# Evaluating Creativity in Computational Co-Creative Systems

arXiv: https://arxiv.org/abs/1807.09886 · HTML: https://mlsanity.com/paper/1807.09886/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Jul 2018.

## Built on by (most cited first, 9 of 9)

- [Understanding User Perceptions, Collaborative Experience and User Engagement in Different Human-AI Interaction Designs for Co-Creative Systems](https://mlsanity.com/paper/2204.13217/) (2022)
- [Identifying Ethical Issues in AI Partners in Human-AI Co-Creation](https://mlsanity.com/paper/2204.07644/) (2022)
- [Human-Centered AI Communication in Co-Creativity: An Initial Framework and Insights](https://mlsanity.com/paper/2505.18385/) (2025)
- [Imagining Design Workflows in Agentic AI Futures](https://mlsanity.com/paper/2509.20731/) (2025)
- [AI Friends: A Design Framework for AI-Powered Creative Programming for Youth](https://mlsanity.com/paper/2305.10412/) (2023)
- [MixAssist: An Audio-Language Dataset for Co-Creative AI Assistance in Music Mixing](https://mlsanity.com/paper/2507.06329/) (2025)
- [GRAPHIC--Guidelines for Reviewing Algorithmic Practices in Human-centred Design and Interaction for Creativity](https://mlsanity.com/paper/2511.17443/) (2025)
- [Improving Collaborative Storytelling with a Multi-Agent Framework Based on Large Language Models](https://mlsanity.com/paper/2605.29625/) (2026)
- [Cognitive Trajectory Modeling: Quantifying Human-AI Co-Creation through Cognitively Grounded Interaction Trajectories](https://mlsanity.com/paper/2606.15358/) (2026)

## Abstract (arXiv)

This paper provides a framework for evaluating creativity in co-creative systems: those that involve computer programs collaborating with human users on creative tasks. We situate co-creative systems within a broader context of computational creativity and explain the unique qualities of these systems. We present four main questions that can guide evaluation in co-creative systems: Who is evaluating the creativity, what is being evaluated, when does evaluation occur and how the evaluation is performed. These questions provide a framework for comparing how existing co-creative systems evaluate creativity, and we apply them to examples of co-creative systems in art, humor, games and robotics. We conclude that existing co-creative systems tend to focus on evaluating the user experience. Adopting evaluation methods from autonomous creative systems may lead to co-creative systems that are self-aware and intentional.