Human/AI Co-Creation in Digital Art – Collaboration and Augmented Creativity
Creators: name: Pillot, Florian
Publisher: name: Zenodo
Year: 2025

description: This repository contains the project plan and supporting documentation for a systematic qualitative meta-analysis on Human–AI Co-Creation in Digital Art – Collaboration and Augmented Creativity. The meta-analysis examines how artificial intelligence (AI) and human creators collaborate across multiple artistic domains—including visual art, music, creative writing, design, and more—to augment creative processes and outcomes.

Project Overview:The project aims to synthesize findings from studies published between 2020 and 2025, drawing on peer-reviewed academic research, industry white papers, professional reports, and artist testimonies. It investigates key research questions such as:





How does human–AI collaboration impact creative quality, novelty, and productivity?




In what ways does AI integration transform creative processes and workflows?




What domain-specific differences exist in co-creation dynamics?




Which factors (e.g., user skill level, tool design, collaborative settings) moderate or mediate the success of human–AI co-creation?



The meta-analysis is designed to be interdisciplinary, incorporating perspectives from computer science, human–computer interaction (HCI), cognitive science, psychology, and art theory. Its goals are to offer concrete, evidence-based insights into how augmented creativity can be effectively realized, while also addressing potential challenges such as creative convergence and issues of authorship.

Key Components:





Systematic Literature Review: A comprehensive search strategy is employed across major databases (Scopus, Web of Science, ACM Digital Library, IEEE Xplore, PubMed, PsycINFO, and Google Scholar) using defined inclusion/exclusion criteria focused on studies from 2020 to 2025.




Data Extraction and Quality Assessment: Standardized forms and quality checklists ensure that only reliable, high-quality sources (e.g., studies with sufficient sample sizes, control groups, and validated measures) are included in the review.




Thematic and Quantitative Synthesis: The analysis integrates findings to address the research questions, with a detailed examination of creative outcomes, workflow changes, domain-specific insights, and moderating factors influencing co-creative success.




Interdisciplinary Integration: The project bridges insights from multiple disciplines to generate a comprehensive understanding of human–AI co-creation, offering both theoretical advancements and practical recommendations for artists, creative teams, and tool developers.



Intended Outcomes and Impact:The meta-analysis will provide a consolidated overview of the state-of-the-art in human–AI co-creation, highlighting how AI tools can augment human creativity while preserving the essential role of the human artist. It is expected to:





Validate the hypothesis that human–AI collaboration can enhance creative outcomes compared to human-only or AI-only approaches.




Detail the transformative changes in creative processes, including accelerated ideation and the emergence of new collaborative workflows.




Identify critical factors that moderate the success of co-creation, such as user experience, interface design, and the specific artistic domain.




Offer actionable insights and guidelines for artists, creative professionals, and developers to optimize the use of AI in creative work.




Serve as a foundation for future research, particularly in addressing long-term impacts and further refining evaluation metrics in this rapidly evolving field.



Keywords:Human–AI co-creation, augmented creativity, digital art, generative AI, systematic review, interdisciplinary research, creative process, visual art, music, creative writing, design.

This repository is intended for researchers, practitioners, and anyone interested in the evolving landscape of AI in creative industries. The comprehensive meta-analysis aims to contribute to both academic knowledge and practical guidelines for harnessing the full potential of human–AI collaborations in digital art.

For more information or questions regarding this project, please contact me at : Florian.pillot.p@hotmail.com