisted image making demonstrates how sociotechnical configurations shape problem definition, iteration, and perceived value. The approach aims to bridge creativity theory, STS, and computational arts.