Creativity in Human-AI Co-Creation: A Two-Stage Model and the Da Vinci Score

Standard collaborative systems for creative problem-solving and innovation often focus on process efficiency rather than the content of ideas. Generative artificial intelligence (GenAI) promises a shift: it can actively generate and evaluate ideas, potentially transforming innovation workflows. Integrating concepts from group support systems and collaboration engineering, we propose a two-stage model of human–AI co-creation. In Stage 1 (AI-seeded ideation), the AI rapidly establishes a foundation by generating knowable ideas; in Stage 2 (human-enhanced ideation), humans engage in unpatterned ideation using this AI-generated output, both refining initial ideas and introducing content gains/losses that extend traditional process gains/losses frameworks. We further define the Da Vinci Score as a composite creativity metric that enables differential weighting of criteria, aligning evaluation with business relevance and practical collaboration. Our three-condition hypotheses (AI-only, Human-only, Hybrid), partially supported by prior data, highlight implications for innovation practice, process design, and future research in business contexts.

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Publication Details

Journal
ScholarSpace (University of Hawaii at Manoa)
Published
2025-12-23
Primary Topic
Team Dynamics and Performance
Type
article
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article

Creativity in Human-AI Co-Creation: A Two-Stage Model and the Da Vinci Score

Ling Hua Jiang, Christian Wagner
ScholarSpace (University of Hawaii at Manoa)
Team Dynamics and Performance
article

Creativity in Human-AI Co-Creation: A Two-Stage Model and the Da Vinci Score

Ling Hua Jiang, Christian Wagner
article en

Abstract

Standard collaborative systems for creative problem-solving and innovation often focus on process efficiency rather than the content of ideas. Generative artificial intelligence (GenAI) promises a shift: it can actively generate and evaluate ideas, potentially transforming innovation workflows. Integrating concepts from group support systems and collaboration engineering, we propose a two-stage model of human–AI co-creation. In Stage 1 (AI-seeded ideation), the AI rapidly establishes a foundation by generating knowable ideas; in Stage 2 (human-enhanced ideation), humans engage in unpatterned ideation using this AI-generated output, both refining initial ideas and introducing content gains/losses that extend traditional process gains/losses frameworks. We further define the Da Vinci Score as a composite creativity metric that enables differential weighting of criteria, aligning evaluation with business relevance and practical collaboration. Our three-condition hypotheses (AI-only, Human-only, Hybrid), partially supported by prior data, highlight implications for innovation practice, process design, and future research in business contexts.

ScholarSpace (University of Hawaii at Manoa)
Industry, innovation and infrastructure
Openalex Percentile: Top 28%
Team Dynamics and Performance
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