Human-AI Co-Creativity: Exploring Synergies Across Levels of Creative Collaboration
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Abstract (arXiv)
Human-AI co-creativity represents a transformative shift in how humans and generative AI tools collaborate in creative processes. This chapter explores the synergies between human ingenuity and AI capabilities across four levels of interaction: Digital Pen, AI Task Specialist, AI Assistant, and AI Co-Creator. While earlier digital tools primarily facilitated creativity, generative AI systems now contribute actively, demonstrating autonomous creativity in producing novel and valuable outcomes. Empirical evidence from mathematics showcases how AI can extend human creative potential, from computational problem-solving to co-creative partnerships yielding breakthroughs in longstanding challenges. By analyzing these collaborations, the chapter highlights AI's potential to enhance human creativity without replacing it, underscoring the importance of balancing AI's contributions with human oversight and contextual understanding. This integration pushes the boundaries of creative achievements, emphasizing the need for human-centered AI systems that foster collaboration while preserving the unique qualities of human creativity.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 19 Nov 2024.
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Citing papers per year: 2025: 5; 2026: 4.
9 papers.
- 2025Beyond Static Responses: Multi-Agent LLM Systems as a New Paradigm for Social Science Researchcited by 10
- 2025Measuring LLM Novelty As The Frontier Of Original And High-Quality Outputcited by 6
- 2025Has the Creativity of Large-Language Models peaked? An analysis of inter- and intra-LLM variabilitycited by 6
- 2025When Models Know More Than They Can Explain: Quantifying Knowledge Transfer in Human-AI Collaborationcited by 4
- 2026The Agentic Researcher: A Practical Guide to AI-Assisted Research in Mathematics and Machine Learningcited by 4
- 2025Exploration vs. Fixation: Scaffolding Divergent and Convergent Thinking for Human-AI Co-Creation with Generative Modelscited by 2
- 2026CoLyricist: Enhancing Lyric Writing with AI through Workflow-Aligned Supportcited by 1
- 2026PlayWrite: A Multimodal System for AI Supported Narrative Co-Authoring Through Play in XRcited by 1
- 2026Incentives shape how humans co-create with generative AIcited by 1
- 2026Incentives shape how humans co-create with generative AI4 Apr 2026
- 2026The Agentic Researcher: A Practical Guide to AI-Assisted Research in Mathematics and Machine Learning16 Mar 2026
- 2026PlayWrite: A Multimodal System for AI Supported Narrative Co-Authoring Through Play in XR2 Mar 2026
- 2026CoLyricist: Enhancing Lyric Writing with AI through Workflow-Aligned Support26 Feb 2026
- 2025Exploration vs. Fixation: Scaffolding Divergent and Convergent Thinking for Human-AI Co-Creation with Generative Models20 Dec 2025
- 2025When Models Know More Than They Can Explain: Quantifying Knowledge Transfer in Human-AI Collaboration5 Jun 2025
- 2025Beyond Static Responses: Multi-Agent LLM Systems as a New Paradigm for Social Science Research2 Jun 2025
- 2025Measuring LLM Novelty As The Frontier Of Original And High-Quality Output13 Apr 2025
- 2025Has the Creativity of Large-Language Models peaked? An analysis of inter- and intra-LLM variability10 Apr 2025